Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods

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.

Forensic genomics as a novel tool for identifying the causes of mass mortality events

“…In theory [35][36][37] , a reduction in genetic diversity and an increase in linkage disequilibrium can be seen around selected regions. Unfortunately, we do not know enough about linked regions in the abalone transcriptome.…”

Uncovering Adaptation from Sequence Data: Lessons from Genome Resequencing of Four Cattle Breeds

“…To check this information we also aligned the bovine sequence against the sequence of three Bovidae species (Rocha et al 2014). For 365,146 SNPs, the ancestral allele in our alignment was consistent with that reported by Utsunomiya et al (2013) so we used this information for sweep detection. For all other SNPs, we used a folded allele frequency distribution; i.e., allele frequencies Y i and 1 2 Y i were considered as the same observed state.…”

“…Implementation: Ancestral Bovinae alleles at 448,289 SNPs included in the Illumina BovineHD BeadChip were obtained from Utsunomiya et al (2013). To check this information we also aligned the bovine sequence against the sequence of three Bovidae species (Rocha et al 2014).…”

“…We estimated the population tree, using neighbor joining on the Reynold's genetic distances between populations (see Bonhomme et al 2010 for details). We used the ancestral allele reconstruction of Utsunomiya et al (2013) to root the population tree and estimate the population kinship matrix.FLK: For the single-marker analysis, we performed the FLK test on all variants and computed P-values using the theoretical x 2 ð3Þ distribution, which was a good fit to the observed distribution ( Figure S4).hapFLK: For the hapFLK test, to save computation time, we removed variants that had low minor allele frequency (, 10%) in all breeds. Note that as the analysis looks for signals of differentiation, removing these variants does not preclude detection.…”

Interrogation of modern and ancient genomes reveals the complex domestic history of cattle

“…Results from the Bovine HapMap project identified selective sweeps centered around the myostatin (MSTN) and the ATP binding cassette sub family G member 2 (ABCG2) genes, which harbor SNPs associated with phenotypic differences in meat and milk production, respectively (Bovine HapMap Consortium, 2009). More recent studies have identified additional genomic regions subject to selective sweeps that encompassed quantitative trait loci and candidate genes associated with beef and dairy production traits, behavioral traits, morphology, fertility, and health (Larkin et al, 2012;Qanbari et al, 2012;Ramey et al, 2013;Rothammer et al, 2013;Utsunomiya et al, 2013). It is important to note, however, that analysis of selective sweeps is challenging; for example, regions of the genome with significantly reduced sequence variation can also be generated by genetic drift, making true population genomic signals of selection difficult to discern fully.…”