Accuracy of genomic-polygenic estimated breeding value for milk yield and fat yield in the Thai multibreed dairy population with five single nucleotide polymorphism sets |
Wongpom, Bodin
(Department of Animal Science, Kasetsart University)
Koonawootrittriron, Skorn (Department of Animal Science, Kasetsart University) Elzo, Mauricio A. (Department of Animal Sciences, University of Florida) Suwanasopee, Thanathip (Department of Animal Science, Kasetsart University) Jattawa, Danai (Department of Animal Science, Kasetsart University) |
1 | Meuwissen TH, Hayes BJ, Goddard ME. Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001;157:1819-29. DOI |
2 | Hayes B, Bowman P, Chamberlain A, Verbyla K, Goddard M. Accuracy of genomic breeding values in multi-breed dairy cattle populations. Genet Sel Evol 2009;41:51. https://doi.org/10.1186/1297-9686-41-51 DOI |
3 | Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, Lawlor TJ. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J Dairy Sci 2010;93:743-52. https://doi.org/10.3168/jds.2009-2730 DOI |
4 | Jattawa D, Elzo MA, Koonawootrittriron S, Suwanasopee T. Comparison of genetic evaluations for milk yield and fat yield using a polygenic model and three genomic-polygenic models with different sets of SNP genotypes in Thai multibreed dairy cattle. Livest Sci 2015;181:58-64. https://doi.org/10.1016/j.livsci.2015.10.008 DOI |
5 | Weigel KA, de los Campos G, Gonzalez-Recio O, et al. Predicting ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. J Dairy Sci 2009;92:5248-57. https://doi.org/10.3168/jds.2009-2092 DOI |
6 | Moser G, Khatkar MS, Hayes BJ, Raadsma HW. Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers. Genet Sel Evol 2010;42:37. https://doi.org/10.1186/1297-9686-42-37 DOI |
7 | TMD. The climate of Thailand. Bangkok, Thailand: Thai Meteorological Department. Available from: https://www.tmd. go.th/en/archive/thailand_climate.pdf |
8 | Koonawootrittriron S, Elzo MA, Thongprapi T. Genetic trends in a Holstein x other breeds multibreed dairy population in Central Thailand. Livest Sci 2009;122:186-92. https://doi.org/10.1016/j.livsci.2008.08.013 DOI |
9 | Sargent FD, Lytton VH, Wall OG. Test interval method of calculating dairy herd improvement association records. J Dairy Sci 1968;51:170-9. https://doi.org/10.3168/jds.S0022-0302(68)86943-7 DOI |
10 | Koonawootrittriron S, Elzo MA, Tumwasorn S, Sintala W. Prediction of 100-d and 305-d milk yields in a multibreed dairy herd in Thailand using monthly test-day records. Thai J Agric Sci 2001;34:163-74. |
11 | Sargolzaei M, Chesnais JP, Schenkel FS. A new approach for efficient genotype imputation using information from relatives. BMC Genomics 2014;15:478. https://doi.org/10.1186/1471-2164-15-478 DOI |
12 | Tsuruta S. Average Information REML with several options including EM-REML and heterogeneous residual variances; 2014 [cited 2018 June 19]. Available from: http://nce.ads.uga.edu/wiki/doku.php?id=application_programs |
13 | Wang H, Misztal I, Aguilar I, Legarra A, Muir WM. Genomewide association mapping including phenotypes from relatives without genotypes. Genet Res 2012;94:73-83. https://doi.org/10.1017/S0016672312000274 DOI |
14 | Misztal I, Tsuruta S, Lourenco D, Aguilar I, Legarra A, Vitezica Z. Manual for BLUPF90 family of programs. Athens, GA, USA: University of Georgia, 2018 [cited 2018 June 19]. Available from: http://nce.ads.uga.edu/wiki/lib/exe/fetch.php?media=blupf90_all7.pdf |
15 | Misztal I, Legarra A, Aguilar I. Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J Dairy Sci 2009;92:4648-55. https://doi.org/10.3168/jds.2009-2064 DOI |
16 | VanRaden PM, Van Tassell CP, Van Tassell GR, et al. Invited review: Reliability of genomic predictions for North American Holstein bulls. J Dairy Sci 2009;92:16-24. https://doi.org/10.3168/jds.2008-1514 DOI |
17 | Legarra A, Aguilar I, Misztal I. A relationship matrix including full pedigree and genomic information. J Dairy Sci 2009;92:4656-63. https://doi.org/10.3168/jds.2009-2061 DOI |
18 | Meyer K, Houle D. Sampling based approximation of confidence intervals for functions of genetic covariance matrices. In: Proceedings of the Association for the Advancement of Animal Breeding and Genetics 2013; 2013 August 20-23:Napier, New Zealand. 2013. p. 523-6. |
19 | Haile-Mariam M, Nieuwhof GJ, Beard KT, Konstatinov KV, Hayes BJ. Comparison of heritabilities of dairy traits in Australian Holstein-Friesian cattle from genomic and pedigree data and implications for genomic evaluations. J Anim Breed Genet 2013;130:20-31. https://doi.org/10.1111/j.1439-0388.2013.01001.x DOI |
20 | Sun C, VanRaden PM, Cole JB, Connell JRO. Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects. PLoS ONE 2014;9:e103934. https://doi.org/10.1371/journal.pone.0103934 DOI |
21 | Petrini J, Iung LHS, Rodriguez MAP, et al. Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions. J Anim Breed Genet 2016;133:384-95. DOI |
22 | Gao H, Christensen OF, Madsen P, et al. Comparison on genomic predictions using three GBLUP methods and two singlestep blending methods in the Nordic Holstein population. Genet Sel Evol 2012;44:8. https://doi.org/10.1186/1297-9686-44-8 DOI |
23 | Okeno TO, Kosgey IS, Kahi AK. Genetic evaluation of breeding strategies for improvement of dairy cattle in Kenya. Trop Anim Health Prod 2010:42;1073-9. https://doi.org/10.1007/s11250-010-9528-z DOI |
24 | Wiggans GR, Cole JB, Hubbard SM, Sonstegard SM. Genomic selection in dairy cattle: the USDA experience. Annu Rev Anim Biosci 2017;5:309-27. https://doi.org/10.1146/annurevanimal-021815-111422 DOI |
25 | Mokhtari MS, Moradi SM, Nejati JA, Rosa GJM. Genetic relationship between heifers and cows fertility and milk yield traits in first-parity Iranian Holstein dairy cows. Livest Sci 2015;182:76-82. https://doi.org/10.1016/j.livsci.2015.10.026 DOI |
26 | Pritchard T, Coffey M, Mrode R, Wall E. Genetic parameters for production, health, fertility and longevity traits in dairy cows. Animal 2013;7:34-46. https://doi.org/10.1017/S1751731112001401 DOI |
27 | Sneddon NW, Lopez-Villalobos N, Davis SR, Hickson RE, Shalloo L. Genetic parameters for milk components including lactose from test day records in the New Zealand dairy herd. New Zealand J Agric Res 2015;58:97-107. https://doi.org/10.1080/00288233.2014.978482 DOI |
28 | Szyda J, Zukowski K, Kaminski S, Zarnecki A. Testing different single nucleotide polymorphism selection strategies for prediction of genomic breeding values in dairy cattle based on low density panels. Czech J Anim Sci 2013;58:136-45. DOI |
29 | VanRaden PM, Tooker ME, O'Connell JR, Cole JB, Bickhart DM. Selecting sequence variants to improve genomic predictions for dairy cattle. Genet Sel Eval 2017;49:32. https://doi.org/10.1186/s12711-017-0307-4 DOI |
30 | Elzo MA, Mateescu RG, Johnson DD, et al. Genomic-polygenic and polygenic predictions for nine ultrasound and carcass traits in Angus-Brahman multibreed cattle using three sets of genotypes. Livest Sci 2017;202:58-66. https://doi.org/10.1016/j.livsci.2017.05.027 DOI |