Abstract
As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10−7) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10−12), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.
Highlights
Selection changes the frequency of advantageous variants and their neighbor polymorphic sites, sweeping the genome and leaving patterns that become prevalent in a population despite chromosome recombination [1]
This paper describes and applies to dairy and beef cattle data a straightforward frequentist meta-analysis approach for combining P-values across different tests for footprints of recent positive selection in genome-wide single nucleotide polymorphism (SNP) data, targeting common, moderate frequency variants
Concordances among extended haplotype homozygosity (EHH) based tests seemed to have led the composite statistics in most cases, and disagreements between Rsb and Integrated Haplotype Score (iHS) scores showed severe drop in significance support
Summary
Selection changes the frequency of advantageous variants and their neighbor polymorphic sites, sweeping the genome and leaving patterns that become prevalent in a population despite chromosome recombination [1] These patterns are broadly referred as signatures (or footprints) of selection, and many methods have been developed for identifying them from genomic data [2]. The available portfolio of methodologies varies in terms of the underlying selection processes assumed, the age of the sweep, and if the test is performed within-population or depends on population comparisons (Table 1). In this scenario, one may expect that correlations among different tests are weak. If there is any given signal consistently supported across different methodologies, it may be strong evidence that the locus has been under past selection
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