A large and diverse collection of bovine genome sequences from the Canadian Cattle Genome Project. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Stothard, Paul; Liao, Xiaoping; Arantes, Adriano; De Pauw, Mary; Coros, Colin; Plastow, Graham; Sargolzaei, Mehdi; Crowley, John; Basarab, John; Schenkel, Flavio; Moore, Stephen; Miller, Stephen
• Is Part Of: GigaScience. Volume 4:Issue 1(2015)
• Page Start: 1
• Page End: 3
• Publication Date: 2015-12
• Subjects: Whole-genome sequencing -- Bos taurus -- Beef -- Dairy; Information storage and retrieval systems -- Research -- Periodicals; Biology -- Research -- Periodicals; Medical sciences -- Research -- Periodicals; Database management -- Periodicals; 570.285
• DOI: 10.1186/s13742-015-0090-5
• Languages: English
• ISSNs: 2047-217X

Abstract

Abstract Background The Canadian Cattle Genome Project is a large-scale international project that aims to develop genomics-based tools to enhance the efficiency and sustainability of beef and dairy production. Obtaining DNA sequence information is an important part of achieving this goal as it facilitates efforts to associate specific DNA differences with phenotypic variation. These associations can be used to guide breeding decisions and provide valuable insight into the molecular basis of traits. Findings We describe a dataset of 379 whole-genome sequences, taken primarily from key historicBos taurus animals, along with the analyses that were performed to assess data quality. The sequenced animals represent ten populations relevant to beef or dairy production. Animal information (name, breed, population), sequence data metrics (mapping rate, depth, concordance), and sequence repository identifiers (NCBI BioProject and BioSample IDs) are provided to enable others to access and exploit this sequence information. Conclusions The large number of whole-genome sequences generated as a result of this project will contribute to ongoing work aiming to catalogue the variation that exists in cattle as well as efforts to improve traits through genotype-guided selection. Studies of gene function, population structure, and sequence evolution are also likely to benefit from the availability of this resource.