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Genetic (co)variance of rainbow trout (Oncorhynchus mykiss) body weight and its uniformity across production environments

Sae-Lim, Panya,Kause, Antti,Janhunen, Matti,Vehviläinen, Harri,Koskinen, Heikki,Gjerde, Bjarne,Lillehammer, Marie,Mulder, Han A.

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RESEARCH ARTICLE Open Access Gene ic (co) a iance o ainbow ou (Onco hynchus mykiss) body weigh and i s uni o mi y ac oss p oduc ion en i onmen s Panya Sae-Lim 1,2* , An i Kause 2 , Ma i Janhunen 2 , Ha i Veh iläinen 2 , Heikki Koskinen 3 , Bja ne Gje de 1 , Ma ie Lillehamme 1 and Han A Mulde 4 Abs ac Backg ound: When ainbow ou om a single b eeding p og am a e in oduced in o a ious p oduc ion en i onmen s, geno ype-by-en i onmen (GxE) in e ac ion may occu . Al hough g ow h and i s uni o mi y a e wo o he mos impo an ai s o ou p oduce s wo ldwide, GxE in e ac ion on uni o mi y o g ow h has no been s udied. Ou objec i es we e o quan i y he gene ic a iance in body weigh (BW) and i s uni o mi y and he gene ic co ela ion ( g ) be ween hese ai s, and o in es iga e he deg ee o GxE in e ac ion on uni o mi y o BW in b eeding (BE) and p oduc ion (PE) en i onmen s using double hie a chical gene alized linea models. Log- ans o med da a we e also used o in es iga e whe he he gene ic a iance in uni o mi y o BW, GxE in e ac ion on uni o mi y o BW, and g be ween BW and i s uni o mi y we e in luenced by a scale e ec . Resul s: Al hough he i abili y es ima es o uni o mi y o BW we e low and o simila magni ude in BE (0.014) and PE (0.012), he co esponding coe icien s o gene ic a ia ion eached 19 and 21%, which indica ed a high po en ial o esponse o selec ion. The gene ic e- anking o uni o mi y o BW ( g = 0.56) be ween BE and PE was mode a e bu g ea e a e log- ans o ma ion, as exp essed by he low g (-0.08) be ween uni o mi y in BE and PE, which indica ed independen gene ic ankings o uni o mi y in he wo en i onmen s when he scale e ec was accoun ed o . The g be ween BW and i s uni o mi y we e 0.30 o BE and 0.79 o PE bu wi h log- ans o med BW, hese alues swi ched o -0.83 and -0.62, espec i ely. Conclusions: Gene ic a iance exis s o uni o mi y o BW in bo h en i onmen s bu i s low he i abili y implies ha a la ge numbe o ela i es a e needed o each e en mode a e accu acy o selec ion. GxE in e ac ion on uni o mi y is p esen o bo h en i onmen s and sib- es ing in PE is ecommended when he aim is o imp o e uni o mi y ac oss en i onmen s. Posi i e and nega i e g be ween BW and i s uni o mi y es ima ed wi h o iginal and log- ans o med BW da a, espec i ely, indica e ha inc eased BW is gene ically associa ed wi h inc eased a iance in BW bu wi h a dec ease in he coe icien o a ia ion. Thus, he scale e ec subs an ially in luences he gene ic pa ame e s o uni o mi y, especially he sign and magni ude o i s g . Backg ound Uni o mi y o ai s depends on an indi idual’s sensi i i y o pe u ba ions in i s in e nal en i onmen and o un- known local mic o-en i onmen al ac o s [1-3]. Addi i e gene ic a iance in uni o mi y is de ined as he gene ic he e ogenei y o he esidual a iance o a ai [4-6]. Acco dingly, less sensi i e geno ypes ha e o sp ing ha a e mo e uni o m and show a smalle wi hin- amily esidual a iance. In animal p oduc ion, uni o mi y is o en a desi ed cha ac e because: (1) i indica es pheno- ypic obus ness and (2) i aids in p oducing homogeneous animal s ocks and uni o m ood p oduc s. Gene ally, aqua ic animals exhibi conside able he e ogenei y in g ow h pe o mance. La ge a ia ion in body weigh (BW) among indi iduals educes ish wel a e and dec eases he sus ainabili y o he aquacul u e indus y [7]. A common p ac ice o educe he e ogenei y in g ow h pe o mance is * Co espondence: [email p o ec ed] 1 No ima Ås, Oslo eien 1 P.O. Box 210, NO-1431 Ås, No way 2 Na u al Resou ces Ins i u e Finland (LUKE), Biome ical Gene ics, FI-31600 Jokioinen, Finland Full lis o au ho in o ma ion is a ailable a he end o he a icle Gene ics Selec ion E olu ion © 2015 Sae-Lim e al.; licensee BioMed Cen al. This is an Open Access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion License (h p://c ea i ecommons.o g/licenses/by/4.0), which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly c edi ed. The C ea i e Commons Public Domain Dedica ion wai e (h p://c ea i ecommons.o g/publicdomain/ze o/1.0/) applies o he da a made a ailable in his a icle, unless o he wise s a ed. Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 DOI 10.1186/s12711-015-0122-8 egula g ading du ing ea ing, whe e he e ogeneous ish schools a e size-so ed in o mo e homogeneous g oups ha a e ha es ed a di e en imes. Howe e , hese p o- cedu es educe o e all p o i a he a m scale because labo and a ming cos s inc ease and he p ice o small- sized ish is lowe . Ano he solu ion would be o selec animals o uni o mi y o g ow h pe o mance, p o ided ha some gene ic a iance exis s o his ai . Rainbow ou , Onco hynchus mykiss (Walbaum 1792), is an economically impo an aquacul u e species, and b eeding p og ams dis ibu e imp o ed ma e ial ac oss con inen s [8]. P oduce s wo ldwide o ainbow ou ega d g ow h pe o mance and i s uni o mi y as wo o he mos impo an ai s o be imp o ed by selec i e b eeding [9]. When ainbow ou om a single b eeding p og am a e in oduced in o a ious p oduc ion en i- onmen s, a geno ype by en i onmen (GxE) in e ac ion on g ow h pe o mance and i s uni o mi y may occu , which hampe s gene ic imp o emen o hese ai s ac oss mul iple en i onmen s. Howe e , o ou knowledge, GxE in e ac ion on uni o mi y o g ow h pe o mance in ain- bow ou has no been s udied. In Finland, ainbow ou is a med in sea and in inland eshwa e en i onmen s. The nucleus o he Finnish na- ional b eeding p og am is loca ed inland, whe e b eeding candida es a e kep in esh wa e , while hei sibs a e pe o mance- es ed in he Bal ic Sea, whe e mos la ge- scale comme cial p oduc ion akes place. To educe he isk o disease in ec ions, sea- es ed indi iduals and hei eggs o mil a e no anspo ed om he sea es s a ion back o he nucleus. Gene ic pa ame e s o uni o mi y o BW in ainbow ou ha e been s udied only in he nucleus en i onmen [10], using he addi i e model desc ibed by Mulde e al. [11]. The s a is ical me hods applied o gene ic analysis o uni o mi y o BW ha e, howe e , e ol ed apidly in ecen yea s. Rönnegå d e al. [12] in oduced a double hie a chical gene alized linea model (DHGLM), which has he ad an age o accoun - ing o he non-no mal dis ibu ion o squa ed esiduals. The e o e, in his s udy, gene ic pa ame e s o uni o mi y o BW ha we e p e iously es ima ed in he nucleus en- i onmen we e con i med by using mul i a ia e DHGLM, and uni o mi y o BW was s udied on ish om bo h he eshwa e nucleus and sea es s a ions. Fo many mo - phological ai s, a posi i e co ela ion be ween mean and a iance is expec ed, i.e. he a iance inc eases wi h he mean, which is e e ed o as a scale e ec [13]. When ai a ia ion is scaled by he mean ai alue, e.g. by log- ans o ming he da a, he esul ing log- ans o med a i- ance quan i ies he a ia ion ha does no depend on he scale e ec [13,14]. Thus, he aims o his s udy we e: (1) o quan i y he gene ic a iance o ha es BW and i s uni o mi y and he gene ic co ela ion be ween hese ai s o sibs ea ed in he eshwa e b eeding nucleus and in he seawa e p o- duc ion en i onmen , and (2) o in es iga e he deg ee o GxE in e ac ion on uni o mi y o BW o hese wo en i- onmen s. Finally, we also log- ans o med he da a o in es iga e whe he gene ic a iance in uni o mi y o BW, GxE in e ac ion on uni o mi y o BW, and he gene ic co ela ion be ween BW and i s uni o mi y we e in lu- enced by he scale e ec , mic o-en i onmen al sensi i i y, o bo h. Me hods Da a The da a used in his s udy o igina ed om he Finnish na ional b eeding p og am [15,16]. All p ocedu es ha in ol ed animals we e app o ed by he animal ca e commi ee o he Finnish Game and Fishe ies Resea ch Ins i u e (FGFRI). The b eeding nucleus (de ined as he b eeding en i onmen o BE) was loca ed on he FGFRI ish a m loca ed in Te o (Cen al Finland). Siblings o he b eeding candida es we e es ed in comme cial sea cages (de ined as he p oduc ion en i onmen o PE) loca ed in he Bal ic Sea. Pheno ypic da a comp ised 53 638 eco ds on BW a agging om ou yea classes and belonged o wo subpopula ions, i.e., 1996/1999 and 1997/2000, which we e measu ed o bo h en i onmen s. Fo each yea class, he numbe o si es and dams and he numbe o eco ded o sp ing a e in Table 1. Bo h subpop- ula ions we e es ablished om he pa en s o yea class 1993. Si es and dams we e ma ed using ei he pa e nal nes ed o pa ial ac o ial ma ing designs. Each yea class consis ed o 94 o 197 ull-sib amilies es ablished om he ma ing o 37 o 95 si es wi h 79 o 129 dams. A e ha ching, inge lings om he same ull-sib amily we e main ained in one o mo e amily anks un il hey eached a body size sui able o indi idual passi e in eg a ed Table 1 Popula ion s uc u e o ainbow ou Subpopula ion I Subpopula ion II 1996 1999 1997 2000 Numbe o pa en s and amilies Si es, dams 57, 129 37, 94 65, 79 95, 121 Si es pe dam, mean ( ange) 1.00 (1-1) 1.00 (1-1) 2.41 (1-3) 1.63 (1-3) Dams pe si e, mean ( ange) 2.26 (1-4) 2.54 (1-4) 2.93 (1-5) 2.06 (1-5) Full-sib amilies, amily anks 129, 129 94, 135 191, 259 197, 197 Numbe o ish wi h eco ds F eshwa e nucleus s a ion 4994 3084 8099 5998 Fish pe ull-sib amily 38.7 32.8 42.4 30.4 Seawa e s a ion 2573 2442 8351 7499 Fish pe ull-sib amily 19.9 26.0 43.7 38.1 Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 2 o 10 ansponde (PIT) agging (i.e. a a mean BW o app oxi- ma ely 50 g). Du ing agging, ull-sibs om each amily we e andomly sampled and di ided in o wo o h ee ba ches ha we e ea ed ei he in BE o PE. When he ish we e 2 yea s old, hey we e indi idually weighed, deno ed by BW BE in g o BE and BW PE o PE. Fo BE, sex and sexual ma u i y s a us we e eco ded based on ex e nal sex cha ac e s, whe eas o PE, since ish we e slaugh- e ed, sex and ma u i y we e iden i ied based on he mo phology o he gonads. In o al, 22 175 and 20 865 indi idual eco ds we e a ailable o BW BE and BW PE , espec i ely (Table 1). A e age BW BE and BW PE (s anda d de ia ion, SD) es i- ma ed om he aw da a we e equal o 1094 (364) and 1050 (335) g, espec i ely. S a is ical analysis We used DHGLM o s a is ical analysis [12,14,17], which uses a log-link unc ion o accoun o he non- no mal dis ibu ion o squa ed esiduals. The models we e un o wo ans o ma ions o he da a. Fi s , obse ed BW we e s anda dized o a mean o 0 and a iance o 1 o escale he o iginal da a, which acili a es con e gence. Second, obse ed BW we e log- ans o med o accoun o he scale e ec . Log- ans o ma ion is one way o educedependencyo a ianceonmean,since he log- a iance ep esen s a pa ame e ha is simila o he coe icien o a ia ion [13]. Bo h s anda dized and log- ans o med da a we e modelled using he ollowing mul i a ia e si e-dam DHGLM in ASReml [18,19]: yE1 ΨE1 yE2 ΨE2 2 6 6 43 7 7 5¼ XE1 sym 0 X ;E1 0 0 XE2 0 0 0 X ;E2 2 6 6 43 7 7 5 bE1 b ;E1 bE2 b ;E2 2 6 6 43 7 7 5þ ZsþZd ðÞ E1000 ZsþZd ðÞ ;E100 sym ZsþZd ðÞ E20 ZsþZd ðÞ ;E2 2 6 6 43 7 7 5 uE1 u ;E1 uE2 u ;E2 2 6 6 43 7 7 5þ QE1000 Q ;E100 sym QE20 Q ;E2 2 6 6 43 7 7 5 cE1 c ;E1 cE2 c ;E2 2 6 6 43 7 7 5þ eE1 e ;E1 eE1 e ;E2 2 6 6 43 7 7 5; whe e y Ej is he ec o o BW pheno ypes o y ij o he i h indi idual measu ed in he j h en i onmen (E j = BE o PE). ψis he ec o o he esidual a iances ϕij ¼ ^ e2 ij 1−hij  , which was linea ized using a Taylo se ies app oxima ion in ASReml, whe e ^ e2 ij is he squa ed e- sidual es ima e o BW , and h ij is he diagonal elemen in he ha -ma ix (p edic ed alue ma ix) o y Ej co e- sponding o y ij .X(X ) is he incidence ma ix o ixed in e ac ion e ec s o yea class, si e ( eshwa e and seawa e ), sex (male, emale, o unknown), and ma u i y (ma u i y a 2 o 3 yea s o age, o unknown). Wi hin- amily addi i e gene ic a iance can be in luenced by pa en al inb eeding [3], bu in ou da a, pa en al a e age inb eeding coe icien s we e equal o 0 [15], and hus his coe icien was excluded om he model. b(b )is he solu ion ec o o ixed in e ac ion e ec s. Z S and Z d a e he incidence ma ices o andom si e (s)and dam (d) e ec s, and u(u ) is he ec o o addi i e gen- e ic e ec s o si es and dams on BW (uni o mi y) and was assumed o ha e he ollowing dis ibu ion: uE1 u ;E1 uE2 u ;E2 2 6 6 43 7 7 5∼N0;1 4G⊗A  ; whe e Gis 4×4 si e-dam (co) a iance ma ix, and Ais he nume a o ela ionship ma ix. Q(Q ) is he inci- dence ma ix o andom e ec s common o ull-sibs ( amily ank p io o communal ea ing and non-addi i e gene ic e ec s) o he han addi i e gene ic e ec s, and c(c ) is he ec o o solu ions o he e ec common o ull-sibs, cE1 c ;E1 cE2 c ;E2 2 6 6 43 7 7 5∼N0;C⊗IðÞ,whe eCis 4×4 (co) a iance ma ix o he e ec common o ull-sibs and Iis an iden i y ma ix. The esidual o y(e)andψ(e )we e assumed independen ly no mally dis ibu ed: eE1 e ;E1 eE2 e ;E2 2 6 6 43 7 7 5∼N 0 0 0 0 ; W−1 E1σ2 ∈000 W−1 ;E1σ2 ∈ 00 sym W−1 E2σ2 ∈0 W−1 ;E2σ2 ∈ 2 6 6 6 4 3 7 7 7 5 0 B B B @ 1 C C C A; whe e WEj ¼diag b ψ−1 Ej  ,W ;Ej ¼diag 1−hj 2  ,andσ2 ∈σ2 ∈  is a scaling a iance ha was expec ed o be 1, since W con ains he ecip ocal o he indi idual esidual a iances. The mul i a ia e si e-dam DHGLM was i ed i e a i ely, wi h upda ing o ψand he diagonal elemen s o W Ej and W ,Ej un il he log-likelihood con e ged [19]. Calcula ion o es ima es o gene ic pa ame e s The es ima ed addi i e gene ic si e-dam a iance com- ponen σ2 u ;exp  o uni o mi y o BW was on he expo- nen ial scale (exp) and was consequen ly con e ed o an addi i e scale σ2 u  using he equa ions de i ed by Mulde e al. [5]. The es ima ed a iance componen o he e ec common o ull-sibs σ2 c; exp  o uni o mi y o Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 3 o 10 BW was con e ed o an addi i e scale σ2 c  using he equa ion de i ed in he Appendix. In he si e-dam model, he es ima ed a iance compo- nen o si es was se equal o he a iance componen o dams and equal o one qua e o he addi i e gene ic a iance σ2 s¼σ2 d¼σ2 u¼1 4σ2 a  , and he es ima ed a i- ance componen o uni o mi y o BW σ2 u  was equal o one qua e o he gene ic a iance o uni o mi y o BW. The e o e, addi i e gene ic a iance componen s es ima ed o BW σ2 a  and o uni o mi y o BW σ2 a  we e equal o 4σ2 uand 4σ2 u , espec i ely. Pheno ypic a iance σ2 p  o BW was equal o 2σ2 uþσ2 cþσ2 e, whe e σ2 cis he a iance componen o he e ec common o ull-sibs and σ2 eis he esidual a iance o BW, which in a si e-dam model includes one hal o he addi i e gene ic a iance plus he andom en i onmen al a iance. The e- o e, σ2 uwas mul iplied by 2 o calcula e σ2 p.He i abili y o BW (h 2 ) was calcula ed as σ2 a=σ2 pand o uni o mi y o BW h2  as σ2 a 2σ4 pþ3σ2 a þσ2 c ðÞ (see [20] and Appendix). Simi- la ly, he common en i onmen al e ec o BW (c 2 ) was calcula ed as σ2 c=σ2 pand o uni o mi y o BW c2  as σ2 c 2σ4 pþ3σ2 a þσ2 c ðÞ (see Appendix). The gene ic coe icien o a ia ion o uni o mi y o BW (CVa ) was calcula ed as σa =σ2 E,whe eσ2 E¼σ2 e−2σ2 u . Th ee gene ic co ela ions ( g ) we e calcula ed based on he addi i e gene ic co a iance di ided by he p od- uc o he wo co esponding addi i e gene ic s anda d de ia ions: (1) be ween BW and i s uni o mi y wi hin an en i onmen , (2) o one ai (BW o i s uni o mi y) in BE e sus PE, i.e. o quan i y gene ic e- anking be ween en i onmen s, and (3) be ween BW in one en i onmen and i s uni o mi y in he o he en i onmen . App oxima e s anda d e o s o a iance componen es ima es we e calcula ed wi h ASReml ollowing Fishe e al. [21]. App oxima ed s anda d e o s o h2 and c2 a e no a ailable in ASReml and o ou knowledge ha e no been de i ed. Compa ison wi h an addi i e model We also used an addi i e model ha e e s o he “i e a- i e bi a ia e model”desc ibed in Mulde e al. [11], o analyze pa o he da a o BW and i s uni o mi y using he log-squa ed esiduals, as desc ibed in [10,11]. In ha analysis, we included only he da a om BE and we epo only he gene ic co ela ion be ween BW and i s uni o mi y. Ou aim was o e i y whe he o no he gene ic co ela ion es ima ed by he addi i e model was consis en wi h ha es ima ed by he DHGLM when he scale e ec on uni o mi y o BW was accoun ed o by log- ans o ma ion o BW. Resul s Gene ic a ia ion o BW and i s uni o mi y Using s anda dized da a, addi i e gene ic a iances o BW we e simila o BE and PE (0.140 o 0.143). He i - abili y es ima es o BW (h 2 ) we e also simila and mod- e a e o BE (0.258) and PE (0.221) (Table 2). He i abili y es ima es o uni o mi y o BW h2 we e low and o simila magni ude o BE (0.011) and PE (0.010). Using log- ans o med da a, addi i e gene ic a iances in BW we e p opo ionally lowe o bo h en i onmen s (0.013 o 0.015) han wi h s anda dized da a. All es ima es o gene ic a iance o uni o mi y o BW we e g ea e han hei s anda d e o s (SE). Using log- ans o med da a, es ima es o h 2 o BW in BE and PE we e sligh ly lowe (0.12 o 0.17) han wi h s anda dized da a, and he es i- ma e o h2  o uni o mi y o BW in BE (0.024) was sligh ly highe han wi h s anda dized da a, whe eas h2 in PE (0.010) was simila o ha ob ained wi h s anda dized da a. While es ima es o h2  we e low, gene ic coe icien s o a ia ion CVa o uni o mi y o BW es ima ed wi h s anda dized da a we e equal o 21.1% o BE and 19.0% o PE, which indica ed a high gene ic po en ial o e- sponse o selec ion ela i e o he mean. The CVa o uni o mi y o BW es ima ed wi h log- ans o med da a was equal o 29.6% and 17.4% o BE and PE, espec - i ely, which suppo s he exis ence o gene ic di e ences o uni o mi y o BW beyond he scale e ec . Es ima es o common en i onmen al e ec s on BW, c 2 , anged om o 0.02 o 0.03 o bo h en i onmen s, which sugges s ha a small amoun o pheno ypic a ia ion was due o sepa a e ull-sib anks be o e communal ea ing and o non-addi i e gene ic e ec s. The es ima e o c2 o uni o mi y o BW anged om 0.004 o 0.005 when es i- ma ed based on s anda dized da a and om 0.019 o 0.021 when es ima ed wi h log- ans o med da a. Geno ype by en i onmen in e ac ion Using s anda dized da a, he es ima e o g o BW be- ween BE and PE was equal o 0.70 ± 0.06, which means ha a low deg ee o e- anking occu ed be ween en i onmen s (Table 3), while sligh ly g ea e e- anking ( g = 0.56 ± 0.20) was ound o uni o mi y o BW be ween BE and PE. Using log- ans o med da a, he es ima e o g o BW be ween BE and PE was equal o 0.66 ± 0.06, which was simila o ha ob ained wi h s anda dized da a. In con as , he es ima e o g o uni o mi y o BW be ween BE and PE was close o 0 (-0.08 ± 0.33), which indica es ha , a e accoun ing o he scale e ec , he anking o Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 4 o 10 b eeding alues o uni o mi y o BW be ween BE and PE was independen . Gene ic co ela ion be ween BW and i s uni o mi y Wi h s anda dized da a, he es ima e o g be ween BW and uni o mi y o BW was lowe in BE (0.30) han in PE (0.79). Howe e , wi h log- ans o med da a, he es i- ma es o g be ween BW and uni o mi y o BW in he wo en i onmen s we e simila bu nega i e (-0.83 in BE and -0.62 in PE). Fo ans o med da a, he magni ude o hese es ima es was g ea e han he es ima es o g be ween BW BE and i s log-squa ed esiduals om he addi i e model (-0.40 ± 0.05). As o gene ic co ela ions wi hin one en i onmen , es ima es o g be ween ai s measu ed in di e en en i onmen s depended on whe he s anda dized o log- ans o med da a we e used (Table 3). Wi h s anda dized da a, he es ima es o g be ween BW BE and uni o mi y PE (0.49) and be ween BW PE and uni o mi y BE (0.46) we e simila . Con e sely, g es ima ed wi h log- ans o med da a was nega i e bu o simila magni ude be ween BW BE and uni o mi y PE (-0.42) and be ween BW PE and uni o mi y BE (-0.31). Discussion Gene ic a ia ion o uni o mi y o body weigh He i abili y o uni o mi y o BW es ima ed wi h s an- da dized da a was low o bo h en i onmen s (<0.02). A e log- ans o ma ion, es ima es o h 2 and c 2 o BW we e lowe in bo h en i onmen s, whe eas es ima es o h2 and c2 o uni o mi y o BW we e highe in BE bu lowe in PE. The es ima es o h2 o uni o mi y o BW ob ained in his s udy a e in line wi h hose p e iously epo ed o ainbow ou h2 ¼0:024  [10] and o e es ial animals such as snail [22], b oile chickens [11,23,24], mice [25], and pigs [26] (  h2 ¼0:028 : min = 0.006 and max = 0.047; e iewed by Hill and Mulde [6]). These h2 es ima es a e low pa ly because he Table 2 Es ima es o a iance componen s and gene ic pa ame e s o body weigh a ha es and i s uni o mi y measu ed unde b eeding and p oduc ion en i onmen s, wi h o wi hou log- ans o ma ion o he da a T ai /Pa ame e En i onmen S anda dized Log- ans o med B eeding P oduc ion B eeding P oduc ion Body weigh σ2 p0.543 0.646 0.089 0.109 σ2 a0.140 0.143 0.015 0.013 σ2 c0.019 0.024 0.003 0.003 h 2 (SE) 0.258 (0.031) 0.221 (0.028) 0.170 (0.023) 0.120 (0.017) c 2 (SE) 0.036 (0.007) 0.038 (0.006) 0.031 (0.005) 0.026 (0.004) Uni o mi y o body weigh σ2 a ;exp (SE) 0.0433 (0.014) 0.0354 (0.012) 0.0814 (0.030) 0.0289 (0.020) σ2 a 0.0068 0.0085 0.0004 0.0003 σ2 c 0.0032 0.0031 0.0004 0.0005 CVa 0.211 0.190 0.296 0.174 h2 0.011 0.010 0.024 0.010 c2 0.005 0.004 0.021 0.019 σ2 p= pheno ypic a iance 2σ2 uþσ2 cþσ2 e  , whe e σ2 eis he esidual a iance o body weigh ; σ2 aand σ2 a = addi i e gene ic a iance o body weigh and i s uni o mi y, espec i ely; σ2 c= common en i onmen al a iance; CVa = coe icien o addi i e gene ic a iance o uni o mi y σa =σ2 E  , whe e σ2 E¼σ2 e −2σ2 u; h 2 = he i abili y o body weigh ; c 2 = common en i onmen al e ec due o ull-sib anks; h2 = he i abili y o uni o mi y; c2 = same as c 2 bu o uni o mi y o body weigh . Table 3 Es ima es o he gene ic co ela ion ( g ) and s anda d e o s be ween body weigh a ha es (BW) and i s uni o mi y, wi hin and be ween en i onmen s and wi h o wi hou log- ans o ma ion o he da a T ai g (SE) S anda dized Log- ans o med Wi hin en i onmen BW BE –uni o mi y BE 0.30 (0.15) −0.83 (0.10) BW PE –uni o mi y PE 0.79 (0.13) −0.62 (0.21) GxE in e ac ion BW BE –BW PE 0.70 (0.06) 0.66 (0.06) uni o mi y BE –uni o mi y PE 0.56 (0.20) −0.08 (0.33) Di e en ai - di e en en i onmen BW BE –uni o mi y PE 0.49 (0.14) −0.42 (0.25) BW PE –uni o mi y BE 0.46 (0.15) −0.31 (0.16) BE = b eeding en i onmen ; PE = p oduc ion en i onmen . Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 5 o 10 he i abili y is de ined a he le el o a single obse a ion and es ima ing a b eeding alue o a iance based on a single obse a ion will be inaccu a e. In addi ion, uni o mi y o BW can be a ec ed by mul iple en i- onmen al ac o s ha educe he i abili y es ima es [27]. In ac , inding low he i abili ies wi h high CV a seems o be a gene al obse a ion o ai s ha a e closely ela ed o i ness, such as ecundi y and age a sexual ma u i y [27]. Al hough we ound low es ima es o h2 o uni o mi y o BW, i s CVa was high in bo h en i onmen s (21.1% in BE and 19.0% in PE), which indica es a high po en ial o gene ic gain in esponse o selec ion o inc eased uni o mi y ela i e o he mean [5,27,28]. The CVa es ima ed in his s udy a e in he lowe ange o hose e- po ed p e iously o uni o mi y o BW in ainbow ou (0.374) [10], A lan ic salmon (0.417) [14], and e es ial animals ( CVa = 40.6%; min = 30.0% and max = 58.0%) [6,11,22-26]. The CVa es ima ed wi h s anda dized BW da a can be explained by bo h he scale e ec and addi i e gene ic e - ec s o mic o-en i onmen al sensi i i y. As expec ed, when he scale e ec was accoun ed o by log- ans o ma ion o BW, he addi i e gene ic a iance o uni o mi y o BW de- c eased. Ye , a e log- ans o ma ion, CVa es ima es emained high, which indica es ha gene ic a ia ion o uni o mi y o BW is scale independen . P e ious s udies ha e epo ed a simila phenomenon by compa - ing ans o med and un ans o med da a o BW in A - lan ic salmon [14] and o li e size in abbi s and pigs [29]. S udies on uni o mi y commonly use ans o med da a o educe non-no mali y o he da a. Fo example, squa ed esiduals we e log- ans o med in he addi i e model applied in [10,11], and a Box-Cox ans o ma ion was used in he Bayesian app oach o [10,23,28,29]. I is likely ha such ans o ma ions also emo ed pa o he scale e ec om he da a, which in luences he gen- e ic pa ame e s o uni o mi y, as e idenced by he cu en and p e ious s udies [14,29]. The de ini ion o uni o mi y be o e and a e log- ans o ma ion is no he same. F om a biological poin o iew, uni o mi y o log- ans o med BW may be mo e ele an because he scale e ec is accoun ed o and hus he ac ual gene ic a ia ion o en i on- men al canaliza ion can be quan i ied. Howe e , o a ish a me , uni o mi y a he obse ed scale may be mo e ele an because i co esponds o he eal ange o ish sizes ha a e p ocessed by he indus y. Va iance a he obse ed scale can be selec ed o di - ec ly, whe eas log- ans o med a iance can be con- olled ei he by di ec selec ion, o by selec ing on an index wi h app op ia e weigh s on mean BW and obse ed a iance. In he si e-dam mixed DHGLM ha we applied, he squa ed esiduals ha we e used as pheno ypic obse a- ions o uni o mi y included bo h he Mendelian sampling e m and he ue esidual ha emained unexplained by he sys ema ic ixed e ec s, he andom addi i e gene ic e ec s, and he non-gene ic andom e ec s. The animal mixed DHGLM, assumes ha he esidual is ee o Mendelian sampling a iance [14]. Howe e , applying his model may c ea e biased gene ic pa ame e s o uni o mi y [30] and hus equi es ha epea ed eco ds om he same indi iduals a e used o minimise he bias o gene ic pa ame e s [12]. A educ ion in pheno ypic a ia ion o animal ai s is bene icial o animal p oduc ion. Howe e , selec ion o uni o mi y in li es ock is in i s ini ial phase o de elop- men . In abbi s, selec ion o uni o mi y o bi h weigh was implemen ed success ully and esul ed in imp o ed su i al a e o baby abbi s wi hou educing mean bi h weigh [31]. To ou knowledge, selec ion o uni- o mi y has no been implemen ed ye in ish b eeding. I has been s a ed ha selec ion o uni o mi y is no ele an when he p o i unc ion based on mean alues o a ai is linea [28], which is he case o g ow h pe o mance o body weigh . Howe e , i is a guable ha uni o mi y pe se has bo h an economic and a non- economic alue [32]. In aquacul u e, a mo e uni o m g ow h pa e n educes he mo ali y o smalle ish [33]. Du ing he g ow-ou pe iod, he size o eed pelle s is inc eased as he mean BW o a ish school inc eases. Thus, a uni o m g ow h pa e n allows mos ish o adap o changes in pelle size. Uni o mi y o g ow h may also pa ially educe nega i e social in e ac ions be ween ish and hus he de elopmen o beha iou al dominance hie a chies [34,35], which u he imp o es ish wel a e. Mo eo e , i has been sugges ed ha uni- o mi y o g ow h pe o mance educes he need o size-g ading and hus, imp o es he e iciency o ish p oduc ion [36]. The e o e, while he economic alue o uni o mi y emains o be calcula ed, simul aneous selec- ion o BW and i s uni o mi y is expec ed o yield di ec and indi ec p o i able p ospec s. Di ec selec ion o uni o mi y o a ai should be ca ied ou i his ai is economically impo an and can be eco ded a an ac- cep able cos . The me hods in es iga ed in his s udy can also be ex- ended o o he ai ypes. Fo example, educing he a ia ion in ca cass quali y ai s ha ha e in e media e op imum alues such as ille colo , ille lipid con en and body shape, has economic alue, i.e. ille colo and ille lipid con en should no be oo low o oo high, and body shape should no be oo hin o oo ound. Conside ing he b eede s equa ion ΔG=i IH σ a [3], esponse o selec ion is de e mined by h ee ac o s: se- lec ion in ensi y (i), accu acy o selec ion ( IH ), and he Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 6 o 10 gene ic s anda d de ia ion (σ a )o CV a when ΔGis ela- i e o a ai mean. We ound ha he CVa o uni- o mi y o BW was high, which indica es ha subs an ial gene ic esponse o selec ion ela i e o he mean can be expec ed. To minimize sampling a iance o he es i- ma es o σa , pheno ypes on a la ge numbe o ela i es a e equi ed. Based on he equa ion in Hill and Mulde [6], he op imal amily size o es ima e a iance compo- nen s o uni o mi y o BW is 85 o ull-sibs when using a e age h 2 es ima es o 0.145 o log- ans o med BW and a CVa o 23.5% o log- ans o med uni o mi y o BW (Table 2). In li es ock, e.g., o dai y ca le, in o - ma ion is mainly a ailable om hal -sibs, o which he op imal design is 190 hal -sibs o he same inpu pa ame e s. Wi h espec o he IH , accu acies o sib selec ion o a ai wi h a h2 o 0.014 and c2 o 0.012 (a e age alues om Table 2) a e equal o 0.234, 0.300, 0.364, and 0.412 o ull-sib amily sizes o 40, 80, 160, and 300, espec - i ely. When he alues o h2 and c2 epo ed by Janhunen e al. [10] a e used, accu acies inc ease sligh ly and he equi ed amily sizes dec ease. Wi h he accu acies o sib selec ion abo e, i is possible o calcula e expec ed changes in uni o mi y o BW. Using a p opo ion o 10% o selec ed animals (selec ion in ensi y = -1.755), a CVa o 0.211 in BE (Table 2), gene ic gain was calcu- la ed ollowing Mulde e al. [5]. Residual a iance o BW (as a pe cen o he ai mean) dec eased by -9%, -11%, -13%, and -15%, o ull-sib amily sizes o 40, 80, 160, and 300, espec i ely. Fo many aquacul u e species, i is possible o ha e la ge amilies. Howe e , he challenge is ha b eeding candida es a e om he o sp ing gene a ion and hei selec ion accu acy is lowe han ha o hei pa en s. P ogeny- es ing schemes a e e ec i e o inc ease he ac- cu acy o selec ion o ai s wi h low he i abili y, includ- ing uni o mi y [5,28], bu ha e no gained popula i y in aquacul u e b eeding. In aquacul u e b eeding schemes, sib- es ing is conside ed o be mo e easible because la ge sib g oups inc ease selec ion accu acy and gene a ion in e als a e sho e han in p ogeny- es ing schemes. The mos sui able designs o imp o e uni o mi y in aquacul u e a e s ill o be de eloped. Ano he app oach o inc ease he accu acy o sib selec ion is o use genomic selec ion [37,38], which can heo e ically inc ease accu acy o selec- ion wi hou p ogeny es ing. Geno ype by en i onmen in e ac ion To he bes o ou knowledge, his is he i s s udy on GxE in e ac ion on uni o mi y o BW in ainbow ou . The main p oduc ion en i onmen o Finnish ainbow ou is in he Bal ic Sea. PE and BE di e conside ably in e ms o wa e empe a u e, salini y, leng h o g owing season, eeding p ac ice, and ype o cage cul u e (sea cages s. ea h-bo omed aceways). Wi h s anda dized da a, mode a e e- anking o amilies o uni o mi y o BW was ound ( g = 0.56), which indica es ha uni o mi y o BW sha es a ce ain deg ee o gene ic backg ound in each en i onmen . When scale e ec s and mic o- en i onmen al sensi i i y simul aneously in luence uni- o mi y o BW, he magni ude o e- anking o uni o mi y o BW is only sligh ly smalle han o BW (0.62 o 0.70). This was su p ising, gi en ha he wo en i onmen s ana- lyzed di e ed g ea ly, and ha s anda d de ia ions o indi- idual BW, measu ed as squa ed esiduals, a e in luenced by many unspeci ic abio ic and bio ic en i onmen al ac- o s, as well as by de elopmen al pe u ba ions du ing he wo yea s o g ow h. Howe e , when he scale e ec was accoun ed o by log- ans o ma ion, he gene ic co el- a ion be ween uni o mi y o BW in BE and PE dec eased o -0.08. This shows ha he scale e ec may be he main ac o ha causes he mode a e posi i e co ela ion be ween uni o mi y o BW in he wo en i onmen s, and ha uni o mi ies es ima ed wi h s anda dized e - sus log- ans o med da a a e gene ically dis inc ai s. Log- ans o med uni o mi y is mo e g ea ly in luenced by mic o-en i onmen al sensi i i y han by scale e ec s. The gene ic co ela ion o -0.08 be ween uni o mi ies o BW in BE and PE was he lowes gene ic co ela ion epo ed o any ai ac oss hese wo en i onmen s, bu had a high s anda d e o (0.33). The high sampling a i- ance o he g may be explained by he low h2 o uni o m- i y o BW in bo h en i onmen s, bu also by he ac ha s anda d e o s o gene ic co ela ions end o inc ease wi h dec easing magni ude o gene ic co ela ions [39]. I he aim is o inc ease gene ic esponse in uni o mi y o BW in bo h en i onmen s, an op imized selec ion s a egy ha accoun s o he GxE in e ac ion on uni- o mi y and uses sib pe o mances in bo h en i onmen s is ecommended [40-42]. Uni o mi y o BW in he nu- cleus en i onmen and in he p oduc ion en i onmen should be conside ed as wo di e en ai s and should be included sepa a ely in a selec ion index. In a si ua ion whe e wo o mo e en i onmen s a e equally impo an , i migh bepossible oes ablishasepa a eb eedingp o- g am o each en i onmen o maximize esponse o selec- ion o uni o mi y in each en i onmen [43]. Ne e heless, es ablishing an addi ional b eeding p og am is e y cos ly and may no be possible in many cases. Gene ic co ela ion be ween body weigh and uni o mi y In addi ion o he deg ee o e- anking o amilies o uni o mi y in he wo en i onmen s, he scale e ec d as ically a ec ed he gene ic co ela ion be ween BW and i s uni o mi y. Gene ic co ela ions o 0.30 and 0.79 we e ound be ween BW and i s uni o mi y in BE and Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 7 o 10 PE, espec i ely, bu hese alues swi ched o -0.83 and -0.62 a e he scale e ec was accoun ed o by log- ans o ma ion. A simila change in sign was obse ed o co ela ions be ween BW in one en i onmen and i s uni o mi y in he o he en i onmen . The da a ob ained o BE we e also analyzed using he addi i e model, which used log-squa ed esiduals [11]. This esul ed in a gene ic co ela ion o -0.40 be ween BW and i s uni o mi y, which is close o he gene ic co ela ion es ima ed a e log- ans o ma ion in he DHGLM. On he whole, he gene ic co ela ion es i- ma ed be ween BW and i s uni o mi y was un a ou able when un ans o med BW da a we e used bu a ou able when log- ans o med BW da a we e used. Hence, selec- ion o BW inc eases he a iance o BW, bu dec eases he coe icien o a ia ion (CV) o BW because he inc ease in a iance o BW is smalle han expec ed i he CV o BW emains cons an o dec eases. I may be a gued ha due o inc eased g ow h a e, a me s can ha es ish ea lie a he han a an inc eased BW. Hence, he gene ic gain in BW o g ow h (e.g. g/day) is exp essed as lowe age a he han highe weigh a slaugh e . In ha case, i is s ill unknown whe he gen- e ic a ia ion in uni o mi y o BW changes since ish a e slaugh e ed a a younge age. We obse ed a change in he magni ude and sign o gene ic co ela ions be ween BW and i s uni o mi y a e da a ans o ma ion, which ag ees wi h o he s udies. Sonesson e al. [14] epo ed ha he Pea son co el- a ion be ween es ima ed b eeding alues o BW and i s uni o mi y in A lan ic salmon changed om 0.42 wi h un ans o med da a o -0.17 wi h log- ans o med da a. Se e al s udies on li es ock species ha e epo ed nega- i e gene ic co ela ions be ween BW and i s uni o mi y ( g= -0.36: min = -0.81 and max = -0.11) [6,11,22-24]. Yang e al. [29] es ima ed he gene ic co ela ion be- ween he mean and a iance o li e size in abbi s and pigs using a model wi h Ma ko chain Mon e Ca lo (MCMC) sampling, which simul aneously es ima ed he model pa ame e s and he Box-Cox ans o ma ion pa- ame e s. They compa ed gene ic co ela ions be o e and a e Box-Cox ans o ma ion and ound ha hey changed om -0.73 o 0.28 o abbi da a and om -0.64 o 0.70 o pig da a. Mo eo e , while he gene ic ends ac oss ou successi e gene a ions showed ha g ow h a e inc eased ac oss gene a ions by selec ion, no co ela ed gene ic change in uni o mi y o g ow h a e was ound du ing he same pe iod, when uni o mi y was es ima ed based on log- ans o med da a ( esidual a i- a ion scaled by he ai mean). Es ima es o gene ic co - ela ions be ween BW and i s uni o mi y ob ained in ou s udy using he DHGLM and an addi i e model we e o he same sign (-0.157) as in Janhunen e al. [10] bu mo e nega i e. Thus, i is likely ha selec ion o inc eased BW based on he gene ic pa ame e s es ima ed he e, will esul in a a ou able co ela ed end o log- ans o med uni o mi y. O iginally, i was sugges ed ha mass selec ion o an inc ease in he mean o a ai may esul in inc eased en i onmen al a iance be- cause he selec ed ex eme indi iduals may also ha e he highes mic o-en i onmen al sensi i i y, e en i he e is no gene ic co ela ion be ween he mean o he ai and i s uni o mi y [4,5]. Howe e , o es his hypo h- esis, i is necessa y o conside whe he he da a on he ai is log- ans o med o no . In o he wo ds, i is im- po an o be explici whe he analysis o uni o mi y (o mic o-en i onmen al sensi i i y) conce ns he combined e ec o scale and ue mic o-en i onmen al sensi i i y, o only he la e . Conclusions We ound a high po en ial o esponse o selec ion o uni o mi y o BW in ainbow ou ela i e o he mean and ha uni o mi y o BW is a gene ically di e en ai in b eeding and p oduc ion en i onmen s. We ecom- mend ha , in p ac ice, aquacul u e b eeding p og ams use sib es ing when he aim is o imp o e uni o mi y ac oss en i onmen s. A la ge numbe o ela i es will aid in ob aining a su icien ly high accu acy o selec ion o uni o mi y o BW. When using log- ans o med ha - es BW, we ound a nega i e gene ic co ela ion be ween BW and i s uni o mi y, which indica es ha selec ing o inc eased BW and mo e uni o m ish is possible. The scale e ec subs an ially in luences he gene ic pa ame e s o uni o mi y o BW, especially he sign and magni ude o he gene ic co ela ions be ween BW and i s uni o mi y and uni o mi y be ween en i onmen s. Appendix The aim he e is o show he ex ension o equa ion 16 in Mulde e al. [5] o mul iple andom e ec s and how o he pa ame e s such as c 2 can be calcula ed. Felleki and Lundeheim [20] showed de i a ions o es ima e he he i abili y o en i onmen al a iance. Fo comple eness, hey a e p o ided he e. In addi ion, we gi e equa ions o c2 , he p opo ion o a ia ion in squa ed pheno ypic de ia ions explained by common en i onmen al e ec s. Fi s , he esidual a iance in he exponen ial model is calcula ed as: σ2 e;exp ¼σ2 E=exp 1 2σ2 a ;exp  exp 1 2σ2 c ;exp  ;ð1Þ whe e σ2 Eis he esidual a iance om he mean model, assuming homogenous esidual a iance and assuming he use o an animal model. Subsequen ly, as an analogy o equa ion 17 in Mulde e al. [5], he sum o he gene ic a iance and common Sae-Lim e al. Gene ics Selec ion E olu ion (2015) 47:46 Page 8 o 10 en i onmen al a iance o he addi i e model can be calcula ed as: σ2 a þσ2 c ¼σ4 e;exp exp 2σ2 a ;exp  exp 2σ2 c ;exp  −σ4 E: ð2Þ The p oduc o equa ion (2) is a combina ion o σ2 a and σ2 c . Unde he assump ion ha he a io o σ2 a σ2 a þσ2 c is equal on bo h he addi i e and exponen ial scales, subse- quen ly σ2 a is calcula ed as: σ2 a ¼σ2 a þσ2 c  σ2 a ;exp σ2 a ;exp þσ2 c ;exp ;ð3Þ and o common en i onmen al e ec s: σ2 c ¼σ2 a þσ2 c  σ2 c ;exp σ2 a ;exp þσ2 c ;exp :ð4Þ The he i abili y o en i onmen al a iance h2 can be calcula ed as: h2 ¼σ2 a 2σ4 pþ3σ2 a þσ2 c  :ð5Þ Simila ly, he a io be ween common en i onmen al e ec s c2  can be calcula ed as: c2 ¼σ2 c 2σ4 pþ3σ2 a þσ2 c  :ð6Þ Fo hese equa ions, i is assumed ha gene ic and common en i onmen al co ela ions be ween mean and a iance a e 0; o he wise he denomina o would be sligh ly highe wi h he exponen ial model (no shown). Howe e , he e ec o his simpli ying assump ion is negligible. The equa ions we e e i ied wi h Mon e Ca lo simula ion and ollowing he same assump ions as in Mulde e al. [5]. Compe ing in e es s The au ho s decla e ha hey ha e no compe ing in e es s. Au ho s’con ibu ions PSL, BG, ML, HAM, and AK planned he s udy. HK con ibu ed o he da a collec ion. PSL pe o med da a analysis. Fo compa ison, MJ and HV pe o med he analysis wi h he addi i e model using he same da ase . HAM con ibu ed o he heo y and o he da a analysis using DHGLM. HAM also de i ed he equa ions shown in he Appendix. AK, HAM, MJ, HV, HK, BG and ML con ibu ed o discussion o he da a analysis and he esul s. PSL d a ed he manusc ip and all au ho s con ibu ed o discussion o he esul s and imp o ed he manusc ip o he inal e sion. All au ho s ead and app o e he inal e sion o he manusc ip . Acknowledgemen s This s udy is a pa o he pos doc o al esea ch p ojec STABLEFISH (NRC: 234144/E40) unded by No wegian Resea ch Council. PSL and AK would like o acknowledge Timo Pi känen (LUKE) o his use ul cons uc i e discussion. PSL would like o hank A hu Gilmou ega ding his commen s on mul i a ia e DHGLM in ASReml 4.0. Au ho de ails 1 No ima Ås, Oslo eien 1 P.O. Box 210, NO-1431 Ås, No way. 2 Na u al Resou ces Ins i u e Finland (LUKE), Biome ical Gene ics, FI-31600 Jokioinen, Finland. 3 Na u al Resou ces Ins i u e Finland (LUKE), Aquacul u e Uni , FI-72210 Te o, Finland. 4 Animal B eeding and Genomics Cen e, Wageningen Uni e si y, P.O. Box 338, 6700 AH Wageningen, he Ne he lands. Recei ed: 7 No embe 2014 Accep ed: 21 Ap il 2015 Re e ences 1. Wadding on CH, Robe son E. Selec ion o de elopmen al canalisa ion. Gene Res. 1966;7:303–12. 2. Le ne IM. Gene ic Homeos asis. London: Oli e & Boyd; 1954. 3. Falcone DS, Mackay TFC. In oduc ion o quan i a i e gene ics. 4 h ed. Essex: Longman; 1996. p. 464. 4. Hill WG, Zhang XS. E ec s on pheno ypic a iabili y o di ec ional selec ion a ising h ough gene ic di e ences in esidual a iabili y. Gene Res. 2004;83:121–32. 5. Mulde HA, Bijma P, Hill WG. P edic ion o b eeding alues and selec ion esponse wi h gene ic he e ogenei y o en i onmen al a iance. Gene ics. 2007;175:1895–910. 6. Hill WG, Mulde HA. 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