Structural and Functional Impacts of Copy Number Variations on the Cattle Genome
Animal Genomics and Improvement Laboratory
2013 Annual Report
1a.Objectives (from AD-416):
Our project will produce a bioinformatics tool to study copy number variation by combining sequence-based and array-based approaches. This framework can easily re-purposed for other species and other purposes such as functional genomics studies using RNA-seq. Our project will provide the next generation cattle CNV map (many events at base resolution) - a crucial resource for developing CNV genotyping platforms and a cattle 1000 genomes project. It will also significantly improve the cattle reference genome and its annotation by filling in novel sequence information.
1b.Approach (from AD-416):
1. Develop a general integrated framework to detect, classify and compare copy number variation by jointly using existing next generation sequencing, aCGH and SNP genotyping data; 2. Apply these pipelines to human and cattle datasets and evaluate their performances through computational comparison and experimental validation; 3. Test functional impacts of cattle CNVs by associating them with animal production and health traits.
For objectives 1, 2, and 3, the first comprehensive discovery of CNV using next-generation sequencing from 100 individuals were performed. Thousands of CNV regions, many of which had not been reported previously were identified. This sequence-based CNV call set was validated using three independent molecular techniques achieving a high validation rate. An integrated tool/algorithm to combine both array and next-generation sequencing (NGS) technologies for CNV discovery is being completed. It will provide the second-generation cattle CNV map. It also will significantly improve annotation of the cattle genome. For objective 4, over 30,000 Bovine50K SNP data were collected and processed by the program PennCNV. Functional impacts of cattle CNV are being tested by associating them with animal production and health traits. This research also supported two objectives of its related in-house project to develop biological resources and computational tools to enhance characterization of ruminant genomes (Objective.
1)and to characterize functional genetic variation for improved fertility and environmental sustainability of ruminants (Objective 3).