期刊
GIGASCIENCE
卷 8, 期 6, 页码 -出版社
OXFORD UNIV PRESS
DOI: 10.1093/gigascience/giz073
关键词
CNV; structural variants; cattle; dairy; beef; whole-genome sequencing; database; sequence visualization
资金
- Genome Canada
- Genome Alberta
- Science Foundation Ireland (SFI) [14/IA/2576]
- Science Foundation Ireland
- Department of Agriculture, Food and Marine on behalf of the Government of Ireland [16/RC/3835]
Background: Copy number variants (CNVs) contribute to genetic diversity and phenotypic variation. We aimed to discover CNVs in taurine cattle using a large collection of whole-genome sequences and to provide an interactive database of the identified CNV regions (CNVRs) that includes visualizations of sequence read alignments, CNV boundaries, and genome annotations. Results: CNVs were identified in each of 4 whole-genome sequencing datasets, which together represent > 500 bulls from 17 breeds, using a popular multi-sample read-depth-based algorithm, cn. MOPS. Quality control and CNVR construction, performed dataset-wise to avoid batch effects, resulted in 26,223 CNVRs covering 107.75 unique Mb (4.05%) of the bovine genome. Hierarchical clustering of samples by CNVR genotypes indicated clear separation by breeds. An interactive HTML database was created that allows data filtering options, provides graphical and tabular data summaries including Hardy-Weinberg equilibrium tests on genotype proportions, and displays genes and quantitative trait loci at each CNVR. Notably, the database provides sequence read alignments at each CNVR genotype and the boundaries of constituent CNVs in individual samples. Besides numerous novel discoveries, we corroborated the genotypes reported for a CNVR at the KIT locus known to be associated with the piebald coat colour phenotype in Hereford and some Simmental cattle. Conclusions: We present a large comprehensive collection of taurine cattle CNVs in a novel interactive visual database that displays CNV boundaries, read depths, and genome features for individual CNVRs, thus providing users with a powerful means to explore and scrutinize CNVRs of interest more thoroughly.
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