A comprehensive comparison of high-density SNP panels and an alternative ultra-high-density panel for genomic analyses in Nellore cattle
Ricardo V. Ventura A B C K , Luiz F. Brito A D , Gerson A. OliveiraA Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 1 Stone Road West, Guelph, Ontario, N1G 2W1, Canada.
B AgSights, 294 Mill St East, Suite 209, Elora, N0B 1S0 Ontario, Canada.
C Department of Animal Nutrition and Production, School of Veterinary Medicine and Animal Science, University of São Paulo, Pirassununga, São Paulo, 13635-900, Brazil.
D Department of Animal Sciences, Purdue University, 270 S. Russell Street, West Lafayette, Indiana, 47907, USA.
E Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, Vic. 3083, Australia.
F School of Applied Systems Biology, La Trobe University, Bundoora, Vic. 3086, Australia.
G Select Sires Inc., Plain City, Ohio, 43064, USA
H Department of Animal Science, Universidade Federal de Vicosa, Vicosa, Minas Gerais, 36570-900, Brazil.
I Angus Genetics Inc., 3201 Frederick Avenue, Saint Joseph, St Joseph, Missouri, 64506, USA.
J Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, São Paulo, 13635-900, Brazil.
K Corresponding author. Email: rvventura@usp.br
Animal Production Science 60(3) 333-346 https://doi.org/10.1071/AN18305
Submitted: 13 May 2018 Accepted: 11 June 2019 Published: 23 December 2019
Abstract
There is evidence that some genotyping platforms might not work very well for Zebu cattle when compared with Taurine breeds. In addition, the availability of panels with low to moderate number of overlapping markers is a limitation for combining datasets for genomic evaluations, especially when animals are genotyped using different SNP panels. In the present study, we compared the performance of medium- and high-density (HD) commercially available panels and investigated the feasibility of developing an ultra-HD panel (SP) containing markers from an Illumina (HD_I) and an Affymetrix (HD_A) panels. The SP panel contained 1 123 442 SNPs. After performing SNP pruning on the basis of linkage disequilibrium, HD_A, HD_I and SP contained 429 624, 365 225 and 658 770 markers distributed across the whole genome. The overall mean proportion of markers pruned out per chromosome for HD_A, HD_I and SP was 15.17%, 43.18%, 38.63% respectively. The HD_I panel presented the highest mean number of runs-of-homozygosity segments per animal (45.48%, an increment of 5.11% compared with SP) and longer segments, on average (3057.95 kb per segment), than did both HD_A and SP. HD_I also showed the highest mean number of SNPs per run-of-homozygosity segment. Consequently, the majority of animals presented the highest genomic inbreeding levels when genotyped using HD_I. The visual examination of marker distribution along the genome illustrated uncovered regions among the different panels. Haplotype-block comparison among panels and the average haplotype size constructed on the basis of HD_A were smaller than those from HD_I. The average number of SNPs per haplotype was different between HD_A and HD_I. Both HD_A and HD_I panels achieved high imputation accuracies when used as the lower-density panels for imputing to SP. However, imputation accuracy from HD_A to SP was greater than was imputation from HD_I to SP. Imputation from one HD panel to the other is also feasible. Low- and medium-density panels, composed of markers that are subsets of both HD_A and HD_I panels, should be developed to achieve better imputation accuracies to both HD levels. Therefore, the genomic analyses performed in the present study showed significant differences among the SNP panels used.
Additional keywords: imputation, LD pruning, run of homozygosity, SNP array, SNP chip development.
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