Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. ...The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits.
A pedigreed population of 1343 trout were genotyped for 57,000 SNP markers and phenotyped for seven traits at 2 years of age: spawning date, female body weight before and after spawning, the spawn weight and the egg number of the spawn, the egg average weight and average diameter. Genetic parameters were estimated in multi-trait linear animal models. Heritability estimates were moderate, varying from 0.27 to 0.44. The female body weight was not genetically correlated to any of the reproduction traits. Spawn weight showed strong and favourable genetic correlation with the number of eggs in the spawn and individual egg size traits, but the egg number was uncorrelated to the egg size traits. The genome-wide association studies showed that all traits were very polygenic since less than 10% of the genetic variance was explained by the cumulative effects of the QTLs: for any trait, only 2 to 4 QTLs were detected that explained in-between 1 and 3% of the genetic variance. Genomic selection based on a reference population of only one thousand individuals related to candidates would improve the efficiency of BLUP selection from 16 to 37% depending on traits.
Our genetic parameter estimates made unlikely the hypothesis that selection for growth could induce any indirect improvement for female reproduction traits. It is thus important to consider direct selection for spawn weight for improving egg production traits in rainbow trout breeding programs. Due to the low proportion of genetic variance explained by the few QTLs detected for each reproduction traits, marker assisted selection cannot be effective. However genomic selection would allow significant gains of accuracy compared to pedigree-based selection.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Single-breed genomic selection (GS) based on medium single nucleotide polymorphism (SNP) density (~50,000; 50K) is now routinely implemented in several large cattle breeds. However, building large ...enough reference populations remains a challenge for many medium or small breeds. The high-density BovineHD BeadChip (HD chip; Illumina Inc., San Diego, CA) containing 777,609 SNP developed in 2010 is characterized by short-distance linkage disequilibrium expected to be maintained across breeds. Therefore, combining reference populations can be envisioned. A population of 1,869 influential ancestors from 3 dairy breeds (Holstein, Montbéliarde, and Normande) was genotyped with the HD chip. Using this sample, 50K genotypes were imputed within breed to high-density genotypes, leading to a large HD reference population. This population was used to develop a multi-breed genomic evaluation. The goal of this paper was to investigate the gain of multi-breed genomic evaluation for a small breed. The advantage of using a large breed (Normande in the present study) to mimic a small breed is the large potential validation population to compare alternative genomic selection approaches more reliably. In the Normande breed, 3 training sets were defined with 1,597, 404, and 198 bulls, and a unique validation set included the 394 youngest bulls. For each training set, estimated breeding values (EBV) were computed using pedigree-based BLUP, single-breed BayesC, or multi-breed BayesC for which the reference population was formed by any of the Normande training data sets and 4,989 Holstein and 1,788 Montbéliarde bulls. Phenotypes were standardized by within-breed genetic standard deviation, the proportion of polygenic variance was set to 30%, and the estimated number of SNP with a nonzero effect was about 7,000. The 2 genomic selection (GS) approaches were performed using either the 50K or HD genotypes. The correlations between EBV and observed daughter yield deviations (DYD) were computed for 6 traits and using the different prediction approaches. Compared with pedigree-based BLUP, the average gain in accuracy with GS in small populations was 0.057 for the single-breed and 0.086 for multi-breed approach. This gain was up to 0.193 and 0.209, respectively, with the large reference population. Improvement of EBV prediction due to the multi-breed evaluation was higher for animals not closely related to the reference population. In the case of a breed with a small reference population size, the increase in correlation due to multi-breed GS was 0.141 for bulls without their sire in reference population compared with 0.016 for bulls with their sire in reference population. These results demonstrate that multi-breed GS can contribute to increase genomic evaluation accuracy in small breeds.
The objective of this study was to quantify the effects of the Charolais-specific inactive myostatin allele on phenotypic means and genetic parameters of heifer breeding traits. Records were ...registered from 1996 to 2006 in 282 herds dedicated to the on-farm French Charolais purebred progeny test. Data consisted of 36,867 female calf records, including 17,518 inseminated heifers that were bred by 186 genotyped sires, of which 43 were heterozygous and 6 were double muscled bulls. Six traits were analyzed under a univariate animal model accounting for maternal effects and myostatin sire genotype: calving difficulty, birth and weaning weights, muscle and skeleton scores at weaning, and fertility of artificially inseminated heifers. The inactive myostatin allele had a large positive effect on weaned heifer muscle score, unfavorable effects on calving difficulty and skeleton score, and small effects on birth and weaning weight. This allele did not induce an adverse effect on heifer fertility. Univariate estimates of polygenic variance parameters were almost unaffected by the estimation of the myostatin sire genotype, except for heifer morphology traits. Direct and maternal genetic variances and covariances were significantly reduced under a model accounting for the myostatin sire genotype effect on muscle score. The myostatin genotype explained 45% of the direct genetic variance and had a pleiotropic action across both direct and maternal effects on muscle score. Because the myostatin sire genotype had no significant effect on birth weight, the multitrait sire analysis concerned only the 5 other traits. Accounting for the myostatin sire genotype, estimates of polygenic correlation between skeleton score and muscle score, on the one hand, and calving difficulty on the other hand, were largely modified: from a negative estimate of -0.3 to 0.0 and from a positive estimate of 0.4 to 0.7, respectively.
Stochastic simulation was used to compare the efficiency of 3 pig breeding schemes based on either traditional genetic evaluation or genomic evaluation. The simulated population contained 1,050 ...female and 50 male breeding animals. It was selected for 10 yr for a synthetic breeding goal that included 2 traits with equal economic weights and heritabilities of 0.2 or 0.4. The reference breeding scheme, named BLUP-AM, was based on the phenotyping of all candidates (13,770 animals/yr) for Trait 1 and of relatives from 10% of the litters (270 animals/yr) for Trait 2 and on BLUP-Animal Model genetic evaluations. Under the first alternative scenario, named GE-1TP, selection was based on genomic breeding values (GBV) estimated with one training population (TP) made up of candidate relatives phenotyped for both traits, with a size increasing from 1,000 to 3,430 over time. Under the second alternative scenario, named GE-2TP, the GBV for Trait 2 were estimated using a TP identical to that of GE-1TP, but the GBV for Trait 1 were estimated using a large TP made up of candidates that increased in number from 13,770 to 55,080 over time. Over the simulated period, both genomic breeding schemes generated 39 to 58% more accurate EBV for Trait 2 than the reference scheme, resulting in 78 to 128% (GE-1TP) and 63 to 84% (GE-2TP) greater average annual genetic trends for this trait. For Trait 1, GE-1TP was 18 to 24% less accurate than BLUP-AM, reducing average annual genetic trends by 27 to 44%. By contrast, GE-2TP generated 35 to 43% more accurate EBV and 8 to 22% greater average annual genetic trends for Trait 1 than the reference scheme. Consequently, GE-2TP was 27 to 33% more efficient in improving the global breeding goal than BLUP-AM whereas GE-1TP was globally as efficient as the reference scheme. Both genomic schemes reduced the inbreeding rate, the greatest decrease being observed for GE-2TP (-49 to -60% compared with BLUP-AM). In conclusion, genomic selection could substantially and durably improve the efficiency of pig breeding schemes in terms of reliability, genetic trends, and inbreeding rate without any need to modify their current structure. Even though it only generates a small TP, limited annual phenotyping capacity for traits currently only recorded on relatives would not be prohibitive. A large TP is, however, required to outperform the current schemes for traits recorded on the candidates in the latter.
Summary
In rainbow trout farming, Flavobacterium psychrophilum, the causative agent of bacterial cold water disease, is responsible for important economic losses. Resistance to F. psychrophilum is ...heritable, and several quantitative trait loci (QTL) with moderate effects have been detected, opening up promising perspectives for the genetic improvement of resistance. In most studies however, resistance to F. psychrophilum was assessed in experimental infectious challenges using injection as the infection route, which is not representative of natural infection. Indeed, injection bypasses external barriers, such as mucus and skin, that likely play a protective role against the infection. In this study, we aimed at describing the genetic architecture of the resistance to F. psychrophilum after a natural disease outbreak. In a 2000‐fish cohort, reared on a French farm, 720 fish were sampled and genotyped using the medium‐throughput Axiom™ Trout Genotyping Array. Overall mortality at the end of the outbreak was 25%. Genome‐wide association studies were performed under two different models for time to death measured on 706 fish with validated genotypes for 30 060 SNPs. This study confirms the polygenic inheritance of resistance to F. psychrophilum with a few QTL with moderate effects and a large polygenic background, the heritability of the trait being estimated at 0.34. Two new chromosome‐wide significant QTL and three suggestive QTL were detected, each of them explaining between 1% and 4% of genetic variance.
Behavioural adaptation of farm animals to environmental changes contributes to high levels of production under a wide range of farming conditions, from highly controlled indoor systems to harsh ...outdoor systems. The genetic variation in livestock behaviour is considerable. Animals and genotypes with a larger behavioural capacity for adaptation may cope more readily with varying farming conditions than those with a lower capacity for adaptation. This capacity should be exploited when the aim is to use a limited number of species extensively across the world. The genetics of behavioural traits is understood to some extent, but it is seldom accounted for in breeding programmes. This review summarizes the estimates of genetic parameters for behavioural traits in cattle, pigs, poultry and fish. On the basis of the major studies performed in the last two decades, we focus the review on traits of common interest in the four species. These concern the behavioural responses to both acute and chronic stressors in the physical environment (feed, temperature, etc.) and those in the social environment (other group members, progeny, humans). The genetic strategies used to improve the behavioural capacity for adaptation of animals differ between species. There is a greater emphasis on responses to acute environmental stress in fish and birds, and on responses to chronic social stress in mammals.
Agroecology uses natural processes and local resources rather than chemical inputs to ensure production while limiting the environmental footprint of livestock and crop production systems. Selecting ...to achieve a maximization of target production criteria has long proved detrimental to fitness traits. However, since the 1990s, developments in animal breeding have also focussed on animal robustness by balancing production and functional traits within overall breeding goals. We discuss here how an agroecological perspective should further shift breeding goals towards functional traits rather than production traits. Breeding for robustness aims to promote individual adaptive capacities by considering diverse selection criteria which include reproduction, animal health and welfare, and adaptation to rough feed resources, a warm climate or fluctuating environmental conditions. It requires the consideration of genotype×environment interactions in the prediction of breeding values. Animal performance must be evaluated in low-input systems in order to select those animals that are adapted to limiting conditions, including feed and water availability, climate variations and diseases. Finally, we argue that there is no single agroecological animal type, but animals with a variety of profiles that can meet the expectations of agroecology. The standardization of both animals and breeding conditions indeed appears contradictory to the agroecological paradigm that calls for an adaptation of animals to local opportunities and constraints in weakly artificialized systems tied to their physical environment.
Agroecology uses ecological processes and local resources rather than chemical inputs to develop productive and resilient livestock and crop production systems. In this context, breeding innovations ...are necessary to obtain animals that are both productive and adapted to a broad range of local contexts and diversity of systems. Breeding strategies to promote agroecological systems are similar for different animal species. However, current practices differ regarding the breeding of ruminants, pigs and poultry. Ruminant breeding is still an open system where farmers continue to choose their own breeds and strategies. Conversely, pig and poultry breeding is more or less the exclusive domain of international breeding companies which supply farmers with hybrid animals. Innovations in breeding strategies must therefore be adapted to the different species. In developed countries, reorienting current breeding programmes seems to be more effective than developing programmes dedicated to agroecological systems that will struggle to be really effective because of the small size of the populations currently concerned by such systems. Particular attention needs to be paid to determining the respective usefulness of cross-breeding v. straight breeding strategies of well-adapted local breeds. While cross-breeding may offer some immediate benefits in terms of improving certain traits that enable the animals to adapt well to local environmental conditions, it may be difficult to sustain these benefits in the longer term and could also induce an important loss of genetic diversity if the initial pure-bred populations are no longer produced. As well as supporting the value of within-breed diversity, we must preserve between-breed diversity in order to maintain numerous options for adaptation to a variety of production environments and contexts. This may involve specific public policies to maintain and characterize local breeds (in terms of both phenotypes and genotypes), which could be used more effectively if they benefited from the scientific and technical resources currently available for more common breeds. Last but not least, public policies need to enable improved information concerning the genetic resources and breeding tools available for the agroecological management of livestock production systems, and facilitate its assimilation by farmers and farm technicians.
The objective of the study was to develop a genomic evaluation for French beef cattle breeds and assess accuracy and bias of prediction for different genomic selection strategies. Based on a ...reference population of 2,682 Charolais bulls and cows, genotyped or imputed to a high-density SNP panel (777K SNP), we tested the influence of different statistical methods, marker densities (50K versus 777K), and training population sizes and structures on the quality of predictions. Four different training sets containing up to 1,979 animals and a unique validation set of 703 young bulls only known on their individual performances were formed. BayesC method had the largest average accuracy compared to genomic BLUP or pedigree-based BLUP. No gain of accuracy was observed when increasing the density of markers from 50K to 777K. For a BayesC model and 777K SNP panels, the accuracy calculated as the correlation between genomic predictions and deregressed EBV (DEBV) divided by the square root of heritability was 0.42 for birth weight, 0.34 for calving ease, 0.45 for weaning weight, 0.52 for muscular development, and 0.27 for skeletal development. Half of the training set constituted animals having only their own performance recorded, whose contribution only represented 5% of the accuracy. Using DEBV as a response brought greater accuracy than using EBV (+5% on average). Considering a residual polygenic component strongly reduced bias for most of the traits. The optimal percentage of polygenic variance varied across traits. Among the methodologies tested to implement genomic selection in the French Charolais beef cattle population, the most accurate and less biased methodology was to analyze DEBV under a BayesC strategy and a residual polygenic component approach. With this approach, a 50K SNP panel performed as well as a 777K panel.
Reproductive success and offspring survival until sexual maturity are essential traits both for fish fitness and aquaculture development. Variation in offspring’s survival among family results in ...unbalanced parental contributions to the next generation and may explain the loss of genetic diversity observed in some farmed populations. Therefore, we studied the variance in parental contributions to a progeny cohort, as well as the biological factors impacting offspring early survival in rainbow trout. The data consisted of 945 individual survival observations from fertilization to the juvenile stage from 135 full-sib families of the INRAE experimental synthetic line. Survival was assessed at eyed-egg stage, hatching, and 3 weeks after first feeding. We used a full-factorial mating design to partition phenotypic variance in early survival traits into maternal and additive genetic effects under threshold GBLUP models considering the inclusion of genomic information for 32,725 SNP. Average offspring survival proportions were 91.0% at the eyed-egg stage, 87.2% at hatching, and 84.4% three weeks after first feeding. Significant unbalanced dam contributions were observed at the eyed-egg and hatching stages. Low heritability was estimated for early survival traits (h²=0.20 ± 0.12 and 0.13 ± 0.09 for survival from egg-eyed stage and, respectively, hatching and first feeding), revealing that additive genetic variance was not significantly different from zero, while maternal effects explained a larger part (c²=0.37 ± 0.16 and 0.15 ± 0.07, respectively) of the phenotypic variances. There was no evidence of inbreeding depression on survival in our study. Phenotypically, offspring early survival was positively correlated with dam fecundity, while it was negatively correlated with dam post-spawning weight. Negative, but not significant association was observed between early survival and dam’s average egg weight. If a study of genetic correlations confirms these phenotypic trends, promoting high fecund females should help the breeders to increase offspring early survival and to maintain genetic diversity in breeding programs.
•Dam contribution to the next generation is moderately unbalanced in farmed trout.•Maternal and non-additive genetic effects are the main factors explaining early survival.•Within the range studied, inbreeding has no significant role in early survival.•Small females but high fecund females show better survival of their offspring.•Eggs of over-average size produce more abnormal alevins and lower early survival.
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