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Title: Detecting Loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods

Author
item UTSUNOMIYA, YURI - Universidade Estadual Paulista (UNESP)
item O'BRIEN, ANA MARIA - University Of Natural Resources & Applied Life Sciences - Austria
item Sonstegard, Tad
item Van Tassell, Curtis - Curt
item SANTANA DO CARMO, ADRIANA - Universidade Estadual Paulista (UNESP)
item MESZAROS, GABOR - University Of Natural Resources & Applied Life Sciences - Austria
item SOLKNER, JOHANN - University Of Natural Resources & Applied Life Sciences - Austria
item GARCIA, JOSE - Universidade Estadual Paulista (UNESP)

Submitted to: PLOS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/13/2013
Publication Date: 5/16/2013
Citation: Utsunomiya, Y.T., O'Brien, A.P., Sonstegard, T.S., Van Tassell, C.P., Santana Do Carmo, A.D., Meszaros, G., Solkner, J., Garcia, J.F. 2013. Detecting Loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods. PLoS One. 8(5):e64280.

Interpretive Summary: This study reports on an attempt to identify regions of the cattle genome or genes affecting meat and milk production using a new statistical approach that identifies regions of the genome that have been altered by selection since domestication of cattle or during subsequent breed formation. This study uses high density marker data based on single nucleotide polymorphisms to determine the allele common in cattle before domestication. Deviations from those alleles towards alternative alleles was considered a potential signal for selection. The main regions found in this study differed from the previous studies, and strongly support newly identified regions that have selected intensively by breeders since domestication. These regions help understand the biological changes caused by selective pressure in performance traits.

Technical 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 tests, it might be a strong evidence of selection. We describe and apply to dairy and beef cattle (taurine and indicine) high density single nucleotide polymorphism (SNP) data, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variants, as well as strategies for extracting biological information from the detected signals. We also report the ancestral Bovinae allele state of over 440,000 SNP. Using this combination of methods, we identified highly significant (P < 3.17 x 10-7) population-specific sweeps that point to candidate genes and pathways implied in beef and dairy production. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82 x 10-12), and may be involved in the regulation of 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. Our integrated method, combined with the strategies applied to retrieve functional information, may be a useful tool for reducing false positives in genome-wide surveys of selective sweeps and providing insights in to the source of selection.