Genetic improvement of pigs

Transcription

1 International Master ANIMAL BREEDING AND BIOTECHNOLOGY OF REPRODUCTION (2 nd edition) Genetic improvement of pigs Valencia, March 2010 Jean-Pierre BIDANEL INRA, UMR1313 Animal Genetics and Integrative Biology Unit Jouy-enJosas - France tél: , jean-pierre.bidanel@jouy.inra.fr Web : Valencia, 29/ F O O D & N U T R I T I O N E N V I R O N M E N T

2 Characterisation use of genetic variability Large White Meishan Hampshire Mongcai Landrace Wutsusan Ibérique Piétrain Duroc Fengjing Bayeux JinHua

3 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

4 Some elements on pig production

5 Pig production in different countries Source: IFIP

6 Main pig meat consumers (2006 % total) USA 9% EU 21% Others 9% Russia 3% Japan 3% Brazil 2% China 53% Source : FAO

7 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

8 Pig breeding schemes Pyramidal Organisation Selection Multiplication Pure breeds and lines Production of crossbred pigs: - Parental sows - Terminal boars 95 herds sows 330 herds sows Commercial level Crossbred slaughter pigs herds sows (Pig selection Agency, IFIP, 2008) Valencia, 29/

9 Pig breeding schemes general principles SELECTION D 100 sows C 100 sows B 280 sows A 280 sows MULTIPLICATION D x C C x D 600 sows B x A A x B 4500 sows 2200 boars/year Male Female gilts/year PRODUCTION (CD or DC) x (AB or BA) Around sows Slaughter pigs

10 Main characteristics of pig production Homogeneity of production conditions A dominant production system Objective : production of (reasonable) quality meat at the lowest price Standardised housing, feed & management conditions Some exceptions Example of the Iberian pig Homogeneity of the pig produced Slaughtered at a given target weight ( kg on average - differences between regions/countries Some heavy pig chains (ex : Italy for Parme ham production) Conversely, pig meat is consumed in many different ways Fresh meat Many processed products «cooked»or «dry»ham & sausages, ready to use dishes,

11 Diversity of processed products in pigs The example of France (2008) Source : IFIP

12 Components of the economic efficiency of pig production Production costs 2 main groups of traits 1. Production cost of piglets (up to 25 kg) Is mainly a function of herd numerical productivity 2. Cost of the growth period Is a function of: Growth rate (cost of housing) Feed conversion ratio (amount of feed consumed) Mortality Usage value of the slaughter pig 1. Quantitative aspect = dressing percentage 2. Qualitative aspects Carcass composition (lean meat content) Meat and fat quality (not paid to farmers except boar taint)

13 Improving performances : a necessity Source : IFIP

14 Numerical productivity = Number of piglets produced per sow per unit of time prolificacy Maternal abilities Pn = Nb litters * NVIV/litter * (1 %Mort BW) * 365 I 100kg-1st Farr. + (Nb litters-1)*fi + I last farr. - culling unproductive periods

15 Traits of economic interest GROWTH RATE Related to the duration of the period from 25 kg to slaughter (D) Low D reduced housing cost Some characteristics of pig growth : - Birth weight x 2 within 8 days - x 5 within 3 weeks - x 20 within 8 weeks -x 80 within 6 months!! Growth curve = sigmoid, with an inflexion point around puberty

16 Traits of economic interest FEED EFFICIENCY Food conversion ratio = amount of feed (kg) necessary for 1 kg live weight gain Considerable economic impact Individual measurement : Production costs Automatic feeders In weaning fattening herds Rémun. Captx propres 100% 80% 60% 40% 20% 0% National élevages Main d'œuvre totale Others Frais financiers Amortissement Divers Feed Renouvellement Aliment

17 Traits of economic interest Carcass traits Definition of a carcass EU regulation n 3220/84, modified by regulation n 3513/93) Dressing percentage 100 * Ratio of carcass to liveweight

18 Traits of economic interest Carcass traits Carcass composition in pigs : 3 main tissues - BONES : stable proportion (13 to 14 % of the carcass) - MUSCLE : 36% in the back, 30% in rear legs, 22% in front legs, 11% in the belly. - GRAS : 2 à 3 times lower than muscle proportion, distributed on the back (61 %), between/within muscles (32%) and in the internal part of the body

19 Traits of economic interest Carcass traits Estimation of carcass composition Through ultrasonic backfat depth

20 Traits of economic interest Carcass traits Carcass cuts LOIN SHOULDER BELLY HAM LEAF FAT REAR LEG FRONT LEG

21 The different aspects of meat quality Dietetic qualities Consumers nutritional requirements Hygienic qualities Consumer health Organoleptic qualities Consumers satisfaction Technological qualities Meat processing

22 Economic consequences of product quality For farmers : no payment for meat quality Some meat defaults can be forbidden For slaughterhouses : Weight losses through exudation (1-3%) For distributors : Weight losses through exudation (1-3%) Selling difficulties For processing units Weight losses at cooking ( 1-10%) Losses when making slides (0 50%) Losses when conservation is poor Pour le consommateur : Weight losses at cooking ( 1-10%)

23 Meat technological quality criteria Post mortem evolution of ph Imbibition time Water Exudation losses Holding Cooking losses Capacity Glycolytic potential (GP) % water Chemical % proteins composition measured on different muscles Technological yields (Napole, cooking or drying %) Fibre characteristics (?)

24 Post mortem evolution of ph Speed ph 1 7 Amplitude ph u Death Time (hours)

25 Fat quality criteria Firmness Rancid character % water, % lipids Fatty acid composition (polyinsaturated/saturated) + organoleptic and dietetic quality Boar taint (androstenone, skatole)

26 Meat organoleptic quality criteria Intramuscular fat content (% IMF) Shear force usually measured on the loin Tenderness Juiciness Flavour Consumer panel tests

27 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

28 Definition of breeding goals Preliminary considerations A breeding goal (BG) is characterised by : The set of traits we want improve or to control The relative weights of these traits global genetic value H = a 1 T 1 + a 2 T a i T i and even beyond A correct definition of the BG is of major importance determines the future of the population the breeding structures and tools example: including meat quality in the BG move from individual selection to selection on sibs

29 Definition of breeding goals What time interval should we consider? Minimum interval Depends on the genetic gain diffusion structure S M P In general, 3 to 5 years = genetic lag + economic lag in a competitive situation = temps necessary for buyers to perceive changes

30 Definition of breeding goals Trait choice Specialised lines / populations (Grand)sire line (Grand)dam lines BG = Production BG = Production + reproduction Economic approach Trait choice based on a. H2 Biological approach Improve the efficaciency of biological functions Ex: lean growth efficiency Desired gains Maintaining meat quality or food consumption at a desired level Selection for an optimum Selection against environmental variability (canalisation)

31 Definition of breeding goals Determining trait weights economic approach Use of an economic function FE f(x 1, x 2,..., x n, z 1,..., z p ) x 1,,x p = traits related to animal characteristics z 1,,z p = other traits Weight computation a FE x x i i using analytic, graphical or finite difference methods

32 Definition of breeding goals Main traits of economic interest Litter size Lean% FCR (25-105kg) ADG (25-105kg) Dressing % Mortality (25-105kg) Postweaning ADG PostweaningFCR Preweaning Mortality ADG Preweaning Age at puberty Sow weight Postweaning mortality Sow feed intake Relative economic value ( /sd unit)

33 Definition of breeding goals Meat quality index (MQI = a phu + b color + c WHC) Desired gain approach : non change for MQI It s necessary to know genetic parameters The weight depends on the weight of other traits Weight of MQI Weight of lean content

34 Future breeding goals How to integrate : Behavioural traits Environmental effects of animal production (including contribution to global warming) Robustness / resistance to diseases Environmental sensitivity

35 Outline - Some elements on pig production - Genetic improvement of pigs - General principles - Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan - Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

36 Genetic parameters Heritability values for production traits Avg Daily Gain 0.30 to 0.50 Food conv. ratio 0.25 to 0.40 Age at 100 kg 0.20 to 0.40 Lean content 0.50 to 0.80 B fat at 100 kg 0.40 to 0.60 Dressing % 0.25 to 0.40

37 Genetic parameters Heritability values for female reproduction traits Total number born/litter Number born alive/litter N weaned/litter Total number of teats Milk production Maternal behaviour Age at puberty Weaning to oestrus interval Intensity of vulvar symptoms 0.24

38 Genetic parameters Heritability values for meat quality traits Lean 0.20 Fat ph Composition Composition Juiciness WHC Colour % IMF Flavour Tenderness Firmness

39 Genetic parameters Genetic correlations between production traits FCR Dressing % Lean% ADG -0,4 à -0,5-0,3 à -0,2-0,3 à +0,1 FCR -0,2 à +0,1-0,2 à -0,8 Dressing % 0,0 à +0,3

40 Genetic parameters Genetic correlations between female reproduction traits Ovul. rate Total born Born alive Birth-W survival N weand Embryo survival Age at puberty Ovulation rate -0,08 0,04 0,04 0,08 0,10 0,08 0,25-0,38 0,10 Unfav. Total born Born alive Birth-weaning S. 0,91-0,11 0,73 0,16 0,81 0,53 favor. favor. Teat number 0 0 0,45 0,34 Milk production Fertlility favor. favor. favor. favor. favorable with all traits

41 Genetic parameters Genetic correlations between production and female reproduction traits In general, null or low correlations Growth rate Lean % Meat quality Age at puberty Litter size favourable (-0,2) <0, >0, =0-0,2 à +0,2 0 à -0,3 <0 with GP = 0 with GP fertility Teat number longevity Low & uncertain?? independent? independent??

42 Genetic parameters Genetic correlations between meat quality traits 1 0,6 0,2-0,2 water loss Cooking Tenderness -0,6-1 ph1 phu Colour WHC %IMF

43 Genetic parameters Genetic correlations between fat quality traits 1 0,6 0,2-0,2 Firmness -0,6-1 %Sat FA % Unsat FA % water

44 Genetic parameters Genetic correlations between meat quality traits And production traits 1 0,6 0,2-0,2 Lean% Fat% ADG -0,6-1 ph1 phu L* WHC %IMF

45 Genetic parameters Genetic correlations between fat quality traits And production traits 1 0,6 0,2-0,2 Lean % Fat % ADG -0,6-1 % sat FA % unsat FA % water

46 Heterosis in pigs Trait Heterosis (%) Direct Maternal Birth weight 3 2 Weaning weight 5 8 Growth rate after weaning 6 0 Food conversion ratio -4 0 Lean % 0 0 PH at 24 h p.m. 0 0 Litter size at birth 2 6 Litter size at weaning 6 9 Litter weight at weaning 12 10

47 Major gene effects The Halothane sensitivity gene 3 genotypes : Normal allele N Mutant allele n N N n N n n HAL is the RYR1 locus (chromosome 6)

48 Major gene effects Effects of the Halothane sensitivity gene Normal allele N Mutant allele n Sensitivity to stress NN = Nn >> nn Meat quality NN > Nn >> nn Carcass quality NN < Nn < nn

49 DFD Normal PSE

50 Major gene effects The RN gene RN = acid meat gene Normal allele rn + Mutant allele RN - 3 genotypes : rn + rn + RN - rn + RN - RN - RN is the PRKAG3 locus (chromosome 15)

51 The NapoleTechnological yield 100 g muscle SM Paris ham RN = Cooked weight Fresh weight

52 Major gene effects Effects of RN gene Normal allele rn + Mutant allele RN - Meat quality* rn + rn + >>RN - rn + =RN - RN - Carcass quality rn + rn + <RN - rn + <RN - RN - *except flavour

53 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

54 Troisième niveau Troisième niveau Selection : pure breeds and lines Quatrième niveau Dam breeds Cinquième niveau Dam type Large White sows Piétrain sows Quatrième niveau Cinquième niveau Sire type LW 500 sows Duroc 350 sows lignées synt truies Sire breeds French Landrace sows (Pig selection agency, IFIP, 2008) Chinese- European lines 950 sows Duroc synthetics 300 sows lignées synt. LW*LD 500 sows Valencia, 29/

55 Commercial level : crossbred slaughter pigs Most frequent crossbreeding system in France Landrac e Dam type Large White Piétrai n LW x LF sow Slaughter pig

56 Sélection : races pures et lignées Dam type populations Large White type femelle truies Piétrain truies Sire type LW 500 sows Duroc 350 sows Synthetic lines sows Sire type pop. French Landrace sows (Agence de la Sélection Porcine, IFIP, 2008) Duroc synthetics 300 sows Chinese-European lines 950 sows LW*LD synthetics 500 sows

57 The French national pig breeding scheme Breeding goal Large White maternal line Large White sire line ADG MQI 37% NBA 31% GTEAT 12% DFI 9% MU% 24% ADG 11% FCR 12% MQI 16% 13% D% 8% FCR 15% D% 11% MU% 1% Piétrain French Landrace MQI 30% MU% 11% NBA 25% GTEAT 12% DFI 7% D% 19% MQI 17% ADG 11% ADG 18% FCR 16% D% 10% FCR 22% MU% 2%

58 The French national pig breeding scheme on-farm performance test production traits Young male and female candidates - age at 100 Kg - backfat thickness at 100 Kg - Loin depth (male lines) - (Meat quality) «reproduction» traits - numbers of live born piglets - number of functional teats station performance test slaughtered sibs from young candidate males - average daily gain - daily feed intake - feed conversion ratio - dressing percentage - carcass lean content - meat quality index

59 The French national pig breeding scheme ~ 60 selection herds Information flow 2 public stations AI centers Selection organizations multiplication ~ 40% litters Technical management database «basic»data «genetic» information ~ 60% litters BLUP national database Data validation File preparation BV and CD estimation

60 The French national pig breeding scheme Genetic evaluation based on animal model BLUP evaluation performed independently in each population Evaluations for production and reproduction traits are performed independently (low genetic antagonism) Multiple trait evaluation for production traits single trait evaluation for NBA Use of the PEST package

61 Genetic evaluation of pigs Production traits - Combined on farm station evaluation since Multiple trait (10 / 11 traits) evaluation - Monthly evaluation -Collaboration between INRA -IFIP -Use of PEST software -Breeds concerned : Large White, French Landrace, Piétrain (Large White male and female lines are jointly evaluated)

62 National genetic evaluation of pigs Combined EBVs EBVs for each trait are combined as follows : EBV (ADG) EBV (FCR) EBV (D%) EBV (MU%) EBV (MQI) "growth" "carcass" EBV (NBA) EBV (GTEAT) EBV (DFI) global EBV (male lines) global EBV (female lines)

63 National genetic evaluation of pigs Results sent to breeders after each evaluation : Growth, carcass and reproduction EBVs + accuracies - of all boars and sows of the herd - of all AI boars - of young males and females tested on farm every six months : Estimated genetic trends (per breed, herd, sex) Estimated breeding values of pigs sent to multiplication herds Elements on Connectedness, management of genetic variability

64 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

65 BLUP estimates of genetic trends BLUP estimates of genetic trends Valencia, 29/

66 BLUP estimates of genetic trends Valencia, 29/

67 BLUP estimates of genetic trends Valencia, 29/

68 Phenotypic trends at the commercial level N T 100*(SEV/NT) N V SE V Porcelets Morts nés

69 Checking the efficiency of breeding schemes Control of terminal products Sample of slaughter pigs from different breeding organisations compared in an official test station Results officially published by the ministry of Agriculture Growth index; 10 points = 2.30 euros Carcass index; 10 points = 3.08 euros Ex : 24rd TP test Meat quality index; 10 points = 1.16 euros

70 Checking the efficiency of breeding schemes Use of frozen semen SMITH, 1976 : use of frozen semen X X = genetic trend : stock of frozen semen of 1977 LW boars 1999 : INRA, ITP & French Ministry of Agriculture reproduction, production, quality

71 schemes Use of frozen semen 17 boars 1977 LW females 23 AI boars 1998 X X Experimental design F litters X X Reproduction traits 5 litters / + 5 litters / + F2 G77 G98 production traits meat and fat quality

72 Estimation of genetic trends using frozen semen - results Growth rate Mean perf. ph G P-value for H0 G=0 ADG weaning / slaughter (g/d)

73 Estimation of genetic trends using frozen semen results Carcass fatness Mean perf. ph G P-value for H0 G=0 avg. US backfat thickness at 20 woa (mm) < backfat weight (kg) < belly weight (kg)

74 Estimation of genetic trends using frozen semen results Carcass leanness Mean perf. ph G P-value for H0 G=0 ham weight (kg) loin weight (kg) loin eye thickness (mm) carcass lean content (kg/100kg) <0.0001

75 Outline - Some elements on pig production - Genetic improvement of pigs - General principles -Selection goals/production characteristics - Genetic variability of economically important traits - Pig breeding plans * an example: French national pig breeding plan -Controlling the efficiency of pig breeding plans - What does genomics bring to the system?

76 Use of genomics in pig breeding schemes Parentage control Control / production of given genotypes for major genes Marker assisted introgression Marker assisted selection (MAS) Genotype assisted selection (GAS) Genomic selection (GS) individual / breed Traceability Characterisation / management of genetic variability

77 Use of genomics in pig breeding schemes 1. Parentage control AM-BLUP Use of pedigree information increases the accuracy of EBVs BUT : pedigree errors => biased EBVs In France, parentage control for all young sires If an error is found : - the true sire canbe found =>OK - unidentified sire => removed from database 2. Chromosomal abnormalities Searched for on all future IA boars => if positive, the boar is culled

78 Marker assisted selection in pigs Apart from major genes (Hal, RN, IGF2, ) Selecom used in pigs Its use mentioned by international companies, but: - little (no) information on SAM programmes ; - No information on the methods ; - No information on the efficiency Only used as a commercial argument? Exemple of anouncement: «use of 140 markers in 2008 in XXX selection programmes»

79 Sélection assistée par marqueurs chez le porc b. Use of SAM in pure breeds Why is it so poorly used? Most QTL mapped in expérimental populations between divergent populations (LW x MS, LW x wild boar, ) : -the QTL explain breed differences; they not necessarily segregating within commercial population Most QTL detected with low density marker maps low accuracy, within-family LD Uneeasy to use in pigs Few QTL are commun between studies validation required

80 Exemple of marker assisted breeding Crossbreeding scheme to produce 1/8 Meishan (MS) sows MS M2A2 LW M1A1 LR x MS M2A2 x M1A1 S1 F1 x LR F1 M1A1 LW M1A1 M2A2 x M1A1 S2 BCR x LW BC M1A1 M1 A1 M1 A1 M1A1 Parental sow M2A2 M1 A2 M2 A1 M1A1 S1, S2 : selection steps Backcross pigs carrying the unfavourable marker (and QTL) alleles are culled

81 Genomic selection : potential use in pigs Genomic selection : General Principle With low density marker panels ( /genome) With high density marker panels (at least 10 3 or 10 4 markers) Linkage equilibrium M Q The QTL genotype m q can be inferred from Marker information m Q only within-family M q Full disequilibrium M Q m q The QTL genotye can be inferred from marker information at the population level

82 Genomic selection : potential use in pigs Genomic selection : General Principle Step 1 : Phenotype and genotype individuals for several thousand SNP = reference population Estimate the effet of each chromosomal fragment An1 Effect of chr. segments = 1 = 1 = 1 = 1 = 2 Other segments = 0 An2 VGAn1 = + 4 VGAn2 = + 6

83 Genomic selection : potential use in pigs Genomic selection : General Principle Step 2 : genotype candidates from the selected population : their EBV can be computed from genotype information and segment effects Effect of chr. segments VGAn3 = + 5 = 1 = 1 = 1 = 2 = 1 VGAn4 = + 7 VGAn5 = 0 Other segments = 0 VGAn6 = + 3 VGAn7 = + 8

84 Genomic selection : potential use in pigs Benefits from genomic selection? A higher genetic trend? increase selection intensity? G = i R a T increase accuracy of EBV? reduce generation interval? Decreasing selection costs? Low cost of on-farm testing Station testing more expensive

85 Genomic selection : potential use in pigs reduce generation interval? Breeding pigs selected at the end of performance testing (no progeny test), and used for breeding as soon as possible short reproductive career (1 year for males, 2 years for femelles) -Already low +< some gain can be expected but it will be limited

86 Genomic selection : potential use in pigs increase accuracy of EBV? - lean%, teats : a lot of cheap information - ADG, FCR, DFI, killing out %, quality : few information (only from station tests) Higher precision of genomic EBV? Accuracy = f() Fraction of the genetic variabce explained by QTL Many markers high accuracy, bu also hig cost?

87 Genomic selection : potential use in pigs increase accuracy of EBV? Average CD (corrélation(vge,vgvraie)²) with AM-BLUP evaluation Age100 BF100 ADG FCR DFI KO% LEAN% MQI Teats NVIV Active AI boar 0,68 0,73 0,34 0,37 0,28 0,24 0,51 0,23 0,65 0,26 Active on-farm boar 0,63 0,69 0,29 0,32 0,22 0,18 0,46 0,17 0,59 0,25 Active sow 0,58 0,66 0,28 0,32 0,22 0,18 0,44 0,18 0,54 0,36 Piglet at birth 0,31 0,34 0,15 0,17 0,12 0,10 0,23 0,10 0,29 0,16 Young candidates (end of test) 0,52 0,60 0,23 0,27 0,17 0,13 0,39 0,13 0,48 0,16

88 Genomic selection : potential use in pigs 1 AI male / 80 male candidates 1 on-farm male / 65 candidates (after culling 63% litters based on parental EBV) 1 female / 10 female candidate (after culling 22% litters based on parental EBV) HIGH SELECTION INTENSITIES

89 Genomic selection : potential use in pigs Increase selection intensity? - Currently : first selection on parental EBV (theoretical max CD = 0.5, but in practice, CD ~ 0,15) Hypothesis : genotype more piglets (all?) more accurate EBV increased selection intensities? BUT : costs proportional to the number of genotyped individuals Possibilities to genotype candidates for a smaller number of markers (=> low cost)? Effect on accuracy?

90 Genomic selection : potential use in pigs Future selection plans New goals / criteria that are difficult to measure Feed intake, manure production Behaviour Health, Majur interest for the selection of such traits But their economic interest and their genetic determinism has to be known before integrating them in selection schemes Valencia, 29/

91 Genomic selection : potential use in pigs Other potential interest of genomic selection : Select populations for crossbreeding Current principle : «Improving purebred performances also increases performances in crossbreeding» BUT : Performance at the selection level performance at the commercial level (rg [0,4 à 0,9]) Genetic trend commercial level Genetic trend selection level

92 Genomic selection : potential use in pigs Large White Landrace Crossbred EBV can be obtained with AM- PLUP, but it requires - to phenotype slaughter pigs - get all the pedigree information LWxLF Piétrain IN MOST CASES IMPOSSIBLE Phenotyped slauhter pigs

93 Genomic selection : potential use in pigs Hypothesis : 1. Reference population of crossbred pigs» phenotyping and genotyping with SNP microarray estimation of chromosomal fragment effects on phenotypes 2. Génotyping purebred candidates Computing EBV from the crossbred reference population NO NEED TO COLLECT PEDIGREE INFORMATION Higher genetic trend at the commercial level

94 Genomic selection : potential use in pigs h² purebred performance (PP) = h² crossbred performance (CP) = 0,4 Genetic correlation (PP, CP) = 0,7 Genetic trend at the commercial leval 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0,2 Genomic selection Crossbred reference population 0,3 0,4 0,5 0,6 0,7 0,8 0,9 Accuracy of genomic EBV Genomic selection Crossbred reference population AM-BLUP- Purebred + crossbred perf. AM BLUPpurebred perf.

95 Genomic selection : potential use in pigs Genomic selection : impact on inbreeding 3,5 Increase in inbreeding / generation (%) 3,0 2,5 2,0 1,5 1,0 0,5 0,2 Genomic selection Crossbred reference population 0,3 0,4 0,5 0,6 0,7 0,8 0,9 AM-BLUP- Purebred + crossbred perf. AM BLUPpurebred perf. Genomic selection Purebred reference population AM-BLUP : High weight of family information Accuracy of genomic EBV Genomic selection : Selection on individual genotype D après Dekkers, 2007