Claude Chevalet

Detection of quantitative trait loci for growth and fatness in pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. Six boars and 23 F1 sows, the progeny of six LW boars and six MS sows, produced 530 F2 males and 573 F2 females. Nine growth traits, i.e. body weight at birth and at 3, 10, 13, 17 and 22 weeks of age, average daily gain from birth to 3 weeks, from 3 to 10 weeks and from 10 to 22 weeks of age, as well as backfat thickness at 13, 17 and 22 weeks of age and at 40 and 60 kg live weight were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half-/full-sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed highly significant gene effects for growth on chromosomes 1, 4 and 7 and for backfat thickness on chromosomes 1, 4, 5, 7 and X, and significant gene effects on chromosome 6 for growth and backfat thickness. Suggestive QTLs were also revealed by both methods on chromosomes 2 and 3 for growth and 2 for backfat thickness. Significant gene effects were detected for growth on chromosomes 11, 13, 14, 16 and 18 and for backfat thickness on chromosome 8, 10, 13 and 14. LW alleles were associated with high growth rate and low backfat thickness, except for those of chromosome 7 and to a lesser extent early-growth alleles on chromosomes 1 and 2 and backfat thickness alleles on chromosome 6.

Detection of quantitative trait loci for carcass composition traits in pigs.

A quantitative trait locus (QTL) analysis of carcass composition data from a three-generation experimental cross between Meishan (MS) and Large White (LW) pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC) regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS) maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.

Detecting Selection in Population Trees: The Lewontin and Krakauer Test Extended

Detecting genetic signatures of selection is of great interest for many research issues. Common approaches to separate selective from neutral processes focus on the variance of FST across loci, as does the original Lewontin and Krakauer (LK) test. Modern developments aim to minimize the false positive rate and to increase the power, by accounting for complex demographic structures. Another stimulating goal is to develop straightforward parametric and computationally tractable tests to deal with massive SNP data sets. Here, we propose an extension of the original LK statistic (TLK), named TF–LK, that uses a phylogenetic estimation of the populations kinship (\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(\mathrm{\mathcal{F}}\) \end{document}) matrix, thus accounting for historical branching and heterogeneity of genetic drift. Using forward simulations of single-nucleotide polymorphisms (SNPs) data under neutrality and selection, we confirm the relative robustness of the LK statistic (TLK) to complex demographic history but we show that TF–LK is more powerful in most cases. This new statistic outperforms also a multinomial-Dirichlet-based model [estimation with Markov chain Monte Carlo (MCMC)], when historical branching occurs. Overall, TF–LK detects 15–35% more selected SNPs than TLK for low type I errors (P < 0.001). Also, simulations show that TLK and TF–LK follow a chi-square distribution provided the ancestral allele frequencies are not too extreme, suggesting the possible use of the chi-square distribution for evaluating significance. The empirical distribution of TF–LK can be derived using simulations conditioned on the estimated \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(\mathrm{\mathcal{F}}\) \end{document} matrix. We apply this new test to pig breeds SNP data and pinpoint outliers using TF–LK, otherwise undetected using the less powerful TLK statistic. This new test represents one solution for compromise between advanced SNP genetic data acquisition and outlier analyses.

Measuring genetic distances between breeds: use of some distances in various short term evolution models

Many works demonstrate the benefits of using highly polymorphic markers such as microsatellites in order to measure the genetic diversity between closely related breeds. But it is sometimes difficult to decide which genetic distance should be used. In this paper we review the behaviour of the main distances encountered in the literature in various divergence models. In the first part, we consider that breeds are populations in which the assumption of equilibrium between drift and mutation is verified. In this case some interesting distances can be expressed as a function of divergence time, t, and therefore can be used to construct phylogenies. Distances based on allele size distribution (such as (δμ)2 and derived distances), taking a mutation model of microsatellites, the Stepwise Mutation Model, specifically into account, exhibit large variance and therefore should not be used to accurately infer phylogeny of closely related breeds. In the last section, we will consider that breeds are small populations and that the divergence times between them are too small to consider that the observed diversity is due to mutations: divergence is mainly due to genetic drift. Expectation and variance of distances were calculated as a function of the Wright-Malécot inbreeding coefficient, F. Computer simulations performed under this divergence model show that the Reynolds distance [57]is the best method for very closely related breeds.

Error tolerant parent identification from a finite set of individuals

We consider using microsatellites for paternity checking and parent identification in different population structures, and allowing for possible typing errors or mutations. Statistical rules derived from the Bayesian and the sampling approaches are discussed in the case involving the choice of the true father–mother pair among a finite set of possible parental pairs. General situations are investigated by means of random simulations, in order to characterize the joint influences of the number and polymorphism of typed loci, the population structure and size, and error rates. Approximate expressions are provided that give the efficiency of a set of markers for identifying the parents in various mating schemes. The importance of a non-zero value for the typing error rate in the likelihood is highlighted.

Genetic components of litter size variability in sheep

Classical selection for increasing prolificacy in sheep leads to a concomitant increase in its variability, even though the objective of the breeder is to maximise the frequency of an intermediate litter size rather than the frequency of high litter sizes. For instance, in the Lacaune sheep breed raised in semi-intensive conditions, ewes lambing twins represent the economic optimum. Data for this breed, obtained from the national recording scheme, were analysed. Variance components were estimated in an infinitesimal model involving genes controlling the mean level as well as its environmental variability. Large heritability was found for the mean prolificacy, but a high potential for increasing the percentage of twins at lambing while reducing the environmental variability of prolificacy is also suspected. Quantification of the response to such a canalising selection was achieved.

An assessment of European pig diversity using molecular markers: Partitioning of diversity among breeds

Genetic diversity within and between breeds (and lines) of pigs was investigated. The sample comprised 68 European domestic breeds (and lines), including 29 local breeds, 18 varieties of major international breeds, namely Duroc, Hampshire, Landrace, Large White and Piétrain, and 21 commercial lines either purebred or synthetic, to which the Chinese Meishan and a sample of European wild pig were added. On average 46 animals per breed were sampled (range 12–68). The genetic markers were microsatellites (50 loci) and AFLP (amplified fragment length polymorphism, 148 loci). The analysis of diversity showed that the local breeds accounted for 56% of the total European between-breed microsatellite diversity, and slightly less for AFLP, followed by commercial lines and international breeds. Conversely, the group of international breeds contributed most to within-breed diversity, followed by commercial lines and local breeds. Individual breed contributions to the overall European between- and within-breed diversity were estimated. The range in between-breed diversity contributions among the 68 breeds was 0.04–3.94% for microsatellites and 0.24–2.94% for AFLP. The within-breed diversity contributions varied very little for both types of markers, but microsatellite contributions were negatively correlated with the between-breed contributions, so care is needed in balancing the two types of contribution when making conservation decisions. By taking into account the risks of extinction of the 29 local breeds, a cryopreservation potential (priority) was estimated for each of them.

Genetic variability, structure and assignment of Spanish and French pig populations based on a large sampling

The Spanish and French pig populations share the common practice of quasi systematic paternity control of pure breed and composite line males. Ten microsatellite markers are in common between Spain and France controls, among the 17 markers used in France and the 13 used in Spain. After the adjustment of allele sizes, it is possible to merge the two datasets and to obtain a set of 5791 animals, including the vast majority of the males in the Duroc, Landrace, Large White and Piétrain French and Spanish breeds. Twelve French composite lines are also available. The genetic diversity analysis of these pig populations is presented, as well as the assignment of an individual to its breed. The effects of heterogeneous sampling across time and of relatedness among animals are also assessed. Consistent with the results of the previous studies, we found that different populations from the same breed clearly clustered together. In addition, all populations of this study, whether purebred or composite, are quite well differentiated from the other ones. As a result, we note that the 10 microsatellites commonly used for paternity control ensure a powerful detection of the breed of origin, with the power of detection being 95-99%. The detection of the exact population within breed is more difficult, but the power exceeds 70% for most of the populations. Practical implications include, for instance, the detection of outlier animals, crosses and admixture events.

Interactions of selection, linkage and drift in the dynamics of polygenic characters

We study the dynamics under directional truncation selection of the genetic variability of a quantitative character controlled by a finite number of possibly linked loci with additive effects. After the first generation of selection, the build-up of linkage disequilibria (Bulmer effect) is analytically demonstrated from a genetical point of view in an infinite population. In the following generations, the dynamics of the system in a finite population are predicted using analytic recurrences under a multi-normal approximation, and computer simulations. The effects of recombination on the dynamics of linkage disequilibria induced by selection and drift, and the consequences for the additive genetic variance are then analysed and discussed from the simulation results. Compared to the rapid exploitation of genetic variability promoted by high recombination rates, low recombination rates promote an early storage of genetic variability in repulsion associations of alleles and a possible late release of genetic variance in the population, so that the variability of the character may be maintained over a longer period of time. In some cases, favourable recombination events in tightly linked systems induce an increase of the additive variance of the character, which may explain some results observed in long-term selection experiments. Our results emphasize that the joint effects of selection, linkage and drift must not be neglected in theoretical quantitative genetics, and require further investigation.

An examination of genetic diversity and effective population size in Atlantic salmon populations.

Effective population size (Ne) is an important parameter in the conservation of genetic diversity. Comparative studies of empirical data that gauge the relative accuracy of Ne methods are limited, and a better understanding of the limitations and potential of Ne estimators is needed. This paper investigates genetic diversity and Ne in four populations of wild anadromous Atlantic salmon (Salmo salar L.) in Europe, from the Rivers Oir and Scorff (France) and Spey and Shin (Scotland). We aimed to understand present diversity and historical processes influencing current population structure. Our results showed high genetic diversity for all populations studied, despite their wide range of current effective sizes. To improve understanding of high genetic diversity observed in the populations with low effective size, we developed a model predicting present diversity as a function of past demographic history. This suggested that high genetic diversity could be explained by a bottleneck occurring within recent centuries rather than by gene flow. Previous studies have demonstrated the efficiency of coalescence models to estimate Ne. Using nine subsets from 37 microsatellite DNA markers from the four salmon populations, we compared three coalescence estimators based on single and dual samples. Comparing Ne estimates confirmed the efficiency of increasing the number and variability of microsatellite markers. This efficiency was more accentuated for the smaller populations. Analysis with low numbers of neutral markers revealed uneven distributions of allelic frequencies and overestimated short-term Ne. In addition, we found evidence of artificial stock enhancement using native and non-native origin. We propose estimates of Ne for the four populations, and their applications for salmon conservation and management are discussed.