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310
Assessing genetic diversity in Canadian beef cattle populations using Illumina BovineSNP50 chip

Thursday, July 21, 2016: 11:45 AM
Grand Ballroom I (Salt Palace Convention Center)
Mohammed K Abo-Ismail , Animal and Poultry Production, Damanhour University, Damanhour, Egypt
Everestus C. Akanno , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Razie Khorshidi , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
John Crowley , Canadian Beef Breeds Council, Calgary, AB, Canada
Liuhong Chen , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Brian K Karisa , Alberta Livestock and Meat Agency Ltd, Edmonton, AB, Canada
Xiuling Li , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Zhiquan Wang , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
John Basarab , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Changxi Li , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Paul Stothard , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Graham Plastow , Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
Audio File Recorded Presentation (mp4)
Abstract Text:

The main objective of this study was to utilize genomic profiles to assess genetic diversity within and between Canadian beef cattle populations to gain insights on population admixture and dynamics. Individuals (n=2,831) were genotyped for Illumina BovineSNP50 for 9 populations (Gelbvieh (GVH, n=488), Charolais (CHA, n=396), Angus (AAN, n=492), Simmental (SIM, n=404), Limousin (LIM, n=205), Hereford (HER, n=591), Hays Converter (HC, n=208), Kinsella composites (KC, n=15) and Lacombe Research Centre (LRC, n=33). A total of 2,828 individuals with 43,172 SNPs across 29 autosomes passed quality control and were used for further analyses. To study population structure between populations, a principal component analysis (PCA) was performed using SNP1101 software. Genomic inbreeding coefficients for each individual were estimated using 4 methods; VanRaden 2008 (Fv), Leutenegger 2003 (Fl), excess of homozygosity (Fh) and GCTA software (Fg) method implemented in SNP1101 software. The PCA analysis reported clear divergence between GVH, CH, AAN, SIM, LIM, HER and HC populations where 7 clusters were well defined, illustrated in Figure 1. The KC and LRC populations are distributed between the other clusters confirming their genetic architectures as crossbred. The most genomically divergent breeds were CHA, AAN, GVH and HER. The correlations between inbreeding coefficients Fv with Fl and Fg were strong; 0.98 and 0.93, respectively. The average estimate of genomic inbreeding coefficients (Fv, Fl, and Fg) were highest for the HER ranged from 12.8 ± 0.1to 18.5 ± 0.2% followed by AAN ranged from 10 ± 0.1 to 12.7 ± 0.1%. In addition, the genomic inbreeding coefficients for composites/crossbreds ranged from 2.0 ± 1.0 to 4.0 ± 1.0 % and from 1.0 ± 0.7 to 7.0 ± 1.0% for KC and LRC, respectively, where these inbreeding levels were low across all methods compared with purebred cattle. In conclusion, the genomic assessment of inbreeding using different methods indicated that HER and AAN breeds had the highest inbreeding level and thus inbreeding depression should be assessed for their traits at the genome level. Information on specific regions that are fixed for deleterious alleles allows directed introgression between breeds to help address performance.

Keywords: Genetic Diversity, Inbreeding, Single Nucleotide Polymorphism, Canadian beef cattle

See more of: Breeding and genetics: Genomic evaluation II - Applications
See more of: Breeding and Genetics
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