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United States Department of Agriculture

Agricultural Research Service

Research Project: ENHANCING GENETIC MERIT OF DAIRY CATTLE THROUGH GENOME SELECTION AND ANALYSIS Title: A high-resolution cattle CNV map by population-scale genome sequencing

Authors
item BICKHART, DEREK
item Hou, Yali -
item SCHROEDER, STEVEN
item Alkan, Can -
item Cardone, Maria -
item Matukumalli, Lakshmi -
item Schnabel, Robert -
item Ventura, Mario -
item Taylor, Jeremy -
item Eichler, Evan -
item SONSTEGARD, TAD
item VAN TASSELL, CURTIS
item LIU, GE

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: June 23, 2011
Publication Date: July 17, 2011
Citation: Bickhart, D.M., Hou, Y., Schroeder, S.G., Alkan, C., Cardone, M.F., Matukumalli, L.K., Schnabel, R.D., Ventura, M., Taylor, J.F., Eichler, E.E., Sonstegard, T.S., Van Tassell, C.P., Liu, G. 2011. A high-resolution cattle CNV map by population-scale genome sequencing [abstract]. Gordon Research Conference. No. 48.

Technical Abstract: Copy Number Variations (CNVs) are common genomic structural variations that have been linked to human diseases and phenotypic traits. Prior studies in cattle have produced low-resolution CNV maps. We constructed a draft, high-resolution map of cattle CNVs based on whole genome sequencing data from 70 individuals by integrating complementary structural variant (SV) discovery approaches (CGH and high density SNP arrays) and experimental validations (PCR and FISH). Our sequence data comprised a total of ~90× coverage of the reference genome (~ 270 Gb) distributed among 5 taurine and 3 indicine breeds. To identify CNVs from these sequence data, we adopted and fine tuned two well-established computational approaches: read depth (RD; using WSSD) and read pair (RP; using VariationHunter) analyses. Our initial RD results identified 2,789 duplications/insertions and 156 deletions while the RP results revealed multiple deletions. Discovered CNVs had an average length of 20 kb (RD) and represented ~70 megabases of the cattle reference genome. We integrated these new SVs with the CNV call sets made from CGH array and SNP array based methods. To confirm our combined CNV dataset, we created new CGH arrays and performed PCR assays. Our results confirmed previously published CNV regions and validated the new candidate CNVs. These CNVs span multiple annotated cattle genes, which are significantly enriched for specific biological functions such as immunity, lactation, reproduction and rumination. In summary, the individually constructed cattle CNV maps provide a valuable resource for future cattle genomic research.

Last Modified: 9/10/2014