Multifaceted investigation into apple to unravel texture physiology

Univ ersit` a degli Studi di Milano
DIP AR TIMENTO DI PR ODUZIONE VEGET ALE
Scienze molecolari e biotecnologie agrarie, alimen tari ed am bien tali
Biologia v egetale e pro duttivit` a della pian ta coltiv ata ciclo XXI I I
Tesi di Dottora to di Ricer ca
Multifaceted in v estigation in to apple to unra v el texture
ph ysiology
A GR/07
Relatore & Co-relatore:
Prof. Ilaria Mignani
F abrizio Costa
Co ordinatore del dottorato:
Prof. Daniele Bassi
Candidato:
Sara Longhi
Anno Accademico 2010–2011
Contents
1 Intro duction 7
1 . 1 T h e m y t h o f a p p l e ......................... 7
1.2 F ruit qualit y facto rs . . . . . . . . . . . . . . . . . . . . . . . . 8
1.3 T exture: definition and imp o rtance . . . . . . . . . . . . . . . . 9
1.3.1 T exture from a senso rial p oint of view and its role in
b reeding p rograms . . . . . . . . . . . . . . . . . . . . 10
1 . 4 F r u i t t e x t u r e ............................ 1 2
1.4.1 State of the a rt . . . . . . . . . . . . . . . . . . . . . . 12
1.4.2 T exture measurement . . . . . . . . . . . . . . . . . . . 12
1 . 4 . 3 C r i s p n e s s .......................... 1 3
1 . 5 C e l l w a l l a n a t o m y ......................... 1 6
1.6 Cell w all gene regulation . . . . . . . . . . . . . . . . . . . . . 17
1.6.1 Cell w all enzymes and their role in fruit rip ening . . . . . 17
1.6.2 Cell w all mo difications during rip ening . . . . . . . . . . 19
1.7 The ho rmone ethylene . . . . . . . . . . . . . . . . . . . . . . . 21
1.7.1 Ethylene and fruit rip ening . . . . . . . . . . . . . . . . 21
1.7.2 Ethylene biosynthesis . . . . . . . . . . . . . . . . . . . 22
1.7.3 Ethylene p erception . . . . . . . . . . . . . . . . . . . . 23
1.7.4 Ethylene impact on cell w all metab olism . . . . . . . . . 25
1.7.5 Genetic manipulation of rip ening regulato ry genes . . . . 26
2 Aim of the w o rk 29
3 Assessment of apple (Malus x domestica Bo rkh.) fruit texture b y
a combined mechanical-acoustic p rofiling strategy 31
3 . 1 A b s t r a c t .............................. 3 1
3 . 2 I n t r o d u c t i o n ............................ 3 2
3.3 Materials and metho ds . . . . . . . . . . . . . . . . . . . . . . 33
3
CONTENTS 4
3.3.1 Plant materials . . . . . . . . . . . . . . . . . . . . . . 33
3.3.2 Instrumental analysis: empirical metho ds and textural
a s s e s s m e n t ......................... 3 4
3.3.3 Rip ening stage evaluation . . . . . . . . . . . . . . . . . 35
3.3.4 Senso ry evaluation b y untrained exp ert panels . . . . . . 35
3.3.5 Data analysis . . . . . . . . . . . . . . . . . . . . . . . 35
3.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . 37
3.4.1 Acoustic-mechanical combined p rofile analysis . . . . . . 37
3.4.2 Clustering and p rincipal comp onent analysis (PCA) . . . 38
3.4.3 Influence of rip ening stage on apple textural p rop erties . 42
3.4.4 Senso ry data and correlation with instrumental data . . . 42
3 . 5 C o n c l u s i o n ............................. 4 3
4 Comp rehensive QTL mapping survey dissects the complex fruit
texture physiology in apple (Malus x domestica Bo rkh.). 45
4 . 1 A b s t r a c t .............................. 4 5
4 . 2 I n t r o d u c t i o n ............................ 4 6
4.3 Materials and Metho ds . . . . . . . . . . . . . . . . . . . . . . 48
4.3.1 Plant material . . . . . . . . . . . . . . . . . . . . . . . 48
4.3.2 F ruit texture assessment . . . . . . . . . . . . . . . . . 48
4.3.3 Molecula r ma rker genot yping . . . . . . . . . . . . . . . 49
4.3.4 RNA isolation and transcription analysis . . . . . . . . . 50
4.3.5 Ethylene Analysis . . . . . . . . . . . . . . . . . . . . . 51
4.3.6 Statistic computation and data analysis . . . . . . . . . 51
4.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . 52
4.4.1 Exp erimental design . . . . . . . . . . . . . . . . . . . . 52
4.4.2 T exture physiology dissection and combined acoustic and
mechanical p rofiling . . . . . . . . . . . . . . . . . . . . 52
4.4.3 Genetic mapping . . . . . . . . . . . . . . . . . . . . . 52
4.4.4 QTL detection and candidate gene mapping . . . . . . . 54
4 . 4 . 5 G e n e m i n i n g ........................ 6 3
4 . 4 . 6 C o n c l u s i o n ......................... 6 5
5 Fine mapping and asso ciation analysis of a fruit texture QTL in
apple (Malus x domestica Bo rkh.) 67
5 . 1 A b s t r a c t .............................. 6 7
5 . 2 B a c k g r o u n d ............................ 6 8
5.3 Materials and Metho ds . . . . . . . . . . . . . . . . . . . . . . 70
5.3.1 Plant material . . . . . . . . . . . . . . . . . . . . . . . 70
5.3.2 T exture phenomic assessment . . . . . . . . . . . . . . . 70
5.3.3 P opulation structure . . . . . . . . . . . . . . . . . . . . 72
5.3.4 Md-PG1 g e n e c l o n i n g ................... 7 2
5.3.5 Genot yping scheme . . . . . . . . . . . . . . . . . . . . 73
5.3.6 Link age Disequilib rium and Asso ciation analysis . . . . . 74
CONTENTS 5
5.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . 75
5.4.1 T exture physiology dissection and combined acoustic and
mechanical p rofiling . . . . . . . . . . . . . . . . . . . . 75
5.4.2 P opulation structure analysis . . . . . . . . . . . . . . . 76
5.4.3 Md-PG1 cloning and Md-Xet and Md-PG1 sequence di-
v e r s i t y ........................... 7 6
5.4.4 Macro and micro allelot yping . . . . . . . . . . . . . . . 79
5.4.5 Asso ciation mapping based on the Md-PG1 candidate gene 82
5.4.6 Allelic dosage of Md-PG 1 S S R 1 0 k d 3 .......... 8 6
5 . 5 C o n c l u s i o n ............................. 8 8
6 T ranscription p rofiling b y microa rra y app roach unravel the apple
climacteric fruit rip ening physiology 91
6 . 1 A b s t r a c t .............................. 9 1
6 . 2 B a c k g r o u n d ............................ 9 2
6.3 Materials and Metho ds . . . . . . . . . . . . . . . . . . . . . . 93
6.3.1 RNA isolation and microa rray hyb ridization . . . . . . . 93
6.3.2 T exture phenomic assessment . . . . . . . . . . . . . . . 94
6.3.3 Ethylene determination via PTR-T oF-MS and sp ectra
a n a l y s i s .......................... 9 4
6.3.4 Scanning electron microscop e observation . . . . . . . . 95
6.3.5 Chip design and synthesis . . . . . . . . . . . . . . . . . 95
6 . 3 . 6 D a t a A n a l y s i s ....................... 9 6
6.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . 96
6.4.1 T exture physiology dissection . . . . . . . . . . . . . . . 96
6.4.2 Data analysis and gene clustering . . . . . . . . . . . . . 99
6.4.3 T ranscriptome variation within the cultiva rs . . . . . . . 108
6.4.4 T ranscriptome variation b et w een cultiva rs . . . . . . . . 110
6.4.5 Candidate genes dynamics . . . . . . . . . . . . . . . . 113
6 . 5 C o n c l u s i o n............................. 1 1 7
7 Conclusions and future p rosp ects 121
8 Supplementa ry material of chapter 3 125
9 Supplementa ry material of chapter 4 131
10 Supplementa ry material of chapter 5 169
References 179

CONTENTS 6
CHAPTER 1
Intro duction
1.1 The myth of apple
“Sno w White longed fo r the b eautiful apple, and when she sa w that the p eddler
w oman was eating pa rt of it, she could no longer resist, and she stuck her hand
out and to ok the p oisoned half. She ba rely had a bite in her mouth when she
fell to the ground dead.” Sno w White and the Seven Dw a rves is one of the
numerous tale and ancient myth that tell ab out tempting and actractive apples
that a re the cause or the beginning of imp o rtant o r wretch events.
In the Holy Bible, Eva w as convinced by the evil snak e to eat the fo rbidden
fruit, a tempting apple symb ol of kno wledge, p rovoking Go d’s anger and the F all
from the Eden Ga rden. The story tells also that Adam’s apple w as caused b y
the fo rbidden fruit sticking in the throat of Adam as wa rning. In the holy b o ok,
ho wever, there is not a sp ecific and clea r reference to the apple as the fruit of
sin, but it w as chosen b y the collective imagination as the fruit pa r excellence
thanks to its tempting app ea rance and go o d taste.
Several a re also the examples in the ancient greek myths. Eris, the greek
go ddess of disco rd, b ecame disgruntled after she w as excluded from the wedding
of P eleus and Thetis. In retaliation, she tossed a golden apple inscrib ed “fo r
the most b eautiful one”, into the w edding pa rt y . Three go ddesses claimed the
apple: Hera, A thena, and Aphro dite. Pa ris of T ro y w as app ointed to select the
recipient. After b eing b rib ed b y b oth Hera and A thena, Aphro dite tempted him
with the most b eautiful w oman in the w o rld, Helen of Spa rta. He a w a rded the
apple to Aphro dite, thus indirectly causing the T rojan W a r. A talanta, also of
Greek mythology , raced all her suito rs in an attempt to avoid ma rriage. She
outran all but Hipp omenes (also kno wn as Melanion, a name p ossibly derived
from melon the Greek w ord fo r b oth “apple” and fruit in general), who defeated
7
1.2. F ruit qualit y facto rs 8
her b y cunning, not sp eed. Hipp omenes knew that he could not win in a
fair race, so he used three golden apples (gifts of Aphro dite, the go ddess of
love) to distract A talanta. It to ok all three apples and all of his sp eed, but
Hipp omenes w as finally successful, winning the race and A talanta’s hand. But
after that Hipp omenes had w on his p rize he w as so happ y that he fo rgot to
thank Aphro dite. He w ent instead to the temple of Zeus to celeb rate his victo ry
with A talanta. Aphro dite w as furious and sent flaming desire coursing through
Hipp omene’s and A talanta’s veins and they la y together right there in Zeus’
holy temple.
The central thread of all these myths is that the app ea rance of p rohibited of
attractive apples tempted humans, enlightening the imp o rtance of this qualit y
in the choice of the fruit. The English w o rd of fruit comes from the latin verb
“frui”, meaning to enjo y , to delight [156], the very first qualit y facto rs that can
describ e apple a re in fact refered to sensual pleasure.
The places where this w ork of thesis w as realised a re also connected by the
apple fruit as a central thread. The main w o rk w as realised in T rentino Alto
Adige (Italy), the region that accounts fo r the 70% of Italian apple p ro duction,
then in the W ashington State (USA), which national symb ol is an apple and
finally in the New Y o rk State. New Y o rk Cit y is one of the most imp o rtant cit y
in the w orld fo r its relevance on the global economy and culture. This cit y is also
knw on as “The Big Apple”, entailing to this fruit a meaning of opp o rtunities,
p rogress and development.
1.2 F ruit qualit y facto rs
F ruit and fo o d qualit y can b e defined as the p rop ert y to resp ond and satisfy con-
sumer requirements, desire and exp ectations. Qualit y , in fact, is determined as
the subjective compa rison that customers make b et w een their exp ectations (de-
riving b y previous experiences) ab out a p ro duct and its p erception. In particula r
custumer’s requirements agree with fruits that have an app ealing app erance,
flavour and taste, that a re fresh, with a go o d shelf life, and cha racterized b y an
app ropriate texture.
F ruit quality is measured accomplishing four main points, also kno wn as
Principal Qualit y Facto r:
1. App ea rance , comp rises colour, shap e, size and gloss; its evaluated b y
optical sense
2. Flavour , comprises taste and odor, p erceived on the tongue and in the
olfacto ry center in the nose, resp ectively . It is the resp onse of recepto rs
in the o ral and nasal cavities to chemical stimuli.
3. T exture is p rima rily the resp onse of the tactile senses to the physical
stimuli resulting from the contact b et w een tactile recepto rs and the fo o d.
1.3. T exture: definition and imp o rtance 9
4. Nutrition comp rises major and mino r nutrients affecting human health.
Rega rding this asp ect w e can mention the 19th century statement:“an ap-
ple a da y keeps the doctor a w a y”. Nutraceutical properties are considered
extremely imp o rtant, but, b ecause of their exp ensive lab o rato ry analysis
and the inabilit y of consumer to p erceive them directly b y their senses,
they a re considered rather an added fo o d value than a qualit y facto r.
No wada ys, fo o ds supply is no longer a crucial issue in develop ed countries,
thus fo o d/fruit qualit y b ecame the driving p rop erties affecting the choice of
consumers. Other factors, such as cost, convenience and pack aging a re also
imp o rtant but a re not considered as fo o d qualit y facto rs.
1.3 T exture: definition and imp o rtance
Contra ry to the other quality facto rs which a re p erceived by a single and spe-
cific sense such as view and taste fo r the evaluation of app eara nce and flavour
resp ectively , it is not p ossible to define texture with a single cha racteristic and
attribute. This trait is in fact a heterogeneous complex of p rop erties having dif-
ferent p eculia rities, with b oth mechanical and acoustic nature. F o r this reason
the definition of texture, o r “textural p rop erties” which infers a group of related
p rop erties, requires pa rticula r attention and rega rd.
Literally , texture assumed different definitions according to p eople’s culture,
customs and education, as describ ed b y Szczesniak and Kleyn [211], Y oshik a w a
et al. [243] and Rohm [186]. It is p ossibile ho w ever to determine some common
cha racteristics of fo o d texture [25].
• it is a group of physical p rop erties that derive from the structure of the
fo o d;
• it b elongs under the mechanical o r rheological subheading of physical
p rop erties;
• it consist in a group of p rop erties, rather than a single attribute;
• texture is sensed p rimarily b y the feeling of touch, usually in the mouth,
even if other pa rt of the b o dy ma y b e involved, hands fo r istance;
• it is not related to the tactile o r olfacto ry sense.
On the light of these observations, texture can b e defined as a multifaceted
group of fo o d p rop erties with the follo wing general definition: “the textural
p rop erties of a fo o d a re that group of physical cha racteristics that arise from
the structural elements of the fo o d, a re sensed prima rily b y the feeling of touch,
a re related to the deformation and flo w of the fo o d under a fo rce and a re
measured objectively b y function of mass, time and distance” [25].
V arious a re the terms that can w ell describ e o r replace the wo rd “texture”
1.5. Cell w all anatomy 16
soak ed green p epp er, b) fresh green p epp er, c) Pringles p otato chips and d)
almond . It is w o rth noting that the higher the amplitude of the amplitude-plot,
the crispier is the fo o d analysed [228].
Figure 1.2: Amplitude-time plot of different fo o ds. A: w ater soak ed green
p epp er, B: fresh green p epp er, C: Pringles p otato chips, D: almond [227]
In conclusion, acoustic and mechanical data a re therefo re co rrelated and
sho w information that a re connected and complementa ry to each other. In fact
the numb er and intensit y of the acoustic p rofile dep ends on the change of energy
released during the fracture [222]. F o r this reason b oth a re usefull and necessa ry
fo r the dissection of a complex trait, such as crispness.
1.5 Cell w all anatomy
F ruit maturation and rip ening p ro cesses are the result of a complex series of
events, determined b y genetically p rogrammed physiological and bio chemical
changes. These va riations generally include pigment mo difications (which af-
fects app ea rance), conversion of sta rch into suga r and accumulation of flavour
and a romatic volatiles (affecting fruit flavour), mo difications of cell w all ultra-
structure (affecting the final fruit texture) and syntesis of vitamins, minerals,
antio xidant and fib er (affecting nutrition) [85],[29]. Among these, mo difications
of the cell w all a rchitecture a re crucial phenomena fo r texture dynamics during
fruit rip ening.
The p rimary cell w all is constituted b y a la rge numb er of p olymers that
va ry b et w een sp ecies; ho w ever eight p olymeric comp onents a re usually p resent:
cellulose, three matrix glycans comp osed of neutral suga rs (xyloglucan, galac-
toglucomannan, gluco ronoa rabino xylan), three p ectin rich in D-galacturonic acid
(homogalacturonan, rhamnogalacturonan I and I I) and structural p roteins [29].
Cell w all is comp osed b y a rigid and inextensible cellulose microfib rils, coated
together b y a crossed-linked matrix of glycans, of which the most adbundant
is xyloglucan [155]. Mo re in detail xyloglucan backb one is binded to cellulose

1.6. Cell w all gene regulation 17
b y hidrogen b onding, and xyloglucan molecules can span b et w een adiacent mi-
crofib rils, linking them toge ther. Also glucomannan and glucuronoa rabino xylan
a re cross-linked to microfib ril. Spaces b et w een the cellulose and the glycans
matrix a re filled by pectins; this final complex netw o rk ma y b e lo ck ed together
b y covalent links b et w een some xyloglucan molecules and p ectins [218].
Other structural p roteins may fo rm an additional net w o rk, causing cell w all
mo difications; these p roteins, all existing in multigene families, a re extensin,
Proline-Rich Protein (PRPs) and Glycine-Rich Protein (GRPs) [241]. The b est-
kno wn structural w all p roteins are the extensins. They a re basic p roteins able to
interact with acidic p ectic blo cks in the cell w all, helping the w all reinfo rcement
[120]. In cases where the cross link ages a re labile, extensins provide a chemical
basis fo r changes in cell wall plasticit y which a re necessary fo r extension of plant
cells [132]. As extensins, PRPs a re p resumably insolubilized in the cell w all
matrix [35]. They a re mainly p resent in the xylem where they might b e involved
either in xylem differentiation o r in lignification [35]. GRPs, mainly lo calized in
the mo dified p rima ry w alls of p roto xylem cells, a re another class of structural
w all proteins. They seem to pla y imp o rtant roles in the development of vascula r
tissues, no dules, and flo w ers and during w ound healing and freezing tolerance
[35].
1.6 Cell w all gene regulation
1.6.1 Cell w all enzymes and their role in fruit rip ening
The mo dification o ccurring in the cell w all p olymers during rip ening is a com-
plex phenomena involving the co-o rdinated and interdep endent action of a
range of cell w all-mo difying enzymes and p roteins lik e P olygalacturonase, Pectin
methylesterase, β Galactosidase, P ectate lyase, Endo 1 → 4 β -D-glucanase, Xy-
loglucan endotransglycosylase and Expansin. One family of cell-w all enzyme
ma y mediate the activity of another, resulting in a co-o rdinated w all mo difica-
tion p ro cess [187]. Cleavage of the matrix backb one of hemicellulose o r p ectins
(made b y endo-glucanases), remove for istance the side-chains allo wing the in-
teraction b et w een p olysacha ride backb ones (made b y glycosidases) [88].
P ectin-degrading enzymes, PG, PME and PL a re surely k ey play ers in fruit
softening, as p ectins a re synthesized and dep osited in the cell w all in a methylester-
ified fo rm, and their main function is to cement plant cells together into tissue
structures [185]. Their action exp oses the w all to the action of other cell w all
enzymes, initiating all the transfo rmations t ypical of rip ening. P olygalactur-
onase (PG) a re enzymes that catalyse the hydrolytic cleavage of galacturonide
link ages (PG substrate in the cell w all a re mainly homogalacturonan) and can
b e of exo- o r endo- acting t yp es, even if the endo-acting enzymes mo re lik ely
contribute to p ectin dep olymerization in rip ening fruits. An increase in the ac-
tivit y of this enzyme has long b een asso ciated with fruit rip ening, although the
amount detected va ries widely with sp ecies and during the different stage of
1.6. Cell w all gene regulation 18
rip ening. The degrading activit y has b een studied in different systems lik e avo-
cado, cherry , tomato, p each, p epp er, p ea r, grap e, melon, stra wb erry and apple
[2],[18],[89],[110],[168]. PG is resp onsible fo r a majo r comp onent of p olyuronide
solubilization and dep olymerization during rip ening; its action how ever is nec-
essa ry but not sufficient fo r fruit softening [88]. The accumulation is regulated
b y the ethylene, with lo w levels of ho rmone able to induce mRNA accumulation
p rop o rtional to ethylene exp osure [204]. During rip ening, methyl-esterification
of cell w all p ectin declines sensibly from mature green fruit to red rip e fruit, ac-
complished b y Pectin methylesterase (PME), which de-esterifies polyuridonides
allo wing their degradation by PG enzymes. De-esterification of homogalactur-
onans ma y also induce the formation of Ca 2+ b onds among p ectins, reinforc-
ing thus the cell w all structure. P ectate Lyase (PL) catalyse the cleavage of
de-esterified p ectin [34]. β -Galactosidase catalyse one of the la rgest changes
o ccurring in the cell w all of rip ening fruits: the loss of galactosyl residues from
w all p olymers which increases the p o rosity of cell w all and allo ws the access of
other hydrolase to p ectic o r glycan substrates and dep olymerization of structural
p olysaccha rides [29]. Endo 1 → 4 β -D-glucanase (EGase), often referred as cel-
lulase, a re b elived to contribute substantially to fruit softening, they hydrolyze
internal link ages of 1 → 4 β -D-linked glucan chains adjacent to unsubstituted
residues. EGase substrates p robably a re xyloglucan, integral and p eripheral re-
gions of non-crystalline cellulose and glucomannan, where is p resent a sufficient
numb er of consecutive 1 → 4 β -D-link ed glucan residues fo r substrate binding.
These genes have b een describ ed in several sp ecies [29]. Hemicellulose mo difica-
tion is b rought by enzymes such as EGase and Xyloglucan endotransglycosylase-
hydrolase. Xyloglucan endotransglycosylase (Xet), enzymes that a re sp e cific fo r
b oth dono r as w ell as accepto r, catalyse the cleavage of internal link age of 1 → 4
β -D-glucan backb ones of xyloglucan and transfer the newly fo rmed reducing
end to another xyloglucan p olymer o r oligosaccha ride [29]. Xet is b elived to
b e involved in different p ro cesses during plant development, lik e in cell w all
lo osening during gro wth and in the rea rrangements o r strengthen of cell w all b y
an inco rp o ration of newly synthesized xyloglucan into the wall, having thus a
maintenance role [30].
Not all cell w all mo difying enzymes sho w hydrolase o r transglycosylase ac-
tivit y or cau se dep olymerization of ca rb o xymethylcellulose o r cell w all matrix
glycans o r p ectins [158]. Expansins (Exp) strongly b ond to cellulose coated
with matrix glycans, cause a reversible disruption of hydrogen b onding b et w een
cellulose microfib rils and p olysaccha rides matrix, particula rly xyloglucan. This
action b rings to a cell w all relaxation without significat expansion, contribut-
ing along with an increased ap oplastic solutes to the reduction in turgo r and a
turgo r-driven slippage of close microfibrils. In pa rticula r, if xyloglucan is b ound
to cellulose, is not accessible to endo 1 → 4 β -D-glucanase, but the p resence
of rip ening-related Expansin could allo w the lo osening of glucan-xyloglucan hy-
drogen b onds and a sufficient sepa ration b et w een chains to p ermit the bind.
Mo re recently a non-enzymatic scission of p olysaccha rides has b een suggested
1.6. Cell w all gene regulation 19
to contribute to fruit softening during rip ening. The release of asco rbate in the
ap oplast, due to memb rane p ermeabilization, ma y in fact p rovok e ap oplastic
hydro xyl production whose radical is p otentially involved in non-enzymatic scis-
sion of plant cell w all p olysaccha rides [68]. In tomato fruit, o xidative ions and
changes in the activit y of sup erosside dismutase, catalase and enzymes involved
in asco rbate cycle during rip ening, suggest that antio xidative system pla ys a role
in rip ening [115].
The final picture that emerges is a series of different enzymes, whose exp res-
sion is regulated b oth in time and amount during maturation, acting in concert
in an interdep endent and synergyc w a y to control changes in softening and tex-
ture. These enzymes a re controlled b y a la rge numb er of genes, which have, in
turn, to b e regulated and exp ressed co-o rdinately . The complexit y of rip ening
physiology and fruit maturation have b een confirmed b y the recent discovery
that in the genomes sequenced to date almost 10% of the entire gene invento ry
is devoted to cell w all metab olism [154].
1.6.2 Cell w all mo difications during rip ening
During rip ening, cell wall a rchitecture is p rogressively mo dified, determining the
texture p eculia r fo r every fruit [29]. General changes in p olysacha rides a re:
p olyuronide dep olymerisation, loss of galactan and a rabinan, p ectin solubiliza-
tion and demethylesterification, cellulose and glycan matrix dep olymerisation.
Usually the first change observed during rip ening is a bio chemical dissolution of
the middle lamella, the p ectin-rich lay er b et w een cells, b y a series of enzymes
degrading p olysaccha rides [28],[29]. Difference in the middle lamella w as ob-
served b y Ben-Arie et al. [19] in mature ha rd and soft tissue of b oth apple
and p ea r fruits. In apple, cell w all from immature and ha rd fully rip e fruits w as
simila r in structure, sho wing a pack ed fib rillar material in the w all of adjacent
cells as w ell as in the middle lamella. In soft mealy fruits instead, some of the
fib rillar material from the outer pa rt of the w all had undergone dissolution and
app ea red to b e disp ersed and the disassembled middle lamella. Also in p ea r cell
w all from hard mature and immature fruit w as not different. It consisted in fact
of tightly pack ed fibrilla r material and a conspicuous middle lamella in b et ween.
Soft fruits, on the contrary , sho w ed a reduced stainig of cell w alls and spa rce
app ea rance of fib rils. The region o ccupied b efo re b y the middle lamella app ered
then reduced and empt y , sho wing a difference also with apple soft fruits. Ben-
Arie w ork sho w ed also that the action of degrading enzymes do not affect the
w all material surrounding the plasmo desmata and their p ersistence in the cell
w all undergoing degradation in softening fruit. The b reakdo wn of plant tissue,
usually involves cell sepa ration o r cell b reakage as mentioned above. In unrip e
fruits o r unco ok ed vegetables cell adhesion is strong and tissue fraction involves
rupture across cell w alls, releasing cells content and making tissue texture juicy
and crisp y . On the contrary , in softened tissue lik e mealy fruits, middle lamella
undergo es extensive dissolution and the cells a re completely sepa rated up on
1.6. Cell w all gene regulation 20
comp ression, slipping one on the other [233].
Cherry crisp y and soft fruit has b een analysed b y Batisse and collab o rato rs [17]
in o rder to see the difference in suga r content b et ween the t w o textural different
fruit. In pa rticula r they concluded that, during maturit y , crisp y fruits have mo re
neutral suga rs than mealy fruits and, consequentely , mo re p ossibilit y of asso-
ciations b et w een the different cell w all p olymers. In contrast, fo r mealy fruit
the situation w as the opp osit. Crisp y fruits had an higher level of rahmnose,
a rabinose and hemicelloluse while, on the other hand, p resented a descreased
amout of galacturonic acid which is instead p ermanent in soft fruits. The rate
of p rotein synthesis was instead greater fo r the soft fruits than the crisp y ones.
A simila r situation observed for soft cherry , w as discerned fo r apples sto red 30
w eeks [151], where a rabinose and galactose content decreased with time. F o r
apple, in pa rticula r, it has b een suggested that softening is the result of t w o
sequential cell w all mo dification, a loss of galactan which p recedes o r accompa-
nies an increase in soluble p olyuronide, derived from a p ectic p olysaccharide of
relatively lo w neutral suga r content [128]. A very sp ecific declines in cell w all
galactose have also b een rep o rted fo r stra wb erries, p ea rs and tomato es rip ening
[4], [92]. Changes in normal ripening are simila r to the t w o-stages pattern of
w all mo dification observed in apple, with a galactose and arabinose reduction
and an increase of soluble p olyuronide content. F rom this description it is easy
to understand that plant tissue mechanical p rop erties dep end on the contribu-
tion of different levels of structure, and how this levels interact to each other
[233]. The lo w est level is the p olymers constitution of the cell w all, the w a y
they connect and ho w they a re a rranged. The next level is constituted b y cells,
which can differ in shap e, size and o rientation, based on their function. Other
imp o rtant levels a re ho w cells a re o rganised in the tissue and the final o rgans’s
cha racteristics. It is imp o rtant to note that every level of this hierachy involves
p rop erties of the cell w all (Figure 1.3).
Figure 1.3: Schematic rep resentation of the levels of structure contributing to
the mechanical p rop erties of plant tissue [233]
1.7. The ho rmone ethylene 21
1.7 The ho rmone ethylene
1.7.1 Ethylene and fruit rip ening
F ruits have b een catego rized in climacteric and non-climacteric t yp e, dep ending
on their enhanced ethylene p ro duction and asso ciated increase in respiration rate
at the onset of rip ening. In climacteric fruits, such as tomato, apple, p each, and
banana, rip ening is in fact accompanied b y a p eak in respiration and a concomi-
tant burst of ethylene required fo r fruit rip ening. In non-climacteric fruits, such
as citrus, grap e, and stra wb erry , respiration sho ws no drammatic change and
ethylene p ro duction remains at a basal level. These distinctions, ho w ever, a re
not absolute. Melon fruit in fact, can b e b oth climacteric and non-climacteric,
and b oth ethylene dep endent and indep endent gene regulation pathw a ys co exist
in o rder to co-o rdinate the different kind of fruits [6], [14]. T o date, molecula r
facto rs influencing fruit maturation, and pa rticula rly ethylene p erception, have
b een mainly describ ed via mutant and gene cloning in Arabidopsis . Arabidop-
sis fruit is ho wever classified as dry and dehiscent, not favo rable fo r studying
the physiological p ro cess o ccurring in fleshy fruits. F o r this reason tomato has
b een chosen as the mo del sp ecies to study fleshy fruit physiology and genet-
ics. T omato is the most genetically tractable plant system fo r studying fruit
rip ening b ecause of its simple diploid genetics, relatively short generation time,
small habit compa red to fruit crop sp ecies, e xcellent genetics, facilit y of rou-
tine transfo rmation and extended rep ertoire of genetic and genome info rmation
(http://www.sgn.co rnell.edu/) [14]. Besides tomato, other plants have b een
used to study the rip ening p ro cess. Stra wb erry fo r example, is a p rima ry mo del
fo r non-climacteric fruits but also apple, p each o r citrus a re b ecoming mo dels
fo r genomics analysis of fruit rip ening in fruit crop sp ecies.
Ho rmonal involvement on plant development was discovered observing plant
placed nea r artificial illumination. Coal ca rb on w as an imp o rtant source of light
but its relevance w as “illuminant” also for fruit ripening process [40]. In 1858
F ahnesto ck attributed the deterio ration of a collection of plants in greenhouse
to the p resence of illumination gas, even if he w as not able to identify the
resp onsible comp onent. Some yea rs later, Gia rardin verified that trees gro wing
nea r places with leaking gas illumination show ed senescence symptoms. In
1886 Neljub ov discovered that the o rizontal gro wth of etiolated p ea seedlings
w as casused by ethylene, the biologically active comp onent of illumination gas.
Since that several observation w ere made on ethylene effects on plants and
in 1930s most of the physiological effects had already b een describ ed. The
chemical p ro of that plants naturally p ro duce ethylene w as p rovided b y Gane in
1934 after a study on apple rip ening, and later, in tomato, the p ro duction of
this ho rmone was associated with a p eak in the respiration rate. Elucidating
that the mechanisms that a re involved in the fruit rip ening p ro cess a re a crucial
k eys to understand fruit quality .

1.7. The ho rmone ethylene 22
1.7.2 Ethylene biosynthesis
Ethylene pathw ay is w ell estabilished in higher plants and is synthesized from
methionine in three fundamental steps [22] (Figure 1.4):
1. conversion of methionine to S-adenosyl-L-methionine (SAM) b y the SAM
synthetase enzyme,
2. fo rmation of 1-amino cyclop ropane-1-ca rb o xylic acid (A CC) from SAM via
A CC synthase (ACS),
3. conversion of ACC to ethylene, which is catalyzed b y ACC o xidase (A CO).
Figure 1.4: P athw ay of the ethylene biosynthesis and metab olism [177]
The fo rmation of ACC also leads to the p ro duction of 5’-methylthioadenosine
(MT A), which is recycled via the methionine cycle to yield a new molecule of
methionine [14]. This savage pathw a y p reserves the methylation group through
every revolution cycle at the cost of one molecule of A TP , in this w a y ethylene
biosynthesis can b e mantained even when the p o ol of free methionine is lim-
ited [6]. A CS and ACO a re b oth enco ded b y a multigene families in all plant
sp ecies studied and their exp ression is regulated acco rding to plant developmen-
tal stage, environmental and ho rmonal signals [121]. Up to no w Arabidopsis
genome p resents nine differently regulated ACS genes that encode eight func-
tional and one non-functional A CS proteins [14]. In tomato plants, nine genes
enco ding A CS have b een describ ed to date, four of which a re differentially ex-
p ressed during fruit rip ening; five A CO where instead identified, three of which
a re differentially expressed in fruit [32], [140]. In pre-climacteric tomato fruits,
few memb ers of the A CS and A CO gene families (namely , Le A CS1, Le A CS3,
Le A CS6, Le A CO1 and Le A CO4) are active and responsible for System 1 basal
ethylene biosynthesis. During rip ening, the transition to System 2 is the result
of Le A CS6 sile ncing and increased exp ression of Le A CS2, Le A CS4, Le ACO1
and Le A CO4 [6], [14]. A CS and A CO genes have b een cha racterized in many
other fruits lik e melon [240], apple [64], banana [142], kiwifruit [238], p each
[192] and p ersimmon [166]. A CS was initially considered as the k ey regulato ry
enzyme in ethylene biosynthesis pathw ay since the rate-limiting reaction of ethy-
lene biosynthesis pathw ay is the conversion of S-adenosylmethionine into A CC,
1.7. The ho rmone ethylene 23
and A CO activity w as thougth constitutuve; ACO role ho w ever b ecome appa rent
in recent y ears. The rise of the activit y of this enzyme p recedes A CS activit y in
p reclimacteric fruit resp onse to ethylene, indicating that A CO is also imp o rtant
fo r controlling the ho rmone p ro duction [6]. In climacteric plants t w o systems
of ethylene regulation have b een p rop osed. System 1, which functions during
no rmal growth and development and during stress responses, is regulated by
an autoinhibito ry feedback, such that exogenous ethylene inhibits the ho rmone
synthesis. System 2, which op erates during flo ral senescence and fruit rip en-
ing, is stimulated b y ethylene and is therefore under an auto catalytic feedback
regulation, and inhibito rs of ethylene inhibit ethylene production [157].
1.7.3 Ethylene p erception
Much of what is no wada ys kno wn rega rding the steps involved in ethylene p er-
ception and signalling transduction, derived b y studies ca rried out on the mo del
plant sp ecies Arabidopsis (Figure 1.5).
Figure 1.5: Current mo del fo r the ethylene signal transduction pathwa y [242]
Ethylene is sensed in Arabidopsis b y a family of receptors which a re related
to bacterial t wo-component histidine kinase (HK) senso rs that bind ethylene
through their N-terminal domain, lo calized in the endoplasmic reticulum [170],
[180]. In Arabidopsis there a re five memb rane recepto rs (ETR1, ETR2, ERS1,
ERS2 and EIN4), while six a re the recepto rs in tomato ( Le ETR1, Le ETR2,
Le ETR4, Le ETR5, Le ETR6 and NR). Analysis of ethylene recepto r null muta-
tions have led to the p rop osal of an inverse-agonist mo del fo r ethylene receptor
1.7. The ho rmone ethylene 24
signaling. In absence of ethylene, fo r instance, the receptor is costitutively ac-
tive, whereas when ethylene is b ound, the receptor in switched off [242]. These
recepto rs thus act as negative regulators through another negative regulato r: the
COSTITUTIVE TRIPLE RESPONSE1 (CTR1). Downstream this regulato r, a
memb rane metal transp o rter-lik e, named EIN2, has a pivotal role in ethylene
signaling. CTR1 seems to regulate the availabilit y of the k ey transcripto r factor
named EIN3, through an unkno wn mechanism. In resp onse to ethylene, EIN3 is
stabilized and accumulated in the nucleous activating ho rmone-inducible p rima ry
transcription [94], [242]. Without exogenous ethylene induction o r application,
EIN3 is degraded constantly through the 26S p roteasome. Successively EIN3
and EIN3 lik e1 transcription factors activate ETHYLENE RESPONSE F A C-
TOR1 (ERF1), which induce the exp ression of the seconda ry resp onse gene in
ethylene-dep endent transcription cascades.
Many fundamental comp onents in the ethylene signal transduction pathw a y
a re also controlled by ethylene, p roviding in this w ay , la y ers of negative o r p os-
itive feedback lo ops fo r the co rrect tuning of resp onse dynamics. ERS1, ERS2
and ETR2 transcripts increase in fact as p rimary response to ethylene [109].
The newly synthesized recepto rs that have not yet perceived ethylene might
supp ress the downstream ethylene signaling, diminishing the ho rmone resp onse
as negative feedback mechanism. By contrast, ethylene binding can initiate the
p roteasome-dep endent degradation of Arabidopsis ETR2, and might increase
the ethylene sensitivit y in plant [242]. Upstream the ethylene regulato ry cas-
cade, is p ossible to identify different developmental transcription facto rs lik e
fo r example MADS-b o x, CNR o r NA C genes. The study of rip ening mutant
sp ecific fo r this gene set, allo w ed to b etter understand their role in rip ening
regulation. Tw o w ell cha racterized phenot yp es a re no r (non-rip ening) and rin
(rip ening inibito r) mutant. In tomato, rin mutant fails to exibit the t ypical
rip ening-asso ciated increase in ethylene p ro duction, lacks in the p ro-vitamin A
and ca rotenoid accumulation and show es a reduced softening and flavour com-
p ounds p ro duction. Rin lo cus enco des a MADS b o x transcription facto r, and
phenot yp e has b een interp reted to reflect a function in rip ening control over
climacteric ethylene synthesis, p robably controlling genes envolved in ethylene
biosynthesis pathw ay [86]. Neverthless, rin fruit do not rip en in resp onse to ex-
ogenous ethylene, y et they displa y induction of at least some ethylene-resp onsive
genes, indicating retention of fruit ethylene sensitivit y . These results have b een
interp retated to mean that the RIN gene enco des a genetic regulato ry comp o-
nent necessa ry to provok e climacteric respiration and rip ening-related ethylene
bio-synthesis, in addition to require facto rs whose regulation is not ethylene
influenced. This picture sho ws that RIN acts upstream of b oth ethylene and
non-ethylene mediated rip ening control [242]. No r mutation effect on tomato
phenot yp e is simila r to rin , except for the final fruit colour that is pale o range.
These t wo mutantion a ffect the abilit y of fruits to produce auto catalytic ethy-
lene, thus to rip en in resp onse to exogenous ethylene [162].
As p reviously rep o rted, in climacteric fruit, rip ening is mainly controlled
1.7. The ho rmone ethylene 25
b y a signalling pathwa y and involves the ho rmone ethylene p erception. This
physiological mechanism has b een used to develop strategies fo r the control of
the climacteric fruit rip ening. One of these strategies relies on the use of 1-
methylcyclop rop ene (1-MCP), a cyclop rop ene derivative, which chemical struc-
ture is simila r to natural ethylene, which binds p ermanently to the ethylene
recepto rs present at the time of treatment, comp eting thus with ethylene bind-
ing. It has b een demonstrated that any return of ethylene sensitivit y is due to
app ea rance of new binding sites [21]. The effect of this inhibito r is va riable
dep ending, on the temp erature, gro wing region, the concentration at which 1-
MCP is applied o r dela ys b et w een ha rvest and fruit treatment [236]. Relatively
little info rmation concerning commercial asp ects of its use a re available; one ex-
ception is apple, fo r which 1-MCP based technology is available throughout the
w orld and fo r which many studies have b een already realised [235], [236]. Apple
va rieties differ each other for ripening rates, ha rvest criteria, p ost ha rvest han-
dling p ro cedures and sto rage p erio ds in controlled atmosphere; is therefo re not
surp rising that these facto rs affect resp onse to the inhibito r. These resp onses
could b e a combination of the effects of the internal ethylene concentration at
the ha rvest p oint, the physiology of the cultivar and their abilities to develop
new ethylene recepto r sites. 1-MCP impact on fruit rip ening science is double,
on one side, in fact, is a comp ound that allows a longer shelf life of ha rvested
fruit, on the other side, is a p o w erful to ol fo r the scientific investigation on
ethylene-dep endent rip ening and fruit senescence.
Eht ylene even having a key role in fruit ripening, is not the unique ho rmone
able to influence plant biology; in fact hormones, including jasmonates, auxin,
and b rassinosteroids, have all b een implicated, together with light and suga r, in
the p romotion of rip ening in va rious sp ecies [14].
1.7.4 Ethylene impact on cell w all metab olism
Enzymatic dynamics, which act in concert in the cell w all mo dification, a re, in
climacteric fruit, fo r the most guided b y the gaseous ho rmone ethylene. Ethy-
lene, in fact, trigger and co-o rdinates the gene activation and exp ression in
genetically p rogrammed sequence.
Accumulation of PG mRNA in tomato, fo r istance, is regulated b y ethy-
lene, with low levels of the ho rmone b eing sufficient fo r inducting the mRNA
accumulation, which increased under ethylene exp osure. Mo reover, PG mRNA
accumulation is ethylene regulated in a concentration and time dep endent man-
ner [204]. The mRNA adbundance of a tomato expansin, LeExp1 , resulted to
b e p ositively and directly regulated b y ethylene in rip ening fruit. Its level is,
in fact, strongly diminished after treatments with ethylene antagonists and in
rip ening plants mutant fo r ethylene syntesis [188]. β -galactosidase activit y is
also ethylene regulated; it w as in fact observed that the total content of β -
galactosidase w as mark edly reduced in non rip ening tomato mutant when com-
pa red to the wild type. In these mutants the loss of cell w all galactose and the
3.2. Intro duction 32
3.2 Intro duction
T exture rep resents one of the four p rincipal facto rs defining fo o d/fruit qualit y ,
together with app ea rance, flavour and nutritional p rop erties [25], and pla ys
a k ey role in consumer acceptabilit y and recognition of apples. In pa rticula r,
textural cha racteristics of apples define d b y “crispness”, “juiciness”, “ha rdness”,
“firmness” and “mealiness” a re often k ey drivers of consumer p reference [99].
T exture o riginates from several different physical p rop erties rather than from a
single trait, and dep ends on cellula r structure and ho w this resp onds to applied
fo rces [210]. In fruit and vegetables, crispness and crunchiness a re mechanically
exp ressed as a rapid decrease in fo rce accompanied b y a rapid textural fracture
p ropagation. They no rmally rep resent the majo r traits contributing to general
“fo o d enjo yment” since b oth a re considered b y consumers as an indication of
the freshness and healthy state of fruit [209], [80], [81].
In apple it has b een sho wn that among the textural traits, crispness accounts
fo r 90% of texture appreciation, and it has b een la rgely recognised as the k ey
attribute affecting consumer acceptabilit y [97]. Microscopically , when the w all
of a turgid cell is b rok en under mechanical p ressure, a sound p ressure w ave is
generated, resulting in the t ypical “sound” p erceived as the crisp y phenot yp e.
Crispness events and sound p ressure waves a re strictly dep endent on the b reaking
p ropagation tow a rd adjacent cells, where the p ressure exerted on the outer cell
w all causes a catastrophic rupture [124]. In crisp y apples, the cell b reak age
generates a sound w ave which causes a vibration betw een molecules a round their
equilib rium, consequently propagating the p ressure w ave and thus producing the
sound [66].
In contrast, low cell w all turgidit y , due to a higher elastic tension of the w all,
o r by pectic p olysaccha ride solubilisation in the middle lamella, determine cell
sepa ration instead of cell wall fracturing [60], with a consequent rubb ery tex-
ture t ypical of mealy apples [184], [167], [7]. Cell rupture (the event generating
crispness) o r separation (responsible for mealiness) have also a direct impact
in the release o r encapsulation of juice and a roma [124], [70]. Therefo re, a
crisp y apple is generally preferred not only fo r texture cha racteristics, but also
fo r an enhanced release of volatile comp ounds p erceived b y the receptors in the
mouth space. T o date, the most complete description of crispness is p rovided
b y sensory testing ca rried out b y exp ert o r trained panellists. Ho wever, there
a re fundamental limitations to this approach due to the difficulties in emplo y-
ing such a strategy fo r assessment of large cultiva r collections and b reeding
material. T o overcome these constraints, instrumental app roaches dedicated
to fruit/fo o d textural qualit y analysis have b een develop ed [190], and do cu-
mented in several studies rep o rting textural analysis in apple p erfo rmed with
different techniques, such as compression [159], single-edged notched test [102],
sound reco rding during mastication [190] and chewing sound measurements [59],
[112]. Ho w ever, the comparison betw een the sound amplitude reco rded during
the fruit biting and the co rresp onding crispness senso rially evaluated resulted

3.3. Materials and metho ds 33
ha rdly reproducible and panellist dep endent [60]. Other metho dologies based
on mechanical app roaches fo cus on the physical resp onse of the samples, such
as defo rmation, fracturing and comp ression, the latter b eing p robably the most
widely used fo r its simplicity [190]. The use of the puncture test to p redict
consumer p reference has b een also review ed and questioned [101].
Novel technological imp rovements in the direct measurement of fruit texture
have b een recently p resented b y T aniw aki et al. [213], based on the concept
that the senso rially p erceived crispness could b e derived b y the vib ration p ro-
duced during the fracturing (p rop osed b y Christensen and Vick ers, [41]). This
device rep resented by a piezoelectric sensor able to detect the vib ration caused
b y the sample’s fracture has b een used to quantify a texture index (TI) in several
sp ecies, including apple [213], [215]. This equipment w as also further coupled
with non-destructive vib ration metho ds (Laser Doppler Vib rometer- LDV) to
measure the change of b oth elasticit y and texture index during the rip ening of
p ersimmons [214] and p ea rs [212]. It is lik ely that the combination of different
metho dologies ma y rep resent a further imp rovement fo r mo re efficient texture
investigation, as already demonstrated in almonds, where a simila r strategy
w as successfully applied and co rrelated with senso ry evaluation [222]. Recently
Zdunek et al . [245] rep o rted crispness and crunchiness evaluation of three apple
cultiva rs by measuring the contact acoustic emission together with the puncture
test, and show ed that the senso ry attributes related to crispness and crunchi-
ness co rrelated b etter with acoustic emission events rather than firmness. The
purp ose of our w o rk w as the imp rovement of the texture va riabilit y dissection,
increasing the numb er of pa rameters acquired during the comp ression phase. W e
investigated whether mechanical and acoustic cha racterisation of a set of apple
cultiva rs could provide a valuable methodology able to encompass all asp ects
related to apple texture, p roviding also a b etter link with senso ry attributes.
3.3 Materials and metho ds
3.3.1 Plant materials
In this exp eriment w e selected 86 apple cultiva rs ha rvested in 2009 in the ex-
p erimental fields of t w o institutions: the Innovation and Resea rch Centre of
Edmund Mach F oundation in San Michele all’Adige (T rento), and the Resea rch
Institute Centre of Agriculture and F orestry Laimburg (B olzano), b oth in the
No rth of Italy (T rentino-Alto Adige region) and with simila r climatic condition
(Supplementa ry T able 8.1). All fruit were collected at commercial harvest, fol-
lo wing the main parameters used to monito r the maturit y and rip ening evolution
(standa rd practice), lik e fruit firmness, skin colour and total acid and sugar con-
tent. All ha rvested fruit were sto red in a cold cella r at 2-4 ◦ C with a relative
humidit y of 95% for t w o months, and p rio r to start the instrumental analysis
fruit w ere kept overnight at ro om temp erature (20 ◦ C). F o r each cultiva r only
samples with simila r size and without visible external damage w ere chosen.
3.3. Materials and metho ds 34
3.3.2 Instrumental analysis: empirical metho ds and textural as-
sessment
F ruit firmness was initially measured using a digital fruit firmness tester (TR
T uroni srl, Fo rl ` ı, Italy) with a 11mm p rob e (held on a stand) on five fruit
samples fo r each cultivar. F o r each fruit, tw o puncture tests w ere p erfo rmed on
the t wo opposite p eeled fruit sides. F or each cultiva r, ten measurements w ere
obtained, analysing the maximum resistance required to enter the p rob e fo r
8mm. T o p erfo rm a mo re comp rehensive analysis of the fruit texture, w e used
a coupled acoustic-mechanical p rofile investigation of the use of a T A-XTplus
T exture Analyzer equipp ed with an Acoustic Envelop Detecto r (AED) device
(Stable MicroSystem Ltd., Go dalming, UK). On the same fruit selected from
the batch o r cultiva r, a cylindrical p o rtion of co rtex tissue w as sampled with
a flesh blade sampler along the vertical lengthwise plane p erp endicula r to the
direction of the puncture test, avoiding the co re p o rtion with seeds. From each
cylinder, four identical discs with a diameter of 1.70 cm and 1 cm thick (after
removing the outer ma rgins with p eel) w ere cut with a home-made six-blade
knife. Adopting this strategy , w e avoided any p ossible influence of fruit size, as
suggested b y Duizer [66]. F o r each cultiva r 20 discs, comp osed of four technical
replications fo r five biological replicates, were tested. The fo rce/displacement
measurement w as carried out using a 5 kg loading cell and a cylindrical flat head
p rob e with a diameter of 4mm. The mechanical p rofile graph w as based on tw o
va riables: fo rce (N) and distance (strain, %). The fo rce w as measured with the
follo wing T A-XT plus settings: test sp eed of 300 mm/min, auto fo rce trigger of 5
g and stop plot at ta rget p osition. Distance was exp ressed in strain, compressing
the sample disc until a defo rmation of 90%. Acoustic p rofiling, as a measure
of sound reco rding, was op erated simultaneously to the force assessment b y
the AED device. The sound generated during the sample comp ression w as
detected with a Br¨ uel & Kjaer microphone (t yp e 4955) p ositioned app roximately
5 cm from the apple disc. The microphone w as calib rated t wice with a sound
calib rator Br¨ uel & Kjaer (t yp e 4231), setting the sound p ressure level calib rato r
(SPLC) initially at 114 dBs (kno wn high level), and then it w as rep eated at
94 dBs (kno wn low er sound p ressure level). Both measurements w ere used to
transfo rm voltage signals into decib els. The envelop gain w as set at 4 (on a 0 to
11 scale, with a gain of x6 dB) co rresp onding to 24 dB, in o rder to increase the
sensitivit y of the system to our environmental condition. The sound pressure
signal, registered b y the microphone, w as automatically converted in dB units
and plotted. With the settings chosen in this exp eriment the emitted sound fell
in the range b et w een 36 dB (background level) and 78 dB (maximum acoustic
p ressure registered during the exp eriment). The acoustic cut off selected b y
the envelop co rner frequency was 3.125 KHz. The acoustic graph w as based
on t wo va riables: sound p ressure level (SPL in dB) and strain (%). F o r b oth
p rofiles, data w ere acquired with a rate of 500 pps (p oints p er second). F rom
the combined mechanical/acoustic p rofile a total of 16 pa rameters w ere defined,
3.3. Materials and metho ds 35
of which 12 w ere derived by the mechanical graph and 4 b y the acoustic p rofile
(T able 3.1).
The value of the pa rameters w ere calculated from the fo rce displacement
curve where four fo rce values (related to the slop e o r yield p oint, maximum
fo rce, fo rce at the end of the travel and mean value), numb er of force peaks,
a rea (compression’s w o rk), fo rce linea r distance, numb er of p eaks/distance, lin-
ea r distance/distance and Y oung’s mo dule (o r elasticit y mo dule) can b e identi-
fied. F rom the mechanical p rofile w e have also derived t w o pa rameters, namely
fo rce index and force difference, b oth linked to the mechanical curve direc-
tionalit y . These t w o indexes, b eing asso ciated with physical p roprieties of the
underlying cell la yers, p rovide info rmation related to the adhesion and comp res-
sion b ehaviour of the cells (indicating where the maximum fo rce o ccurs) and the
relative magnitude level. Mo reover, w e have ta rgeted four pa rameters on the
acoustic signature related to the acoustic p eak numb er, maximum and mean
acoustic p ressure and acoustic linear distance.
3.3.3 Rip ening stage evaluation
Prio r to instrumental analysis, the rip ening stage of each fruit used in the exp eri-
ment w as instrumentally assessed with a p o rtable visible/nea r infra red (vis/NIR)
sp ectroscop y ([249]; [47]; commercialized b y TR T uroni srl, F o rl ` ı, Italy). This
equipment w as used in order to obtain a rapid, non destructive and objective
cha racterization of rip ening. This is necessa ry b ecause the cultiva rs considered
in this exp eriment w ere ha rvested at different times sta rting from mid July to
the end of Octob er.
3.3.4 Senso ry evaluation b y untrained exp ert panels
Senso ry data on a subset of 21 cultiva rs (listed in Supplementa ry T able 8.1)
w ere collected over 5 y ea rs at the Laimburg Research Centre fo r Agriculture and
F orestry in a specific lab o rato ry used fo r sensory testing. The panel, comp osed of
a minimum of 12 to a maximum of 23 judges, w as recruited from the Laimburg
Resea rch Centre staff exp ert in the field of apple b reeding. F o r each evaluation
da y , six different samples (with 5 replicas/sample) w ere analyzed. Each sample
w as presented to the panellist as anonymous p eeled apple slice and evaluated
on a 1 to 9 scale, where 1 w as used fo r lo w (soft, mealy and dry) and 9 fo r high
(firm, crisp y and juicy) values resp ectively . The three attributes evaluated were
defined fo r firmness as the mechanical resistance exerted b y the sample during
chewing, crispness as the acoustic emission during the first bite and juiciness as
the p erceived release of juice in the mouth space during mastication.
3.3.5 Data analysis
Data acquisition of the combined acoustic-mechanical p rofiles w as p ro cessed b y
the soft wa re Exp onent v.4 (Stable MicroSystem) p rovided with the T A-XT plus
3.3. Materials and metho ds 36
Mechanical P a rameters General description Unit
Yield F o rce F o rce measured at the yield p oint indicating the transition from the elastic to the plastic phase of the compressed sample N
Max F o rce Maximum fo rce value reco rded over the p rob e’s travel N
Final F o rce F o rce measured at the end of the p rob e’s travel N
Mean F o rce Mean fo rce value over the entire mechanical p rofile N
F o rce Peak Numb er of counted fo rce p eaks -
Area Area underlying the mechanical p rofile N%
F o rce Linear Distance Computation of the fo rce curve length -
Y oung’s Mo dule Elasticit y mo dule, computed as ratio b et ween stress and strain N%
P eaks/Distance Numb er of P eaks/mm of p rob e’s travel calculated as physical distance on the x axis -
Linea r Distance/Distance Averaged length of linea r distance /mm -
∆ F o rce Difference b et w een F1 and F3, giving the direction of the fo rce p rofile N
F o rce Ratio Ratio b et w een F1 and F3, rep orting the magnitude of the direction change -
Acoustic P a rameter General description Unit
Acoustic P eak Number of the acoustic p eaks calculated ab ove the threshold of 10 dB -
Max Acoustic Pressure Highest acoustic p eaks detected on the sound p ressure w ave dB
Mean Acoustic Pressure Mean value of the sound p ressure reco rded over the acoustic p rofile dB
Acoustic Linea r Distance Computed length of the acoustic p rofile -
T able 3.1: Description of the mechanical and acoustic pa rameters.
3.4. Results and Discussion 37
instrument. With the same soft w are a macro instruction w as also compiled to
automate the pa rameter extraction from the fo rce/sound curves. Basic descrip-
tive statistical analysis, in pa rticula r b o xplots, P ea rson correlation analysis, p rin-
cipal comp onent analysis (PCA), pa rtial least squa res (PLS) and dendrograms
fo r cluster analysis (Manhattan distance and the complete link age metho d; [8])
w ere carried out in R. Details on PCA and PLS can b e found in Jolliffe (2002)
[117] and Ma rtens and Naes (1992) [150]. Ro ot mean squa re erro r of cross
validation (RMSECV) w as used to quantify the quality of the p rediction mo del
[150].
3.4 Results and Discussion
3.4.1 Acoustic-mechanical combined p rofile analysis
The T A-XT plus texture analyzer equipp ed with the AED system allow ed the
simultaneous acquisition of t wo different t yp es of source data, acoustic and
mechanical, that a re efficiently collected b y the same instrument, as w ell as
plotted and analyzed b y the same softw a re.
The mechanical p rofile obtained as a resp onse to compression is mainly
comp osed b y t w o pa rts (Figure 3.1).
Figure 3.1: F o rce defo rmation p rofiled during the p enetration of an apple disc.
F1: yield fo rce; F2: maximum fo rce; and F3: final fo rce. Ancho rs a re indicated
with a and b,
In the first step a comp ression slop e is observed until the yield p oint (F1),
which ma rks the transition from the elastic (reversible) to the plastic phase of
the material (irreversible crushing). On the comp ression slop e Ho ok’s region
the compiled macro computed the Y oung’s mo dule (o r elasticit y mo dule), a
pa rameter directly linked to the stiffness p rop rieties of the sample and p ositively
co rrelated with the crispness sensorially evaluated, as suggested b y Duizer [66].
After the yield p oint the p rob e b reaks the tension of the outer tissue, sta rting the

3.4. Results and Discussion 38
travel through the apple disc. On the mechanical travel, t w o other p oints w ere
identified: maximum fo rce (F2) and final fo rce (F3). Three main mechanical
b ehaviours w ere identified after the yield p oint from the comp ression profile
(Supplementa ry Figure 8.1): (i) descending resistance, where the yield p oint
fo rce value is higher than final p oint (F1 > F3); (ii) equal resistance, when these
t wo points are at a simila r level (F1 = F3); (iii) increased resistance, exerted b y
the comp ressed lay ers, resulting in an increased comp ression resistance during
the p rob e travel (F1 < F3). The high heterogeneit y of the fruit tissue creates a
continuous series of b rittle micro events leading to a jagged p rofile that generates
the acoustic signal. Dep ending on the fruit flesh anatomic features, each va riet y
resp onds with a distinct sound p rofile due to the acoustic emission generated
during the p rob e travel (Supplementa ry Figure 8.2). As in the case of the
fo rce displacement, the sound curve was also reco rded until a comp ression of
90%, resulting in a cha racteristic acoustic signature for each cultiva r analyzed.
The sound w as reco rded b y a microphone directly p ositioned nea r the sample.
Such a metho d is rema rk ably different from the emplo yment of an op erato r fo r
the sound reco rded emitted during biting, where the b one-conducted sound is
registered, often damp ed b y mouth tissues [144].
Figure 3.2 sho ws the differences in the combined textural profiles of three
selected cultiva rs. The first va riet y , Delearly (Figure 3.2 panel a), is distinguished
fo r its low er general textural p erfo rmance. The other t w o cultivars, Granny
Smith and COOP39 (Crimson Crisp), resp ectively (Figure 3.2 panel b and c),
b oth had a higher acoustic resp onse, but with a clea r difference in mechanical
b ehaviour, b eing COOP39 much firmer than Granny Smith.
The 16 pa rameters identified here through the analysis of the combined
acoustic-mechanical p rofile were extracted from the 86 cultiva rs sho wing a wide
trait va riation (Supplementary Figure 8.3), as a result of the different genetic
control of the textural traits as w ell as different p ost ha rvest rip ening p erfo r-
mance during sto rage. Along with the data p ro cessed b y T A-XT plu s, w e also
included in the analysis the data obtained from the firmness measurements ca r-
ried out b y the fruit digital puncture test (p enetrometer), which is still the most
common instrument utilized in texture analysis [99]. The p enetrometer alone is
limited to a single data p oint/measurement, currently considered inapp rop riate
to describ e complex apple texture va riabilit y [112]. The use of the T A-XT plus
coupled with the AED allo w ed us to ta rget several parameters related to fo rce
displacement and acoustic resp onse p rofiling, which can contribute to b etter
define the apple fruit qualit y .
3.4.2 Clustering and p rincipal comp onent analysis (PCA)
Data related to the pa rameters computed here w ere standa rdized b y means sub-
traction and rescaled b y standard deviation, and dendrograms w ere constructed
to displa y the clustering of the cultiva rs acco rding to their textural p rop erties
(Supplementa ry Figure 8.4). Clustering based only on mechanical parameters
3.4. Results and Discussion 39
Figure 3.2: Combined mechanical and acoustic p rofile of three apple cultiva rs:
Delea rly (A), Granny Smith (B) and COOP39 (C). The black line refers to the
fo rce displacement.
3.4. Results and Discussion 40
results in some inconsistency . F o r instance, Granny Smith w as p ositioned in
a different group with resp ect to the cultiva rs with a simila r crisp y b ehaviour,
such as F uji and Cripps Pink, and group ed closer to Golden Delicious than the
other t wo va rieties. Previous rep o rts have already published the distinct crisp y
p rop erties of these cultiva rs, indicating Granny Smith, F uji and Cripps Pink had
sup erio r crispness compa red to Golden Delicious after a sto rage p erio d [53],
[113], [81]. Implementing the acoustic pa rameters in the computation, Fuji,
Cripps Pink and Granny Smith w ere clustered together, while Golden Delicious
w as group ed with cultiva rs with mealy o r lo w textural properties after storage,
such as Renetta Canada, Elsta r, Gloster and other old apple varieties. The ob-
served change in cluster o rganization validates the implementation of acoustic
pa rameters for a better characterization of textural p rop rieties.
Multiva riate statistical techniques, such as p rincipal comp onent analysis
(PCA), illustrate the main features rega rding the cultivars investigated in a
single bidimensional plot. Figure 3.3 shows the p rojection of the data on the
first t wo p rincipal comp onents (PC1 and PC2) that explain 83.4% of the total
va riance (PC1: 71% and PC2: 12.4%).
Figure 3.3: First t wo dimensions of PCA analysis of the texture data, calculated
using all pa rameters extracted from the combined mechanic and acoustic anal-
ysis. Numb ers indicate the apple cultiva rs as rep o rted in Supplementa ry T able
8.1, a rrows ma rk the pa rameters co o rdinates.
Each pa rameter is indicated by an a rro w, and the entire set of va riables is
3.4. Results and Discussion 41
clea rly separated into three main groups: the first one related to the mechanical
pa rameters, the second group joined together the acoustic parameters, while
the third group comp rises the tw o derived pa rameters ( ∆ fo rce and fo rce ratio),
b oth describing the fo rce direction change (named fo rce direction). The three
sets of va riables highlighted b y PCA rep resented the three types of info rmation
related to fruit texture. In addition it is imp o rtant to note that the t wo mechan-
ical pa rameters “numb er of fo rce p eaks” and “numb er of fo rce p eaks/distance”
w ere group ed in the acoustic pa rameter set, suggesting that these pa rameters
a re suitable to describ e the acoustic p rofile. This asso ciation could b e explained
considering that the crispness resp onse is la rgely controlled b y the rapid drop
in fo rce o ccurring during the mechanical comp ression, and thus asso ciated with
the fracturing p rogression, as describ ed by Vincent [228]. On the PCA plot
(Figure 3.3( the first axis describ es the va riabilit y related to b oth acoustic and
mechanical pa rameters, sepa rating mealy apples (group A in Figure 3.3) such as
Delea rly (27),Dalla Rosa (23) and Ea rly Gold (30), from b oth ha rd and crisp y
apples, on the p ositive and negative section of the plot, resp ectively . The second
comp onent describ es the va riabilit y asso ciated with the interpla y of acoustic and
mechanical pa rameters. Along the p ositive axes of the second comp onent, apple
cultiva rs COOP39 (16), Nevson (57), CIV G198 (14) Scifresh (78) and Delco ros
(26) w ere characterized b y a high level of firmness and acceptable crispness. In
compa rison, apple cultiva rs along the negative axes of PC2 a re cha racterized b y
a higher acoustic signature and a lo wer firmness the va riabilit y related to b oth
acoustic and mechanical pa rameters. Along the p ositive axes of the second
comp onent, apple cultiva rs COOP39 (16), Nevson (57), CIV G198 (14) Scifresh
(78) and Delco ros (26) were cha racterized b y a high level of firmness and ac-
ceptable crispness. In compa rison, apple cultiva rs along the negative axes of
PC2 a re characterized b y a higher acoustic signature and a lo w er firmness than
the p revious ones. It is w orth noting that the cultiva rs considered to have the
b est fruit qualit y w ere included in this latter group (group C in Figure 3.3) such
as Minnew ashta (55), Ligol (50), F uji (35), Granny Smith (44), Cripps Pink
(18) and Amb rosia (1). The correlation matrix over the entire pa rameter set
(Supplementa ry Figure 8.5) confirmed the indications of the PCA: the mechani-
cal pa rameters were in fact significantly co rrelated, with values ranging b et w een
0.81 and 0.99 (p < 10 − 4 ) , apa rt from the numb er of fo rce p eaks (and conse-
quently the numb er of p eaks/distance), which are less co rrelated with the rest
of the mechanical readings (p < 10 − 4 ) than with the acoustic data (p < 10 − 4 ).
In the follo wing we will refer to the mechanical pa rameters excluding “numb er
of p eaks” and “numb er of p eaks/distance”. Mechanical parameters exhibited a
mo derate co rrelation (p < 10 − 4 ) with the acoustic data, indicating the necessit y
of complementing textural analysis with acoustic data fo r a b etter dissection of
general trait complexit y . Indeed in our PCA plot w e observed that some cul-
tiva rs, rep resented b y Ananas Renette (2), Tiroler Spitzlederer (83), Breaburn
(8) and Nevson (57), despite their high average firmness values of 16.25, 17.62,
12 and 13 N, sho w ed a limited numb er of acoustic p eaks: 35, 31.7, 46.1 and
4.3. Materials and Metho ds 48
4.3 Materials and Metho ds
4.3.1 Plant material
Tw o full-sib progenies derived b y crossing the high texture qualit y apple cv.
’F uji’ (common maternal parent) with cv. ’Delea rly’ (p o o r texture cultiva r) and
cv. ’Pink Lady’ (high texture cultiva r) had 94 seedlings each, w ere lo cated in the
same blo ck at the exp erimental o rcha rd of FEM (F oundation Edmund Mach,
T rento, Italy), and maintained in situ follo wing standa rd technical management.
Each individual w as grafted on M9 ro otsto ck, and at the time of the first
ha rvest the plants were 10 y ea rs old. T otal genomic DNA w as isolated from
y oung leaf tissue using the Qiagen DNeasy Plant kit. DNA quantit y and qualit y
w as measured sp ectrophotometrically with a Nano drop ND-8000 R
 (Thermo
Scientific, USA).
4.3.2 F ruit texture assessment
The optimal ha rvest time fo r the t wo progenies, o ccurring from August to the
b eginning of Novemb er, w as instrumentally determined through the use of a
vis/NIR (nea r infrared spectrometer) DA-meter [47], collecting the samples
within a IAD range of 1-1.4. After ha rvesting, fruit samples w ere sto red at
2 ◦ C in a controlled temp erature cella r fo r t w o months p rio r to assessment. High
resolution phenot yping was ca rried out measuring the apple texture comp onents
in three consecutive y ears (2008, 2009 and 2010). F o r the first t w o y ea rs b oth
p opulations w ere assessed, while fo r the last exp erimental season the pheno-
t yping was ca rried out only fo r ’F uji x Delea rly’ (’FjxDel’). ’F uji’, as kno wn, is
affected b y biennial b ea ring, and b ecause of that the yield of 2010 fo r ’F uji x
Pink Lady’ (’FjxPL’) w as not sufficient for genetic investigation, thus w e did not
include this y ear of analysis in the study . Mechanical and acoustic signatures
w ere detected and measured using a texture analyser T A-XT plus coupled with
an AED - acoustic envelop device (Stable Micro System Ltd., Go dalming, UK).
Sample p reparation, instrument setting and pa rameter cha racterization a re fully
describ ed b y Costa et al. [46]. Mechanical and acoustic assessments w ere p er-
fo rmed in isolated ro om avoiding p ossible external noise interference. T exture
p rofiles were analyzed with an ad-hoc compiled macro (op erated with Exp o-
nent v.4 soft wa re, Stable Microsystems) which allow ed the definition of three
pa rameter categories: (i) mechanical: yield fo rce (end of the initial slop e), max-
imum fo rce, final fo rce, mean fo rce, a rea, force linea r distance, Y oung’s mo dule
(elasticit y) and numb er of fo rce p eaks; (ii) acoustic: acoustic linear distance,
numb er of acoustic p eaks, maximum and mean acoustic p ressure; (iii) fo rce
direction: ∆ fo rce and force index (as difference and ratio, resp ectively , b et ween
the yield fo rce and the final force). F or each sample 20 measurements w ere
p erfo rmed, comp osed b y 5 technical (samples obtained from the same fruit)
and 4 biological replicates (samples obtained from different fruit). Each sample

4.3. Materials and Metho ds 49
rep resented by a cortex disc w as comp ressed until the defo rmation of 90% (as
describ ed in [46]).
4.3.3 Molecula r ma rk er genot yping
T o p erfo rm genetic mapping and QTL calculation t w o t yp es of genetic ma rkers
w ere used: SSR and SNPs. The microsatellite mark ers used to ancho r the tw o
maps to the published data in literature [147],[137] w ere selected based on their
chromosome p osition as sho w ed in the HiDRAS w eb-site (www.hidras.unimi.it).
SSR p rimers were assembled in new triplex (three p rimer pairs in multiplex;
Supplementa ry T able 9.1 and lab eled with three different fluo ro chromes 6-F AM,
HEX and NED). PCR reactions w ere p erfo rmed in a final volume of 20 µ l with 5
ng DNA, 10X buffer, 0.25 mM dNTPs, 0.075 µ M fo rw a rd lab elled and reverse
p rimers and 0.625 U of Epp endo rf R
 T aq p olymerase. Amplification thermal
condition sta rted with a denaturation at 94 ◦ C fo r 2 min follo w ed b y 10 cycles of
denaturation at 94 ◦ C fo r 30 sec, annealing at 58 ◦ C fo r 30 sec, extension at 72 ◦ C
fo r 1 min; 15 cycles of denaturation at 94 ◦ C fo r 30 sec, annealing at 57 ◦ C fo r 30
sec, extension at 72 ◦ C fo r 1 min and a final round of 10 cycles of denaturation
at 94 ◦ C fo r 30 sec, annealing at 56 ◦ C fo r 30 sec, extension at 72 ◦ C fo r 1 min
finishing with a final extension at 72 ◦ C fo r 5 min. The three consecutive rounds
of annealing temp eratures allo w ed the amplification of all the triplex emplo ying
the same thermal setting, avoiding sp ecific optimization for each set. Single SSR
PCR mix contained 5 ng of DNA, 10X buffer, 0.25 mM dNTPs, 0.12 µ M of
fo rwa rd lab elled and reverse p rimers and 0.5 U of Epp endo rf R
 T aq p olymerase
in a final volume of 12.5 µ l. Amplification thermal setting sta rted with 94 ◦ C
fo r 2 min follo w ed by 32 cycles of denaturation at 94 ◦ C for 30 sec, annealing at
58 ◦ C fo r 30 sec, extension at 72 ◦ C fo r 45 sec, and a final extension at 72 ◦ C fo r
5 min.
SSR-ancho red to functional candidate genes were also p ositioned on b oth
p opulations. Sequences used for SSR screening rega rding the p olygalacturonase
( Md-PG1 ) and the alcohol acyltransferase ( Md-AA T6 ) were retrieved from lit-
erature [48], [69], resp ectively). The other elements were derived b y a combined
homologous/heterologous investigation to analyze the common gene set differ-
entially exp ressed during the apple and tomato rip ening [45]. Sequences fo r
MADS-RIN and NOR w ere obtained from the TED database (T omato Expres-
sion Database, http://ted.bti.co rnell.edu; [79]). These sequences w ere used to
query the apple genome [223] via blastn algo rithm. The SSR based on candi-
date genes w ere tested following the strategy of the labelled tail [199], where
a M13, SP6 o r T7 sequence (tail) was synthesized at the 5’ of each fo rw a rd
p rimer, acting as annealing site fo r the fluorescent p rob e. PCR reactions mix
fo r the tailed SSR w ere ca rried out in a final volume of 25 µ l containing 5 ng
of DNA, 10X buffer, 0.2 mM dNTPs, 0.2 µ M reverse p rimers, 0.04 µ M fo rw a rd
p rimers, 0.16 µ M lab elled p rimer and 0.75 U of Epp endo rf R
 T aq p olymerase.
Amplification condition w as 94 ◦ C for 90 sec, 30 cycles of denaturation at
4.3. Materials and Metho ds 50
94 ◦ C fo r 30 sec, annealing at 58 ◦ C fo r 30 sec, extension at 72 ◦ C fo r 1 min,
10 cycles of denaturation at 94 ◦ C fo r 30 sec, annealing at 53 ◦ C for 30 sec,
extension at 72 ◦ C fo r 1 min and a final extension at 72 ◦ C fo r 7 min. Fragments
analysis w as p erfo rmed with an ABI PRISM R
 3730 capilla ry sequencer (Apply ed
Biosystem b y Life T echnologies) in a final mix of 0.3 µ l of PCR p ro duct, 9.67 µ l
fo rmammide and 0.03 µ l of 500-LIZ denaturated for 3 min at 95 ◦ C. F ragment
sizing w as op erated with GeneMapp er R
 soft wa re (Applied Biosystems, b y Life
T echnologies). Both maps w ere saturated using SNP mark ers (Supplementa ry
T able 9.2) high throughput genot yp ed with t wo genomic platfo rms: Golden
Gate assa y by Illumina (384 SNP chip), and SNPlex T echnology b y Applied
Biosystem (as describ ed in [176]) testing 9 SNPset of 48 SNPs/each. The
SNPs w ere identified during an ea rly assembly draft (4X sequencing depth) of
the ’Golden Delicious’ genome sequencing p roject [223], as describ ed in detail
b y Micheletti et al. [160].
4.3.4 RNA isolation and transcription analysis
T otal RNA w as isolated from fruit collected at ha rvest of four cultiva rs,’Golden
Delicious’ (used as reference), ’Delea rly’, ’F uji’ and ’Pink Lady’ using the Plant
total RNA kit (Sigma) with a mo dified p roto col. T otal RNA w as initially puri-
fied from gDNA with a Deo xyrib onuclease I, Amplification Grade (Invitrogen R
 ),
then complementa ry DNA was synthesized b y Sup erScript R
 VILO cDNA Syn-
thesis kit. In o rder to cho ose the b est housek eeping, six different genes w ere
tested: ubiquitin, t w o actin genes, co rtex genes: 8283:1:a, 4592:1:a and Ef α 1
(p rimer sequences available in [24], [55], [135]). RT PCR w as p erfo rmed using
an Applied Biosystem (AB) 7000 Sequence Detection System machine in a final
volume of 12.5 µ l containing 1 µ l of p rop erly diluted cDNA, 6.25 µ l of Plat-
inum SYBR green qPCR Sup er-Mix UDG, 0.25 µ l of Ro x Reference Dy e and
0.2 µ M of fo rwa rd and reverse p rimer. Amplification conditions w ere 50 ◦ C fo r
2 min, 95 ◦ C fo r 2 min and 40 cycles of denaturation at 95 ◦ C fo r 15 sec, anneal-
ing and extension at 60 ◦ C fo r 1 min. T o cho ose the b est housek eeping genes
and fo r real time data analysis geNo rm [221] and LinRegPCR version 12.9.0
soft wa re w ere used. The transcript levels of 11 sp ecific genes including: Md-
PG1 , Md-PG5 , Md-NOR , Md-RIN , Md-P el , Md-ACS1 , Md-A CO1 , Md-Exp7 ,
Md-XET , Md-XXT and Md-XEG w as investigated. Besides Md-PG1 , where
p rimers sequences were obtained from [48], the p rimer sequences fo r the other
10 genes w ere retrieved from the apple genome contigs [223] using Primer3 soft-
w are (http://p rimer3.sourcefo rge.net/). Designed primers w ere then tested b y
p erfo rming an electronic PCR (http://www.ncbi.nlm.nih.gov/p rojects/e-p cr/)
with the apple in silico p redicted transcriptome (T able 9.3).
4.3. Materials and Metho ds 51
4.3.5 Ethylene Analysis
Ethylene p ro duction w as monito red over p ost ha rvest rip ening fo r a p erio d of 15
da ys. Sta rting from ha rvest, ethylene w as measured at da y 1, 6, 10 and 15. F o r
each measurement data p oint three fruit/cultiva rs w ere closed in a sealed glass
of 5 L fo r 1h. F rom the headspace, 10 ml of air were sampled with a siring and
injected in a gas chromatographer (Ca rlo Erba Instruments GC6000) equipp ed
with a flame ionization detecto r (FID).
4.3.6 Statistic computation and data analysis
F or both progenies sepa rated pa rental and combined genetic maps were con-
structed using JoinMap R
 4.0 [171]. A LOD of 5 and a recombination frequency
of 0.45 w ere used in o rder to define link age groups, and genetic distances b e-
t ween ma rk ers w ere calculated using the Kosambi mapping function. Link age
groups w ere visualized using MapCha rt R
 2.1 (V o o rips, 2002) and numb ered
from 1 to 17 (acco rding to [147], [202] and www.hidras.unimi.it). QTL anal-
ysis ca rried out to detect genomic regions asso ciated to textural comp onents
w as p erfo rmed using MapQTL R
 6 [172]. Initially the genomic regions with
p otential QTL effects w ere identified emplo ying the Interval Mapping (IM) al-
go rithm. T o tak e over the role of other QTLs and to minimize the residual
va riance, ma rk ers coincident with the highest LOD value w ere selected as co-
facto rs and further implemented in the MQM computation. Threshold estab-
lished after running 1000 p ermutation w as set at LOD=3, defined as average
of the I t yp e erro r α =0.05 for all pa rameters across the 17 link age groups
fo r b oth mapping p opulations. QTL-LOD p rofiles a re sho wn in a heatmap
p ro duced b y Ha rry Plotter soft w a re, a stand-alone p rogram written in Java.
Ha rry Plotter has b een develop ed internally at FEM as a new to ol to visual-
ize genome and genetic map features. Multiva riate statistical Principal Com-
p onent Analysis (PCA) w as computed with ST A TISTICA soft w a re v7. Mi-
crosatellite motives w ere identified in the ’Golden Delicious’ genomic assem-
bled contigs through Sputnik, an algo rithm fo r sea rching rep eated nucleotide
pattern (http://esp ressosoftw a re.com/sputnik/index.html). ’Golden Delicious’
info rmation related to gene ID and contigs is available at the FEM data w a re-
house (http://genomics.resea rch.iasma.it) and GDR (Genomic Database for
Rosaceae; http://rosaceae.org). Genes w ere annotated through the Unip rot
database (http://www.unip rot.org) and further compa red with the info rmation
available at the GDR database
4.4. Results and Discussion 52
4.4 Results and Discussion
4.4.1 Exp erimental design
F ruit from the t w o progenies w ere assessed after t w o months of cold sto rage,
in o rder to study the contribution of the t w o different genetic backgrounds in
the fruit texture control. Moreover, from p revious rep o rts it has b een empha-
sized that after t wo months of cold sto rage the physiological rip ening evolution
is maximized [130], enhancing therefo re the trait va riabilit y , a fundamental re-
quirement fo r the QTL intervals resolution. F o r the three y ears of phenot ypic
assessments all the pa rameters investigated show ed a P ea rson co rrelation from
0.57 to 0.9, resulting in a consistent quantitative trait distribution.
4.4.2 T exture physiology dissection and combined acoustic and
mechanical p rofiling
F ruit from b oth p rogenies w ere ha rvested at the same physiological rip ening
stage, objectively determined b y a vis/NIR p o rtable sp ectrometer (D A-meter).
Complex texture phenot yp e w as assessed employing the texture analyzer T A-
XT plus which p ro duced a different texture p rofile fo r the three pa rental cultivars
as w ell as for the t w o progenies (Figure 4.1).
’F uji’ and ’Pink Lady’ greatly differ from ’Delea rly’ in terms of general texture
p erfo rmance, as demonstrated b y the different mean value fo r the maximum
fo rce: 11.95 N, 13.30 N and 6.14 N; numb er of fo rce p eak: 22.23, 22.05
and 6.11; numb er of acoustic p eaks: 107.23, 71 and 5.83 and mean acoustic
p ressure: 49.7 dB, 45.7 dB and 39.65 dB, resp ectively . The overall va riabilit y
of the texture sub-traits rep resented b y the set of 14 pa rameters fo r the t wo
p opulations is sho w ed in the t w o dimensional PCA plot (Figure A 4.2).
The first p rincipal comp onent (PC1), describing 55.39% of the entire pheno-
t ypic variabilit y , together with the second p rincipal comp onents (PC2), account-
ing fo r an additional 20.29%, discriminated the o rientation of the mechanical
comp onent from the acoustic signature (Figure B 4.2), confirming the results
p reviously obtained from a large apple collection [46]. The PCA plot fo r the t wo
p rogenies show ed a bimo dal distribution, in fact the va riabilit y detected in ’F uji
x Delea rly’ (’FjxDel’) was mainly distribu ted along the PC1, with the extreme
values rep resented by the t w o parental cultiva rs. The scena rio observed in ’F uji
x Pink Lady’ (’FjxPL’) w as different, where the transgressive distribution ob-
served fo r this progeny w as o riented mo re to wa rds the PC2, with the seedlings
exceeding the values observed fo r the tw o pa rental cultivars.
4.4.3 Genetic mapping
T o unravel the highly co o rdinated cell w all physiology leading to the textu-
ral p rop erties of apple during the p ost ha rvest rip ening to w a rd QTL mapping
4.4. Results and Discussion 53
Figure 4.1: Combined acoustic-mechanical texture p rofiles. The nine panels
rep resent: a- ’Delea rly’, b- ’Pink Lady’, c- ’F uji’; d, e and f three seedlings of
the ’FjxDel’ p opulation; g, h and i-three seedlings of the ’FjxPL’ p opulation.
F or each graph the black line rep resents the mechanical force displacement
p rofile scaled on the Y prima ry axis (Newton), while the grey line is the acoustic
p rofile scaled on the Y sec onda ry axis (dB). On the X axis is sho w ed the 90%
defo rmation (strain).
Figure 4.2: Principal comp onent analysis plot sho wing the general texture va ri-
abilit y of the tw o mapping p opulations explained b y the first t w o comp onents.
In the figure a and b a re fo r ’FjxDel’ and ’FjxPL’, resp ectively , while the three
pa rental cultivars a re indicated b y full name.

4.4. Results and Discussion 54
app roach, t w o genetic maps w ere de-novo develop ed and assembled. T o con-
struct the map scaffolds 734 ma rk ers w ere totally p ositioned (671 SNPs and 63
SSRs, Supplementary material T able 9.1, 9.2). The SNP transferabilit y b et w een
the reference cv. ’Golden Delicious’ and the pa rental va rieties w as of 38.97%,
50.38% and 50.95% fo r ’Fuji’ ’Pink Lady’ and ’Dela rly’ resp ectively , (in agree-
ment with Micheletti et al. [160]). W e anchored the saturated link age maps
with SNPs (newly identified during the ea rly apple genome assembling) to the
reference published maps with a set of 38 SSRs [137], [202] out of which 30 w ere
assembled in novel triplex. Several multiplex have b een published so fa r [175] re-
quiring, ho w ever, several optimizations. The advantage of the set p resented here
is the common amplification p roto col, which allo w ed a mo re standa rdized and
efficient mapping. In b oth maps w ere also p ositioned new microsatellite ma rk-
ers identified into contigs where sp ecific functional genes w ere tackled. Genes
related to ethylene synthesis/p erception, cell w all metab olism and transcription
facto rs were selected from a heterologous microa rra y exp eriment designed to
highlight a common set of differentially exp re ssed genes during the rip ening of
b oth apple and tomato [45], [5]. The genetic maps fo r b oth p opulations w ere
initially computed fo r single parental meiosis and then the assembled maps w ere
further used fo r QTL mapping purp oses. F o r the ’FjxDel’ p opulation the 494
segregating ma rkers w ere assembled in 17 link age groups (Supplementa ry Fig-
ure 9.1) with a final length of 1053.24 cM, and an averaged densit y of 2.28 cM
b et w een ma rk ers (range from 1.24 to 3.67 cM). In ’FjxPL’ 487 ma rk ers w ere
assembled in a map with a length of 1470.8 cM (Supplementa ry Figure 9.2) and
an averaged densit y of 3.25 (1.61-6.96 cM). T o test the synteny b etw een the
t wo genetic maps and the apple genome, w e compa red the genetic p osition of
the 16 SSR ancho red to candidate genes with their physical p osition on the ap-
ple genome (Supplementa ry Figure 9.3). The SSR-ancho red to candidate genes
w ere lo cated in 8 chromosomes (2, 5, 8, 9, 10, 13, 14, 15 and 16), sho wing a
consistent p osition b eside three elements ( Md-A CS1 and t wo MYB TFs). This
inconsistency is due to a lo w sequencing coverage of these genomic regions,
leading to an erroneous genome assembling.
4.4.4 QTL detection and candidate gene mapping
Mechanical and acoustic data w ere used in a QTL analysis which allo w ed the
identification of 22 total QTLs asso ciated to texture sub-traits, 12 mapp ed
in ’FjxDel’ (Figure 4.3) and 10 in ’FjxPL’ (Figure 4.4), resp ectively . QTL
computed with IM algo rithm and further validated by MQM rep orted a LOD
values ranging from 3.11 to 10.86 and accounting fo r an explained va riance from
10 up to 49%.
QTLs w ere detected based on a LOD threshold of 3, obtained after averaging
the value co rresp onding to α =0.05 fo r all traits over the 17 LGs (Supplementa ry
Figure 9.5). QTL mapping investigation ca rried out in the ’FjxDel’ p rogeny
enabled the detection of a QTL set related to textural comp onents lo cated in
4.4. Results and Discussion 55
Figure 4.3: QTL-A TLAS fo r ’F uji x Delea rly’ rep resenting the heat-map QTL p rofiles detected in 9 link age groups. Numb ers ab ove
each heat-map ba r refers to texture parameters (described in the b o x on the left side), while a and b a re fo r Interval Mapping
and MQM algo rithm, resp ectively . In red text a re indicated the ma rkers link ed to candidate genes. In the b o x on the right side is
illustrated the Heatmap colours scale, going from black (LOD = 0) to white (LOD ≥ 8)
4.4. Results and Discussion 56
Figure 4.4: QTL-A TLAS rep resenting the heat-map QTL p rofile for ’F uji x Pink Lady’. Letters and numb ers a re the same as fo r
’F uji x Delearly’ 4.3. Mark ers link ed to candidate genes are visualized in red colour text.
4.4. Results and Discussion 57
9 link age groups (1, 5, 6, 10, 12, 14, 15, 16 and 17, Figure 4.3). F rom the
general QTL-A TLAS has emerged that LG10 rep resents a hot sp ot fo r texture
control, b eing most of the QTLs computed fo r the three yea rs asso ciated to the
texture pa rameters clustered in this chromosome (b eside ∆ fo rce), with LOD
values spanning from 4.35 to 10.97 and explaining from 20 to 49% of the total
phenot ypic variance (T able 4.1)
QTLs identified b y IM w ere fo r the most confirmed also b y MQM algo rithm,
exception made fo r fo rce linea r distance, mean fo rce and Y oung’s mo dule (in
2009). This QTL cluster co-lo cated with Md-PG1 gene (mapp ed in this study
as Md-PG1 S S R , a new microsatellite ta rgeted app ro ximately at 3 kb up-stream
the sta rting co don (Supplementa ry T able 9.1); a candidate cell w all gene ethy-
lene dep endent [45] [48]. The Md-PG1 -trait asso ciation in this region w as
consistent with the several w orks reporting QTLs mapp ed in this link age group
and asso ciated with fruit firmness [148], [138], [122], [127] as w ell as vitamin C
[58], that in tomato has b een p rop osed to interact with the cell w all lo osening
p ro cess during cell expansion and fruit rip ening [84]. The only pa rameter not as-
so ciated with LG10 w as ∆ fo rce, instead mapp ed on link age group 6, 14 and 15.
QTLs fo r force index w ere mapp ed on link age groups 14, 15 and 10, but in the
latter case it sho wed the lo w er statistical value. This observation is consistent
with the p rojection of the parameters sho wn in the PCA (Figure B 4.2) where
these t wo pa rameters a re differentially o riented, suggesting therefo re a different
genetic control. On link age group 14 t w o candidate genes w ere mapp ed in the
QTL intervals asso ciated to the t w o fo rce directional pa rameters, Md-RIN (or-
tholog of the tomato MADS-RIN transcription facto r, [229]) and the cell w all
enzyme p ectate ly ase ( Md-P el ), a gene kno wn to b e sp ecifically over exp ressed
during rip ening and involved in the fruit softening p ro cess, as do cumented fo r
stra wb erry [116], [149]. Md-RIN w as interestingly asso ciated to the Y oung’s
mo dule (o r elasticit y mo dule) fo r all the three y ears of assessments in ’FjxDel’.
This result ma y suggest that this transcription facto r pla ys an imp o rtant phys-
iological role also fo r apple, influencing the rigidit y of the cell w all. F rom the
functional assessment ca rried out on the three parental cultiva rs (plus ’Golden
Delicious’ used as reference) w e observed a different transcript accumulation fo r
Md-P el , its transcript accumulation w as in fact highly abundant in ’Delea rly’
with resp ect to the other cultiva rs, where lo w exp ression levels w ere detected
(Figure 4.5).
This functional pattern w as also consistent with the ethylene dynamics ob-
served fo r this set of cultiva rs. ’Delea rly’, in fact, at ha rvest w as already in
the climacterium phase (p ro ducing 34.05 µ lKg − 1 h − 1 of ethylene), and sho wed
also the highest ethylene burst at the b eginning of the p ost ha rvest rip ening (8
da ys after harvest). ’Golden Delicious’ is also a cultiva r kno wn to p ro duce high
amount of ethylene, but its burst was detected at the end of the observation
p erio d, thus at ha rvest (0.18 µ lKg − 1 h − 1 of ethylene) the exp ression of Md-P el
is still at the minimum level. As additional p ro of of the tight ethylene dep en-
dent exp ression of Md-Pel , in ’F uji’ and ’Pink Lady’ the transcript accumulation
4.4. Results and Discussion 64
tiva r coincides with the b eginning of the climacteric phase, the stage where all
the rip ening changes o ccur. All these cell w all mo difying p roteins, together with
the w ater loss regulation, a re thought to act in concert in influencing the fruit
softening p ro cess [194],[29]. Tw o majo r asso ciated phenomena are depolymer-
ization of the p ectin net w o rk through a hydrolytic cleavage of homogalacturonan
(a majo r comp onent of the middle lamella) b y p olygalacturonase action, and
the endo cleavage of the hemicellulosic glycan matrices (of which xyloglucan is
the most abundant in dicots) b y the action of the hemicellulases [30],[29],[28].
While still p o o rly understo o d, it seems that dep olymerization of xyloglucan ma y
act as majo r contributor in the reduction of the cell w all turgidit y [187],[195].
This theo ry find consistency with the results sho w ed in the QTL-A TLAS re-
p o rted fo r the t w o p opulations (Figure 4.3 and Figure 4.4). In ’FjxDel’ p rogeny
the high texture va riabilit y resulted in a majo r QTL cluster lo cated in the link age
group 10, coinciding with the p osition of Md-PG1 gene. This gene acting on the
middle lamella can b e the causal facto r determining the difference b et ween the
mealy and the high texture apple. Ho w ever this is not sufficient to discriminate
mechanical and acoustic b ehaviour, Md-PG1 is in fact indistinctively asso ciated
to all the pa rameters defined and related to the different textural comp onents.
Sequencing of the genomic region ha rb ouring Md-PG1 S N P highlighted that
’Pink Lady’ sha res the same allelot yp e of ’F uji’ (T/T), while ’Delea rly’ sho w ed
a heterozygous state (G/T) as ’Mondial Gala’, where the “G” w as describ ed as
the causal allele fo r the loss of firmness [48]. The homozygousit y of the “T”
allele fo r b oth pa rents of the second p opulation ma y b e the reason that a QTL
w as not identified on the link age group 10 in the ’FjxPL’ p opulation. Tw o rele-
vant QTLs w ere instead detected in this progeny , one asso ciated to mechanical
comp onents (LG16) and one sp ecific fo r the acoustic signature (LG12), where
a xyloglucan transglycosylase w as annotated. In this scena rio the enzymatic
action on the middle lamella could b e less evident b ecause of the absence of the
Md-PG1 S N P − G allele, enabling the p ossible action of Md-XET in reducing the
rigidit y of the cell w all. The hyp othesis that solubilisation and dep olymerisation
of p ectic and hemicellulosic p olymers caused b y these t w o enzymes ma y act
in concert during the fruit softening p ro cess found consistency in the study of
Hiw asa and collegues [104] carried out on three different cultiva rs of p ea r such
as “La-F rance”, showing a climacteric melting ripening with fruit undergoing
a dramatic softening, “Nijisseiki”, with a non-climacteric b ehaviour showing a
limited change in firmness during rip ening, and “Y ali”, which sho ws a massive
climacteric ethylene p ro duction but flesh remains crisp y even in late rip ening.
The distinct physiology observed in these cultiva rs w as asso ciated to a sp ecific
gene exp ression patterns. In “La-F rance”, in fact, the transcript abundance of
Pc-PG1 and Pc-PG2 w as high and the expression of Pc-XET1 slightly increased
during rip ening, resulting in a rema rk able softening and melting texture. In “Ni-
jisseki” the gradual decrease in fruit firmness and mealy texture w as attributed
to the lo w and absent expression of Pc-PG2 and Pc-PG1 , respectively , and to
a constitutive exp ression of Pc-XET1 . In “Y ali”, the small change in firmness

4.4. Results and Discussion 65
and the crisp y phenotype was explained b y the observed lack of a detectable
endo-PG activit y and the constitutive expression of Pc-XET1 . The effect of
XET in regulating texture change in fruit w as also supp o rted b y the functional
assessment that w as carried out fo r xyloglucan endotransglycosilase ( Md-XET ),
xyloglucan-6-xylo xyltransferase ( Md-XXT ) and xyloglucan endoglucanase ( Md-
XEG ). Amongst these only Md-XET sho w ed a distinct exp ression pattern, with
its majo r transcript accumulation in ’F uji’ (crisp y type of apple). The role of
this gene ma y b e the causal event of the acoustic segregation observed in the
’FjxPL’ p opulation, detectable fo r the absence of Md-PG1 exp ression. The
interpla y b et w een p olygalacturonase and xyloglucan endotransglycosylase ma y
regulate the differential w eakening of the binding in the middle lamella and cell
w all, resp ectively , event putatively resp onsible fo r the crisp y and mealy pheno-
t yp e [28]. No w ada ys crispness is a p rio rit y in w o rldwide b reeding p rograms, thus
functional ma rkers ba sed on these t wo candidate genes ma y b e fundamental fo r
a ma rker assisted b reeding to w a rds the selection of new sup erio r cultiva rs.
4.4.6 Conclusion
F ruit texture is a feature comp osed of several sub-traits determined b y the
activit y of different enzymes enco ded b y multi-gene families and regulated b y a
transcriptional net wo rk. This complex physiology and genetic control is sho w ed
in this w ork b y the high numb er of significant QTLs ta rgeted in the t w o mapping
p opulations, co-lo cated with several cell w all structural and regulato ry genes.
The emplo yment of a high sophisticated texture analyzer (T A-XT plus ) fur-
nished with an acoustic envelop device (AED) allo wed a comprehensive phe-
not ypic dissection of the textural comp onents. Thanks to this advanced phe-
nomics to ol w e have discovered and mapp ed the highest numb er of texture
QTLs rep o rted till no w, unravelling new genomic regions and genes with p os-
sible imp o rtant effects in the texture control. The choice of the tw o mapping
p opulations cha racterized b y a divergent but very distinct textural b ehaviour
enabled assessment of a wide textural va riability . In ’FjxDel’ w e have identified
several QTLs lo cated on 9 link age groups, with the majo r lo cated on chromo-
some 10 and coincident with Md-PG1 , explaining from 28 to 45.2% of total
va riance and indistinctly related to all the textural pa rameters.
The new SSR-ancho red to this gene can b e used as a valuable and efficient
ma rker to imp rove fruit texture in apple. Mo reover, in this exp erimental design
the use of ’FjxPL’ p opulation w as of great value, where its transgressive segre-
gation (essential fo r breeding) has shed light on other lo ci, sp ecifically involved
in the control of either the mechanical o r acoustic comp onent.
The kno wledge of the genetic lo ci controlling texture traits together with
the annotation of the genes underlying the QTL intervals, allo w ed b y the avail-
abilit y of the apple genome, can gain insight to b etter understand the complex
physiology regulating the fruit texture dynamic during apple rip ening. F uture
candidate genes asso ciation studies will further validate this finding in o rder to
4.4. Results and Discussion 66
fine mapping these p otential ma rk ers valuable fo r assisted b reeding.
CHAPTER 5
Fine mapping and asso ciation analysis of a fruit texture QTL
in apple ( Malus x domestica Bo rkh.)
1
5.1 Abstract
Apple is one of the most cultivated fruit crops, due to its qualit y p rop erties and
extended sto rability . These qualities mainly dep end on the degradation p ro cess
o ccurring in b oth fruit cell w all and middle lamella, which a re regulated b y an
enzymatic net wo rk generally enco ded b y large gene families. Among them, the
p olygalacturonase gene ( Md-PG1 ), and a gene enco ding fo r a Endo Xyloglu-
can T ransferase ( Md-Xet ) were mapped on chromosome 10 and 12 resp ectively ,
within a QTL cluster asso ciated to several texture dissected sub-phenot yp es. In
this w ork, a fine mapping of these genes w as ca rried out in o rder to validate the
asso ciation with the texture va riabilit y in a collection of apple cultiva rs, with the
final aim to ta rget mark er alleles and haplot yp es as valuable mark ers suitable
fo r assisted breeding p rograms. A new set of SNP mark ers w ere used fo r fine
mapping the QTL discovered a round the Md-PG1 and the Md-Xet genes, using
asso ciation analysis app roach and novel high resolution phenomic strategy . A
total of 495 ma rk ers w ere genotyped, out of which 44 w ere lo cated in the Md-
PG1 region, and 83 on LG12. After the asso ciation analysis, just the ma rk ers
mapp ed within the region of Md-PG1 resulted to b e statistically asso ciated to
the phenot ypic traits under investigation. Among them, 12 ma rk ers, sho wing a
MAF > 0.05, and four sp ecific haplot yp es w ere statistically asso ciated with sev-
eral texture comp onents. It is w o rth noting that haplot y es 3 and 10, asso ciated
1 Submitted
67
5.2. Background 68
to favourable texture p rop erties, lack the allele “3” of the microsatellite ma rk er
Md-PG1 S S R 10kd, which show ed an allelic dosage effect with the general apple
fruit texture distribution, as illustrated b y the p rincipal comp onent analysis. In
this study w e emphasize that prio r QTL mapping data and basic kno wledge on
the gene’s role can successfully lead to candidate-gene asso ciation mapping p ro-
gram, to resolve complex trait va riation also in apple. In link age disequilib rium
with the SNPs identified within PG gene, a novel microsatellite ma rk er w as also
ta rgeted and statistically asso ciated to the texture dissected sub-phenot yp es.
The allele Md-PG1 S S R 10kd 3, together with the four haplot yp e, can b e thus
considered as a novel and reliable ma rker tool to b e p romptly used in advanced
b reeding programs, to w a rds the selection of new apple ideot yp es cha racterized
b y high fruit texture quality behaviour.
5.2 Background
In a so ciet y where fo o d is la rgely available, consumers’ app reciation has b e-
come one of the main criteria in fo o d p reference, together with fo o d healthiness
and nutritional values [190]. General fo o d qualit y is determined by four p rin-
cipal facto rs: app ea rance, flavour, texture and nutritional p rop erties [25]. The
p resent study is fo cused on apple texture, in pa rticula r fruit crispness which
accounts fo r mo re than 90% of general texture fruit qualit y [97]. Crispness is
physically determined b y the tissue fracturing combined with the sound am-
plitude p ro duced during the crushing p ropagation [124], and it is describ ed by
b oth kinesthesic and audito ry comp onents [190]. The fruit-rip ening process in-
volves a la rge numb er of enzymes, acting in concert to mo dify b oth cell w all and
middle lamella. These p ro cesses a re regulated by a complex net w o rk, involving
cell w all, ethylene related and transcription facto r genes [16], [45] leading to
the final fruit softening, a physiological p ro cess o riginally programmed fo r seed
disp ersing [85]. These physiological p ro cesses can b e thought as quantitative
traits, which inheritance is no rmally regulated b y the action of several genes,
their interaction plus the environmental impact [77].
F ruit texture is no w adays considered a trait controlled b y a wide gene set
[154], and QTL mapping can b e considered a valuable strategy to dissect the
genetic basis of complex traits [153],[63],[145],[105]. The QTL mapping ap-
p roach, generally ca rried out on bi-parental crosses, has b een already exten-
sively used in fruit texture assessment in apple. Several rep o rts have already
identified majo r genomic lo ci putatively involved in fruit firmness and soften-
ing control [148],[127],[126],[122],[49],[50],[48], with the la rgest texture QTL
survey describ ed b y Longhi et al . [143].
Ho wever, QTL mapping ca rried out using full-sib p rogenies presents impor-
tant limitations due to the numb er of alleles that can b e simultaneously analysed
which, in the case of apple, a re a maximum of four/lo cus. Link age analysis,
mo reover, requires the design of a new segregating p opulation fo r the traits of
5.2. Background 69
interest, making this p ro cedure lab o rious and time consuming. In addition, in
this t yp e of material the numb er of recombination events p er chromosome is
generally lo w, limiting the genetic mapping resolution [82],[57],[165]. Thus, the
numb er of genes included in the QTL statistical interval can va ry from hundreds
till thousand [63]. T o overcome these limitations, asso ciation mapping rapidly
b ecame the main strategy fo r the dissection of complex genetic a rchitecture in
plants [73],[72],[87],[111]. Asso ciation mapping analysis is in fact realized on
la rge p opulation (o r germplasm collection) with unknown relatedness and with
recombination events that have o ccurred over evolutiona ry histo ry , thus increas-
ing the numb er of alleles [165]. Asso ciation mapping can b e p erformed follo wing
t wo main app roaches: whole genome asso ciation (GW AS) and candidate gene
asso ciation mapping (CG). The choice b et w een the tw o metho ds la rgely de-
p ends on the extent of link age disequilib rium (LD). If LD deca ys rapidly , a high
ma rker densit y will b e required in o rder to identify the allelic va riants asso ci-
ated to the trait, and mapping resolution will b e high. Where LD is extensive,
a relatively mo dest numb er of ma rk ers is needed fo r a whole genome investi-
gation, but with no p ossibilit y of resolution at the single gene level [181]. In
sp ecies with sho rt LD blo cks and la rge genome, asso ciation mapping can b e
feasibly p erfo rmed at the CG resolution level, but in this case p rio r kno wledge
ab out the genes regulating the bio chemical pathw a y is essential to select the
right candidates [103]. In this scena rio, CG asso ciation mapping can tak e ad-
vantage of p rior genetic kno wledge, fo r instance QTL p osition on a bi-parental
mapping p opulation [182],[239]. This t yp e of asso ciation analysis have b een
already emplo yed to ta rget statistic asso ciation b et w een allele va riants and phe-
not ypic variance in different crops, such as lettuce [203], maize [239] and rice
[61]. Recently , this app roach has also b een used in p erennial trees to study
drought stress resp onse in pine [87] and Muscat flavour control in grap evine
[74]. Asso ciation based on a candidate gene has also b een recently published
fo r apple [69], where sp ecific SNPs and haplot yp es related to the Md-AA T1
gene (involved in the pathw ay of ester) w ere asso ciated with the overall ester
content. In this w o rk, asso ciation mapping of a candidate gene is conducted to
validate and fine map QTLs p reviously identified on LG10 and LG12 [48],[143].
F or this study a high resolution phenomic strategy [46] w as emplo y ed in order
to imp rove the phenotypic data qualit y , to date considered the majo r b ottleneck
limiting the asso ciation statistical p o w er [182]. Application of ma rker assisted
strategy can greatly imp rove the trait selection efficiency , sp ecially fo r qualit y
traits in fruit crop sp ecies, due to the long unp ro ductive juvenilit y phase. The
aims of this study w ere 1) fine mapping of the Md-PG1 and Md-Xet regions,
2) test fo r asso ciations b et ween individual polymorphisms an d texture dissected
sub-phenot yp es and 3) haplot yp e cha racterization. Finally we also p resent the
discovery and validation of a new valuable microsatellite ma rker, suitable fo r a
simple selection of novel individuals defined b y a sup erio r fruit texture.

5.3. Materials and Metho ds 70
5.3 Materials and Metho ds
5.3.1 Plant material
A panel of 77 individuals, including b oth mo dern and old apple cultiva rs (T able
5.1), w as chosen from t w o germplasm: the Resea rch and Innovation Centre
of the Edmund Mach F oundation, in San Michele all’Adige (T rento), and the
Laimburg Resea rch Centre for Agriculture and F orestry (Bolzano). Both insti-
tutes a re lo cated in the No rth of Italy (T rentino-Alto Adige region) and have
simila r climatic conditions. All the cultiva rs w ere planted in triplicates on M9
ro otsto ck and maintained follo wing standa rd technical management. Apple fruit
w ere collected at the commercial ha rvest stage defined b y standard p omologi-
cal pa rameters, such as skin and seed colour, b rix value (total suga r content),
co rtex firmness value assessed on site and starch conversion index. T otal ge-
nomic DNA w as isolated from young leaf tissue, using the Qiagen Dnasy Plant
kit. DNA quantit y and qualit y w as measured sp ectrophotometrically with the
Nano drop ND-8000 R
 (Thermo Scientific, USA).
5.3.2 T exture phenomic assessment
F ruit samples after harvest w ere sto red in a controlled temp erature cellar at 2 ◦ C
fo r tw o months, and high resolution phenot yping w as ca rried out in y ea rs 2009
and 2010. Apples w ere maintained overnight at ro om temp erature (20 ◦ C) p rior
the analysis, in order to avoid any effect of lo w temp erature on the fruit cor-
tex physiological p rop erties. F ruit texture w as assessed simultaneously p rofiling
b oth mechanical and acoustic signatures, dissected into sp ecific sub-phenot yp es
b y using a texture analyser T A-XT plus (Stable Micro System Ltd., Go dalming,
UK). Sample p reparation, instrument setting and pa rameter cha racterization a re
fully describ ed in [46]. The phenot yping assessment w as p erfo rmed in a sp ecific
isolated ro om, avoiding thus any p ossible external noise interference. T exture
p rofiles were analysed with an ad-ho c compiled macro (Exp onent v.4, Stable
Microsystems), which allo w ed to distinguish the pa rameters in three catego ries,
i mechanical: yield fo rce (end of the initial slop e), maximum fo rce, final fo rce,
mean fo rce, a rea, fo rce linea r distance, Y oung’s mo dule (elasticity module) and
numb er of fo rce p eaks; ii acoustic: acoustic linea r distance, numb er of acous-
tic p eak, maximum and mean acoustic p ressure; iii fo rce direction: ∆ fo rce and
fo rce index (as difference and ratio b et w een yield and final fo rce, resp ectively).
Tw enty measurements fo r each cultiva r w ere p erfo rmed, rep resented b y 5 tech-
nical (discs obtained from the same apple) and 4 biological (discs isolated from
different apples b elonging to the same cultiva r) replicates. Each flesh disc w as
comp ressed until the defo rmation of 90%, during which the t w o p rofiles, me-
chanical and acoustic, w ere simultaneously acquired and digitally analyzed b y
the soft wa re p rovided with the instrument. General texture va riabilit y , exp ressed
b y the 14 defined pa rameters (see [46] fo r more details), w as illustrated b y mul-
5.3. Materials and Metho ds 71
n ◦ cultiva r a b c t yp e n ◦ cultiva r a b c t yp e
1 Amb rosia x E 40 La Flamb o yante (Mairac) x x x E
2 Ananas Renette x x x O 41 Ligol x x x E
3 Ariane (Les Naturiannes) x x x E 42 Limoncini x x O
4 Ariw a x x x E 43 Magre x x x O
5 Baumans Renette x x O 44 Maigold x x x E
6 Bellida x x x E 45 Milw a (Junami) x x x E
7 Berner Rosen x x O 46 Minnew ashta (Zestar) x x x E
8 Boujade x x x E 47 Nap oleone x x x O
9 Breaburn x x x E 48 Nevson (Sony a) x x x E
10 Brina x x x E 49 Nicogreen (Greenstar) x x x E
11 Bro okfield x x x E 50 Nicoter (Kanzi) x x x E
12 Calama ri x O 51 P ermain Do rato x x x O
13 Calvilla x x x O 52 Pilot x x x E
14 Caudle x x x E 53 Pinova x E
15 CIV G198 (Mo di) x x x E 54 Red chief x x x E
16 Civni (Rub ens) x E 55 Red Elsta r x x x E
17 Co op 39 (Crimson Crisp) x x x E 56 Red Field x x x E
18 Crimson Snow x x x E 57 Rome Beauty x E
19 Cripps Pink (Pink Lady) x x x E 58 Rosmarina Bianca x x x O
20 Cripps Red x x x E 59 Ro y al Gala x x x E
21 Croncels x x x O 60 Rubinola x x x O
22 Dalinette (Choup ette) x x x E 61 Sansa x E
23 Dalla Rosa x x x O 62 Santana x x x E
24 Delblush (T entation) x x x E 63 Saturn x x x E
25 Delco rf (Delba restivale) x x x E 64 Sca rlet x x x E
26 Delea rly x x x E 65 Schifresh (Jazz) x x x E
27 Delfloki x E 66 Schinano Gold x x x E
28 Delo rina (Ha rmonie) x E 67 Schniga x x x E
29 Ea rly Gold x x x E 68 Scilate (Envy) x x x E
30 Florina x x x E 69 Summerfree x x x E
31 F uji x x x E 70 Tiroler Spitzlederer x O
32 Galmac x x x E 71 T opaz x E
33 Gelb er Edelapfel x x x O 72 W eisser Wintertaffen x x x O
34 Gewurtzluik en x O 73 T avola bianca x x O
35 Gloster x x x E 74 San Lugano x x O
36 Golden Delicious x x x E 75 Renetta Champagne x x O
37 Golden Orange x x x E 76 Co op 38 x x E
38 Granny Smith x x x E 77 Gold chief x x E
39 Red Delicious (Hapk e Delicious) x E
T able 5.1: Cultiva r collection. V a rieties listed b y name and trade ma rk, b et w een
b rackets when available. The phenot yping assessments a re indicated with the
letters: “a” and “b” fo r p ostharvest of 2009 and 2010, resp ectively , and “c”
fo r harvest of 2010 . With “t yp e” is indicated if the va riety is considered as old
(O) o r elite (E, new) cultivar.
5.3. Materials and Metho ds 72
tiva riate techniques, such as p rincipal comp onent analysis (Statistica soft w a re
v7). PCA w as emplo y ed to plot the data in a reduced hyp erspace defined b y
the first t wo p rincipal comp onents.
5.3.3 P opulation structure
The genetic p opulation structure of the apple collection w as initially investigated
with a set of 17 SSR ma rkers (one p er each chromosome, Supplementa ry T able
10.1). Each mark er w as selected acco rding to the map p osition, amplification
efficiency , allele size and multilo cus p rop erties as sho wn in the HiDRAS w ebsite
(www.hidras.unimi.it). P opulation structure w as inferred using the admixture
mo del of the soft w a re pack age STRUCTURE 2.3.3 [178], assuming co rrelation
of allele frequencies among subgroups and indep endent segregation of alleles
[78]. Q matrix w as estimated with a burn-in length of 100,000 and a run of
100,000 steps. Three indep endent runs with K ranging from 2 to 8 w ere p er-
fo rmed, and the smallest K, after having reached a plateau of the “LnP(D)”
value, w as chosen to capture the majo r structure in the data set, follo wing the
criterion suggested b y Pritchard and Donnelly [178]. Because old apple culti-
va rs are affected b y p re-ha rvest drop and biannual b ea ring, not all the cultiva rs
included in the apple collection p ro duced enough fruit to b e evaluated fo r the
t wo consecutive y ea rs. As a consequence, 70, 65 and 64 cultivars w ere in-
cluded in the asso ciation study fo r 2009 and 2010 at p ost ha rvest and 2010 at
ha rvest, resp ectively , calculating the p opulation structure indep endently fo r the
t wo y ea rs of analysis. Coloured images rep resenting the p opulation structures
w ere obtained with Excel softw a re, while genetic distance among the cultiva rs
w as estimated using NTSYS v2.0, emplo ying the SIMQUAL mo dule with sim-
ple match (SM) co efficient. The similarit y matrix w as used for cluster analysis,
visualized as a dendrogram designed b y the unweighted pair clustering group
metho ds (UPGMA), and implemented in the Sequential and Hiera rchical Nu-
meric algo rithm (SHAN).
5.3.4 Md-PG1 gene cloning
In this study a region of 6 Kb ha rb ouring the Md-PG1 region w as investi-
gated. In pa rticula r, 2,395 bp (gene full length) and t w o regions of 800 bp
each lo cated app ro ximately at 1 kb up and do wnstream from the ST ART and
STOP co don resp ectively , w ere cloned and sequenced among a reference set of
8 cultiva rs (Golden Delicious, Delea rly , Granny Smith, Braeburn, Cripps Pink,
Sca rlet, Roy al Gala and F uji). The cloning w as p erfo rmed in o rder to design sp e-
cific p rimers able to distinguish Md-PG1 from its homo eologous Md-PG5 . The
cha racterization b et w een these t wo members allow ed the design of the sp ecific
p rimers further used in the GBS (genot yping b y sequencing) phase. F o r cloning
the follo wing primers w ere used: PG full, PG 1ku and PG 1kd (Supplementa ry
T able 10.2). F ragment amplification fo r the subsequent Md-PG1 cloning w as
5.3. Materials and Metho ds 73
p erfo rmed fo r the 1 kb up and do wnstream regions in a final volume of 25 µ l
with 10 ng DNA, 10X buffer, 0.25 mM dNTPs, 0.1 µ M reverse and fo rwa rd
p rimers and 0.625 U of Epp endo rf R
 T aq p olymerase. Amplification thermal
condition sta rted with a denaturation at 94 ◦ C fo r 2 min, follo w ed b y 32 cycles
of denaturation at 94 ◦ C fo r 30 sec , annealing at 56 ◦ C fo r 30 sec, extension at
72 ◦ C fo r 1 min and a final extension at 72 ◦ C for 7 min. The Md-PG1 gene
w as amplified in a final volume of 50 µ l, with 10 ng DNA, 10X Advantage
2 PCR Buffer, 0.2 mM dNTPs, 0.4 µ M reverse and fo rw a rd primers and 50X
Clonthech R
 Advantage 2 P olymerase Mix. Amplification sta rted with a denat-
uration at 95 ◦ C fo r 1 min follow ed b y 30 cycles of denaturation at 94 ◦ C for 30
sec, annealing and extension at 68 ◦ C fo r 3 min and 30 sec, and a final extension
at 68 ◦ C fo r 3 min. T en amplicons/PCR fragment w ere cloned using TOPO R
 XL
PCR Cloning Kit (Invitrogen R
 ), follo wing manufacturer’s instructions. Plasmid
DNA w as then extracted using QIAp rep Spin Minip rep Kit (Qiagen R
 ). SNPs
found in the Md-PG1 region w ere genotyped by sequencing the appl e collection.
The t wo SNP identified in the 1kb upstream w ere instead genot yp ed using the
a rtificial mismatch strategy (as describ ed b y Costa et al. [48]) in a final vol-
ume of 20 µ l, with 10 ng DNA, 5X GoT aq R
 Buffer, 0.3 mM dNTPs, 0.4 µ M
reverse and fo rw a rd primers and 2.5U GoT aq R
 DNA p olymerase. Amplification
condition sta rted with a denaturation at 94 ◦ C fo r 2 min, follo w ed b y 35 cycles
of denaturation at 94 ◦ C fo r 30 sec , annealing at 56 ◦ C fo r 30 sec, extension at
72 ◦ C fo r 45 sec, and a final extension at 72 ◦ C fo r 5 min. PCR fragments w ere
sco red on a 5% p olyacrylamide gel.
5.3.5 Genot yping scheme
T o find asso ciation with texture sub-phenotypes, ma rk ers distributed over the
chromosome 10 and 12 w ere genotyped at tw o scale levels, here named “macro”
and “micro allelot yping”.
F or Md-PG1 the genot yping ca rried out at the macro scale w as p erfo rmed
using SSR ma rkers already availab le in literature (www.hidras.unimi.it) and dis-
tributed in a region spanning from 5 to 25 cM up and do wnstream with re-
sp ect to Md-PG1 gene. F o r LG12 w e de-novo develop ed one SSR fo r every
conting indentified within the QTL interval, determined in a p revious QTL
analysis [143] on the chromosome under investigation (Supplementa ry T able
10.2). The strategy to investigate the entire QTL interval w as chonsen b e-
cause of the p o o r info rmation ab out QTLs on LG12 and Xet role in apple
fruit rip ening. The PG micro-allelot yping w as p erformed in o rder to have a
mo re dense mark er coverage in the candidate gene region (10 kb up-do wn
stream), b y using SSR and SNP ma rk ers de-novo develop ed b y the availabil-
it y of the apple genome [223]. Microsatellite ma rk ers w ere identified within
the contig sequences with Sputnik, a soft w are fo r sea rching microsatellite mo-
tives (http://esp ressosoftw a re.com/sputnik/index.html). In the analysis M d −
P G 1 S S R , a microsatellite ma rk er p reviously identified at 3 kb upstream from
5.4. Results and Discussion 80
Figure 5.2: Md-PG1 full length sequence cha racterization. In grey a re sho wn
the p redicted exons as for the Golden Delicious sequenced genome. Bold green
colour is fo r SNP asso ciated to texture sub-traits. Bold underlined green colour
is fo r SNP asso ciated to texture sub-traits causing a non-synonymous va riation
in the p redicted aminoacid sequence. Red text is fo r SNP identified b y rese-
quencing the other 7 cultiva rs, but not p resent in Golden Delicious. Bold red text
is fo r SNP asso ciated to texture sub-traits but not detected within the Golden
Delicious heterozygous genome. Underlined red text is fo r SNP asso ciated to
texture sub-traits, not detected in Golden Delicious and with a MAF < 0.05.

5.4. Results and Discussion 81
Figure 5.3: Md-Xet full length sequence cha racterization. In y ello w the SNPs
used in th asso ciation study and p resent in Golden Delicious. In red the SNPs
used in the asso ciation but not detected in the Golden Delicious heterozygous
genome
5.4. Results and Discussion 82
levels w as p erfo rmed, here named macro and micro allelot yping, to investigate
the different level of LD b et w een ma rk ers a round the candidate genes. F o r PG
the macro-allelot yping aim w as to study the asso ciation with alleles in a region
from 5 to 25 cM upstream and do wnstream the PG co ding region, while the
micro-allelot yping investigated a region in a window of 10 kb up and do wnstream
from the ST ART and the STOP co don resp ectively , with SNP and SSRs de-novo
develop ed. F or Md-Xet a different strategy has b een chosen; less information
ab out the gene involvement in apple texture w ere in fact available. A wider
investigation interval w as for this reason considered. In pa rticula r on LG12
the attention has b een fo cus within the QTL interval identified in a p revious
w ork [143]. T o p erfo rm the asso ciation analysis, a total of 495 ma rk ers were
emplo yed. Among them, 368 were scattered over the genome tested b y a 384
Illumina platfo rm Golden Gate assay , available from p revious study [143]; and
w ere used to evaluate p opulation structure and kinship matrix. On LG10 four
w ere SSR mark ers chosen fo r the macro-allelot yping scale (HiDRAS series), 2
w ere SSR mark ers used fo r the micro-allelot yping, of which one was retrieved
from [143] ( Md-PG1 S S R ), and one ( Md-PG1 S S R 10kd) was de-novo designed.
Finally , a set of 38 SNPs w ere genot yp ed b y sequencing in the region spanning
6 kb up and do wnstream the Md-PG1 gene. On LG12 t w ent y-tw o w ere the de-
novo designed SSR ma rkers chosen fo r the macro-allelot yping scale, while for the
micro-allelot yping a set of 60 SNPs were genot yp ed b y sequencing Md-Xet full
length. Within the set of 384 SNPs, 16 failed, and a p ossible explanation could
b e the fact that the p rob es w ere originally designed on the Golden Delicious
genome, thus other additional p olymo rphisms p resent in other cultiva rs of the
collection might have inhibited the co rrect annealing. The ma rk er selected fo r
the macro-allelot yping and all the mark ers selected fo r LG12 did not sho w any
relevant asso ciation with the texture sub-traits, and fo r this reason they a re
no longer discussed. Also the analysis p erfo rmed during ha rvest time did not
sho w any significant asso ciation, suggesting physiological differences with p ost
ha rvest, which strongly impact the final trait variance.
5.4.5 Asso ciation mapping based on the Md-PG1 candidate gene
In apple a rapid LD deca y was expected, thus a candidate gene asso ciation map-
ping w as chosen as the b est strategy to genetically dissect apple fruit texture
complexit y , finding relationships b et w een causal alleles and phenot ypic va riation
[247],[95]. LD analysis, p erfo rmed in o rder to estimate the non-random asso cia-
tion among the 40 ma rk ers emplo yed in the Md-PG1 micro-allelot yping design,
w as computed b y HaploView using the statistic r 2 (Figure 5.4). F our haplotype
blo cks w ere identified, defined b y ma rk ers showing a r 2 betw een 0.19 and 0.85.
The first blo ck includes t w o SNPs p ositioned in t w o adjacent exons, the
second comp rises SNPs in b oth exons and introns, while the other t w o blo cks
contains ma rkers identified after the Md-PG1 STOP co don. The third hap-
loblo ck, in fact, contains t w o SNPs identified in the 3’UTR region and 1 kb
5.4. Results and Discussion 83
Figure 5.4: Figure 3 LD plot and haploblo ck of Md-PG1 region. The LD
image is based on r 2 values, the da rk er the colour of the b o x the higher
is the r 2 value. In the upp er pa rt of the plot a re indicated the numb er of
p olymo rphic site and the ma rk er considered into the computation. The four
haploblo cks a re highlighted in grey . On the top a re also illustrated the p o-
sitions of the ma rkers on the Md-PG1 contig on which a re distinguished the
three main p o rtion: 3 Kb upstream, gene full length and the 10 Kb do wn-
stream. Ma rk ers in b old a re those included in the haploblo cks. The Md-PG1 S S R
microsatellite alleles a re indicated as Md-PG1 S S R 3.1Ku, Md-PG1 S S R 3.2Ku
and Md-PG1 S S R 3.3Ku. The Md-PG1 S S R 10Kd alleles a re indicated as Md-
PG1 S S R 10Kd 1, Md-PG1 S S R 10Kd 2 and Md-PG1 S S R 10Kd 3.
5.4. Results and Discussion 84
2009 2010
PC 1 PC 2 PC 1 PC 2
PG full 1 0,004995** 1 0,004995** 0,5255
PG full 6 0,01299** 1 0,002997** 0,988
PG full 10 0,004995** 1 0,000999** 0,9441
PG full 12 0,092910 1 0,008991** 1
PG full 18 0,03097** 1 0,002997** 0,8362
PG full 19 0,126900 1 0,008991** 1
PG full 20 0,575400 1 0,04096** 1
PG full 21 0,004995** 1 0,000999** 0,9401
PG full 23 0,005994** 1 0,01199** 0,7672
PG 1kd 1 0,520500 1 0,02498** 1
PG 1kd 5 0,330700 1 0,00999** 1
PG 1kd 7 0,01598** 1 0,000999** 0,991
M d − P G 1 S S R 10kd 2 0,705300 1 0,03297** 0,977
M d − P G 1 S S R 10kd 3 0,000999** 1 0,000999** 0,3986
T able 5.4: SNP asso ciation with the first t w o p rincipal comp onents (PC1 and
PC2). **significative statistic asso ciation at P-value ≤ 0.05. “-”: data not
significative fo r b oth p rincipal comp onents.
do wnstream, resp ectively , the fourth is instead cha racterized b y the p resence
of a SSR identified at 10 kb do wnstream t he Md-PG1 STOP co don, and here
named Md-PG1 S S R 10kd. F ruit texture has b een cha racterized b y fourteen
pa rameters, clustered in t w o fundamental categories (named mechanical and
acoustic comp onents), as illustrated b y the PCA p rojection and defined b y the
first t wo phenot ypic p rincipal comp onents (explaining, at the p ost ha rvest stage,
86.58 and 83.9% fo r the t w o yea rs resp ectively Supplementa ry Figure 10.1). A
p reliminary association was ca rried out using the t w o phenot ypic PCs, as traits,
and a total numb er of 412 ma rk ers (368 genome-wide SNPs and 44 on LG10).
Among them 14 alleles, included in the micro-allelot yping co re set, resulted as-
so ciated with the PC1 values fo r the t w o y ea rs of phenot ypic assessments. PC1
computed over the phenot ypic data distribution fo r 2010 resulted with a higher
numb er of ma rk ers asso ciated resp ect 2009 (T able 5.4). No asso ciation w ere
found using PC2, p ossibly due to the lo w er p ercentage of va riability exp ressed
b y this comp onent.
This hyp othesized that other genes ma y b e involved in the control of the
sp ecific dissection b et w een mechanical and acoustic comp onents. The identifi-
cation of new elements together with the use of a mo re wide cultiva r collection
able to imp rove the quote of va riabilit y explained by the PC2 (increased statis-
tical p o w er fo r the dissection of the mechanical-acoustic comp onent), will b e
required to define novel ma rkers suitable fo r the selection of the acoustic phe-
5.4. Results and Discussion 85
not yp e. T o fine map the Md-PG1 region (previously identified as a majo r QTL
fo r fruit firmness and softening [143]) 40 ma rk ers were emplo y ed, out of which
fifteen SNPs had a MAF < 0.05. This set, how ever, w as initially included in the
asso ciation analysis p erfo rmed b et w een single SNP alleles and texture sub-traits
(Supplementa ry T able 10.3) b ecause discovered in four cultiva rs cha racterized
b y a high texture p erfo rmance (CIV G198, COOP39, Minnew ashta and Ligol).
The collection here assembled do es not rep resent the entire genetic diversit y and
phenot ypic variabilit y , thus a future implementation with additional novel crisp y
flesh t yp e cultiva rs ma y increase their frequency , making their use relevant fo r
further asso ciation studies. These SNPs w ere finally excluded in the follo wing
haplot yp e-texture sub-traits asso ciation analysis. In the asso ciation analysis all
the 14 pa rameters, cha racterizing the te xture sub-phenot yp es, were considered.
Ho wever, four texture sub-traits (Y oung mo dule, fo rce linea r distance, ∆ fo rce
and fo rce index) did not present a significant association with any of the selected
ma rkers, suggesting that these traits a re controlled b y other genes not y et iden-
tified (thus they a re no longer describ ed). F o r the data collected at p ost ha rvest,
t went y-one alleles resulted asso ciated with the texture sub-traits (Supplemen-
ta ry T able 10.3), with the higher numb er (20) significant fo r the five acoustic
comp onents (acoustic linea r distance, maximum and mean linea r distance, num-
b er of acoustic p eaks and numb er of fo rce p eaks; the latter mo re asso ciated to
acoustic resp onse, according to [46]), and only 8 alleles asso ciated with the
five mechanical pa rameters (yield, maximum, mean and final force and a rea).
Among the SNP set asso ciated with acoustic sub-traits, six were significant (fo r
the same texture sub-traits) fo r b oth y ea rs. Out of these six, three (PG full 10,
21 and 23) w ere correlated, sho wing a LD value of r 2 =0.76 and 0.93, while the
other three (PG 10Kd 1, Md-PG1 S S R 10kd 3 and GDsnp02072) w ere inde-
p endent. GDsnp02072 is a SNP not included in the set used fo r the Md-PG1
fine mapping, but still lo cated on chromosome 10, at 0.3 and 0.5 cM apa rt from
the Md-PG1 gene based on FjxDel and FjxPL p opulations, resp ectively [143].
In addition to the ma rk er lo cated on chromosome 10, other t w o SNPs resulted
asso ciated with texture sub-traits (Supplementa ry T able 10.3), GDsnp02371
and GDsnp01634. These tw o ma rk ers a re lo cated on chromosomes kno wn to
contain QTLs and candidate genes involved in fruit rip ening metab olism [49],
[143]. These regions can be e xploited fo r future candidate gene based asso-
ciation studies. In addition to the asso ciation analysis ca rried out with trait
data b y individual yea rs, a second investigation w as p erfo rmed joining all the
p ost ha rvest data from b oth y ea rs into a single dataset containing all the 77
apple cultiva rs (see Metho ds). F o r this analysis w e emplo yed the MLM mo dule
implemented in T ASSEL, which co rrects fo r kinship relatedness [244]. Effect
of p opulation structure and genetic relatedness, leading to false p ositive, w as
illustrated b y the -log quantile-quantile (Q-Q plot) P-value distribution (Sup-
plementa ry Figure 10.6). The asso ciation data obtained b y MLM (with Q+K
matrix defined with 368 SNPs, which resulted the sup erio r mo del; Supplemen-
ta ry T able 10.3 column C) a re quite consistent with the computation made

5.4. Results and Discussion 86
initially b y PLINK (GLM mo del + Q matrix defined b y 17 SSRs), b eside minor
exceptions. In some cases MLM did not confirm the results obtained b y PLINK,
and this can b e attributed to p ossible false p ositive asso ciation, further adjusted
b y the Q+K matrix. In other cases, T ASSEL highlighted new asso ciations, and
this can b e interp reted as results igno red b y PLINK (false negative) o r by the
different stringency of the t wo soft w a res. Finally , to mo del mo re accurately
the frequency of relevant SNPs and to imp rove the p o w er of the asso ciation
analysis, adjacent ma rk ers w ere considered estimating the asso ciation of ma rk er
haplot yp es with the texture sub-traits. F o r this purp ose, haplot yp es w ere con-
structed with the soft wa re F astPHASE, and only ma rk ers with a MAF > 0.05
and a P-value ≤ 0.05 w ere considered. Tw elve allele w ere finally selected and
included into the analysis: PG full 1-6-10-12-18-19-20-21, 23 3’ UTR, 1kd 1,
1kd 7 and Md-PG1 S S R 10kd 3, defining a total of 16 haplot yp es. Out of
these, 10 haplot yp es w ere sha red b et w een the t w o y ea rs of asso ciation, while
three w ere unique for each yea r. Among the 16 total haplot yp es identified, four
w ere statistically asso ciated to the different texture dissected subtraits collected
during p ost ha rvest (haplot yp es 1, 3, 9 and 10, T able 5.5). These haplot yp es
resulted statistically asso ciated to the mechanical comp onents, with haplot yp e
1 and 3 mo re asso ciated to the va riabilit y exp ressed in the second y ea r, and
haplot yp e 9 and 10 to the first one, with P -value ranging from 0.047 to 0.004,
a frequency range of 2.6%-26% and an effect size of r 2 =1.04-27.93. F or the
acoustic subtraits, haplot yp es 1 and 3 resulted mo re significantly asso ciated in
the analysis ca rried out in the second yea r, while haplot yp e 10 w as more associ-
ated with the data collected in the first y ea r of assessment. F o r the t w o texture
comp onents, such as acoustic linea r distance and numb er of acoustic p eaks, the
asso ciation w as consistent across y ea rs. Haplot yp e 3 and 10 w ere discovered in
va rieties known fo r their sup erio r texture p erfo rmance, such as Cripps Pink, F uji
and Granny Smith cha racterized by haplot yp e 3, and CIV G198, COOP39, Min-
new astha and Ligol characterized b y haplot yp e 10 (Supplementa ry T able 10.4).
Haplot yp e 1 w as sha red b y cultiva rs plotted in b oth p ositive and negative PCA
a reas, such as Amb rosia, Braeburn, Golden Delicious, Roy al Gala and Gelb er
Edelapfel, while haplot yp e 9 w as p resents in pa rticula r in the cultiva rs plotted
in the p ositive PC1 a rea of the PCA graph, thus cha racterized b y an extremely
p o o r textural b ehaviour (Brina, Gelb er Edelapfel, Rome Beaut y , Rubinola and
T opaz). These findings suggest that b oth haplot yp es 3 and 10, as w ell as Md-
PG1 S S R 10kd can b e considered as a valuable to ol fo r ma rk er assisted b reeding
p rograms.
5.4.6 Allelic dosage of Md-PG1 S S R 10kd 3
The microsatellite Md-PG1 S S R 10kd w as tagged in a contig overlapping the
genomic scaffold containing Md-PG1 region, which resulted to b e in LD with
the SNPs ta rgeted within the Md-PG1 co ding p o rtion. W e have emphasized
this ma rker since it resulted highly significant with the texture phenot yp e in
5.4. Results and Discussion 87
Yield F o rce Final Fo rce F o rce P eaks Max F o rce Mean F o rce
N. Haplot yp e % size effect A B A B A B A B A B
1 GA TTCGTCTCAG 26,0 9,95-27,93 0,1608 0,1039 0,1808 0,0119** 0,3027 0,0329** 0,0999 0,0209** 0,1109 0,0279**
3 TGCCT ACTGTGA 17,0 5,36-22,04 0,2458 0,1908 0,0989 0,1908 0,3526 0,0219** 0,1379 0,1369 0,1858 0,0819
9 GA TCCA TCTCAG 3,9 3,18-13,16 0,4675 0,999 0,0219** 0,2178 0,1239 0,5355 0,3397 0,99 0,2438 0,9351
10 TGCCT A TTGTGA 2,6 1,04-22,22 0,1359 0,999 0,0389** 0,8262 0,0339** 0,1199 0,0509 0,8881 0,0549 0,9141
Area Acoustic Linea r Distance Acoustic Peaks Max Acoustic Pressure Mean Acoustic Pressure
N. Haplot yp e % size effect A B A B A B A B A B
1 GA TTCGTCTCAG 26,0 9,95-27,93 0,0849 0,0239 0,2378 0,0039** 0,3077 0,0029** 0,1588 0,0039** 0,7333 0,0049**
3 TGCCT ACTGTGA 17,0 5,36-22,04 0,1409 0,0769 0,08192 0,0009** 0,07792 0,0019** 0,3057 0,0029** 0,6913 0,0019**
9 GA TCCA TCTCAG 3,9 3,18-13,16 0,2018 0,959 0,3926 0,4585 0,6653 0,6533 0,6484 0,9301 0,05395 0,4935
10 TGCCT A TTGTGA 2,6 1,04-22,22 0,0439** 0,9261 0,0009** 0,0359** 0,0009** 0,0149** 0,0009** 0,1239 0,0029** 0,0989
T able 5.5: Asso ciation b et ween the four significant haplot yp es and texture sub-phenot yp es fo r the t w o y ea rs of phenot ypic assess-
ments (A 2009, B 2010). **significative statistic asso ciation at P-value ≤ 0.05. % is for hapl ot yp e frequency .
5.5. Conclusion 88
all the analysis p erfo rmed in this w o rk. T exture assessed fo r the t w o y ea rs
at p ost ha rvest, sho w ed a consistent cultiva r distribution, as demonstrated by
the PCA graphs in Figure 5.1 and the asso ciation results ca rried out using the
first t wo PCs (T able 5.4). It is w o rth noting that apple cultivars p resenting a
homozygote allelic state fo r Md-PG1 S S R 10kd 3 (Supplementa ry Figure 10.7)
w ere distributed in the p ositive PC1 values a rea of the PCA plot cha racterizing
the general lo w texture p erfo rmance (Supplementa ry Figure 10.8). Opp osite
w as the scenario in case this allele w as absent, with all the cultiva rs generally
distinguished b y PC1 values from 0 to -8, thus with a sup erior texture p rop-
erties. Apple cultiva rs cha racterized b y a heterozygous state for the “3” allele
sho wed an intermediate texture distribution, b eing sp read over the PCA plot
and comp rehended b et w een the other t w o catego ries. The consistent distribu-
tion across the t wo y ea rs (as illustrated in Supplementary Figure 10.8) hyp oth-
esized a dosage effect fo r the “3” allele. On the PCA plot the only exception is
rep resented by Amb rosia (1) that, even if it sho ws a homozygous allelot yp e fo r
this allele, is plotted in the negative PC1 a rea of the texture distribution. Also
the haplot yp e asso ciation with the texture traits reflected the allele dosage ob-
servation. The four significant haplot yp es can in fact b e divided in t w o different
groups, acco rding to the p resence/absence of the allele Md-PG1 S S R 10kd 3,
as w ell as the p osition on the PCA plot. Haplot yp e 1 and 9, p resenting the
Md-PG 1 S S R 10kd 3 allele in homozygous state, cha racterized those cultivar
sho wing a general low texture performance, such as Gelb er Edelapfel, Dalla
Rosa, Ea rly Gold, Croncels, Rubinola and Delearly . Haplot yp e 3 and 10, which
lack this allele, are sha red b y cultivars such as CIV G198, COOP39 and Ligol,
and it is w orth noting that the cultiva rs p ositioned in the PCA graph defined b y
negative value of b oth p rincipal comp onents (thus with the b est acoustic resolu-
tion), sho w ed only the haplot yp e 10. T o date great technological progress have
b een made in ma rk er high throughput genot yping, which has elected SNP as
the most suitable ma rker fo r genetic study , esp ecially fo r high densit y and time
effective genome wide scanning. Ho w ever, microsatellites still remain a useful
to ol fo r assisted selection p rograms, b ecause of their higher allele diversit y and
easiness of transferabilit y across sp ecies and lab o ratories [93]. F o r this reason, in
addition to the haplot yp es, w e also p rop ose this SSR mark er Md-PG1 S S R 10kd
as a valuable ma rker fo r assisted b reeding programs to w ards the selection of
high texture p erfo rming apple cultiva rs.
5.5 Conclusion
F ruit texture is one of the main principal qualit y facto rs as well as a w o rld wide
main p riorit y in mo dern apple b reeding p rograms. T o date texture has b een
phenot yp ed with to o p o o r and empirical metho ds, reducing its complexit y to a
simple and not alw a ys exhaustive flesh firmness assessment. Many w o rks have
b een already p resented to the scientific communit y , but all a re related to a QTL
5.5. Conclusion 89
survey fo cused on bi-pa rental map, thus with alleles involved in the genetic con-
trol restricted to the genetic background of the pa rental cultivars. In this study ,
fo r the first time, w e fine mapp ed the Md-PG1 region with a set of new SNP and
SSR ma rkers discovered mining the apple genome contig sequences. LD map-
ping analysis defined a set of 12 SNPs in link age, with a MAF value > 0.05 and
cha racterizing 16 haplotypes. SNPs and haplotypes, together with the texture
comp onents dissected with a novel texture analyzer equipment coupled with an
acoustic device, w ere used for a candidate gene association mapping investiga-
tion. Haplot yp es 3 and 10 resulted significantly asso ciated to the high texture
b ehaviour in pa rticula r with the acoustic comp onent, the most p referred features
b y consumers. It is also interesting to note that these t w o haplot yp es lack the
allele Md-PG 1 S S R 10kd 3, that sho w ed an allelic dosage co rrelated with the
texture va riability illustrated b y the PCA, where its homozigousit y co rresp onded
with the cultiva rs characterized b y the most extreme lo w texture p erfo rmance.
Here, w e finally rep o rt the cha racterization and the validation in a la rge apple
collection of t wo haplot yp es, as well as a microsatellite as a novel tool kit for
the selection of high texture fruit qualit y apple accessions.
6.4. Results and Discussion 96
6.3.6 Data Analysis
Statistical analysis, data no rmalization and qualit y control were realised using
LIMMA lib rary (R pack age). All values w ere log transformed (base 2) and
genes with an absolute fold change log2 ≥ 1 and a P-value ≤ 0.05 w ere considered
differentially exp ressed b et w een t wo different samples. In o rder to obtain a mo re
consistent exp ression result, media value w as considered from the data deriving
from p rob es designed in different a reas of the gene (replicates), while the median
value w as computed for the p rob e copies. Differentially exp ression statistics
w as visualized using V enn diagrams, dra wn with V enny [169], allowing in ter and
intra developmental and rip ening compa rison among the different stages of one
cultiva r and b et w een the t wo cultiva rs. Data were clustered acco rding to SOT A
(Self-Organizing T ree Algo rithm) algo rithm, and visualized by MultiExperiment
View er [193].
6.4 Results and Discussion
6.4.1 T exture physiology dissection
Microa rray slides w ere designed to identify differentially exp ressed genes in apple
fruit over a time-course based exp eriment. Seven time p oints were selected to
study the physiology related to fruit development and rip ening. Seven differ-
ent time p oint w ere chosen as describ ed p reviously , sta rting from flo w er to p ost
ha rvest. Successively , apple physiology w as cha racterized analysing the ethylene
bio-synthesis and texture p rofile in the t w o different cultivars. The ethylene p ro-
duction, for the t w o cultiva rs, w as assessed emplo ying a PTR-T oF-MS over a
p erio d of 30 da ys sta rting from ha rvest, compa ring the normal physiology with
the disto rted one by 1-MCP . The ethylene burst o ccurred within 10 da ys after
ha rvest, confirming the data rep o rted b y Costa et al . [49]. The compa rison b e-
t ween the t w o cultiva rs sho w ed substantial differences in ho rmone p ro duction,
Golden Delicious, in fact, produced 1120,5 ppbv of ethylene 7 da ys after har-
vest, while Granny Smith, in the same p erio d, p ro duced only 35.9 ppbv (Figure
6.1). The second cultiva r reached the highest amount of ethylene 19 da ys after
ha rvest, p ro ducing 121.6 ppbv of ho rmone (almost ten time less than Golden
Delicious). In b oth cultiva rs the ethylene p ro duction was affected b y 1-MCP
treatment. In the treated samples at the 7 t h day of the post harvest ripening
the ethylene level w as 3 and 5 ppvb in Granny Smith and Golden Delicious
resp ectively , and constantly remained at a basal level fo r almost 20 da ys. After
this p oint the ethylene concentration slo wly increased in Golden Delicious (Fig-
ure 6.1). This result find consistency with the analysis ca rried out in Golden
Delicious b y Dal Cin and collegues [54], where they observed an increased ethy-
lene level of apple treated with 1-MCP 24 da ys after harvest. In Granny Smith,
instead, the ethylene concentration after the treatment remained at basal level
fo r all the analysed p erio d (Figure 6.1).

6.4. Results and Discussion 97
Figure 6.1: Ethylene bio-synthesis evolution fo r Golden Delicious (a) and Granny
Smith (b). On the x axis the numb er of da ys after ha rvest is rep orted. Y axis
is fo r ethylene concentration, measured in part per billion b y volume (ppbv)
In apple is kno wn that ethylene has a direct impact on texture, b eing several
cell w all enzymes hormone dependent. T exture dynamics was p rofiled over the
time course using a texture analyser equipment, distinctively cha racterizing the
mechanical and acoustic texture p rofiles (Figure 6.2) [46]. The figure clea rly
sho wed as the mechanical component has a distinct kinetics resp ect the acoustic
p rofile. In b oth cultiva rs the mechanical p rofile decreased continuously over the
stages, while the acoustic resp onse increased until the harvest stage fo r b oth
cultiva rs, than it sho w ed a sp ecific trend va riet y dep endent. In Golden Delicious,
the acoustic p rofile decreased tow a rds the p ost harvest stage, while in Granny
Smith it remained almost unmo dified, validating the different texture b ehaviour
existing b et w een the t w o cultiva rs. Ethylene regulation of the last rip ening
stages, has b een also suggested b y the dissection of the textural p rofile after
the 1-MCP treatment. As sho wed in Figure 6.2, the mechanical p rofile fo r
the treated samples, in b oth the cultiva rs, p resented a trend which w as simila r
to the p rofile describ ed at the ha rvest p oint, indicating a p ossible slo wdo wn
of the physiological dynamics due to 1-MCP . The treatment heavily effected
the acustic p rofile of Golden Delicious, which sho w ed results closer to ha rvest.
Granny Smith, instead, did not sho w any pa rticula r change b et w een the samples
analysed during the three last rip ening stages: ha rvest, p ost harvest control and
treated. T able 6.1 summa rized the numb er of the acoustic and mechanical p eaks
during the time course, enlightening the differences o ccurring in the p rofiles
b et w een the va rieties and texture ethylene dep endency .
6.4. Results and Discussion 98
Figure 6.2: Mechanical and acoustic p rofiles fo r the t w o cultivars. Abb reviations: D, Golden Delicious; S, Granny Smith; G, green;
MG, mature green; B, b reaker; H, ha rvest; PC, p ost ha rvest control; PM, p ost ha rvest treated.
6.4. Results and Discussion 99
cultiva r Green Mature Green Break er
F p eaks A p eaks F p eaks A p eaks F p eaks A p eaks
Golden Delicious 10 3,5 12 16 16 60
Granny Smith 11 5 13 34 18 58
cultiva r Harvest P ost ha rvest Control Post ha rvest treated
F p eaks A p eaks F p eaks A p eaks F p eaks A p eaks
Golden Delicious 24 84 7 29 14 84
Granny Smith 17 128 23 87 22 88
T able 6.1: The table rep o rts the numb er of the fo rce p eaks (F p eaks) and the
acoustic p eaks (A p eaks) fo r all the fruit stages analysed in the t wo cultiva rs.
Also the observation p erfo rmed with the electronic microscop e, supp orted
the ethylene impact of fruit texture. Samples fixed at the green and break er
stages w ere similar fo r b oth cultiva rs, confirming the data collected with the
texture analyser (Figure 6.3). Sta rting from harvest, the differences b et w een
va rieties were mo re evident (Figure 6.4). A t the ha rvest stage, Granny Smith
cells w ere completely brok en. In Golden Delcious, instead, most of the cell
remain intact, but with a mo re collapsed shap e. The situation w as emphasized
at the p ost ha rvest stage, where the differences o ccurring b et w een the cultivars’
cells w as higher. Granny Smith cells app ea red simila r to the cells fixed at the
ha rvest time, supp o rting the texture assessment. In Golden Delicious, instead,
the cells w ere completely separated but intact. These results w ere consistent
with the data rep o rted b y W aldron et al. [233]. In this w ork it w as p resented
that in crisp y fruit cell adhesion is strong and tissue fraction involves rupture
across cell w alls, releasing cells content and lendig to the cha racteristic crispness.
On the contra ry , in mealy fruits, middle lamella undergo es extensive dissolution
and the cells a re completely sepa rated up on comp ression, slipping one on the
other. This miscoscopic investigation confirmed also the p reviously measured
differences o ccurring in the cultiva rs in b oth the ethylene bio-synthesis p rofile
and texture pa rameters dynamics.
6.4.2 Data analysis and gene clustering
The rep ro ducibilit y of the replicates and the accuracy of the hyb ridizations w ere
confirmed b y Pea rson co rrelation and PCA analysis. A graphical overview of the
co rrelation was sho w ed b y the t wo-dimensional heatmap plot of the 8 different
conditions fo r Golden Delicious and Granny Smith (Figure 6.5). The PCA plot
sho wed that the three replicates/sample w ere mo re closely clustered resp ect the
seven samples of the time course, which sho w ed a developmentally time p rogres-
sion. The samples treated with the ethylene inhibito r 1-MCP w ere sp ecifically
group ed closer to the ha rvest stage samples resp ect to the p ost ha rvest control
stage, suggesting as the treatment dela y ed the overall rip ening physiology at
a functional level. In order to investigate gene exp ression and patters in the
6.4. Results and Discussion 100
Figure 6.3: S.E.M. image analysis of Golden Delcious (a, c green stage and e,
g b reaker stage) and Granny Smith (b,d green stage and f, h b reak er stage).
6.4. Results and Discussion 101
Figure 6.4: Figure microsopio: S.E.M. image analysis of Golden Delcious (a,
c ha rvest time and e, g p ost ha rvest) and Granny Smith (b,d ha rvest and f, h
p ost ha rvets).

6.4. Results and Discussion 102
Figure 6.5: Tw o-dimensional graphical overview of the co rrelations existing
among the exp ression values and the samples during the time course.
t wo different time course, a set of 3810 genes, sub divided in eleven classes,
w ere represented on a Combimatrix Microa rra y gene catego ries (Figure 6.6).
These classes w ere identified as: aminoacid pathwa ys, biological p ro cesses, ca r-
b ohydrate metab olism, cell wall metabolism, cellula r comp onent, energy path-
w ay , plant ho rmone, p olysaccha ride metab olism, regulato ry p ro cesses, seconda ry
metab olism and transcription facto r (Figure 6.6).
Sp ecific gene classes, rep resenting 1/15 of the total gene numb er in the
apple genome, have b een selected in o rder to capture and investigate a lim-
ited, but rip ening sp ecific, physiological dynamics, excluding supplemental in-
fo rmation that a wide genome investigation w ould have given. The 75% of
the selected genetic elements w ere genes involved in rip ening p ro cesses lik e
transcription facto rs (34% of the genes synthesized on the chip), seconda ry
metab olism (16%), cell w all metab olism (15%) and plant ho rmone regulation
(10%). The remaining 25% comp rehended genes involved in ca rb ohydrates
metab olism (10%), biological o r regulato ry p ro cesses (1% each), cellula r com-
p onents (10%), signal transduction or aminoacid and energy pathw a ys (0.07 and
4% resp ectively). The gene-set selection sta rted from the annotation, based on
the UNIPROT database, of all the genetic elements ta rgeted in a p revious QTL
analysis study [143]. The annotated genes w ere successively blasted against
the Apple Genome database, identifying all the genetic elements b elonging to
the gene-families. A total of 3404 genes passed the standa rd qualit y control
and w ere finally considered fo r the exp ression data analysis. These genes w ere
6.4. Results and Discussion 103
Figure 6.6: Pie chart summa rizing the p ercentage of the gene-classes hyb ridized
on the Combimatrix microa rray chip.
6.4. Results and Discussion 104
group ed together acco rding to their exp ression p rofile analysed b y a SOT A clus-
tering algo rithm (MeV softw a re). In Golden Delicious, chosen to rep resent the
no rmal climacteric rip ening dynamics, sevent y clusters, each describing a sp e-
cific trend, w ere identified. Tw o clusters sho w ed an increasing dynamics after
the flo wering time and a decreasing sha rp p rofile after the fruitlet stage (Figure
a, b 6.7). The t w o main gene groups classified in these stages w ere transcrip-
tion facto rs (22.6%) and genes involved in the cell w all metab olism (32.1 %).
The classes less rep resented were genes involved in biological p ro cess (1.9 %),
while w ere not identified genes involved in the aminoacidic patha ys, regulato ry
p ro cesses o r p olysaccha rides metab olism. The transition from flo w er to fruitlet
w as characterized b y a complete change in shap e and mo rfology . It is therefo re
reasonable that the genes mainly involved in this p ro cesses w ere mainly rep re-
sented b y transcription factors, which a re devoted to initiate new developmental
p rograms, and genes involved in the cell w all metab olism, which re-o rganize the
p olysaccha ride structure to allo w cell enla rgement and division. Five clusters
sho wed an initial up-regula tion after the flo wering time, and a following de-
crease after b reaker stages to w a rds the end of the time course (Figure c, d, e, f,
g 6.7). The tw o main gene classes exp ressed in these stages were transcription
facto rs (16.9 %) and genes involved in seconda ry metab olism (22.9 %). The
class less rep resented comprehend genes involved in regulato ry p ro cesses (0.48
%), while were not p resent genes involved in the p olysaccha rides metab olism.
The genes here clustered w ere p robably not involved in the final rip ening, but
mainly in fruit initial development and gro wth. In these clusters, genes in-
volved in the ethylene bio-synthetic pathw ay w ere also identified. In pa rticula r
4 genes b elonging to the Amino cyclop ropane-1-Ca rb o xylate Ossidase (A CO)
family , 3 elements memb er of the Amino cyclop ropane-1-Ca rb o xylate Synthase
(A CS) family and 2 S-adenosyl-l-methionine synthetase (SAM) were identified.
These genes could b e involved in the synthesis of the basal ethylene levels, but
not in the rip ening p ro cess, since they w ere not identified in the clusters having
an increasing dynamics at the onset of rip ening.
A endo-xyloglucantransferase (Xet), p resented in p revious QTLs analysis as
putatively involved in the determination of the acoustic comp onent of apple
texture, w as also group ed in this set of clusters, suggesting its role in the c ell
w all metab olism and mantainance [143]. This gene has b een the ta rget of a
candidate gene asso ciation study (chapter 5). The asso ciation p erfo rmed with
phenot ypic data collected at the p ost ha rvest stage was not statisticaly signifi-
cant. This might b e explained b y the observation obtained after this exp ression
study , where it w as sho w ed an involvement of the gene exp ecially during the
initial-mid stages of fruit development and maturation, and not during the late
rip ening stages. Exp ression studies, describing genes dynamics, can therefo re
b e a useful to ol in the determination of the b est developmental stage fo r phe-
not ypic data collection and follo wing genetic analysis. Tw o w ere the clusters
that p resented a slight decrease after the flo w ering stage, follo w ed by an in-
crease at b reaker and reaching the highest value at the ha rvest p oint (Figure
6.4. Results and Discussion 105
Figure 6.7: 12 sp ecific clusters investigated fo r their pa rticula r dynamics along
the time course.
h,i 6.7). Within this clusters, the gene catego ries mo re rep resented were plant
ho rmone (20.5%) and transcription facto rs (22.9%). Genes involved in bio-
logical and regulato ry processes and in the p olysaccha ride metab olism w ere,
instead, not exp ressed. Fruit ripening is characterized b y a dramatic change in
softening, o ccurring in concomitance with the initiation of the ethylene burst.
This observation can explain the high p ercentage of genes regulating phyto-
ho rmones and transcription pathwa ys. Finally , three clusters group ed together
the genes putatively involved in the rip ening p ro cess and senescence, showing
a sha rp up-regulation after break er stage to wa rds the p ost ha rvest (Figure l,
m, n 6.7). The tw o main gene classes exp ressed in these clusters w ere related
to seconda ry metab olism (20.3%) and transcription facto rs (26.9%). The gene
catego ries less represented w ere aminoacid pathw a ys, biological processes and
p olysaccha ride metab olism (0.43% each). Some of the genes clustered in this
final group w ere already known to be involved in apple climacteric rip ening p ro-
cess, such as Md-A CO1 and Md-A CS1 which are genes involved in the ethylene
biosynthetic pathw ay , ethylene recepto rs, expansin and p olygalacturonase ( Md-
PG1 ), involved in the cell wall modification. The role of these genes in the
determination of apple texture has b een already investigate in different studies
[49],[247],[50],[143]. Differently from the A CS and A CO genes underlined in
the p revious groups, the elements identified in these clusters ( Md-A CO1 and
Md-A CS1 ) a re involved in the ethylene burst o ccurring during rip ening, sug-
gesting t wo different observations. The first is that elements b elonging to the
same gene family a re transcrib ed in very p recise and genetically determinated
6.4. Results and Discussion 112
namics of genes rip ening sp ecific, supp o rted b y the distinct ethylene p ro duction
assessed, suggests as an anticipated and high exp ression of this gene set might
also control the different ha rvest time. These t w o cultiva rs w ere, in fact, ha r-
vested with 26 da ys of difference. T ranscription facto rs such as MADS b o x and
NA C were instead mo re exp ressed in Granny Smith. The late functional tran-
script accumulation of this set of transcription facto rs in Granny Smith at this
stage (compa red to Golden Delicious) suggest that this cultiva r has a dela y ed
rip ening initiation, hyp othesis also supp o rted b y the lack of an evident ethylene
burst. A differential mo de of activation in this gene-set might b e the causal
effect of the different rip ening b et w een these tw o cultiva rs. 107 genes resulted
differentially exp ressed at the p ost ha rvest stage (T able 6.3 and Figure a 6.9),
with A CS, ACO and SAM genes mo re exp ressed in Golden Delicious, confirming
the different rip ening physiology b et w een these t w o varieties. Md-PG1 , a gene
kno wn to b e involved in the cell w all mo dification and, consecutively , in texture
determination, is also mo re exp ressed in Golden Delicious than Granny Smith.
This results confirms the p revious QTL survey and candidate genes asso ciation
study ([143], and chapter 5), which p rop osed this gene as a relevant genetic
element fo r the genetic control of the apple textural attributes. The differences
in the transcripts accumulation b et w een the t w o cultiva rs finds consistency with
the t wo different texture behaviours (Figure 6.2), in pa rticula r with the acous-
tic p rofile. Tw o a re the main differences in the acoustic resp onse of the tw o
va rieties. The first is that, while in Golden Delicious the acoustic resp onse
increase until ha rvest, and the decrease to wa rds the p ost ha rvest, in Granny
Smith the p rofile remained almost unmo dified after ha rvest until the end of the
time course. The second w as that in Granny Smith, at p ost ha rvest stage, the
numb er of the acoustic p eak w as noticeably higher than in Golden Delicious;
having the cultiva rs 87 and 29 p eaks resp ectively (T able 6.1). Ho w ever, there
w ere differences also at the mechanical profile. The numb er of the p eak fo rce
w ere for Granny Smith 23 and 7 fo r Golden Delicious, evidencing thus a simila r
mechanic p rofile dynamics b et ween the t w o cultiva rs, but with different p rop-
erties. This different physical resp onse w as also biologically enlightened b y the
analysis p erfo rmed with the S.E.M., at the p ost harvest stage (Figure 6.4). P ost
ha rvest samples treated with 1-MCP sho w ed an anatomical structure simila r to
the ha rvest. In this stage 97 genes w ere differentially exp ressed b et w een the t w o
cultiva rs (T able 6.3 and Figure a 6.9), with A CO, A CS, expansins and p ectate
ly ase more exp ressed in Golden Delicius, while MADS b o x and NA C transcription
facto rs more expressed in Granny Smith. The application of 1-MCP , comp eting
with the ethylene p erception, delay ed the general rip ening physiology . Ho w ever,
a simila r functional pattern to harvest of the treated samples, suggest a re-
activation of the functional machinery , in o rder to restore the no rmal rip ening
physiology .

6.4. Results and Discussion 113
6.4.5 Candidate genes dynamics
This microa rray platfo rm w as used to highlights the gene dynamics of a pa rtic-
ula r set of genes sp ecifically involved in the fruit rip ening p ro cess, such as cell
w all enzymes and plant hormone metabolism. T o enlight the functional impact
of these genes on the final rip ening, the accumulation trend w as analysed in
co rrelation with the evaluation of the texture and ethylene physiology . PG a re
p ectin-degrading enzymes that catalyse the hydrolytic cleavage of galacturonide
link ages in the middle lamella, contributing to its mo dification. An increase in
the activit y of this enzyme has long b een asso ciated with fruit rip ening in many
studies although the amount detected va ries widely during the different rip ening
stages of different sp ecies [88],[2] . The main PG involved in the apple rip en-
ing, indicated as Md-PG1 (MDP0000326734) was mapped on LG10 co-lo cating
with imp o rtant QL Ts asso ciated with several texture sub-traits [48],[143]. In
this study , Md-PG1 show ed a lo w accumulation during the initial stages of fruit
development, and sta rted to increase after b reak er tow a rds the end of the time
course, where it reached the highest level. This p rofile underlined the involve-
ment of this gene in the fruit rip ening, validating its role in the final texture
determination (Figure 6.10). F o r this gene w as detected an increased exp res-
sion of 4.4 and 4.7 fold b et w een b reak er and ha rvest in Golden Delicious and
Granny Smith resp ectively . Md-PG1 increased in the gene exp ression of 2.4
fold b et w een ha rvest and p ost ha rvest in Golden Delicious, while no differential
exp ression has b een detected fo r the same stages in Granny Smith. The dif-
ference b et w een the t w o cultiva rs at p ost ha rvest w as, in fact, 1.6 fold. The
differential exp ression b et w een the cultiva rs at the p ost ha rvest stage, reflected
the textural p rofiles, esp ecially the acoustic trend (Figure 6.2). F o r b oth cul-
tiva rs, at harvest, this gene sho w ed a consistant functional p rofile, suggesting
an initial common regulation (Figure 6.2). During the late rip ening stage a
mo re sp ecific functional exp ression w as observed, suggesting a sp ecific gene ac-
tivation cultiva r dep endent. The functional dynamics of Md-PG1 b et w een the
t wo cultiva rs w as in agreement with the acoustic profile evolution. In Golden
Delicious, in fact, Md-PG1 exp ression increased, while the acoustic p rofile de-
creased. In Granny Smith, on the contra ry , the unchanged acoustic p rofile w as
supp o rted b y an un-mo dified transcription accumulation of this gene (T able
6.3). While, in fact, during ha rvest the numb er of acoustic and fo rce p eaks fo r
the cultiva rs w ere simila r, the differences w ere considerable mo re evident during
the p ost ha rvest stage. This validated the different texture b ehaviour existing
b et w een the t w o cultiva rs, which, at p ost ha rvest w as mo re evident than in
other stages. After 1-MCP treatment, the Md-PG1 level decreased consider-
ably in b oth cultiva rs, reaching the same level as detected at the b reaker stage,
confirming the ethylene regulation of this gene [29]. A compa rison b et w een
the control/treated p ost ha rvest samples, sho w ed a reduction of transcript ac-
cumulation of 7 and 5.7 fold change in Golden Delicious and Granny Smith
resp ectively . Also this result finds consistency with the texture p rofiles assessed.
6.4. Results and Discussion 114
T extural p rofiles (acoustic and mechanical) of the treated p ost ha rvest stage
w as similar as the one registered during the ha rvest (T able 6.3). The higher
fold change measured fo r Md-PG1 w as detected fo r Golden Delicious in the
compa rison b et w een no rmal and 1-MCP treated p ost ha rvest stage. This differ-
ence is functionally aligned with the ethylene reduction caused b y the treatment,
highlighting as this gene is included in the do wnstream ethylene related path-
w ays. Considering the strict relationship existing b et w een PG1 and ethylene
[204], the clea r reduction on the gene exp ression indicated that ethylene action
is ma rkely inhibited b y 1-MCP . In the apple ethylene bio-synthetic pathw a y , the
majo r gene is represented b y Md-A CS1 (MDP0000370791), which catalise the
conversion of SAM to 1-amino cyclop ropane-1-ca rb oxylic acid ( A CC ) the ethy-
lene p recursor. Md-A CS1 transcripts accumulation increased of 3.2 and 2.4
fold in Golden Delicious and Granny Smith resp ectively , b et w een ha rvest and
p ost ha rvest control stages (Figure 6.10). Also fo r this gene the application of
1-MCP caused a reduction of 3.2 fold change b et w een the p ost ha rvest control
and the p ost ha rvest treated samples in Golden Delicious, sho wing a transcript
accumulation level simila r to the amount registered during harvest. No differ-
ences w ere instead detected for Granny Smith. The Md-A CS1 accumulation
supp ression in apple, after 1-MCP treatment, has b een rep o rted also in p revious
w orks [54],[216], indicating that this gene might rep resent a crucial facto r in the
ho rmone synthesis and fruit rip ening. The last enzyme involved in the ethylene
biosynthetic pathw ay is A CO. This enzyme catalyse the final conversion of A CC
to ethylene. Md-A CO1 functional p rofile was simila r fo r b oth cultiva rs, sho wing
an increased gene exp ression along the time course, reaching the highest level
at the ha rvest p oint (Figure 6.10). In Golden Delicious and Granny Smith an
increase of 7 and 6.8 fold times b et ween b reak er and ha rvest w as detected. The
fold change of this gene in Golden Delicious is the highest functional va riation
detected in this transcriptional investigation. F or Md-A CO1 no significant dif-
ferential exp ression was detected from ha rvest to p ost ha rvest, as w ell as after
the treatment, fo r b oth cultiva rs. Among the genes involved in the ethylene
synthesis, Md-ASC1 in Golden Delicious w as highly down-regulated (3.2 fold)
after the action of 1-MCP . These results w ere consistent with the data p resented
fo r the same cultivar b y Dal Cin at el. [54], which detected a reduction of A CS
transcript accumulation after the treatment. Also the results obtained analysing
the transcript accumulation of Md-A CO1 after the treatment a re confirmed b y
a p revious study realysed on tw o different apple cultiva rs; Orin and F uji [216].
In this w ork T atsuki and collegues determined that Md-A CO1 exp ression did
not decrease in 1-MCP-treated Orin fruit, and it decreased very slo wly in 1-
MCP-treated F uji fruit resp ect to control samples. In the w o rk of Dal Cin and
collegues [54], a pa rallel b et w een apple and p each, b oth climacteric fruit, after
1-MCP treatment w as presented, sho wing as the t w o sp ecies reacted differently
to the inhibition of the ethylene synthesis. In opp osite with the data p resented
in this study fo r apple, in p each, the enzymes involved in the ethylene synthesis
seemed to b e slightly affected b y the inhibito r. The autho rs hyp otized that
6.4. Results and Discussion 115
the different resp onse to 1-MCP might b e related to differences in terms of
exp ression pattern o r turn-over of the ethylene recepto rs. The different rip ening
and shelf-life physiology b et w een apple and p each can b e thus controlled by a
distinct functional ethylene p ro duction and p erception mechanism. A p ossible
different ethylene sensitivit y might b e the cause of the different fruit texture
and sto rability betw een the t w o sp ecies. Among the genetic elements analysed
with the a rray , also ethylene recepto rs w ere investigated. Among the element
b elonging to this family , t w o genes, ETR and ETR2 (MDP0000393617, and
MDP0000195916 resp etively; b oth mapp ed on LG5), p resented a simila r trend
of differential exp ression during the last stages of fruit rip ening (Figure 6.10).
The transcript fo r b oth genes w as up-regulated from b reak er to harvest. The
t wo ETR genes p resented a ho rmone dep endent regulation, b eing the exp res-
sion level reduced significantly in p ost ha rvest treated samples in resp ect to
the control in b oth cultiva rs (1.4 and 1.8 fold fo r ETR in Granny Smith and
Golden Delicious resp ectively and 1.7 and 1.9 fo r ETR2, in Granny Smith and
Golden Delicious resp ectively). The sp ecific exp ression of these t wo elements
can b e involved in the transition from the system 1 (p re-climacterium) to the
system 2 (full climacterium phase) of the ethylene pathw ay . Other elements
b elonging to the ETR family , did not sho w any pa rticula r regulation over the
time course, s uggesting the co-existance of dep endent and indep endent ethy-
lene gene regulation. Cell w all degradation is a physiological p ro cess regulated
b y a co o rdinated action of several genes. Among them, expansin have b een
p rop osed as one of the majo r enzymatic agent in cell-w all mo dification [44]. In
this study the exp ression of the expansin gene family resulted quite consistent
b et w een the t w o cultiva rs.
Tw o genes (exp a, MDP0000431696 and exp b, MDP0000772420; b oth
mapp ed on LG1), how ever, sho w ed a significant increased expression at the
mature green stage in Golden Delicious, reaching the highest accumulation at
the p ost ha rvest (Figure 6.11). During the evolution from b reaker to ha rvest,
their exp ression increase of 2.1 and 1.7 times resp ectively . Exp a sho w ed also an
increased exp ression (1.3 fold) from harvest to p ost ha rvest. Contra ry to Golden
Delicious, the exp ression level of these tw o expansin in Granny Smith w as very
lo w during the entire time course, without sho wing any differential exp ression.
A t the harvest point, the exp ression of exp a w as 2.4 times higher in Golden Deli-
cious resp ect to Granny Smith, while exp b w as 2.1 times higher. At post harvest
the exp ression of the exp a w as 2.8 times higher in Golden Delicious resp ect to
Granny Smith, while exp b, w as 3.4 times higher in Golden Delicious than in
Granny Smith. These indications, together with the identification in previous
studies of QTLs asso ciated to texture traits in the link age group 1, supp o rt their
involvement as imp o rtant candidate in the texture control [50]. The reduced
exp ression of the tw o elements in Golden Delicious after the 1-MCP treatment
(of 2.9 fo r exp a and 1.8 fo r exp b ), confirmed their ethylene dep endent reg-
ulation, as initially p rop osed in tomato [188]. Another expansin gene ( exp c,
MDP0000292477) w as detected as differentially expressed, but with a higher
6.4. Results and Discussion 116
Figure 6.10: Exp ression pattern fo r the a set of genes involved in ethy-
lene and cell w all metab olism. The blu line indicates the control samples,
the red line indicates the samples treated with 1-Methylcyclop rop ene. Ab-
b reviations: D, Golden Delicious; S, Granny Smith; PG1, p olygalacturonase;
A CO1, amino cyclop ropane-1-carboxylate ossidase; A CS1 amino cyclopropa ne-1-
ca rb o xylate synthase; ETR, ethylene receptors
6.5. Conclusion 117
accumulation in Granny Smith resp ect to Golden Delicious [143],[36](Figure
6.11). During harvest and post harvest, this expansin w as 1.9 and 1.6 times
higher in Granny Smith than in Golden Delicious, resp ectively . In Granny Smith
the dynamics increased 2.4 times from b reak er to ha rvest and reached its highest
value at the p ost ha rvest. The exp ression of this expansin resulted also function-
ally controlled b y ethylene, since decreased 2 times b et w een the control and the
treated Granny Smith samples. In Golden Delicious there was no differentially
esp ression among any considered stages fo r the expansin, suggesting a p ossible
differential exp ression based on genetic background. Another gene that show ed
an up regulation over the Golden Delicious rip ening stages is the p ectin esterase
gene (MDP0000251256). Its expression increased of 2.4 fold from b reak er to
ha rvest, and 1.3 fold from harvest to post harvest (Figure 6.11), sho wing an
ethylene-related dynamics. The direct ethylene regulation on the exp ression of
this gene w as proved b y 1-MCP , which do wn regulated its accumulation b y 4.2
fold. The exp ression of this cell wall gene did not p resent any significant dif-
ferential exp ression in Granny Smith fo r any of the pairwise compa rison ca rried
out among the considered stages, confirming its activation ethylene dep endent.
The t wo cultiva rs p resented significant differences of the expression level of this
gene, b oth at ha rvest and p ost ha rvest. A t ha rvest, Golden Delicious sho wed an
exp ression of the p ectin esterase 2.3 times higher than Granny Smith, while the
value w as 2.6 higher during p ost ha rvest. The functional p rofile investigated in
this survey , highlighted as rip ening in apple is cha racterized b y b oth developmen-
tally and climacteric rip ening dep endent mechanisms. The last stages resulted
also controlled b y few sp ecific genetic elements b elonging to the p rincipal gene
families involved in the rip ening p ro cess. This gene-set might b e considered as
a novel set of candidates fo r the design of new asso ciation mapping study to
imp rove the dissection of imp o rtant trait related to apple fruit quality .
6.5 Conclusion
The aim of this w o rk w as the functional dynamics investigation of a sp ecific set
of genes during the majo r rip ening physiological changes (mainly fruit texture
and ethylene). The assembling of the gene-set sta rted from the identification
of the genomic intervals detected in the QTL mapping survey , o riented to ge-
netically dissect the fruit texture complexit y . Due to the fact that this gene-set
w as initially selected b ecause statistically asso ciated to the phenot yp e detected
only after t wo month of cold sto rage, additional understanding w ere necessa ry
to b etter define their involvement in fruit climacteric rip ening control. The
genomic app roach presented here, based on a custom microa rra y platfo rm, p ro-
vided a picture of a sub-set of molecula r events o ccurring during apple fruit
development, maturation and rip ening. This investigation also contributed to
gain kno wledge ab out the complex regulato ry machinery of these physiological
events. The analysis of the transcription p rofiles over the time course in t wo

6.5. Conclusion 118
Figure 6.11: Exp ression pattern of cell w all genes. The blu line indi-
cates the control samples, the red line indicates the samples treated with 1-
Methylcyclop rop ene. Abb reviations: D, Golden Delicious; S, Granny Smith;
Exp, expansin; P ect est, p ectin esterase
6.5. Conclusion 119
apple cultiva rs, cha racterized b y a different rip ening b ehaviours, allo w ed the
identification of the stages fo r w hich the most evident functional va riation o c-
curred. These stages might b e though as a crucial steps in the complex changes
acting to turn the ha rd fruit into soft and edible. Among the several stages
comp osing the rip ening time course here defined, the last one, p rop er of the
p ost ha rvest shelf-life rip ening, rep resented the fundamental stage. Ethylene,
the ho rmone co o rdinating the physiological events leading to the final fruit qual-
it y , is in fact p ro duced after harvest, and its accumulation directly control other
p ro cesses, such as fruit texture. In this view, it is imp o rtant to define the func-
tional pattern to highlight the genes sp ecifically involved in the late rip ening
stage. Ho w ever, ethylene dep endent and indep endent resp onsive pathw a ys a re
kno wn to co-exist in different sp ecies. T o dissect this functional interpla y and to
shed light on the regulato ry processes underlying the rip ening changes, the ethy-
lene comp etito r 1-MCP w as emplo y ed in addition to the cultiva r compa rison.
The pa rallel b et w een Golden Delicious and Granny Smith emphasized putative
candidate genes with exclusive dynamics fo r genetic background and ethylene
relationship, which could b e considered as new target fo r texture complexit y
dissection. The results here obtained can b e exploited in future w orks aiming
to define the sp ecific gene-set involved in the control of b oth mechanical and
acoustic texture comp onents. This will improve the kno wledge to date avail-
able ab out the cell w all disassembly , as w ell as the definition of a novel set of
candidate gene to exploit fo r the design of new functional mak ers suitable fo r
assisted b reeding programs to w a rd the creation of ideot yp es with sup erio r fruit
qualit y .
6.5. Conclusion 120
CHAPTER 7
Conclusions and future p rosp ects
F ruit quality is measured accomplishing four main p rincipal facto rs, among which
texture is one of them. T exture, fo r apple in pa rticula r, is a fundamental trait
accounting fo r most of the consumers app reciation. It is directly p erceived b y
human senses, therefo re it allo ws the distinguishing of a pa rticula r fo o d o r fruit
and drive the p reference tow a rds an apple va riet y resp ect to another. T exture
has also the capacit y to influence directly the general fruit qualit y , regulating the
maintenance during shipping and shelf life. Considering the imp ortance of fruit
texture on the qualit y of fresh apple, many research groups initiated, in the last
decade, p rograms aimed to investigate the genes controlling the dynamics of
this trait. Breeding, in fact, can take advantage of biotechnological applications,
such as molecula r mark ers, p roviding p rediction p ow er asso ciated to a sp ecific
trait of interest. T echnological imp rovement in genot yping techniques, and the
follo wing decrease in cost analysis, made the high-throughput genot yping fea-
sible and economically affo rdable. Ho w ever, despite this great imp rovement,
phenot yping investigation is nevertheless much more limited. The study of a
sp ecific trait, in fact, is still affected b y to o individual investigations, inade-
quate instrumentations o r insufficient technologies for the dissection of complex
phenot yp es on la rge sample sets. Most of the phenotyping a re still based on
estimation rather than analytical measures, consequently reducing the quote of
va riability necessa ry to increase the statistical p o wer of the asso ciation studies
p rograms, designed to ta rget new elements involved in the control of imp o rtant
agronomical traits. Currently apple texture measurements and phenot ypic ob-
servations a re b oth instrumentally and senso rially p erfo rmed. This, ho w ever, is
not sufficient fo r a complete and accurate phenotyping investigation of all the
p eculia rities describing apple texture in a time-efficient fashion.
T o imp rove the texture comp rehension and sub-traits dissection, a new high
121
128
Figure 8.2: Sound p ressure p rofiles generated during the mechanical p enetration
registered b y the microphone and converted in dB. In the panel a is rep o rted
the acoustic p rofile of an apple characterized b y a high sound p ressure w ave.
Arro w p oints the main p eak registered over the acoustic p rofile. In figure b is
sho wed a p rofile of a sample cha racterized by a mealy texture
Figure 8.3: Bo x plot of the textural pa rameters measured for the 86 apple
cultiva rs. Black line within each b o x rep resent the median, the width of the
b o x is the data interqua rtile, dashed lines sho w the standa rd deviation and dots
p oint the outliers.

129
Figure 8.4: Simila rit y dendrogram computed fo r the 86 apple cultiva rs con-
sidering: a) mechanical pa rameters, b) mechanical and acoustical pa rameters.
Arro ws indicate Fuji, Cripps Pink, Granny Smith and Golden Delicious.
130
Figure 8.5: General P ea rson co rrelation matrix visualized by a heat map plot
calculated among all the pa rameters identified fo r mechanical and acoustic p ro-
files. In the computation w ere also included also the ID A index fo r the rip ening
stage assessment and the fruit digital puncture test.
CHAPTER 9
Supplementa ry material of chapter 4
SNP LG FJ PL DEL
CONS12 – p np –
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131
132
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133
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134
GD SNP00211 14 np np np
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135
GD SNP00273 15 np np p
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136
GD SNP00341 17 np – –
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GD SNP00452 9 p p p
GD SNP00452 9 p p p
GD SNP00453 14 p p np
GD SNP00464 12 np np –
GD SNP00471 2 np np np
137
GD SNP00472 6 np p p
GD SNP00477 3 p p np
GD SNP00480 3 p p np
GD SNP00483 2 np p np
GD SNP00487 8 p np np
GD SNP00495 1 np p –
GD SNP00503 8 p np np
GD SNP00505 2 np np p
GD SNP00514 9 p p np
GD SNP00522 14 p p np
GD SNP00525 15 np np p
GD SNP00527 8 p np p
GD SNP00531 13 – np p
GD SNP00532 13 p p np
GD SNP00533 1 np p np
GD SNP00538 – np np –
GD SNP00559 5 np np np
GD SNP00562 7 p np p
GD SNP00575 1 np p p
GD SNP00578 16 p np –
GD SNP00581 13 np np np
GD SNP00584 8 np p np
GD SNP00588 3 p p p
GD SNP00590 7 p np –
GD SNP00604 10 np np np
GD SNP00611 5 np np np
GD SNP00619 4 np np np
GD SNP00626 16 np p np
GD SNP00627 8 np np p
GD SNP00629 2 np p np
GD SNP00631 1 np np p
GD SNP00632 5 np np np
GD SNP00633 2 p np p
GD SNP00638 5 np np p
GD SNP00639 8 p p np
GD SNP00640 15 np p np
GD SNP00646 11 np p np
GD SNP00655 2 np np p
GD SNP00661 15 np np p
GD SNP00664 3 np np p
GD SNP00674 1 p – p
144
GD SNP01780 7 np p np
GD SNP01783 1 p np p
GD SNP01786 13 np np np
GD SNP01789 10 p np np
GD SNP01793 12 p p np
GD SNP01797 11 np p np
GD SNP01801 17 np p p
GD SNP01804 11 np p np
GD SNP01805 15 np np p
GD SNP01807 8 np np np
GD SNP01809 – np np np
GD SNP01810 10 np p np
GD SNP01811 14 np np p
GD SNP01813 15 p np np
GD SNP01815 1 np p np
GD SNP01820 15 np p p
GD SNP01821 3 p p np
GD SNP01826 1 np np p
GD SNP01829 2 np p p
GD SNP01830 5 np np np
GD SNP01831 6 np p p
GD SNP01840 2 np p –
GD SNP01842 17 p p p
GD SNP01844 13 np np p
GD SNP01846 14 np p np
GD SNP01848 7 p np np
GD SNP01850 15 np – p
GD SNP01851 3 p p p
GD SNP01855 12 – – –
GD SNP01857 11 p np np
GD SNP01859 5 np np np
GD SNP01862 8 p p p
GD SNP01866 16 p p np
GD SNP01867 10 p np np
GD SNP01872 7 p p p
GD SNP01875 15 np p np
GD SNP01878 11 p np np
GD SNP01880 9 np np p
GD SNP01886 4 np np np
GD SNP01887 17 p p p
GD SNP01888 14 np p np

145
GD SNP01891 9 p np p
GD SNP01892 5 p np p
GD SNP01899 13 np np np
GD SNP01910 12 np np p
GD SNP01911 9 np p np
GD SNP01912 11 p p p
GD SNP01914 3 – np p
GD SNP01915 – p p p
GD SNP01917 13 p p np
GD SNP01919 7 – np –
GD SNP01935 11 np np np
GD SNP01937 3 p p np
GD SNP01942 5 np p p
GD SNP01945 2 p np np
GD SNP01947 10 np np p
GD SNP01954 6 np p p
GD SNP01955 3 np – np
GD SNP01956 5 np np np
GD SNP01957 3 np p np
GD SNP01961 10 np p p
GD SNP01962 14 np np np
GD SNP01964 17 np – p
GD SNP01965 4 p p np
GD SNP01967 9 p np p
GD SNP01969 3 p np p
GD SNP01971 15 p np np
GD SNP01974 17 p np np
GD SNP01978 5 p np np
GD SNP01982 3 p p p
GD SNP01984 12 np p p
GD SNP01989 15 np p p
GD SNP01990 3 np np np
GD SNP01993 5 np p p
GD SNP01994 7 np np np
GD SNP01995 12 p np np
GD SNP01996 6 np p np
GD SNP01997 7 p p np
GD SNP02001 6 np p np
GD SNP02002 13 p p p
GD SNP02003 15 np p p
GD SNP02005 11 np p np
146
GD SNP02008 12 np p p
GD SNP02009 10 p p p
GD SNP02013 9 p np p
GD SNP02014 9 p p np
GD SNP02018 13 np p np
GD SNP02020 3 p p p
GD SNP02021 14 np p p
GD SNP02022 8 p p np
GD SNP02025 4 np – p
GD SNP02027 3 p p p
GD SNP02028 13 np np –
GD SNP02029 15 np np np
GD SNP02030 3 p p np
GD SNP02033 3 np np np
GD SNP02037 8 p np p
GD SNP02046 9 np p np
GD SNP02049 17 np np np
GD SNP02051 10 p np p
GD SNP02055 2 np np np
GD SNP02058 – np np np
GD SNP02063 13 np p –
GD SNP02069 13 np – np
GD SNP02071 9 p p np
GD SNP02072 10 np p p
GD SNP02075 17 np np p
GD SNP02076 2 np p np
GD SNP02083 17 np np np
GD SNP02087 16 np – p
GD SNP02091 7 np np np
GD SNP02092 1 np p p
GD SNP02093 2 np p p
GD SNP02094 3 np p p
GD SNP02138 6 p np p
GD SNP02144 2 np p np
GD SNP02183 10 np p p
GD SNP02201 9 p p p
GD SNP02274 7 p np np
GD SNP02281 11 p np np
GD SNP02291 7 p p np
GD SNP02296 4 np np np
GD SNP02304 3 np p np
147
GD SNP02326 12 np np np
GD SNP02371 1 np p p
GD SNP02428 1 np np p
GD SNP02436 7 np np np
GD SNP02437 9 p p p
GD SNP02452 13 np np np
GD SNP02460 9 np p p
GD SNP02464 6 p np np
GD SNP02482 9 p p p
GD SNP02502 12 np p p
GD SNP02535 2 np np np
GD SNP02537 12 np p np
GD SNP02543 14 np np np
GD SNP02550 17 p p p
GD SNP02580 1 np p np
GD SNP02581 9 p p np
GD SNP02646 4 np p p
GD SNP02655 13 np np p
GD SNP02657 7 np np np
GD SNP02664 16 np – p
GD SNP02674 5 p p np
GD SNP02701 5 np p p
GD SNP02703 17 np np np
GD SNP02706 14 np np np
GD SNP02823 15 p np p
GD SNP02834 5 p np –
GD SNP02838 11 np np np
GD SNP02840 7 p np np
GD SNP02845 9 np p p
GD SNP02857 12 np np np
GD SNP02859 15 np p p
T able 9.2: In the SNP table a re listed all the SNP ma rk ers
tested with b oth technologies (Golden Gate and SNPlex). F o r
each ma rker is rep orted the LG and the p olymorphism on each
pa rental cultivar (where ’p’ means p olymo rphic, ’np’ non p oly-
mo rphic and ’-’ not determined).
148
FjxDel
T rait LG Gene ID Gene
N ◦ fo rce p eaks 1 MDP0000025650 A CO
1 MDP0000633218 AP2/ERF
1 MDP0000401140 AP2/ERF
1 MDP0000199078 CCR4
1 MDP0000159587 MADS
1 MDP0000588331 P ectinesterase
1 MDP0000588332 P ectinesterase
1 MDP0000156045 Xylan 1,4-b eta-xylosidase
Initial fo rce 3 MDP0000202829 P ectinesterase
3 MDP0000184620 P olygalacturonase
3 MDP0000267641 Xyloglucan 6-xylosyltransferase
3 MDP0000646125 β -1,3-glucanase
3 MDP0000275455 β a-galactosidase
3 MDP0000300393 NA C-domain
3 MDP0000222045 NA C-domain
5 MDP0000217947 β -1,3-glucanase
5 MDP0000189637 β -1,3-glucanase
5 MDP0000140016 β -glucosidase
5 MDP0000165135 β -glucosidase
5 MDP0000134558 CCCH type zinc finger
5 MDP0000193664 Hydrolase
5 MDP0000696333 MADS
5 MDP0000234073 MADS
5 MDP0000215760 MYB
5 MDP0000118810 WRKY
Max fo rc e 5 MDP0000217947 β -1,3-glucanase
5 MDP0000189637 β -1,3-glucanase
5 MDP0000140016 β -glucosidase
5 MDP0000165135 β -glucosidase
5 MDP0000134558 CCCH type zinc finger
5 MDP0000193664 Hydrolase
5 MDP0000215760 MYB
5 MDP0000118810 WRKY
5 MDP0000696333 MADS
5 MDP0000234073 MADS
8 MDP0000211931 AP2
8 MDP0000149337 β -glucosidase
8 MDP0000273450 Expansin
8 MDP0000232313 MADS
8 MDP0000221319 P ectinacetylesterase
8 MDP0000200867 P ectinacetylesterase
8 MDP0000211931 AP2
8 MDP0000149337 Beta-glucosidase
8 MDP0000273450 Expansin
8 MDP0000232313 MADS
8 MDP0000200867 P ectinacetylesterase
149
Final fo rce 10 MDP0000510383 A CO
10 MDP0000286915 AP2/ERF
10 MDP0000326734 P olygalacturonase
10 MDP0000934866 bHLH
10 MDP0000684989 bHLH
10 MDP0000219146 bHLH
10 MDP0000285151 Cellulose synthase
10 MDP0000155026 Cellulose synthase
10 MDP0000697030 NA C domain
10 MDP0000130686 NA C domain
F orce index 10 MDP0000687812 CCAA T
10 MDP0000878773 Chitinase
10 MDP0000131702 EIL
10 MDP0000224275 Ethylene recepto r
10 MDP0000510383 GA T A
10 MDP0000586400 Glucan endo-1,3- β -glucosidase
10 MDP0000128964 Glucan endo-1,3- β -glucosidase
10 MDP0000246388 Glucan endo-1,3- β -glucosidase,
10 MDP0000136027 GRAS
10 MDP0000168650 GRAS
10 MDP0000269126 GRAS
10 MDP0000220092 MADS
10 MDP0000266968 MYB
10 MDP0000166020 NA C domain
10 MDP0000191925 NA C domain
10 MDP0000897594 P ectinesterase
10 MDP0000938309 P ectinesterase
10 MDP0000226667 P ectinesterase
10 MDP0000697030 P ectinesterase
10 MDP0000626215 P ectinesterase
10 MDP0000130686 WRKY
10 MDP0000190788 Xyloglucan galactosyltransferase
10 MDP0000326734 Xyloglucan galactosyltransferase
10 MDP0000168287 A CO
10 MDP0000281965 A CO
10 MDP0000320017 A CO
Initial fo rce 10 MDP0000510383 A CO
10 MDP0000286915 AP2/ERF
10 MDP0000934866 bHLH
10 MDP0000684989 bHLH
10 MDP0000219146 bHLH
10 MDP0000285151 Cellulose synthase
10 MDP0000155026 Cellulose synthase
10 MDP0000697030 NA C domain
10 MDP0000130686 NA C domain
10 MDP0000326734 P olygalacturonase
Max acoustic p ressure 10 MDP0000457509 AP2/ERF
10 MDP0000286915 AP2/ERF
10 MDP0000934866 bHLH

150
10 MDP0000791364 bHLH
10 MDP0000285151 Cellulose synthase
10 MDP0000155026 Cellulose synthase
10 MDP0000269126 Endo-1,4- β -glucanase
10 MDP0000307619 GRAS
10 MDP0000326734 P olygalacturonase
10 MDP0000206034 SAM
10 MDP0000566005 WRKY
10 MDP0000320017 Xyloglucan endotransglucosylase
Max fo rc e 10 MDP0000510383 ACO
10 MDP0000286915 AP2/ERF
10 MDP0000326734 P olygalacturonase
10 MDP0000219146 bHLH
10 MDP0000934866 bHLH
10 MDP0000684989 bHLH
Mean acoustic pressure 10 MDP0000457509 AP2/ERF
10 MDP0000286915 AP2/ERF
10 MDP0000934866 bHLH
10 MDP0000791364 bHLH
10 MDP0000285151 Cellulose synthase
10 MDP0000155026 Cellulose synthase
10 MDP0000269126 Endo-1,4- β -glucanase
10 MDP0000307619 GRAS
10 MDP0000326734 P olygalacturonase
10 MDP0000206034 SAM
10 MDP0000566005 WRKY
10 MDP0000320017 Xyloglucan endotransglucosylase
N ◦ acoustic p eaks 10 MDP0000510383 A CO
10 MDP0000286915 AP2/ERF
10 MDP0000934866 bHLH
10 MDP0000684989 bHLH
10 MDP0000219146 bHLH
10 MDP0000285151 Cellulose synthase
10 MDP0000155026 Cellulose synthase
10 MDP0000697030 NA C domain
10 MDP0000130686 NA C domain
10 MDP0000326734 P olygalacturonase
N ◦ fo rce p eak 10 MDP0000235663 Beta-1,3-glucanase
10 MDP0000146967 Beta-1,3-glucanase
10 MDP0000205113 bHLH
10 MDP0000137050 bZIP
10 MDP0000679946 NA C domain
10 MDP0000302503 P ectate Ly ase
10 MDP0000188160 Xyloglucan galactosyltransferase
10 MDP0000669665 Xyloglucan galactosyltransferase
10 MDP0000475945 Xyloglucan galactosyltransferase
Area 10 MDP0000687812 A CO
10 MDP0000878773 A CO
10 MDP0000131702 A CO
151
10 MDP0000224275 A CO
10 MDP0000510383 A CO
10 MDP0000586400 alpha-mannosidase
10 MDP0000934866 bHLH
10 MDP0000246388 AP2/ERF
10 MDP0000187369 AP2/ERF
10 MDP0000286915 AP2/ERF
10 MDP0000457509 AP2/ERF
10 MDP0000266968 Ethylene-regulated transcript
10 MDP0000166020 Ethylene-regulated transcript
10 MDP0000136027 Endo-1,3- β a-glucanase
10 MDP0000168650 Endo-1,3- β -glucanase
10 MDP0000269126 Endo-1,4- β -glucanase
10 MDP0000220092 Endo-1,4- β -glucanase
10 MDP0000307619 GRAS
10 MDP0000326734 P olygalacturonase
10 MDP0000281965 WRKY
10 MDP0000320017 Xyloglucan endotransglucosylase
10 MDP0000897594 MYB
10 MDP0000938309 MYB
10 MDP0000226667 MYB
10 MDP0000697030 NA C domain
10 MDP0000139773 NA C domain
10 MDP0000626215 NA C domain
10 MDP0000130686 NA C domain
10 MDP0000190788 NA C domain
10 MDP0000151113 A CO
10 MDP0000187687 Beta-glucosidase-lik e
10 MDP0000122965 bZIP
10 MDP0000155956 Endo-1,3-b eta-glucanase
F orce index 14 MDP0000326390 MADS
14 MDP0000289836 MADS
14 MDP0000905135 BZIP transcription facto r
14 MDP0000157628 AP2/ERF
14 MDP0000197375 AP2/ERF
14 MDP0000261735 BZIP-lik e p rotein
14 MDP0000853568 MYB transcription facto r
14 MDP0000119204 AP2/ERF
14 MDP0000130785 NA C domain p rotein
14 MDP0000779358 Putative bZIPtranscription facto r
14 MDP0000160026 Endo-1,4- β -glucanase
14 MDP0000313820 Endo-1,4- β -glucancase
14 MDP0000234846 MYB transcription facto r
14 MDP0000184989 MYB transcription facto r
14 MDP0000620281 MYB transcription facto r
14 MDP0000402013 Myb transcription facto r
14 MDP0000478453 R2R3 MYB transcription facto r
14 MDP0000231274 BZIP transcriptional rep resso r
14 MDP0000319851 GRAS family transcription facto r
152
14 MDP0000171602 GRAS
14 MDP0000840369 GRAS
14 MDP0000265114 MYB transcription facto r
14 MDP0000656112 MYB transcription facto r
14 MDP0000656113 NA C domain p rotein
N ◦ acoustic p eak 15 MDP0000146933 AP2-ERF
15 MDP0000650702 AP2-ERF
15 MDP0000144922 AP2-ERF
15 MDP0000557234 AP2-ERF
15 MDP0000263391 P ectinesterase
15 MDP0000171994 Alpha-expansin 13
15 MDP0000163398 Alpha-expansin 13
15 MDP0000159387 Ethylene resp onsive transcription
15 MDP0000295058 Ethylene resp onsive transcription
15 MDP0000187914 NA C domain
15 MDP0000241137 WRKY transcription facto r
15 MDP0000188349 A CO
15 MDP0000629440 A CO
15 MDP0000843889 A CO
15 MDP0000258530 A CO
15 MDP0000392859 A CO
15 MDP0000753730 Alpha-mannosidase
15 MDP0000556230 mannose-6-phosphate isomerase
15 MDP0000123530 AP2/ERF
15 MDP0000446321 Endo-1,3- β -glucanase
15 MDP0000188610 Endo-1,3- β -glucanase
15 MDP0000133266 Endo-1,4- β -glucanase
15 MDP0000630192 Endo-1,4- β -glucanase
Y oung’s mo dule 15 MDP0000902970 Ethylene regulated transcript
15 MDP0000505151 Ethylene regulated transcript
15 MDP0000297684 Jumonji domain
15 MDP0000654314 MYB transcription facto r
15 MDP0000179962 MYB transcription facto r
15 MDP0000182455 MYB transcription facto r
15 MDP0000289385 NA C domain
15 MDP0000392859 NA C domain
F orce index 15 MDP0000683515 1,3- β -glucan synthase
15 MDP0000654314 AP2
15 MDP0000182455 AP2
15 MDP0000289385 AP2
15 MDP0000453797 AP2
15 MDP0000283350 AP2
15 MDP0000503275 β -glucanase
15 MDP0000277999 bZIP
15 MDP0000171308 Endo-1,3-1,4- β -d-glucanase
15 MDP0000750914 Extensin
15 MDP0000263391 GA T A
15 MDP0000245023 Glucan endo-1,3- β -glucosidase
15 MDP0000241137 GRAS
153
15 MDP0000846004 MADS
15 MDP0000759612 NA C domain
15 MDP0000181608 P ectate ly ase
15 MDP0000225437 P olygalacturonase
17 MDP0000551969 AP2/ERF
17 MDP0000945267 AP2/ERF
17 MDP0000863909 bZIP
17 MDP0000280712 MADS
17 MDP0000366022 MADS
17 MDP0000144744 MYB
17 MDP0000126343 MYB
17 MDP0000842702 NA C domain
17 MDP0000501518 NA C domain
17 MDP0000128464 WRKY
Y oung’s mo dule 17 MDP0000132870 Glucan endo-1,3- β -glucosidase
17 MDP0000123429 GRAS
17 MDP0000296007 MADS
17 MDP0000619897 NA C domain
17 MDP0000520807 P ectate ly ase
17 MDP0000657441 P olygalacturonase
T able 9.4: F o r b oth p opulations and fo r each trait are reported the
genes identified and annotated within each QTL intervals b elonging
to ethylene biosynthesis/p erception, c ell w all metab olism and tran-
scription facto rs. Fo r each gene is also rep o rted, the LG, the gene ID
(acco rding t o [223] and the annotation.)
FjxPL
T rait LG Prediction Gene
Y oung’s mo dule 3 MDP0000595295 NA C domain
3 MDP0000130797 NAC domain
3 MDP0000133636 NAC domain
3 MDP0000759504 NAC domain
F orce index 3 MDP0000324718 AP2/ERF
3 MDP0000255676 β -1,2-xylosyltransferase
3 MDP0000106455 β -1,3-galactosyltransferase
3 MDP0000134936 BZIP
3 MDP0000308685 BZIP-like p rotein
3 MDP0000212702 C2H2
3 MDP0000289626 Endo-1,4- β -glucanase
3 MDP0000243113 Ethylene resp onsive transcription factor
3 MDP0000306058 Expansin
3 MDP0000793615 GRAS
3 MDP0000205622 GRAS
3 MDP0000722954 MYB transcription factor
3 MDP0000890154 MYB transcription factor
3 MDP0000183451 MYB transcription factor
3 MDP0000144751 Myb-related protein
3 MDP0000180343 NAC domain p rotein