Partitioning of the genetic trends of French dairy sheep in Mendelian samplings and long-term contributions.

The genetic trend of milk yield for 4 French dairy sheep breeds (Lacaune, Basco-Béarnaise, Manech Tête Noire, and Manech Tête Rousse) was partitioned in Mendelian sampling trends by categories of animals defined by sex and by selection pathways. Five categories were defined, as follows: (1) artificial insemination (AI) males (after progeny testing), (2) males discarded after progeny testing, (3) natural mating males, (4) dams of males, and (5) dams of females. Dams of males and AI males were the most important sources of genetic progress, as observed in the decomposition in Mendelian sampling trends. The yearly contributions were more erratic for AI males than for dams of males, as AI males are averaged across a smaller number of individuals. Natural mating males and discarded males did not contribute to the trend in terms of Mendelian sampling, as their estimated Mendelian sampling term is either null (natural mating males) or negative (discarded males). Overall, in terms of Mendelian sampling, females contributed more than males to the total genetic gain, and we interpret that this is because females constitute a larger pool of genetic diversity. In addition, we computed long-term contributions from each individual to the following pseudo-generations (one pseudo-generation spanning 4 years). With this information, we studied the selection decisions (selected or not selected) for females, and the contributions to the following generations. Mendelian sampling was more important than parent average to determine the selection of individuals and their long-term contributions. Long-term contributions were greater for AI males (with larger progeny sizes than females) and in Basco-Béarnaise than in Lacaune (with the latter being a larger population).

Genomic and pedigree estimation of inbreeding depression for semen traits in the Basco-Béarnaise dairy sheep breed.

Inbreeding depression is associated with a decrease in performance and fitness of the animals. The goal of this study was to evaluate pedigree-based and genomic methods to estimate the level of inbreeding and inbreeding depression for 3 semen traits (volume, concentration, and motility score) in the Basco-Béarnaise sheep breed. Data comprised 16,196 (or 15,071) phenotypic records from 620 rams (of which 533 rams had genotypes of 36,464 SNPs). The pedigree included 8,266 animals, composed of the 620 rams and their ancestors. The number of equivalent complete generations for the 620 rams was 7.04. Inbreeding coefficients were estimated using genomic and pedigree-based information. Genomic inbreeding coefficients were estimated from individual SNP and using segments of homozygous SNP (runs of homozygosity, ROH). Short ROH are of old origin, whereas long ROH are due to recent inbreeding. Considering that the equivalent number of generations in Basco-Béarnaise was 6, inbreeding coefficients for ROH with a length >4 Mb refer to all (recent + old) inbreeding, those with a length >17 Mb correspond to recent inbreeding, and the difference between them indicates old inbreeding. Pedigree-based inbreeding coefficients were also estimated classically, or accounting for nonzero relationships for unknown parents, or including metafounder relationships (estimated using markers) to account for missing pedigree information. Finally, inbreeding coefficients combining genotyped and nongenotyped animal information were computed from matrix H of the single-step approach, also including metafounders. Inbreeding depression was estimated differently depending on the approach used to compute inbreeding coefficients. These 8 estimators of inbreeding coefficients were included as covariates in different animal models. No inbreeding depression was detected for sperm volume or sperm concentration. Inbreeding depression was significant for the motility of spermatozoa. The effect of old and recent inbreeding on motility was null and negative, respectively, demonstrating the existence of purging by selection of deleterious recessive alleles affecting motility. A 10% increase in inbreeding would result in a reduction in mean motility ranging between 0.09 and 0.22 points in the score (from 0 to 5). Motility is unfavorably affected by increasing recent inbreeding but the impact is very small. Runs of homozygosity and metafounders allow us to accurately estimate inbreeding depression and detect recent inbreeding.

Dissecting total genetic variance into additive and dominance components of purebred and crossbred pig traits.

The partition of the total genetic variance into its additive and non-additive components can differ from trait to trait, and between purebred and crossbred populations. A quantification of these genetic variance components will determine the extent to which it would be of interest to account for dominance in genomic evaluations or to establish mate allocation strategies along different populations and traits. This study aims at assessing the contribution of the additive and dominance genomic variances to the phenotype expression of several purebred Piétrain and crossbred (Piétrain × Large White) pig performances. A total of 636 purebred and 720 crossbred male piglets were phenotyped for 22 traits that can be classified into six groups of traits: growth rate and feed efficiency, carcass composition, meat quality, behaviour, boar taint and puberty. Additive and dominance variances estimated in univariate genotypic models, including additive and dominance genotypic effects, and a genomic inbreeding covariate allowed to retrieve the additive and dominance single nucleotide polymorphism variances for purebred and crossbred performances. These estimated variances were used, together with the allelic frequencies of the parental populations, to obtain additive and dominance variances in terms of genetic breeding values and dominance deviations. Estimates of the Piétrain and Large White allelic contributions to the crossbred variance were of about the same magnitude in all the traits. Estimates of additive genetic variances were similar regardless of the inclusion of dominance. Some traits showed relevant amount of dominance genetic variance with respect to phenotypic variance in both populations (i.e. growth rate 8%, feed conversion ratio 9% to 12%, backfat thickness 14% to 12%, purebreds-crossbreds). Other traits showed higher amount in crossbreds (i.e. ham cut 8% to 13%, loin 7% to 16%, pH semimembranosus 13% to 18%, pH longissimus dorsi 9% to 14%, androstenone 5% to 13% and estradiol 6% to 11%, purebreds-crossbreds). It was not encountered a clear common pattern of dominance expression between groups of analysed traits and between populations. These estimates give initial hints regarding which traits could benefit from accounting for dominance for example to improve genomic estimated breeding value accuracy in genetic evaluations or to boost the total genetic value of progeny by means of assortative mating.

Prediction of complex traits: Conciliating genetics and statistics.

This review focuses on methods used to predict complex traits. Main characteristics of prediction approaches are given: the deterministic or stochastic nature of prediction, the objects of prediction, the sources of information and the main statistical methods. Sources of information discussed are the traditional genealogies and phenotypes, nucleotide sequences, expression data and epigenetics marks. Statistical methods are presented as successive degrees of generalization from the definition of the conditional expectation as the prediction rule, to best linear unbiased prediction, then Bayesian and, recently, machine learning methods, including meta-methods. We highlight the contributions of Daniel Gianola to this methodological evolution.

Estimates of the actual relationship between half-sibs in a pig population.

Genomic relationships based on markers capture the actual instead of the expected (based on pedigree) proportion of genome shared identical by descent (IBD). Several methods exist to estimate genomic relationships. In this research, we compare four such methods that were tested looking at the empirical distribution of the estimated relationships across 6704 pairs of half-sibs from a cross-bred pig population. The first method based on multiple marker linkage analysis displayed a mean and standard deviation (SD) in close agreement with the expected ones and was robust to changes in the minor allele frequencies (MAF). A single marker method that accounts for linkage disequilibrium (LD) and inbreeding came second, showing more sensitivity to changes in the MAF. Another single marker method that considers neither inbreeding nor LD showed the smallest empirical SD and was the most sensible to changes in MAF. A higher mean and SD were displayed by VanRaden's method, which was not sensitive to changes in MAF. Therefore, the method based on multiple marker linkage analysis and the single marker method that considers LD and inbreeding performed closer to theoretical values and were consistent with the estimates reported in literature for human half-sibs.

A comparison of methods to estimate genomic relationships using pedigree and markers in livestock populations.

Accurate prediction of breeding values depends on capturing the variability in genome sharing of relatives with the same pedigree relationship. Here, we compare two approaches to set up genomic relationship matrices for precision of genomic relationships (GR) and accuracy of estimated breeding values (GEBV). Real and simulated data (pigs, 60k SNP) were analysed, and GR were estimated using two approaches: (i) identity by state, corrected with either the observed (GVR-O ) or the base population (GVR-B ) allele frequencies and (ii) identity by descent using linkage analysis (GIBD-L ). Estimators were evaluated for precision and empirical bias with respect to true pedigree IBD GR. All three estimators had very low bias. GIBD-L displayed the lowest sampling error and the highest correlation with true genome-shared values. GVR-B approximated GIBD-L 's correlation and had lower error than GVR-O . Accuracy of GEBV for selection candidates was significantly higher when GIBD-L was used and identical between GVR-O and GVR-B . In real data, GIBD-L 's sampling standard deviation was the closest to the theoretical value for each pedigree relationship. Use of pedigree to calculate GR improved the precision of estimates and the accuracy of GEBV.

Sex impact on the quality of fatty liver and its genetic determinism in mule ducks.

Recent changes to French regulations now allow farmers to produce "foie gras" from both male and female mule ducks. The aim of this study was to assess the quality of female fatty liver and to compare, from a phenotypic and genetic point of view, liver quality in males and females. A total of 914 mule ducks (591 males and 323 females), hatched in a single pedigree batch, were reared until 86 d of age and then force-fed for 12 d, before being slaughtered. Carcasses and livers were weighed and liver quality was assessed by grading the extent of liver veining and measuring the liver melting rate, either after sterilization of 60 g of liver or pasteurization of 180 g of liver. Sexual dimorphism was observed in favor of males, with a difference of approximately 10% in carcass and liver weights and up to 54% for the liver melting rate. Moreover, one-third of female livers showed moderate to high veining, whereas this was not the case for male livers. The fatty livers of female mule ducks are, therefore, of poorer quality and could not be transformed into a product with the appellation "100% fatty liver." According to sex and parental line, heritability values ranged from 0.12 ± 0.05 to 0.18 ± 0.07 for fatty liver weight and from 0.09 ± 0.05 to 0.18 ± 0.05 for the 2 melting rate traits. The genetic correlations between the fatty liver weight and both melting rates were high (greater than +0.80) in the Muscovy population, whereas in the Pekin population, the liver weight and melting rates were less strongly correlated (estimates ranging from +0.36 ± 0.30 to +0.45 ± 0.28). Selection for lower liver melting rates without reducing the liver weight would, therefore, be easier to achieve in the Pekin population. Finally, as the 2 melting rate measurements are highly correlated (0.91 and over 0.95 for phenotypic and genetic correlations, respectively), we suggest using the easiest method, that is, sterilization of 60 g of liver.

Short communication: Analysis of association between the prion protein (PRNP) locus and milk traits in Latxa dairy sheep.

The purpose of this study was to analyze associations between polymorphisms in the PRNP gene and ewe milk traits. A total of 242,565 lactations of the Latxa breed were used. Milk, fat and protein yields, and fat and protein content from black-faced Latxa from Spanish Basque Country, black-faced Latxa from Navarra, and blond-faced Latxa were collected. To evaluate evidence of association, the different traits were analyzed using an animal model, where the PRNP genotype effect was included or not as a random effect. Adding the PRNP effect to the model improved the fitting for milk yield in black-faced Latxa from Spanish Basque Country and in blond-faced Latxa, for fat yield in black-faced Latxa from Navarra, and for protein yield in blond-faced Latxa. However, the proportion of the phenotypic variance explained by the PRNP effect for milk yield (1.0×10(-3)), fat yield (3.6×10(-3)) and protein yield (9.4×10(-4)) were near zero. The PRNP locus accounts for about 0.5, 1.5, and 0.4% of total genetic (PRNP and polygenic) variance in milk, fat, and protein yield. These values indicated that the PRNP effect is not relevant regarding genetic additive contribution. For breeding purposes, it is unlikely that selection for scrapie resistance will have an effect on the milk traits studied in the Latxa breed.

Unknown-parent groups in single-step genomic evaluation.

In single-step genomic evaluation using best linear unbiased prediction (ssGBLUP), genomic predictions are calculated with a relationship matrix that combines pedigree and genomic information. For missing pedigrees, unknown selection processes, or inclusion of several populations, a BLUP model can include unknown-parent groups (UPG) in the animal effect. For ssGBLUP, UPG equations also involve contributions from genomic relationships. When those contributions are ignored, UPG solutions and genetic predictions can be biased. Options to eliminate or reduce such bias are presented. First, mixed model equations can be modified to include contributions to UPG elements from genomic relationships (greater software complexity). Second, UPG can be implemented as separate effects (higher cost of computing and data processing). Third, contributions can be ignored when they are relatively small, but they may be small only after refinements to UPG definitions. Fourth, contributions may approximately cancel out when genomic and pedigree relationships are constructed for compatibility; however, different construction steps are required for unknown parents from the same or different populations. Finally, an additional polygenic effect that also includes UPG can be added to the model.

Modeling the relationships between quality and biochemical composition of fatty liver in mule ducks.

The fatty liver of mule ducks (i.e., French "foie gras") is the most valuable product in duck production systems. Its quality is measured by the technological yield, which is the opposite of the fat loss during cooking. The purpose of this study was to determine whether biochemical measures of fatty liver could be used to accurately predict the technological yield (TY). Ninety-one male mule ducks were bred, overfed, and slaughtered under commercial conditions. Fatty liver weight (FLW) and biochemical variables, such as DM, lipid (LIP), and protein content (PROT), were collected. To evaluate evidence for nonlinear fat loss during cooking, we compared regression models describing linear and nonlinear relations between biochemical measures and TY. We detected significantly greater (P = 0.02) linear relation between DM and TY. Our results indicate that LIP and PROT follow a different pattern (linear) than DM and showed that LIP and PROT are nonexclusive contributing factors to TY. Other components, such as carbohydrates, other than those measured in this study, could contribute to DM. Stepwise regression for TY was performed. The traditional model with FLW was tested. The results showed that the weight of the liver is of limited value in the determination of fat loss during cooking (R(2) = 0.14). The most accurate TY prediction equation included DM (in linear and quadratic terms), FLW, and PROT (R(2) = 0.43). Biochemical measures in the fatty liver were more accurate predictors of TY than FLW. The model is useful in commercial conditions because DM, PROT, and FLW are noninvasive measures.

Evaluation of a multi-line broiler chicken population using a single-step genomic evaluation procedure.

Effects on prediction of analysing a multi-line chicken population as one line were evaluated. Body weight records were provided by Cobb-Vantress for two lines of broiler chickens. Phenotypic records for 183 695 and 164 149 broilers and genotypic records for 3195 and 3001 broilers were available for each line. Lines were combined to create a multi-line population and analysed using a single-step procedure combining the additive relationship matrix and the genomic relationship matrix (G). G was scaled using allele frequencies from each line, the multi-line population, or 0.5. When allele frequencies were calculated from each line, distributions of diagonal elements were bimodal. When allele frequencies were calculated from the multi-line population, the distribution of diagonal elements had one peak. When allele frequency 0.5 was used, the distribution was bimodal. Genomic estimated breeding values (GEBVs) were predicted using each allele frequency. GEBVs differed with allele frequency but had ≥ 0.99 correlations with GEBVs predicted with correct allele frequencies. Means of each line and differences in mean between the lines differed based on allele frequencies. Assumed allele frequencies have little impact on ranking within line but larger impact on ranking across lines. G may be used to evaluate multiple populations simultaneously but must be adjusted to obtain properly scaled estimates when population structure is unknown.

Bias in genomic predictions for populations under selection.

Prediction of genetic merit or disease risk using genetic marker information is becoming a common practice for selection of livestock and plant species. For the successful application of genome-wide marker-assisted selection (GWMAS), genomic predictions should be accurate and unbiased. The effect of selection on bias and accuracy of genomic predictions was studied in two simulated animal populations under weak or strong selection and with several heritabilities. Prediction of genetic values was by best-linear unbiased prediction (BLUP) using data either from relatives summarized in pseudodata for genotyped individuals (multiple-step method) or using all available data jointly (single-step method). The single-step method combined genomic- and pedigree-based relationship matrices. Predictions by the multiple-step method were biased. Predictions by a single-step method were less biased and more accurate but under strong selection were less accurate. When genomic relationships were shifted by a constant, the single-step method was unbiased and the most accurate. The value of that constant, which adjusts for non-random selection of genotyped individuals, can be derived analytically.

The fusion of lipid droplets is involved in fat loss during cooking of duck "foie gras".

Fat loss during cooking of duck "foie gras" is the main quality issue in processing plants. To better understand this phenomenon, a histological and ultrastructural study was conducted. The aim was to characterize changes in lipid droplets of duck "foie gras" related to fat loss during cooking. Ten fatty livers were sampled before and after cooking and prepared for optical and transmission electron microscopy. In raw livers, the lipid droplets were nearly spherical while after cooking, they were larger and lost their spherical shape. We also observed a decrease in the number of droplets after cooking, probably due to droplet fusion caused by the heat treatment. Before cooking, there were fewer lipid droplets and a higher osmium tetroxyde staining intensity in the fatty liver, which later gave a lower technological yield. Fat loss during cooking was higher when there was more fusion of lipid droplets before cooking.

Genetic parameters of product quality and hepatic metabolism in fattened mule ducks.

Genetic parameters of traits related to hepatic lipid metabolism, carcass composition, and product quality of overfed mule ducks were estimated on both parental lines of this hybrid: the common duck line for the maternal side and the Muscovy line for the paternal side. The originality of the statistical model was to include simultaneously the additive genetic effect of the common ducks and that of the Muscovy ducks, revealing a greater genetic determinism in common than in Muscovy. Plasma metabolic indicators (glucose, triglyceride, and cholesterol contents) were heritable, in particular at the end of the overfeeding period, and heritabilities increased with the overfeeding stage. Carcass composition traits were highly heritable in the common line, with values ranging from 0.15 for liver weight, 0.21 for carcass weight, and 0.25 for abdominal fat weight to 0.32 for breast muscle weight. Heritabilities of technological outputs were greater for the fatty liver (0.19 and 0.08, respectively, on common and Muscovy sides for liver melting rate) than for the pectoralis major muscle (between 0.02 and 0.05 on both parental sides for cooking losses). Fortunately, the processing industry is mainly facing problems in liver quality, such as too high of a melting rate, than in meat quality. The meat quality appraisal criteria (such as texture and cooking losses), usually dependent on pH and the rate of decline of pH, were also very lowly heritable. This study demonstrated that genetic determinism of meat quality and ability of overfeeding is not similar in the common population and in the Muscovy population; traits related to fattening, muscle development, and BW have heritability values from 2 to 4 times greater on the common line than on the Muscovy line, which is relevant for considering different selection strategies.

Comparison of nonlinear and spline regression models for describing mule duck growth curves.

This study compared models for growth (BW) before overfeeding period for male mule duck data from 7 families of a QTL experimental design. Four nonlinear models (Gompertz, logistic, Richards, and Weibull) and a spline linear regression model were used. This study compared fixed and mixed effects models to analyze growth. The Akaike information criterion was used to evaluate these alternative models. Among the nonlinear models, the mixed effects Weibull model had the best overall fit. Two parameters, the asymptotic weight and the inflexion point age, were considered random variables associated with individuals in the mixed models. In our study, asymptotic weight had a greater effect in Akaike's information criterion reduction than inflexion point age. In this data set, the between-ducks variability was mostly explained by asymptotic BW. Comparing fixed with mixed effects models, the residual SD was reduced in about 55% in the latter, pointing out the improvement in the accuracy of estimated parameters. The mixed effects spline regression model was the second best model. Given the piecewise nature of growth, this model is able to capture different growth patterns, even with data collected beyond the asymptotic BW.

Immune reactivity to type VII collagen: implications for gene therapy of recessive dystrophic epidermolysis bullosa.

Recessive dystrophic epidermolysis bullosa (RDEB) is a severe genodermatosis caused by loss-of-function mutations in COL7A1 encoding type VII collagen, the component of anchoring fibrils. As exogenous type VII collagen may elicit a deleterious immune response in RDEB patients during upcoming clinical trials of gene therapies or protein replacement therapies, we developed enzyme-linked immunosorbent assay (ELISA) and enzyme-linked immunosorbent spot (ELISPOT) assays to analyze B- and T-cell responses, to the full-length type VII collagen. The ELISA was highly sensitive and specific when tested against sera from 41 patients with epidermolysis bullosa acquisita (EBA), and the IFN-gamma ELISPOT detected a cellular response that correlated with ongoing EBA manifestations. Both tests were next applied to assess the risk of an immune response to type VII collagen in seven RDEB patients with a range of type VII collagen expression profiles. Immune responses against type VII collagen were dependent on the expression of type VII collagen protein, and consequently on the nature and position of the respective COL7A1 mutations. These immunologic tests will be helpful for the selection of RDEB patients for future clinical trials aiming at restoring type VII collagen expression, and in monitoring their immune response to type VII collagen after treatment.

A dynamic deterministic model to optimize a multiple-trait selection scheme.

A mathematical approach was developed to model and optimize simultaneous selection on 2 traits, a quantitative trait with underlying polygenic variation and a monogenic trait (e.g., resistance to a disease). A deterministic model allows global optimization of the selection scheme to maximize the frequency of the desired genotype for the monogenic trait, while minimizing the loss of genetic progress on the polygenic trait. An additive QTL or gene was considered. Breeding programs with overlapping generations, different selection strategies for males and females, and assortative mating were modeled. A genetic algorithm was used to solve this optimization problem. This modeling approach may easily be adapted to a variety of underlying genetic models and selection schemes. This model was applied to an example where selection on the Prp gene for scrapie resistance was introduced as an additional selection criterion in an already existing dairy sheep selection scheme.

No associations between PrP genotypes and reproduction traits in INRA 401 sheep.

In this study, the potential association of PrP genotypes with ewe reproductive traits and lamb growth traits was investigated. Data were included on ewes and lambs of the INRA 401 breed from the Bourges-La Sapinière INRA experimental farm. This breed was chosen because of good breeding (prolificacy and maternal abilities) and carcass qualities, and the large number of available animals with performance records and PrP genotypes. Ewes were categorized into 3 PrP genotype classes: ARR homozygous, ARR heterozygous, and animals without any ARR haplotype. Two analyses differing in the traits considered were carried out. Firstly, the potential association of the PrP genotype of ewes with their reproduction traits (fertility, litter size, and ovulation rate) was studied. The data included 801, 779, and 587 genotyped ewes for fertility, litter size, and ovulation rate, respectively. Secondly, the association of the PrP genotype of the ewes with growth traits of their lambs (birth weight, ADG between 10 and 30 d of age) was investigated. The data included 3,749 and 3,512 lambs for birth weight and ADG, respectively. The different traits were analyzed using an animal model, where the PrP genotype effect was included as a fixed effect. The reproductive traits were modeled under a probit or a threshold approach. The results of this study indicate no evidence of an association between PrP genotypes and reproductive and growth traits. It is unlikely that selection for scrapie resistance will have an effect on the reproductive or performance traits studied in the INRA 401 breed.