Mark Henryon

Genetic variation for growth rate, feed conversion efficiency, and disease resistance exists within a farmed population of rainbow trout

Abstract The objective of this study was to test that additive genetic (co)variation for survival, growth rate, feed conversion efficiency, and resistance to viral haemorrhagic septicaemia (VHS) exists within a farmed population of rainbow trout. Thirty sires and 30 dams were mated by a partly factorial mating design. Each sire was mated to two dams, and each dam was mated to two sires, producing 50 viable full-sib families (29 sires, 25 dams). The fish from these families were reared for a 215-day growout period, and were assessed for survival between days 52 and 215, growth rate (i.e., body weight on days 52, 76, 96, 123, 157, 185, and 215, and body length on days 52 and 215); feed conversion efficiency between days 52–215, 52–76, 77–96, 97–123, 124–157, 158–185, and 186–215, and VHS resistance. REML estimates of additive genetic variation for the body weights, body lengths, and feed conversion efficiencies were obtained by fitting univariate linear (reduced) animal models. Additive genetic variation for VHS resistance was estimated by fitting a Weibull, sire–dam frailty model to time until death of fish challenged with VHS. Genetic correlations were estimated among the body weights, body length, and feed conversion efficiencies that expressed additive genetic variation, while genetic correlations between VHS resistance and the body weights, body length, and feed conversion efficiencies were approximated as product–moment correlations among predicted breeding values of the sires and dams. Additive genetic variation was found to be very low for survival, body weight on days 52 and 76, body length on day 52, and feed conversion efficiency between days 185 and 215. However, additive genetic variation was detected for body weight on days 96, 123, 157, 185, and 215 [coefficient of additive genetic variation (CV)=8.4–28.4%, heritability (h2)=0.35 for body weight on day 215], body length on day 215 (CV=6.9%, h2=0.53), feed conversion efficiency between days 52–215, 52–76, 77–96, 97–123, 124–157, and 158–185 (CV=4.0–13.9%), and VHS resistance (additive genetic variance for log-frailty=0.24, h2 on the logarithmic-time scale=0.13). Genetic correlations among the body weights, body length, and feed conversion efficiencies that expressed additive genetic variation were generally favourable and moderate-to-very strong (0.55–0.99), though there were unfavourable correlations (−0.01 to −0.33) between the predicted breeding values for VHS resistance and the predicted breeding values for the body weights, body length, and feed conversion efficiencies. These results demonstrate that additive genetic (co)variation for growth rate, feed conversion efficiency, and VHS resistance does exist within the farmed population of rainbow trout, and indicates that selective breeding for these traits can be successful.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

Deregressed EBV as the response variable yield more reliable genomic predictions than traditional EBV in pure-bred pigs

BackgroundGenomic selection can be implemented by a multi-step procedure, which requires a response variable and a statistical method. For pure-bred pigs, it was hypothesised that deregressed estimated breeding values (EBV) with the parent average removed as the response variable generate higher reliabilities of genomic breeding values than EBV, and that the normal, thick-tailed and mixture-distribution models yield similar reliabilities.MethodsReliabilities of genomic breeding values were estimated with EBV and deregressed EBV as response variables and under the three statistical methods, genomic BLUP, Bayesian Lasso and MIXTURE. The methods were examined by splitting data into a reference data set of 1375 genotyped animals that were performance tested before October 2008, and 536 genotyped validation animals that were performance tested after October 2008. The traits examined were daily gain and feed conversion ratio.ResultsUsing deregressed EBV as the response variable yielded 18 to 39% higher reliabilities of the genomic breeding values than using EBV as the response variable. For daily gain, the increase in reliability due to deregression was significant and approximately 35%, whereas for feed conversion ratio it ranged between 18 and 39% and was significant only when MIXTURE was used. Genomic BLUP, Bayesian Lasso and MIXTURE had similar reliabilities.ConclusionsDeregressed EBV is the preferred response variable, whereas the choice of statistical method is less critical for pure-bred pigs. The increase of 18 to 39% in reliability is worthwhile, since the reliabilities of the genomic breeding values directly affect the returns from genomic selection.

Genetic variation for resistance to clinical and subclinical diseases exists in growing pigs

The objective of this study was to test that genetic variation for resistance to clinical and subclinical diseases exists in growing pigs. A total of 13 551 male growing pigs were assessed for resistance to five categories of clinical and subclinical disease: (i) any clinical or subclinical disease, (ii) lameness, (iii) respiratory diseases, (iv) diarrhoea, and (v) other diseases (i.e. any clinical or subclinical disease with the exception of (ii), (iii), and (iv)). Additive genetic variation for resistance to each disease category was estimated by fitting a Weibull, sire-dam frailty model to time until the pigs were first diagnosed with a disease from that category. Genetic correlations among the resistances to each disease category were approximated as product-moment correlations among predicted breeding values of the sires. Additive genetic variation was detected for resistance to (i) any clinical or subclinical disease (additive genetic variance for log-frailty (± s.e. ) = 0·18 ± 0·05, heritability on the logarithmic-time scale = 0·10), (ii) lameness (0·29 ± 0·11, 0·16), (iii) respiratory diseases (0·24 ± 0·16, 0·12), (iv) diarrhoea (0·30 ± 0·27, 0·16), and (v) the other diseases (0·34 ± 0·15, 0·19) and there were generally positive and low-to-moderate correlations among the predicted breeding values (–0·03 to + 0·65). These results demonstrate that additive genetic variation for resistance to clinical and subclinical diseases does exist in growing pigs, and suggests that selective breeding for resistance could be

Immunological traits have the potential to improve selection of pigs for resistance to clinical and subclinical disease

It was reasoned that, if we used a large sample of pigs, we could demonstrate that total and differential numbers of leukocytes, expression levels of swine leukocyte antigens (SLA) I and II, and serum concentrations of IgG and haptoglobin show additive genetic variation and are, therefore, potentially useful as criteria to improve selection of pigs for resistance to clinical and subclinical disease. We tested this premise by assessing 4204 male pigs from the Duroc, Landrace, and Yorkshire breeds for total and differential numbers of leukocytes and serum concentrations of IgG and haptoglobin; 1217 of the Duroc and Landrace pigs were also assessed for expression levels of SLA I and II. We estimated the amount of additive genetic variation by fitting linear animal models to the total and differential numbers of leukocytes and serum concentrations of IgG and haptoglobin. We fitted linear sire models to the expression levels of SLA I and II. We detected additive genetic variation for each group of traits. Total and differential numbers of leukocytes were moderately heritable ( h 2 =0·22 to 0·30), expression levels of SLA I and II were moderate-to-highly heritable ( h 2 =0·46 to 1·23), while serum concentrations of IgG and haptoglobin were lowly heritable ( h 2 =0·14 to 0·16). The additive genetic variation shown for the immunological traits is encouraging for pig breeders. It indicates that these traits are potentially useful as criteria to improve selection of pigs for resistance to clinical and subclinical disease.

Definition of a breeding objective for commercial production of the freshwater crayfish, marron (Cherax tenuimanus)

This study tested the hypothesis that profitability of commercial marron production would be increased by the development of a rapidly growing strain that has a large tail, a proportional claw size, and a high survival, food conversion efficiency, reproductive rate, and fecundity. A profit equation was developed for commercial marron production, and expressed as function of the production characteristics associated with maintenance of the broodstock (growth rate, survival, food conversion efficiency, reproductive rate, and fecundity), incubation of the eggs and hatchlings (survival), rearing of the juveniles (growth rate, survival, and food conversion efficiency), and grow out of the marron (growth rates of the carapace, tail, and claws, survival, and food conversion efficiency). Economic values were estimated for these characteristics when profit was set to zero, and the sensitivity of selection response to potential errors in these estimates was analysed. The results showed that profit was increased by a genetic increase in the growth rate of the juveniles, growth rates of the carapace and tail of the marron, survivals of the broodstock, eggs and hatchlings, juveniles, and marron, food conversion efficiencies of the broodstock, juveniles, and marron, and the reproductive rate and fecundity of the broodstock. By contrast, profit was decreased by a genetic increase in the growth rate of the broodstock, and a genetic increase in the growth rate of the claws of the marron, given that there was a smaller claw weight to carapace weight ratio that was ideal. Growth rate of the tail of the marron was the most economically important characteristic. Its economic value (per genetic standard deviation improvement) was between 4.7 and 11.6 times larger than an improvement in the growth rate of the carapace, survival of the marron, and growth rate of the claws. In turn, growth rate of the tail was between 30 and 7900 times more important than the food conversion efficiency of the marron, and the characteristics associated with the broodstock, eggs and hatchlings, and juveniles. The sensitivity analysis indicated that response to selection was not sensitive to potential errors in the magnitude of the economic values. These results demonstrate that breeding programs for commercial production should concentrate on the improvement of those characteristics associated with the marron, with emphasis on the growth rate of their tail. They also suggest that the economic values are suitable for implementation in breeding programs, even when future production systems and market conditions are uncertain. The hypothesis tested in this study was supported. Profitability of commercial marron production would be increased by the development of a rapidly growing strain that has a large tail, a proportional claw size, and a high survival, food conversion efficiency, reproductive rate, and fecundity.

Structural gene variants in the porcine mannose-binding lectin 1 (MBL1) gene are associated with low serum MBL-A concentrations.

Mannose-binding lectin (MBL) is a collagenous lectin that kills a wide range of pathogenic microbes through complement activation. The MBL1 and MBL2 genes encode MBL-A and MBL-C, respectively. MBL deficiency in humans is associated with higher susceptibility to viral as well as bacterial infections. A number of single nucleotide polymorphisms (SNP) have been identified in the collagen-like domain of the human MBL gene, of which several are strongly associated with decreased concentrations of MBL in serum. In this study, we have identified a number of SNPs in the porcine MBL-A gene. Sequence comparisons identified a total of 14 SNPs, eight of which were found in exons and six in introns. Four of the eight exon-located SNPs were non-synonymous. Sequence data from several Duroc and Landrace pigs identified four different haplotypes. One haplotype was found in Duroc pigs only, and three haplotypes were found in the Landrace pigs. One of the identified haplotypes was associated with low concentration of MBL-A in serum. The concentration of MBL-A in serum was further assessed in a large number of Duroc and Landrace boars to address its correlation with disease frequency. The MBL-A concentration in Duroc boars showed one single population, whereas Landrace boars showed four distinct populations for MBL-A concentration. The Landrace boars were finally assessed for disease incidence, and the association with the concentration of MBL-A in serum was investigated. No association between MBL and disease incidence was found in this study.

Most of the benefits from genomic selection can be realized by genotyping a small proportion of available selection candidates.

We reasoned that marginal returns from genomic selection diminish as the proportion of genotyped selection candidates increases and breeding values (BV) based on a priori information are used to choose candidates that are genotyped. We tested this premise by stochastic simulation of breeding schemes that resembled those used for pigs. We estimated rates of genetic gain and inbreeding realized by genomic selection in breeding schemes where candidates were phenotyped before genotyping and 0 to 100% of the candidates were genotyped based on predicted BV. Genotyping was allocated to male and female candidates at ratios of 100:0, 75:25, 50:50, 25:75, and 0:100. For genotyped candidates, a direct-genomic value (DGV) was sampled with reliabilities 0.10, 0.50, and 0.90. Ten sires and 300 dams with the largest BV after genotyping were selected at each generation. Selection was for a single trait with heritability 0.20. We found that the marginal returns did diminish as genotyping proportion was increased, while the rate at which the returns diminished slowed as DGV became more reliable. With DGV reliability 0.10, genotyping as little as 5% of the selection candidates realized 86% of the additional genetic gain and 67% of the reduction in inbreeding that was realized by genotyping 100% of the candidates. All of the genetic gain and reduction in inbreeding was realized by genotyping 40 and 50% of the candidates. When the reliability was increased to 0.90, genotyping 20% of the candidates was required to realize 76% of the genetic gain and 85% of the reduction in inbreeding. Genotyping 50% of the selection candidates with DGV reliability 0.90 realized 91% of the genetic gain and 94% of the reduction in inbreeding. Regardless of DGV reliability, returns at small genotyping proportions of 0.5 to 10% were maximized when only male candidates were genotyped. At the large genotyping proportions of 20 to 50%, returns were maximized by genotyping both males and females. Our findings indicate that, provided a priori information is available, only 5 to 20% of the selection candidates need to be genotyped to realize most of the benefits from genomic selection. At these genotyping proportions, it is best to target males in schemes when selection intensity for males is greater than females. Our findings should benefit breeders because they suggest that large investments in genotyping are not required to reap most of the benefits from genomic selection.

Eggs and hatchlings of the freshwater crayfish, marron (Cherax tenuimanus), can be successfully incubated artificially.

Abstract The objective of this study was to test whether marron eggs and hatchlings can be incubated artificially with high levels of survival. Marron eggs were collected from 30 gravid females. The eggs from each female were divided into two replicate groups, and each replicate group was incubated separately within an artificial incubator until the eggs had hatched and developed into independent juveniles. Eighty-nine percent of the eggs hatched and developed into independent juveniles, while the variation in survival between replicate female groups was not significant. These results demonstrate that the artificial incubator was a suitable replacement for the maternal care provided by the female marron after spawning, and that a uniform environment existed within the incubator. The success of the artificial incubation technique enables experiments to be carried out on eggs and hatchlings independent of the females, under a common and controlled environment, and with many separate treatment groups.

Most of the long-term genetic gain from optimum-contribution selection can be realised with restrictions imposed during optimisation

BackgroundWe tested the hypothesis that optimum-contribution selection (OCS) with restrictions imposed during optimisation realises most of the long-term genetic gain realised by OCS without restrictions.MethodsWe used stochastic simulation to estimate long-term rates of genetic gain realised by breeding schemes that applied OCS without and with restrictions imposed during optimisation, where long-term refers to generations 23 to 25 (approximately). Six restrictions were imposed. Five of these removed solutions from the solution space. The sixth removed records of selection decisions made at earlier selection times. We also simulated a conventional breeding scheme with truncation selection as a reference point. Generations overlapped, selection was for a single trait, and the trait was observed for all selection candidates prior to selection.ResultsOCS with restrictions realised 67 to 99% of the additional gain realised by OCS without restrictions, where additional gain was the difference in the long-term rates of genetic gain realised by OCS without restrictions and our reference point with truncation selection. The only exceptions were those restrictions that removed all solutions near the optimum solution from the solution space and the restriction that removed records of selection decisions made at earlier selection times. Imposing these restrictions realised only −12 to 46% of the additional gain.ConclusionsMost of the long-term genetic gain realised by OCS without restrictions can be realised by OCS with restrictions imposed during optimisation, provided the restrictions do not remove all solutions near the optimum from the solution space and do not remove records of earlier selection decisions. In breeding schemes where OCS cannot be applied optimally because of biological and logistical restrictions, OCS with restrictions provides a useful alternative. Not only does it realise most of the long-term genetic gain, OCS with restrictions enables OCS to be tailored to individual breeding schemes.