Yang, Tianfu and Miller, Michelle and Forgacs, David and Derr, James and Stothard, Paul (2020) Development of SNP-Based Genomic Tools for the Canadian Bison Industry: Parentage Verification and Subspecies Composition. Frontiers in Genetics, 11. ISSN 1664-8021
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Abstract
Genomic technologies have been increasingly applied in livestock production due to their utility in production management and animal genetic improvement. The current project aimed to develop genomic resources for the Canadian bison industry, specifically a parentage verification tool and a subspecies composition tool. Both products stand to help with building and maintaining purebred and crossbred bison populations, and in turn bison conservation and production. The development of this genomic toolkit proceeded in two stages. In the single-nucleotide polymorphism (SNP) discovery and selection stage, raw sequence information from 41 bison samples was analyzed, and approximately 52.5 million candidate biallelic SNPs were discovered from 21 samples with high sequence quality. A set of 19,954 SNPs (2,928 for parentage verification and 17,026 for subspecies composition) were then selected for inclusion on an Axiom myDesign custom array. In the refinement and validation stage, 480 bison were genotyped using the custom SNP panel, and the resulting genotypes were analyzed to further filter SNPs and assess tool performance. In various tests using real and simulated genotypes, the two genomic tools showed excellent performance for their respective tasks. Final SNP sets consisting of 191 SNPs for parentage and 17,018 SNPs for subspecies composition are described. As the first SNP-based genomic toolkit designed for the Canadian bison industry, our results may provide a new opportunity in improving the competitiveness and profitability of the industry in a sustainable manner.
Item Type: | Article |
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Subjects: | Open Digi Academic > Medical Science |
Depositing User: | Unnamed user with email support@opendigiacademic.com |
Date Deposited: | 23 Jan 2023 09:14 |
Last Modified: | 24 Jun 2024 05:00 |
URI: | http://publications.journalstm.com/id/eprint/163 |