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Title:   Author  item
                                            Bickhart, Derekitem
                                            XU, LINGYANG - University Of Marylanditem
                                            Hutchison, Janaitem
                                            Sonstegard, Taditem
                                            Van Tassell, Curtis

                                                         - *Curt*item
                                            Schroeder, Steven

                                                         - *Steve*item
                                            GARCIA, JOSE - Sao Paulo State University (UNESP)item
                                            TAYLOR, JEREMY - University Of Missouriitem
                                            Schnabel, Robertitem
                                            LEWIN, HARRIS - University Of Californiaitem
                                            Liu, Ge

                                                         - *George*
  Submitted to: Plant and Animal Genome Conference Proceedings
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 1/10/2014
                                    Publication  Date: 1/10/2014
                                    Citation: Bickhart, D.M., Xu, L., Hutchison, J.L., Sonstegard, T.S., Van Tassell, C.P., Schroeder, S.G., Garcia, J.F., Taylor, J.F., Schnabel, R.D., Lewin, H., Liu, G. 2014. The use of population-scale sequencing to identify CNVs impacting productive traits in different cattle breeds. Plant and Animal Genome Conference Proceedings. Plant Animal Genome XXII, San Diego, CA, Jan. 11–15, P078.Interpretive Summary:
                                Technical Abstract: Individualized copy number variation (CNV) maps have highlighted the need for population surveys of cattle to detect rare and common variants. While SNP and comparative genomic hybridization (CGH) arrays have provided preliminary data, next-generation sequence (NGS) data analysis offers an increased resolution and sensitivity for CNV detection. In this study, we analyzed NGS sequence data derived from 67 taurine (consisting of the Angus, Holstein, Jersey, Limousin and Romagnola breeds) and 20 indicine cattle (consisting of the Brahman, Gir and Nelore breeds). Individual genome sequence coverage ranged from 4X to 30X , with an average coverage of 11.8X across animals. To identify CNVs, we used a customized read-depth CNV calling algorithm that utilizes population-scale data to derive a smoothing coefficient for lowess normalization. We identified 2,947 unique CNV regions that account for approximately 4% (117 Mbp) of the cattle genome. Several dairy- and beef-breed specific variants were found, including a duplication of the cell growth-related RICTOR gene in dairy breeds and a duplication of the Patatin-like phospholipase 3 (PNPLA3) gene in beef breeds. Identification of low frequency and breed-specific CNVs within cattle will enable a better understanding of functional variants influenced by domestication and selection for performance traits.


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