Search

Using two successive types of diets (100% concentrate and 67% forage), this study explores the relationship between the ruminal microbiota of 78 Romane lambs and their feed efficiency (residual feed intake trait) or feeding behavior (feeding rate trait). Analysis was carried out phenotypically by correlating feed efficiency or feeding behavior traits with the relative abundance of bacteria at the phylum, family, and genus levels, and then genetically by comparing the microbiota of lambs selected for extreme breeding values for residual feed intake or feeding rate. Our results confirmed the major effect of diet on the ruminal microbiota composition. The microbiota of lambs consuming a forage-based diet was distinguished by higher microbial diversity and also by higher relative abundance of Firmicutes, whereas Bacteriodetes and Actinobacteria were relatively more abundant in the microbiota of lambs consuming a concentrate-based diet. Moreover, the comparison of lambs divergent for residual feed intake breeding values revealed that regardless of diet, more efficient lambs possessed a ruminal microbiota enriched in Coprococcus, Moryella, [Eubacterium] Brachy group, and [Eubacterium] hallii group, but depleted in Lachnospiraceae FD2005 and Shuttleworthia. The connection between microbiota composition and feeding rate was more tenuous, with no link between the abundance of particular genera and lambs genetically divergent for feeding rate.

Background International standard panels of single nucleotide polymorphisms (SNPs) have replaced microsatellites in several species for parentage assessment and assignment (PA) purposes. However, such a resource is still lacking in goats. The application of a cheap tool for PA would help the management of goat populations by improving the reliability of pedigree registration and, consequently, allow a better implementation of breeding schemes or conservation programs. Results Using data from the current GoatSNP50 chip, starting from a worldwide dataset of more than 4000 animals belonging to more than 140 breeds and populations from the AdaptMap initiative, we selected a panel of 195 SNPs. The assignment rate of this panel was up to 100% on an additional dataset that included 2000 Alpine and Saanen animals and highly related candidate sires. Conclusions In this study, we defined a highly informative SNP panel, which will be publicly available to worldwide breeders and laboratories. Its development on such a large number of breeds and populations, together with validation on a second set of cosmopolitan breeds, makes it a promising and important genomic tool for the goat species. Electronic supplementary material The online version of this article (10.1186/s12711-018-0423-9) contains supplementary material, which is available to authorized users.

Background One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs. Results Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species (“selection hotspots”) including ABCG2, LCORL/NCAPG, MSTN, and coat colour genes such as ASIP, MC1R, MITF, and TYRP1. For one of these regions (ABCG2, LCORL/NCAPG), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds. Conclusions Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations. Electronic supplementary material The online version of this article (10.1186/s12864-018-4447-x) contains supplementary material, which is available to authorized users.

The overall sustainability and innovative capacity of the sheep and goat sector in Europe have to be improved to cope with current and future economic, environmental and societal challenges. Innovations in genetic resource management and breeding for sheep and goat populations will be explored in the iSAGE European project (WP5) in order to help the industry to cope with such future challenges. In France, genetic evaluation for small ruminants is performed in a large variability and poorly characterized environments. In this regard, we will consider multi-generation data from existing French breeding programs and experimental field studies. Effects of herd for traits under genetic selection will be investigated in commercial farms in order to better characterize the production environment, particularly using meteorological data but also feeding, breeding system and economic criteria. Such characterization will enable to follow-up trends in animal performances according to weather changes. This work could also contribute to characterize farm typologies to which a set of sustainability indicators will be tested. Then, contrasted environments will be identified and genotype by environment interactions studies will be carried out aiming to improve genetic selection efficiency in a variety of environments. In addition to existing data, we will explore new phenotypes considered as key functional traits for robustness and for which stakeholders are particularly interested. These new phenotypes will be also explored in combination with feed efficiency in experimental facilities under contrasted environments or under feed shortage challenges. Genetic and genomic studies will be performed for new phenotypes used to assess individual robustness. The total merit indices will be revisited from the technical and economic point of view in order to evaluate economic weights of each trait in the "breeding goal", for diversified production systems.; En France, l’évaluation génétique des petits ruminants estime simultanément la valeur génétique des reproducteurs ainsi que les effets d’environnement dont le plus important est l’effet troupeau. Cette évaluation est réalisée dans des environnements variés et mal caractérisés faisant l’hypothèse d’absence d’interaction GxE. Pour tester cette hypothèse et disséquer les composantes des effets troupeaux, les environnements de production seront caractérisés à partir des données collectées en fermes (disponibles dans les systèmes nationaux d’information génétique ou collectées ponctuellement) décrivant les systèmes d’élevages et des données météorologiques. La discrimination des types d’environnements de production établis par la typologie des élevages permettra d’analyser les interactions GxE pour différentes races ovines et caprines en France.Par ailleurs, l’adaptation des petits ruminants à ces environnements variés et changeants implique entre autre leur efficacité d’utilisation des ressources et leur capacité biologique à mobiliser et reconstituer leurs réserves énergétiques sous forme de lipides. Des travaux expérimentaux seront conduits pour étudier les mécanismes biologiques et le déterminisme génétique de la dynamique des réserves corporelles en lien avec l’efficacité alimentaire. Cette approche permettra d’identifier de nouveaux phénotypes pour l’amélioration génétique de la robustesse des petits ruminants.

Background The efficiency of breeding programs partly relies on the accuracy of the estimated breeding values which decreases when pedigrees are incomplete. Two reproduction techniques are mainly used by sheep breeders to identify the sires of lambs: animal insemination and natural matings with a single ram per group of ewes. Both methods have major drawbacks, notably time-consuming tasks for breeders, and are thus used at varying levels in breeding programs. As a consequence, the percentage of known sires can be very low in some breeds and results in less accurate estimated breeding values. Results In order to address this issue and offer an alternative strategy for obtaining parentage information, we designed a set of 249 SNPs for parentage assignment in French sheep breeds and tested its efficiency in one breed. The set was derived from the 54 K SNP chip that was used to genotype the thirty main French sheep populations. Only SNPs in Hardy-Weinberg equilibrium, displaying the highest Minor Allele Frequency across all the thirty populations and not associated with Mendelian errors in verified family trios were selected. The panel of 249 SNPs was successfully used in an on-farm test in the BMC breed and resulted in more than 95% of lambs being assigned to a unique sire. Conclusion In this study we developed a SNP panel for assignment that achieved good results in the on-farm testing. We also raised some conditions for optimal use of this panel: at least 180 SNPs should be used and a minute preparation of the list of candidate sires. Our panel also displays high levels of MAF in the SheepHapMap breeds, particularly in the South West European breeds. Electronic supplementary material The online version of this article (doi:10.1186/s12863-017-0518-2) contains supplementary material, which is available to authorized users.

Background The availability of a high-density SNP genotyping chip and a reference genome sequence of the pig (Sus scrofa) enabled the construction of a high-density linkage map. A high-density linkage map is an essential tool for further fine-mapping of quantitative trait loci (QTL) for a variety of traits in the pig and for a better understanding of mechanisms underlying genome evolution. Results Four different pig pedigrees were genotyped using the Illumina PorcineSNP60 BeadChip. Recombination maps for the autosomes were computed for each individual pedigree using a common set of markers. The resulting genetic maps comprised 38,599 SNPs, including 928 SNPs not positioned on a chromosome in the current assembly of the pig genome (build 10.2). The total genetic length varied according to the pedigree, from 1797 to 2149 cM. Female maps were longer than male maps, with a notable exception for SSC1 where male maps are characterized by a higher recombination rate than females in the region between 91–250 Mb. The recombination rates varied among chromosomes and along individual chromosomes, regions with high recombination rates tending to cluster close to the chromosome ends, irrespective of the position of the centromere. Correlations between main sequence features and recombination rates were investigated and significant correlations were obtained for all the studied motifs. Regions characterized by high recombination rates were enriched for specific GC-rich sequence motifs as compared to low recombinant regions. These correlations were higher in females than in males, and females were found to be more recombinant than males at regions where the GC content was greater than 0.4. Conclusions The analysis of the recombination rate along the pig genome highlighted that the regions exhibiting higher levels of recombination tend to cluster around the ends of the chromosomes irrespective of the location of the centromere. Major sex-differences in recombination were observed: females had a higher recombination rate within GC-rich regions and exhibited a stronger correlation between recombination rates and specific sequence features.

Background In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs. Methods In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees. Results Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL. Conclusions Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals.

International audience