UNCOVER AND PROMOTE TOLERANCE TO TEMPERATURE AND
WATER STRESS IN CAMELINA SATIVA
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
INNOVATION PROGRAMME UNDER GRANT AGREEMENT NO 862524
D6.3
Da a Managemen
Plan
Re . A es(2022)6763777 - 30/09/2022
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D6.3
Da a Managemen Plan
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
INNOVATION PROGRAMME UNDER GRANT AGREEMENT NO 862524
Table o Con en s
Documen Summa y ..................................................................................................................... 3
Abs ac ........................................................................................................................................ 4
Lis o Abb e ia ions ..................................................................................................................... 5
1. In oduc ion ........................................................................................................................... 6
2. DMP Model ............................................................................................................................ 9
2.1. Da a Summa y ................................................................................................................................. 9
2.2. FAIR da a ....................................................................................................................................... 10
Making da a indable, including p o isions o me ada a ........................................................................... 10
Making da a openly accessible .................................................................................................................... 11
Making da a in e ope able .......................................................................................................................... 13
Inc ease da a euse ( h ough cla i ying licences) ........................................................................................ 13
2.3. Alloca ion o esou ces .................................................................................................................. 14
2.4. Da a secu i y ................................................................................................................................. 14
2.5. E hical aspec s ............................................................................................................................... 15
2.6. O he issues................................................................................................................................... 15
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D6.3
Da a Managemen Plan
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
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Documen Summa y
Deli e able numbe & i le: D6.3 – Da a Mangagemen Plan
Ve sion & submission da e: V2 – 30 h Sep embe 2022
Lead Bene icia y: FZJ
Rela ed Wo k Package: WP6
Au ho (s): Bjö n Usadel (FZJ)
Re iewe (s): Richa d Haslam (RRes), Juan Rod igues (RTDS), Filoklis Pileidis (RTDS), S éphane Be nillon
(INRAe), Maide Goñi (INI), Camino Fáb egas (INI), Dominik G osskinsky (AIT), Claudia Jonak (AIT)
Da ase s unde lined: None
Communica ion le el:
☒ PU Public
☐ CO Con iden ial, only o membe s o he conso ium (including he Commission Se ices)
App o ed by:
☒ AIT (COO) ☒ CCE ☒ INRAE ☒ RRes
☒ RTDS ☒
UNIBO
☒ FZJ ☒
INI
G an Ag eemen Numbe : 862524
P og amme: SFS-30-2019 / Ag i-Aqua Labs: Looking behind plan adap a ion
S a da e o P ojec : 1s Sep embe 2020
Du a ion: 5 yea s
P ojec coo dina o : AIT
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D6.3
Da a Managemen Plan
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
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Abs ac
UNTWIST is pa o he Open Da a ini ia i e o he EU. To bes p o i om open da a i is necessa y o no only
s o e da a bu o make his indable, accessible, in e ope able and eusable (FAIR). Open and FAIR da a,
howe e , conside s he need o p o ec indi idual da a se s.
The aim o his documen is o p o ide guidelines on:
● P inciples guiding he da a managemen in UNTWIST
● End poin eposi o ies o da a deposi ion
● Answe s o he EU ques ionnai e on DMP as a DMP documen
The Da a Managemen Plan (DMP) de ails how da a is o be handled du ing and a e he p ojec . The UNTWIST
DMP is modelled a ound he H2020 Online Manual. I will be upda ed/i s alidi y checked du ing he UNTWIST
p ojec se e al imes. A he e y leas , his will happen a mon h 36 (D6.4) and a he p ojec end (D6.6).
Disclaime : The opinions exp essed on his deli e able a e hose o he au ho (s) only and should no be
conside ed as ep esen a i e o he Eu opean Commission’s o icial posi ion. This public deli e able is a e ised
e sion o D6.3 Da a Managemen Plan (submi ed by M6), upda ed as eques ed by e iewe s in he 1s p ojec
pe iodic assessmen .
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D6.3
Da a Managemen Plan
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
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Lis o Abb e ia ions
AIT AIT Aus ian Ins i u e o Technology GmbH
CCE Camelina Company España S.L.
CC C ea i e Commons
DDBJ DNA Da a Bank o Japan
DEC dissemina ion exploi a ion and communica ion ( o UNTWIST)
DMP Da a Managemen Plan
DOI Digi al Objec Iden i ie
EBI Eu opean Bioin o ma ics Ins i u e
EMPHASIS Eu opean Mul i-En i onmen Plan Pheno yping And Simula ion In as uc u e
ENA Eu opean Nucleo ide A chi e
EU Eu opean Union
FAIR Findabili y, Accessibili y, In e ope abili y, and Reusabili y
FAME Fa y Acid Me hyl Es e s
FZJ Fo schungszen um Jülich GmbH
GA Gene al Assembly (o UNTWIST)
GDPR Gene al da a p o ec ion egula ion (o he EU)
GRA G an Ag eemen
INI Inicia i as Inno ado as, S.A.L.
INRAe Ins i u na ional de eche che pou l’ag icul u e, l’alimen a ion e l’en i onnemen
IP In ellec ual P ope y
MIAMET Minimal In o ma ion abou Me aboli e expe imen
MIAPPE Minimal In o ma ion abou Plan Pheno yping Expe imen
MinSEQe Minimum In o ma ion abou a high- h oughpu Sequencing Expe imen
MS Mass Spec ome y
NCBI Na ional Cen e o Bio echnology In o ma ion
NFDI Na ional Resea ch Da a In as uc u e (o Ge many)
NGS Nex Gene a ion Sequencing
PRIDE P o eomics Iden i ica ion Da abase
RNASeq RNA Sequencing
SOP S anda d Ope a ing P ocedu es
SRA Sho Read A chi e
ONP Ox o d Nanopo e
qRT PCR quan i a i e eal ime polyme ase chain eac ion
RRes Ro hams ed Resea ch
RTDS RTDS Associa ion
UNIBO Alma Ma e S udio um - Uni e si à di Bologna
WP Wo k Package
XC-MS any (x) ch oma og aphy coupled o mass spec ome y
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D6.3
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1. In oduc ion
UNTWIST ollows an open access s a egy. In addi ion o plan da a, UNTWIST is dedica ed o modelling a la ge
se o mul i-omics da a, some o which a e well de ined and s anda dized in e ms o aw ou pu and easily
compa able wi hin his omics discipline (sequencing da a), o he s a e s anda dized o ou pu (p o eomics da a)
and he emainde ha e a ying le els o s anda disa ion o ou pu (e.g. me aboli e measu emen s o e en
plan phenology). Despi e his a ia ion, in all cases necessa y s anda ds and specialis eposi o ies exis (e.g.
ENA o ansc ip and genomics da a). Hence UNTWIST will ul ima ely deposi la ge olumes o da a in public
eposi o ies, besides keeping de i ed alues and models in he UNTWIST Knowledge Hub. S anda dized omics
eposi o ies ha e p o en hei eliabili y and pe ec in eg a ion in o he FAIR landscape.
2. Da a Managemen
Da a Managemen and sample acking is e y impo an o UNTWIST. Hence UNTWIST has a sepa a e wo k
package o da a managemen , sample acking which a e leading o da a o he knowledge hub. The main wo
hings ha a e being acked:
a) physical ma e ials i.e.
plan s (plan lo s) ha a e pheno yped o (whole) plan ai s
seeds which ha e been cen ally p oduced in INRAE-IJPB and
samples ha a e gene a ed om plan s which a e g own. These migh be shipped o o he loca ions o be
analysed (e.g. lea samples om RRES o INRAE - Bo deaux o me aboli e p o iling) o a e analysed on he spo
(e.g. RRES lea samples o be subjec ed o lipidomic p o iling). He e samples can ge a code as de e mined on
he sampling wo kshop, howe e in addi ion samples a e mos ly iden i ied by he p ima y g ow h loca ion. In
any case hese samples a e linked o he plan s ha hey came om.
A e physical samples ha e been subjec ed o analysis (e.g. FAME p o iles, ca bon iso ope disc ima ion o
pheno ypes such as plan heigh ) hese hen esul in
b) measu emen s such as
i) genomic in o ma ion which is independen o he en i onmen
ii) measu emen s dependen on he en i onmen (e.g. ield condi ions; g eenhouse-imposed ea men s such
as d ough by wi hholding wa e ) such as
• ca bon iso ope disc imina ion
• o al edox s a us
• pheno ypic da a
iii) “high h oughpu omics” measu emen s
• FAME oil con en
• de ailed lipidomic da a
• ansc ip omic
• me abolomic
• epigene ic
• p o eomic
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D6.3
Da a Managemen Plan
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INNOVATION PROGRAMME UNDER GRANT AGREEMENT NO 862524
• enzyme ac i i y da ase s
• de ailed edox s a us
i ) measu emen s and/o desc ip ions desc ibing he en i onmen .
He e, he di e en ia ion be ween ii and iii is o en a bi a y bu is e lec ed in he WP s uc u e o UNTWIST. In
any case, genomic da a can hus be made a cha ac e is ic o a plan line o modelling in ask WP4 and o be
sha ed wi h he communi y (keeping in mind ha he e ozygous SNPs will ge los o ixed in indi iduals).
All measu emen s which a e dependen on he en i onmen (i.e. ii and iii) need o be also clea ly linked agains
he en i onmen hey we e g own in. As samples a e g own in se e al loca ions, measu emen da a is linked
o a sample which is desc ibed by speci ic en i onmen al in o ma ion and can ea u e a “ ield map” which
desc ibes whe e plan s whe e g own in a simple map in a g eenhouse and/o a ield (which is de i ed om
coo dina es desc ibing p ecise loca ion).
These da a a e i s checked o consis ency and comple eness by INRAE and FZJ and a e a e wa ds made
a ailable in a da abase. The e he alues can be looked a , plo ed and downloaded a con enience.
Using he da abase ensu es ha once da a is checked i is a ailable and will no be los .
Ne e heless, unde lying da a ables a e also kep on a s p se e and a e backed up egula ly. Raw da a (such
as sequencing un as q da a) ha is o be uploaded in o o he eposi o ies is also kep he e whe e necessa y.
B inging hese da a oge he in a da abase allows o link he di e en se s. Fo example, he sample me ada a
desc ibing he sample ca be de i ed by de e mining he plan (line) and he en i onmen he plan was g own
in. By ancho ing samples o he p ima y p oduce o he plan he samples we e de i ed om i is also possible
o check and echeck en i onmen s.
Fu he mo e, he sample da a base allows o sea ch o plan and samples (See Figu e 1) and allows plo ing
and compa ing measu emen s wi hin he da abase.
Figu e 1 sea ch and au ocomple e sea ching as o 8/2022 o C18 lipid measu emen s o e s se e al da a se s o selec (in
mol % as well as in µg /mg)
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D6.3
Da a Managemen Plan
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Figu e 2 plo ing a measu emen se and showing he alues o he plo in he da abase. The example shows C18:2 lipid
measu emen s
The loca ion da a allows o check o spa ial e ec s bu also allows o check easily i associa ions we e co ec
and hus allows an addi ional way o check o da a consis ency.
The da abase is hus concep ionally associa ing di e en plan s, samples and en i onmen s as concep ualised
in Figu e 3.
Figu e 3 concep ional model o he UNTWIST da abase
The ac ual low o samples is de e mined by plan p oduce s (lysime e , glasshouse, con olled chambe s) and
by he pa ne s analysing he samples depending on whe he samples a e measu ed on si e o shipped o
measu emen s. The loca ion o a sample is an impo an cha ac e is ic allowing o ace i s p o enience. Hence
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Da a Managemen Plan
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he loca ion is kep no only in he sho sample name, bu also usually in eeze boxes e c. In addi ion, o en
sample ables a e accompanying samples in physical o m (i.e. a p in ou ) as an addi ional measu e o make
su e ha samples a e no con used and ha da a in he da abase can hus be ec i ied in an upda ed e sion.
This is pa icula ly impo an o la ge ba ches o shipmen s whe e only a simpli ied naming scheme is used
on he ac ual sample ial o allow as enough sampling in o de o accoun o diu nal and o he p ocesses
equi ing as sampling and based on he expe ience wi h “ eezing esis an ” s icke s (please check e ised
e sion o 6.1). Hence, when en e ing da a in o he da abase he ull sample code is being es o ed whe e
applicable.
Once all da a is comple e and co ec i can hen also be submi ed as da a se s o public domain speci ic
da abases such as he ones om he EBI.
3. DMP Model
The sample acking pla o m now elies on a i s wo king e sion o he UNTWIST. I is passwo d p o ec ed,
so be o e any da a can be ob ained o samples gene a ed an au hen ica ion needs o ake place. (please check
MS7)
3.1. Da a Summa y
Wha is he pu pose o he da a collec ion/gene a ion and i s ela ion o he objec i es o
he p ojec ?
Fo UNTWIST, da a collec ion and in eg a ion is absolu ely necessa y as da a is no only used o unde s and
p inciples, bu i is also used o de eloping models in WP6, which need o be in o med abou da a p o enance.
I is he e o e o impo ance ha no only da a is well gene a ed, bu also well anno a ed using open s anda ds
and me ada a as i is laid ou in he ollowing sec ion. As UNTWIST aims a unco e ing new p inciples ac oss
di e se camelina lines, cul u e condi ions (coun ies, ield s con ained) and as i c osses mul iple omics
disciplines expe imen s, good documen a ion, da a keeping and in eg a ion a e necessa y.
Wha ypes and o ma s o da a will he p ojec gene a e/collec ?
We o esee ha he ollowing da a will be collec ed and gene a ed a he e y leas : Fi s ly, pheno ypic da a
abou camelina plan s, secondly expe imen al desc ip ions and whe e necessa y logging o he da a, hi dly
omics da a including genomics, epigenomics, me abolomics, ansc ip omics, lipidomic, enzyme ac i i y
p o iles, and p o eomics da a se s s emming om di e en app oaches such as nex gene a ion sequencing
(NGS) and/o quan i a i e Real Time PCR-based app oaches. In addi ion, de i ed da a om he o iginal aw
da a se s will also be collec ed. This is impo an , as di e en analy ical pipelines migh yield di e en esul s
o include ad-hoc da a analysis pa s. The e o e, speci ic ca e needs o be aken o documen and a chi e hese
esou ces (including he analy ic pipelines) as well.
Will you e-use any exis ing da a and how?
The p ojec builds on exis ing da a se s and elies on hem. Fo ins ance, wi hou a p ope genomic e e ence
i is e y di icul o analyze NGS da a se s, e en hough be e genomes will be p oduced in he cou se o he
p ojec . I is also impo an o include exis ing da a se s on he exp ession and me abolic beha io o camelina
and he backg ound knowledge o he pa ne s. Genomic e e ences can simply be ga he ed om e e ence
da abases o genomes/sequences like he Na ional Cen e o Bio echnology In o ma ion: NCBI1 (US);
1 h ps://www.ncbi.nlm.nih.go /
16
D6.3
Da a Managemen Plan
THIS PROJECT HAS RECEIVED FUNDING FROM THE EUROPEAN UNION’S HORIZON 2020 RESEARCH AND
INNOVATION PROGRAMME UNDER GRANT AGREEMENT NO 862524
UNCOVER AND PROMOTE TOLERANCE TO TEMPERATURE AND
WATER STRESS IN CAMELINA SATIVA
UNTWIST PARTNERS
