Signatures of local adaptation in lowland and highland teosintes from whole-genome sequencing of pooled samples.

Spatially varying selection triggers differential adaptation of local populations. Here, we mined the determinants of local adaptation at the genomewide scale in the two closest maize wild relatives, the teosintes Zea mays ssp parviglumis and ssp. mexicana. We sequenced 120 individuals from six populations: two lowland, two intermediate and two highland populations sampled along two altitudinal gradients. We detected 8 479 581 single nucleotide polymorphisms (SNPs) covered in the six populations with an average sequencing depth per site per population ranging from 17.0× to 32.2×. Population diversity varied from 0.10 to 0.15, and linkage disequilibrium decayed very rapidly. We combined two differentiation-based methods, and correlation of allele frequencies with environmental variables to detect outlier SNPs. Outlier SNPs displayed significant clustering. From clusters, we identified 47 candidate regions. We further modified a haplotype-based method to incorporate genotype uncertainties in haplotype calling, and applied it to candidate regions. We retrieved evidence for selection at the haplotype level in 53% of our candidate regions, and in 70% of the cases the same haplotype was selected in the two lowland or the two highland populations. We recovered a candidate region located within a previously characterized inversion on chromosome 1. We found evidence of a soft sweep at a locus involved in leaf macrohair variation. Finally, our results revealed frequent colocalization between our candidate regions and loci involved in the variation of traits associated with plant-soil interactions such as root morphology, aluminium and low phosphorus tolerance. Soil therefore appears to be a major driver of local adaptation in teosintes.

On the importance of being structured: instantaneous coalescence rates and human evolution--lessons for ancestral population size inference?

Most species are structured and influenced by processes that either increased or reduced gene flow between populations. However, most population genetic inference methods assume panmixia and reconstruct a history characterized by population size changes. This is potentially problematic as population structure can generate spurious signals of population size change through time. Moreover, when the model assumed for demographic inference is misspecified, genomic data will likely increase the precision of misleading if not meaningless parameters. For instance, if data were generated under an n-island model (characterized by the number of islands and migrants exchanged) inference based on a model of population size change would produce precise estimates of a bottleneck that would be meaningless. In addition, archaeological or climatic events around the bottleneck's timing might provide a reasonable but potentially misleading scenario. In a context of model uncertainty (panmixia versus structure) genomic data may thus not necessarily lead to improved statistical inference. We consider two haploid genomes and develop a theory that explains why any demographic model with structure will necessarily be interpreted as a series of changes in population size by inference methods ignoring structure. We formalize a parameter, the inverse instantaneous coalescence rate, and show that it is equivalent to a population size only in panmictic models, and is mostly misleading for structured models. We argue that this issue affects all population genetics methods ignoring population structure which may thus infer population size changes that never took place. We apply our approach to human genomic data.

Genome-wide linkage disequilibrium in the Blonde d'Aquitaine cattle breed.

We present here the first genome-wide characterization of linkage disequilibrium (LD) in the French Blonde d'Aquitaine (BLA) breed, a well-muscled breed renowned for producing high-yielding beef carcasses. To assess the pattern and extent of LD, we used a sample of 30 unrelated bulls and 36 923 single nucleotide polymorphisms (SNPs) covering all cattle autosomes. The squared correlation of the alleles at two loci (r(2) ) was used as a measure of LD. The analysis of adjacent marker pairs revealed that the level of LD decreases rapidly with physical distance between SNPs. Overall mean r(2) was 0.205 (±0.262). Strong LD (r(2)  > 0.8) and useful LD (measured as r(2 ) > 0.2) were observed within genomic regions of up to 720 and 724 kb, respectively. We analysed the genetic structure of the BLA population and found stratification. The observed genetic sub-structuring is consistent with the known recent demographic history that occurred during BLA breed formation. Our results indicate that LD mapping of phenotypic traits in the BLA population is feasible; however, because of this sub-structuring, special care is needed to reduce the likelihood of false-positive associations between marker loci and traits of interest.

Detection of signatures of selective sweeps in the Blonde d'Aquitaine cattle breed.

Identifying recent positive selection signatures in domesticated animals could provide information on genome response to strong directional selection from domestication and artificial selection and therefore could help in identifying mutations responsible for improved traits. We used genotyping data generated using Illumina's BovineSNP50 Genotyping BeadChips to identify selection signatures in the Blonde d'Aquitaine breed, a well-muscled French beef breed. For this purpose, we employed a hidden Markov model-based test, which detects selection by studying local variations in the allele frequency spectrum along the genome, within a single population. Three regions containing selective sweeps were identified. Annotation of genes located within these regions revealed interesting candidate genes. For example, myostatin (also known as GDF8), a known muscle growth factor inhibitor, is located within the selection signature region found on chromosome 2. In addition, we have identified chromosomal regions that show some evidence of selection within QTL regions for economically important traits. The results of this study could help to better understand the mechanisms related to the selection of the Blonde d'Aquitaine breed.

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.