Genomic prediction for carcass traits in Japanese Black cattle using single nucleotide polymorphism markers of different densities
Shinichiro Ogawa A E , Hirokazu Matsuda A , Yukio Taniguchi A , Toshio Watanabe B , Yuki Kitamura C , Ichiro Tabuchi C , Yoshikazu Sugimoto D and Hiroaki Iwaisaki A
+ Author Affiliations
- Author Affiliations
A Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan.
B National Livestock Breeding Center, Nishigo, Fukushima 961-8511, Japan.
C Tottori Prefectural Agriculture and Forest Research Institute Livestock Research Center, Kotoura, Tottori 689-2503, Japan.
D Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Nishigo, Fukushima 961-8061, Japan.
E Corresponding author. Email: sogawa@kais.kyoto-u.ac.jp
Animal Production Science 57(8) 1631-1636 https://doi.org/10.1071/AN15696
Submitted: 4 October 2015 Accepted: 27 June 2016 Published: 1 September 2016
Abstract
Genomic prediction (GP) of breeding values using single nucleotide polymorphism (SNP) markers can be conducted even when pedigree information is unavailable, providing phenotypes are known and marker data are provided. While use of high-density SNP markers is desirable for accurate GP, lower-density SNPs can perform well in some situations. In the present study, GP was performed for carcass weight and marbling score in Japanese Black cattle using SNP markers of varying densities. The 1791 fattened steers with phenotypic data and 189 having predicted breeding values provided by the official genetic evaluation using pedigree data were treated as the training and validation populations respectively. Genotype data on 565 837 autosomal SNPs were available and SNPs were selected to provide different equally spaced SNP subsets of lower densities. Genomic estimated breeding values (GEBVs) were obtained using genomic best linear unbiased prediction incorporating one of two types of genomic relationship matrices (G matrices). The GP accuracy assessed as the correlation between the GEBVs and the corrected records divided by the square root of estimated heritability was around 0.85 for carcass weight and 0.60 for marbling score when using 565 837 SNPs. The type of G matrix used gave no substantial difference in the results at a given SNP density for traits examined. Around 80% of the GP accuracy was retained when the SNP density was decreased to 1/1000 of that of all available SNPs. These results indicate that even when a SNP panel of a lower density is used, GP may be beneficial to the pre-selection for the carcass traits in Japanese Black young breeding animals.
Additional keywords: carcass weight, genomic estimated breeding value, lower-density SNP markers, marbling score.
References
Ashida I, Iwaisaki H (1998) A numerical technique for REML estimation of variance components using average information algorithm and its computing property. Animal Science and Technology 69, 631–636.| A numerical technique for REML estimation of variance components using average information algorithm and its computing property.Crossref | GoogleScholarGoogle Scholar | [in Japanese].
Boddhireddy P, Kelly MJ, Northcutt S, Prayaga KC, Rumph J, DeNise S (2014) Genomic prediction in Angus cattle: comparisons of sample size, response variables, and clustering methods for cross-validation. Journal of Animal Science 92, 485–497.
| Genomic prediction in Angus cattle: comparisons of sample size, response variables, and clustering methods for cross-validation.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXjs1KnurY%3D&md5=c42e0e7074e437726da9efba050197e5CAS | 24431338PubMed |
Boerner V, Johnston DJ, Tier B (2014) Accuracies of genomically estimated breeding values from pure-breed and across-breed predictions in Australian beef cattle. Genetics Selection Evolution 46, 61
| Accuracies of genomically estimated breeding values from pure-breed and across-breed predictions in Australian beef cattle.Crossref | GoogleScholarGoogle Scholar |
Bolormaa S, Pryce JE, Kemper K, Savin K, Hayes BJ, Barendse W, Zhang Y, Reich CM, Mason BA, Bunch RJ, Harrison BE, Reverter A, Herd RM, Tier B, Graser H-U, Goddard ME (2013) Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality in Bos taurus, Bos indicus, and composite beef cattle. Journal of Animal Science 91, 3088–3104.
| Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality in Bos taurus, Bos indicus, and composite beef cattle.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtFChsLrL&md5=c0d0f1ea74fc294d86ec6dfaccc75f9bCAS | 23658330PubMed |
Browning BL, Browning SR (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. American Journal of Human Genetics 81, 1084–1097.
| Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1KmsL3M&md5=866c30a92417b21c5abf4209817ba5a3CAS | 17924348PubMed |
Chen L, Vinsky M, Li C (2015) Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle. Animal Genetics 46, 55–59.
| Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC2M3nslOktQ%3D%3D&md5=6e9ec68890b2e58a186bd15d6cebea91CAS | 25393962PubMed |
Clark SA, Kinghorn BP, Van Der Werf JH (2013) Comparisons of identical by state and identical by descent relationship matrices derived from SNP markers in genomic evaluation. In ‘Proceedings of the Twentieth Conference of the Association for the Advancement of Animal Breeding and Genetics’. pp. pp. 261–265. (Association for the Advancement of Animal Breeding and Genetics: Napier, New Zealand) Available at http://e-publications.une.edu.au/1959.11/14477 [Verified 23 October 2013]
Endelman JB (2011) Ridge regression and other kernels for genomic selection with R package rrBLUP. The Plant Genome 4, 250–255.
| Ridge regression and other kernels for genomic selection with R package rrBLUP.Crossref | GoogleScholarGoogle Scholar |
Fernandes Júnior GA, Rosa GJM, Valente BD, Carvalheiro R, Baldi F, Garcia DA, Gordo DGM, Espigolan R, Takada L, Tonussi RL, de Andrade WBF, Magalhaes AFB, Chardulo LAL, Tonhati H, de Albuquerque LG (2016) Genomic prediction of breeding values for carcass traits in Nellore cattle. Genetics Selection Evolution 48, 7
| Genomic prediction of breeding values for carcass traits in Nellore cattle.Crossref | GoogleScholarGoogle Scholar |
Forni S, Aguilar I, Misztal I (2011) Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information. Genetics Selection Evolution 43, 1
| Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information.Crossref | GoogleScholarGoogle Scholar |
Goddard ME, Hayes BJ (2009) Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics 10, 381–391.
| Mapping genes for complex traits in domestic animals and their use in breeding programmes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXmtVKrsLw%3D&md5=b0088ace2eee47d34a2b2c0ac5ae854bCAS | 19448663PubMed |
Habier D, Fernando RL, Dekkers JCM (2009) Genomic selection using low-density marker panels. Genetics 182, 343–353.
| Genomic selection using low-density marker panels.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXlvFCmt7c%3D&md5=8e2d8e23852fca57bdc3f27c5087e2f1CAS | 19299339PubMed |
Japan Meat Grading Association (JMGA) (1988) ‘New beef carcass grading standards.’ (Japan Meat Grading Association: Tokyo)
Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178, 1709–1723.
| Efficient control of population structure in model organism association mapping.Crossref | GoogleScholarGoogle Scholar | 18385116PubMed |
Legarra A, Granie CR, Manfredi E, Elsen JM (2008) Performance of genomic selection in mice. Genetics 180, 611–618.
| Performance of genomic selection in mice.Crossref | GoogleScholarGoogle Scholar | 18757934PubMed |
Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819–1829.
Meuwissen THE, Luan T, Woolliams JA (2011) The unified approach to the use of genomic and pedigree information in genomic evaluations revisited. Journal of Animal Breeding and Genetics 128, 429–439.
| The unified approach to the use of genomic and pedigree information in genomic evaluations revisited.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3Mbnt12itA%3D%3D&md5=148eb97e6d53ec8f98f259cdc96f53ebCAS |
Moser G, Khatkar MS, Hayes BJ, Raadsma HW (2010) Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers. Genetics Selection Evolution 42, 37
| Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers.Crossref | GoogleScholarGoogle Scholar |
Nomura T, Honda T, Mukai F (2001) Inbreeding and effective population size of Japanese Black cattle. Journal of Animal Science 79, 366–370.
| Inbreeding and effective population size of Japanese Black cattle.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXjsFCnsb4%3D&md5=7b61b8381b115f69fa36339bc80415beCAS | 11219445PubMed |
Ogawa S, Matsuda H, Taniguchi Y, Watanabe T, Nishimura S, Sugimoto Y, Iwaisaki H (2014) Effects of single nucleotide polymorphism marker density on degree of genetic variance explained and genomic evaluation for carcass traits in Japanese Black beef cattle. BMC Genetics 15, 15
| Effects of single nucleotide polymorphism marker density on degree of genetic variance explained and genomic evaluation for carcass traits in Japanese Black beef cattle.Crossref | GoogleScholarGoogle Scholar | 24491120PubMed |
Oyama K (2011) Genetic variability of Wagyu cattle estimated by statistical approaches. Animal Science Journal 82, 367–373.
| Genetic variability of Wagyu cattle estimated by statistical approaches.Crossref | GoogleScholarGoogle Scholar | 21615828PubMed |
Saatchi M, McClure MC, McKay SD, Rolf MM, Kim JW, Decker JE, Taxis TM, Chapple RH, Ramey HR, Northcutt SL, Bauck S, Woodward B, Dekkers JCM, Fernando RL, Schnabel RD, Garrick DJ, Taylor JF (2011) Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation. Genetics Selection Evolution 43, 40
| Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.Crossref | GoogleScholarGoogle Scholar |
Snelling WM, Cushman RA, Keele JW, Maltecca C, Thomas MG, Fortes MRS, Reverter A (2013) Breeding and genetics symposium: networks and pathways to guide genomic selection. Journal of Animal Science 91, 537–552.
| Breeding and genetics symposium: networks and pathways to guide genomic selection.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXlvVKntbs%3D&md5=4c6c0d2112cc6290586856b6b0132904CAS | 23097404PubMed |
VanRaden PM (2008) Efficient methods to compute genomic prediction. Journal of Dairy Science 91, 4414–4423.
| Efficient methods to compute genomic prediction.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhtlajtLzO&md5=5f5d518ecbd76e274a573e8a260c7914CAS | 18946147PubMed |
Vazquez AI, Rosa GJM, Weigel KA, de los Campos G, Gianola D, Allison DB (2010) Predictive ability of subset of single nucleotide polymorphisms with and without parent average in US Holsteins. Journal of Dairy Science 93, 5942–5949.
| Predictive ability of subset of single nucleotide polymorphisms with and without parent average in US Holsteins.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2MXotVWjsr8%3D&md5=6ffb235298e40d03785ca640b2488193CAS | 21094768PubMed |
Wagyu Registry Association (2014) ‘Wagyu.’ No. 269. p. 23. (Wagyu Registry Association: Kyoto, Japan) [In Japanese]
Weigel KA, de los Campos G, González-Recio O, Naya H, Wu XL, Long N, Rosa GJM, Gianola D (2009) Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. Journal of Dairy Science 92, 5248–5257.
| Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhtF2qt77P&md5=ec43c39aec3bf03d7234bc2f1c095067CAS | 19762843PubMed |
Yang J, Benyamin B, McEvoy BP, Gordon S, Henders A, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM (2010) Common SNPs explain a large proportion of the heritability for human height. Nature Genetics 42, 565–569.
| Common SNPs explain a large proportion of the heritability for human height.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXns1GisL8%3D&md5=87c86e0e4e3abd4cdf362212783229e0CAS | 20562875PubMed |
