On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations

Abstract

Background Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations.ResultsAnalysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic–pituitary–thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors.ConclusionsWe show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0258-1) contains supplementary material, which is available to authorized users.

On the haplotype diversity along the genome in Spanish beef cattle populations

“…Nevertheless, some other causes can be also argued, such as the presence of some kind of natural or artificial selection or the incidence of structural variants in the genome. Both of them have been previously analyzed in these populations (Da Silva et al, 2014;González-Rodríguez et al, 2016) and these studies could not find any consistent pattern between populations, reinforcing the hypothesis that mutation and recombination rates are linked to the observed haplotype diversity. In addition, the results were coherent with the strong heterogeneity of the recombination rate along the cattle genome found by Ma et al (2015).…”

Genomic signatures of divergent selection for production and adaptation in domestic goats (Capra hircus)

“…The di analysis detected four candidate regions, compared with 19 and 13 that were detected by Rsb and iHS, respectively. The differences can be attributed to the con guration of the three selection mapping statistics that capture different patterns in the genome [32,33,34]. Selection signatures based on genetic differentiation persists for a longer period than signals based on haplotype structure.…”

“…Selection signatures based on genetic differentiation persists for a longer period than signals based on haplotype structure. The, di therefore can detect older signatures of selection [32,34] which are most likely associated with long term adaptive divergence. The signatures that are based on haplotype structure arise from short-and/or medium-term events.…”

Detection of hard and soft selective sweeps fromDrosophila melanogasterpopulation genomic data

“…Subsequent studies found that soft sweeps seem to be common not only in this North American population, but also in Sub Saharan populations of D. melanogaster (17,18,36). Finally, these haplotype homozygosity statistics have been applied to several other organisms including pigs (37,38), dogs (37), cattle (39,40), soy beans (41), and humans (42) to identify hard and soft sweeps, and have become standard summary statistics in machine learning methods for detecting selection (43,44). Harris et al 2018 (45) recently reanalyzed the DGRP data using our statistics and argued that that there is scant evidence for abundant recent strong selective sweeps in the North American D. melanogaster population.…”