French genomic experience: genomics for all ruminant species Eric Venot, Anne Barbat, Didier Boichard, Pascal Croiseau, Vincent Ducrocq, Rachel Lefebvre, Florence Phocas, Marie Pierre Sanchez, Thierry Tribout, Aurelie Vinet, et al.
To cite this version:
Eric Venot, Anne Barbat, Didier Boichard, Pascal Croiseau, Vincent Ducrocq, et al.. French genomic experience: genomics for all ruminant species. 2016 Interbull Meeting, Oct 2016, Puerto Varas, Chile. hal-02743221
HAL Id: hal-02743221 https://hal.inrae.fr/hal-02743221 Submitted on 3 Jun 2020
HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Version preprint Lefebvre, R.,Phocas,F., Sanchez,M. P.,Tribout,T., Vinet,A.,Fouilloux, M.-N., Govignon Gion, numberorganization ofthese a to collaborative breeds, thanks hardy breeds. sheep in leadersEuropean the of one also is (SAL)) Salersand (ROU)prés des Rouge (PAR), Parthenaise (GAS), Gasconne Limousine (LIM) and Blonde d’Aquitaine also large with ( production 5 for (used breed Lacaune and the by represented (NOR)) Normande (MON), Montbéliarde (HOL), onesregional (Holstein breeds cattle dairy national species ruminant of panel large a maintain Considering Introduction Keywords: defects were genomic information is not limited to genomic evaluation: other new services of interest for breeders facilitated through sharing of technological to possible compared m specifi genes informationbeused will in breed extended to 3 beef and 5 extra dairy cattle breeds. It Genomic selection Abstract 6 5 4 3 2 [email protected] 1 Boulesteix Palhière Barbat Sanchez Venot E. ruminantFrench species genomicsforall genomic experience: Red Faced and Black Faced Black and Faced Red
GenPhySE Institut del’Elevage, domaine GABI, Jouy de 78350 Vilvert, GABI, INRA, AgroParisTech Venot, E. (Auteurdecorrespondance), Barbat,A.,Boichard, D.,Croiseau, P.,Ducrocq, V., Institut del’ElevageInstitut del’ElevageInstitut A ulti llice
-
developed, such as the determination of the animal status animal the of determination the as such developed, in 2015, and breed evaluations, evaluations, breed ci 3 . , GABI,de domaine rne a mngd o mlmn o wl so ipeet eoi slcin o a large a for selection genomic implement soon will or implement to managed has France inFrance represented with well are alsoMeat breeds of Use goals. breeding in included be can that traits new for selection allow tools Genomic R between strongpartnership A the for account to adapted been has methodology genomic the breed, and species each For
A Baur A. , 1 ties regarding ties 4 1 T Tribout T. , , C. Robert C. , , 6 across species
, Université de Toulouse, INRA, INPT, ENVT, 31326Castanet , S.Mattalia genomic selection . Barbat A.
mlmn ti tcnlg i large in technology this implement its size ( size its
are nowadays under selection in France. The same can be found in dairyin found becan sameFrance. The in selection under arenowadays
2
major 3 C Hoze C. , will will was - 1 550,000 km 550,000 1 Granié , , A Vinet A. ,
D Boichard D. , genomic evaluation: genomic 87060 Limoges 31326 CastanetTolosan,
start
2 breeds: Saanen andbreeds: Saanen Alpine implemented in France (Corresponding Author)
.
addition Comment citer cedocument: Vilvert, Jouy 78350
3 in 4 ), Basco ), S Fritz S. , , , R. Rupp R. ,
, Université Paris ruminant 2017 1 , 2
meat inthe sheep
), France ), N Fouilloux MN f oeg gntc n gnmc information genomic and genetic foreign of
for 1 - P Croiseau P. , Béarnaise and Corsican breeds. Corsican and Béarnaise , France 3 esearchand R Saintilan R. ,
4 , the 2 main goat breeds and 3 , F. Tortereau F. ,
dairy
(BLA)) and 6 regional (Aubrac (AUB), Bazadaise (BAZ),
expertise presents a large landscape diversity and has managed to to managed has and diversity landscape large a presents the of size meat production relying on more than 20 specialized or specialized 20 than more on relyingproduction meat and breeds and ,
in - meat - en
France Saclay, 78350JouySaclay, 2
A Govignon A. , 2009 for 3 French dairy cattle breeds and populations . -
Josas, France was D 1 nearfuture
V Ducrocq V. ,
3 and fast innovation transfer down to farm level. evelopment , C. Carillier C. , 4 reference population, linkage disequilibrium, disequilibrium, linkage population, reference
, JM. Astruc JM. , also
of adapted to these landscape specificities: 3 specificities: landscape these to adapted
Roquefort cheese), followed by Manech by followed cheese), Roquefort
implemented implemented in in cattle, -
en at nationallevel . s el as well as
- - for
Gion Josas, France organizations
1 R Lefebvre R. , 4
5 - - H Larroque H. , specific other dairy sheep breeds , V. Clement V. , Tolosan, France en
3 national (Charolaise (CHA), national (CHA), (Charolaise 3 2 The A Launay A. , - Josas, FranceJosas,
in n
the Lacaune dairy sheep umber major genes major
small .
and
1 beef beef , F Phocas F. ,
5 , V. Loywyck V. , cost and benefits benefits and cost 4 2
A Legarra A. , of goat breeds is breeds goat of J Promp J. , industry
ones breeds. France breeds. sheep .
or genetic or hs was This
was was then
made it it made . Major 1 mainly M , 2 5 M. , 4 , P. , I. , - P
Version preprint Lefebvre, R.,Phocas,F., Sanchez,M. P.,Tribout,T., Vinet,A.,Fouilloux, M.-N., Govignon Gion, estimated together. density chip. In practice, a completely equivalent model is used where haplotype and SNP effects are a through QTL, (tiny) remaining generations. between QTL defined for each applied first is detection which National genomic selection of 1. Table Reference and expected populationsizes inTable reliabilitycandidates are1. for presented place also took exchange Belgium ( size population reference helped is cost genotyping of proportion MON, NOR) situation An ideal The dairy cattle pioneers: 20 years of collective investments IN private joint two by out carried the at France FGE) inter EBV suppressing most for (Idele) Institute Livestock French database central de production semen association, breed recording, performance defined legislation The initially Venot, E. (Auteurdecorrespondance), Barbat,A.,Boichard, D.,Croiseau, P.,Ducrocq, V.,
used internationally and participate sign (trait dependent) RA, I RA, - professional association for genetic improvement of all ruminants (France Génétique , in charge of the coordination of the overall national system for all ruminants all for system national overall the of coordination the of charge in , French
at combines The Developments of The to dele and the Frenchanddele the Federation of (A breeding companies ed
S and Sweden and – build up build ize
the current approach n 2009 in French French
because because of their of HOLSTEIN & RED HOLSTEIN MONTBELIARDE AI, AI,
nentoa Cmite f nml Recording Animal of Committee International French National Institute BROWN SWISS BROWN genetic
ABONDANCE TARENTAISE NORMANDE
VOSGIENNE the
of the 3000 compared with the with compared gathering the monopolistic monopolistic situations the
a
Breed genetic male and female reference populations in d in populations referencefemale and male - h gnrl rmwr fr nml reig prtos ( operations breeding animal for framework general the expected reliabilityforyoung expected advantages of QTL advantages of
consorti , and , France, Finland, Denmark, high cost of progeny test, progeny of cost high
organization
genomic evaluation : the : using a Bayesian method (Bayes C (Bayes method Bayesian a using Comment citer cedocument:
ae i the in later phenotype and pedigree all
organization organization later
rsda plgnc opnn i add o estimate to added is component polygenic residual A
main
of of cattledairy um
( favorable characteristics:
an extension of extension an
Eurogenomics
- with other countries to exchange genotypes and therefore increase therefore and genotypes exchange to countries other with Spain
public structures (UMT 3G and UMT GGPR) GGPR) UMT and 3G (UMT structures public genomic QTL. NumberofBulls value value s
33 000 33 to Interbull
2 400 2 800 2 000 6 rw Sis re through breed Swiss Brown
350 300 and Poland and - for Agricultural It is expected that haplotypes trace better the transmission of 60
detection and genomicand selection detection was
but confirming the roles of INRA and Idele and
of
relationship matrix based on about 8000 SNP of the low the of SNP 8000 about on based matrix relationship
first
breeding animal breeding originally consortium gather consortium Boichard al, et 2012) delivery
a
focused on
genotyped animals international emn, the Germany, reduced ). A similar A Number of Cows Numberof Ti legislation This . data a built through built Research (INRA) as large number of 16 000 16 000 31
1 100 1 300 1 900 1
genetic population genetic and running and
, semen , the 3 national dairy cattle breeds (HOL,
s … Moreover, the Moreover, …
) cattle airy (ICAR evaluation
international ed . Haplotypes of 4 markers are then then are markers 4 of Haplotypes . llice Netherlands
7 organizations from 8 countries 8 from organizations 7 consists in consists
.
the distribution
the 1966 the ) ) . .
genetic evaluation genetic
cmo RD fot is effort R&D common A progeny Intergenomics (GS): for each trait, a QTL QTL trait, for a each (GS): for youngCandidates for
was s Expected reliability Expected breeds . This international status the center operating the initiative for initiative , [0.20 [0.30 [0.35 [0.55 [0.55 [0.45 [0.55
nml identification, animal
a size updated Livestock the
major breed (HOL) breed major genomic , extension ,
in 2016 in tested tested bulls, ------rnig together bringing , 0.50] 0.50] 0.55] 0.65] 0.70] 0.70] 0.70] . FGE. Flanders part of of part Flanders a the sum of the the of sum the relative
in consortium.
creating evaluation Law and represents
Elevage
s and s genotype 2006
) . ly
It also It a high . This . range
low
the
by an –
Version preprint Lefebvre, R.,Phocas,F., Sanchez,M. P.,Tribout,T., Vinet,A.,Fouilloux, M.-N., Govignon Gion, moment: moment: especiallythe reference focus accurate ifwe brackets on animals phenotypes(in 2). Table with in but traits, weaning and birth for fo areratherlarge populations currentreferenceThe geneticeffects. directfor dams genotyped by and direct both groups of traits evaluated. G populations, allowi the in genotyped no and around 777,000SNPs). However, only very few 2014 and bull service natural and large reference populations of situation general The Implementation of genomic selection in usedeachyear bulls most decreased14% betwfrom 32%to diversity genetic of maintenance decreased 50% t from and 22% 2001 to 2012, trai functional and production between selection balanced more yet information daughter no with respectively bulls young to corresponded practices increased by more than 25% per year, reaching 1 larger of bull. number progenyper themuch of reliability, because a muchhigher GEBV) butwith with initial availablecompared(and also are evaluations selected are Bulls already high reliability for all kind W 2010. had Practical implications accuracy. chip estimation). (without genotype new with animals all for weekly and estimation) in and Venot, E. (Auteurdecorrespondance), Barbat,A.,Boichard, D.,Croiseau, P.,Ducrocq, V., 201
large impact in the . Nevertheless, all AI bulls bulls AI all Nevertheless, . 1 2016 for regional breeds (ABO, TAR, VOS).
Eventually, 2 Table bulls of panel larger a of use the induced also GS on Relying technology: this adopted quickly breeders Dairy G Official genomic selecti benefit benefit limited limited Ntoa eautos r rn tms e ya (including year per times 6 run are evaluations National . ith GS, GEBV of any genotyped animal genotyped any of GEBV GS, ith enomic selection e.g.,
from 13% to 13% from n nw any s y use mainly now and to study to
. Since 2013, most genotypes are obtained with the EuroG10k chip and imputed to the 50k
+0.1 the economic weights was found to develop multi develop to found was amount of information (own performance or offspring ones) maternal presents s context
on selection schemes of these breeds. and used on a large scale as soon as they reach sexual maturity. Regular genetic Regular maturity. sexual reach they as soon as scale large a on used and 0 ng breed within GSimplementation s similar a a
and genotyped grandsires, and are therefore smaller than reference populations populations reference than smaller therefore are and grandsires, genotyped and . for birth trait
gain multi performed, so EBV of these bulls based on progeny performances are still still are performances progeny on based bulls these of EBV so performed, o 35%. To circumvent these difficulties, a r a difficulties, these circumvent To
18% in 18%
beef h sz o te r the of size the researchprogram this of genetic in r in
was Comment citer cedocument: - level are breed genomic evaluation with the use of use the with evaluation genomic breed e
nomic nomic
elia cattle breeds was less favorable less was breeds cattle
more more difficult to quickly implemented inthe3national dairycattle breeds and on the s are (re)genotyped with the 50k the with (re)genotyped are .
s effects. bility
they organization breed traits, all across reliability of started in s
ug eoi bls i 21, 8, 7 ad 90% and 67% 68%, 2015, in bulls: genomic oung I
of
n Holstein total merit index, whereas index, merit total Holstein of traits (between 0.6 and 0.7 for production or functional traits). evaluations for
the the young Charolais cal are more limited for maternal effects and for carcass traits, carcass for and effects maternal for limited more are
through fertility and udder health increased Montb Reference populations for the latter the for populations Reference frne population eference -
breed GS breed 2009 for HOL, MON and NOR breeds,
constitute for genomic e 4 QTLs were found liarde breed, the proportion of AI done with the 5 5 the with done AI of proportion the breed, liarde beef are 0
constituted valuable initial valuable constituted
, some 000 in 201 Genomic
available (Gunia et al., 2014) al., et (Gunia
.
cattle No
since 2011, since
beef evaluation exists but exists evaluation ves
due to the low use of AI bulls in beef herds
esearch new , in particular sires of sons, of sires particular in , een 2007 andeen 2015.
or +0.06 for Growth Total Merit Index.
evaluation cattle cattle traits predict breeding values 6
than the main dairy breeds one: first, one: breeds dairy main the than breeds at the latest the at
available in December 2016 for the the for 2016 December in available . young bull entered ts in their selection goals: selection their in ts Br chip project to be eeder the i , haplotype haplotype to maintain a high imputation high a maintain to
high HL MON HOL, n number of genotype of number the one for for one the s s common common .
of also
was Nevertheless, the animals the Nevertheless, respectively 3 months after birth with birth after months 3 -
available female density chip density
within breed within r direct geneticeffects directr effects
quickly
is set up between 2010 between up set
and and quite across progeny test s became official in s milk production milk SNP
SNP can now apply apply now can are constituted are for 2013 for BSW changed changed limited at the the at limited , from 13% to
for a better a for
beef
most most of the
n NOR and effect (including of effect e.g., reference d calves d quickly the br
from from s their their after s eeds eeds
for re re AI - - ,
Version preprint Lefebvre, R.,Phocas,F., Sanchez,M. P.,Tribout,T., Vinet,A.,Fouilloux, M.-N., Govignon Gion, compared to classical evaluations for milk production traits, udder type traits and somatic cells score. evaluation acc population candidate and reference between population genotyped with the Illumina goat SNP50 Bead genesinclude major defects ( of interest for breeders, such as determination of planned Béarnaise,Blackfor FacedManechthe and the 500Corsican 225 breed genotyped so far) size Because they are well related, a Lacaune breed kept ext without gain economic study showed that applying TMI classical than higher TMIof progenytesting: yearsof 2 the after performed was (TMI) Index Merit Total of comparison a and results genomic on based candidates ram the of La (Baloche et al., 2014): r phantom (with Lacaune breed can bebetweenand dairy distinguished and to compared Developments and implementation Genomicof Selection for small ruminants with com official results genomic breeding values are estimated using deregressed greater reliability than0.7 EBV 2. Table Venot, E. (Auteurdecorrespondance), Barbat,A.,Boichard, D.,Croiseau, P.,Ducrocq, V., caune breed s (Legarra et al, 2014). A
in AI center AI in I specificities (use of fresh semen and AI dem genetic effect are blended are In French dairy goats, 825 bucks (471 Alpine and 354 Saanen) and 1945 females 1945 and Saanen) 354 and Alpine (471 bucks 825 goats, dairy French In testing progeny and use AI limited With study experimental specific A G ruminants small for favorable less even is situation The The in e.g., in the Maternal enomic developments enomic Type of plete markereffect Direct ie f ef ate r cattle beef of Size 2015 for the 3 main French cattle breeds s
eoi evaluation genomic
tutr soe ta lnae disequilibrium linkage that showed structure the hyperprolificacy
uracy . : in the classic progeny test process, a one close future and replaced by GS. Extension of and byother replaced GS.Extension GS to dairy sheep The The parent ra cost, the genotyping the cost, ra animal
(Buisson et al, 2014) al, et (Buisson is
following
OvineSNP50 Illumina chip near 5,500 ( in genetic evaluation. in Carillier etCarillier al group eliability gains obtained varied between 0.1 Weaning Weaning Carcass value, a limited potential gain in gain potential limited a value, Traits Birth Birth
Comment citer cedocument:
for meat sheep breeds. T by s he s
) re )
the method the ,
+0.5 TMI standard deviation standard TMI +0.5
for the Lacaune, 2 approach - size size of the or or mu population eference in sheep in
estimation ehd sd o be cattle beef for used method for for parentage ., 2014 l t i - breed evaluation this this was . 16 571 (1816) 15064 (1376)
meat cost 2 336 (426) Following these results, progeny test test progeny results, these Following 5081 (383) 6250 (598)
Charolaise ). Two ). occurred
was
one reference population of
,
then set up in 2011 to 2011 in up set then s
and weeklywithout )) (December)) 2016) the
being balanced by the reduction reduction the by balanced being
VanRaden et al. et VanRaden sheep, or goats. or sheep, of the two breeds two the of - - etd o ae no con al nomto available information all account into take to tested third third extra selection
Chip Chip ha
the - Bayes verification and assign step genomicevaluation step ,1
However, g s
n n epce pstv profitability positive expected no and
up to now mainly now to up (Tribout et al., 2016). It 00 for the Red Faced Manech been animal and highly concentrated in time) available since 2011 bten rces nme o animal of number brackets: (between -
may C C methodology. rams - available since 2009 third third selection generation interval generation ’s 6 302 (2 373) 7 047 (2 766) 3 385 (1003)
2 458 (370) 1 756 (233) circumvent smaller reference population
and status on specific major genes or genetic
Limousine selected based on GS results GS on based selected
enotyping Brle e a. 2014) al., et (Barillet
(2009). Genomic Genomic (2009).
s were not ideal to maximize genomic maximize to ideal not were
two a is
(progeny re inbreeding - de o a to due , 0 intensity estimation balance
and 0.20 depending on the trait. in the largest dai largest the in ment. ment. R Then Then polygeni intensity was can can be used for new services - . The study of s - tp approach step breeds foreseen is in2017
tested tested rams that have been did not improve did not accuracy is
.
Blonde d'Aquitaine
pros and cons of GS in GS of cons and pros led to 15% extra genetic . levels
performed
. 6 791 (1 319) in A which is which
ih eoyig cost genotyping high was esearch is 2 327 (188) 3 255 (258) 4 193 (770) 786 (138)
Single Step GBLUP evaluations the , 600 for the Basco
ended in 2015 in ended . In addition In .
and relationship relationship and . Different cases number
applied on half c and genomic
already short already ry breed, the breed, ry the
T . twice going
n G is GS no , was found was have been have reference e direct he
of rams of bec
s
a
on on
with year a ,
me an an in in to - .
Version preprint Lefebvre, R.,Phocas,F., Sanchez,M. P.,Tribout,T., Vinet,A.,Fouilloux, M.-N., Govignon Gion, aRdn .. Vn asl .. Wgas .. Sntgr TS, cnbl .. Tyo J. Taylor R.D., Schnabel T.S., Sonstegard G.R., Wiggans C.P., Tassel Van P.M., VanRaden 2015. F. Phocas E., Venot M.N., Fouilloux R., Saintilan M., Barbat T., Tribout al. et F, Barillet G, Baloche A, Legarra Gunia Venot R., M.,Saintilan Fouill E.,HozéC., Carillier LarroqueC., H., Robert Robert H., Larroque C., Carillier (2014) al. et D., Buisson, Boichard D., Guillaume F., Baur A., Croiseau P., Rossignol M.N., Boscher M.Y., Druet T., Genestout Frégeat, F., Fidele, P., Boulenc, X., Aguerre, G., Lagriffoul, D., Buisson, G., Baloche, Robert F., Barillet, J.M., Astruc H., Larroque A., Legarra G., Baloche List ofReferences of revolution: extended to4 organizations efficient on gain genetic test progeny of end breeds or species: it has France in years C by goats French breed. Saanen in content protein for 14% to breed Alpine in yield protein for 10% from accuracy average parent within or breed step single using When Venot, E. (Auteurdecorrespondance), Barbat,A.,Boichard, D.,Croiseau, P.,Ducrocq, V.,
onclusion new phenotypes, Dairy 16 Sci., 92: françaises 2009. F.S., Schenkel allaitantes bovines populations les dans LimousineCharolaise, Blonde et d’Aquitaine. nationales génomiques d’évaluations Basco and Manech Latxa, breed sheep dairy Béarnaise. Pyrenees Western for relationships genomic 92,3258 Anim. Sci. in Frenchcattle Charolais using beef high evaluationsgoats. 48:54. ofFrench Genet dairy Evol, Sel evaluation theFrenchmulti in designgenetic expected and gain. Sci,52,115 Anim Prod L., Colleau J.J., Journaux L., Ducrocq V., Fritz S. 2012. breeding schemes. (2014). Giral G., Assessment of genomic selection efficiency in French Lacaune dairy sheep. integrating major gene integrating major However, it is not the end of the story yet! It is even only the beginn the only even is It yet! story the of end the not is it However, has selection Genomic collective Genomic selection in French dairy sheep: main results and design to implement genomic implement to design and results main sheep: dairy French in selection Genomic
o - Viala, B., Guibert, P., Pan P., Guibert, B., Viala, . Its routine implementation routine Its . rganizational reforms, rganizational . G .
J Dairy Sci, J extra Clearly - . It . a variety a breed model model breed S
is now in place in now is
started sheep partnership use and the fast and steady increase of the of increase steady and fast the and - 24. 39th. ICAR Biennal39th. ICAR Berlin, Session, ,
- single step GBLUP provides opportunities for opportunities provides GBLUP step single
3269 of sequence areof information… exciting all new challenges tocom already GBLUP
bulls. Holstein American North for predictions genomic of Reliability
of traits. of s such breeds
97: 3200 97: Ge - Comment citer cedocument: with 120.
nomic breeding schemes in French Lacaune and Manech dairy sheep: sheep: dairy Manech and Lacaune French in schemes breeding nomic was
generated
between
had had a the
as
- - and 2 goat breeds. goatand breeds. 2 based on female performances, t performances, female on based Granié C (2016) Including
bree All these quick developments quick these All similar
in - – t
rné (04 Cmaio o jit n prbe genomic purebred and joint of Comparison (2014) C Granié he maintenance national dairy national 3212.
10thWCGALP, Vancouver,10thWCGALP, Canada 1 huge d dairy goatd dairyGenet 46:67. Evol, Sel population.
1 αs1
is, P., Soulas, C., Larroque, H., Legarra, A., Astruc, J. Astruc, A., Legarra, H., Larroque, C., Soulas, P., is, cattle and 1 sheep breeds. In the very ne very the In breeds. sheep 1 and cattle industry partners industry
. is (2014) Within (2014)
a -
Genomic breeding value accuracy of candidates exceeds candidates of accuracy value breeding Genomic casein (Carillier casein impact on considerable planned - density single markers. nucleotidedensity polymorphism
oux M.N.,Phocas F.oux (2014). Genomic prediction and enlargement and Renc. Rech.Renc. 22 Rum., cattle
for the
- 2018
and across and organization breeds and breeds technological Genomic Selection in French Dairy Cattle.
and national and
use of young of use et al.,2016). α
. Accurac . s1 casein gene information in genomic - rné . and C. Granié were made possible made were he pr he
reference population reference - breed genomic prediction genomic breed was
efficient of breeding y
ediction revolution revolution
Research and Development and Research
could be slightly improved improved slightly be could “
quickly genomic J J Dairy Sci, 97, 1107. genomic selection in selection genomic
quality n fte genomic the of ing ar Barillet F. (2014) (2014) F. Barillet
extended scheme ” during future, it will be will it future,
bulls for higher higher for bulls
by the by ie n place en Mise
using multi using , integration e. s these last last these , with
existing existing other to s and s J. J. - the the M. F., J. J. - -