Accuracy of polygenic and genomic predictions for milk production traits in a Thai multibreed dairy cattle population

Name: Bodin Wongpom

LCSH: Kasetsart University -- Dissertations. Ph.D. (Animal SCience) 2018

Classification :.LCCS: SF208

LCSH: Kasetsart University. -- Department of Animal Science -- Dissertations

LCSH: Dairy cattle -- Genetics

LCSH: Dairy cattle -- Breeding

Abstract: The objectives of this study were 1) to estimate genetic parameters for milk yield (MY), fat yield (FY), and fat percentage (FP), 2) to estimate variance ratios and to compare animal rankings of genomic-polygenic (GP), genomic (G), and polygenic (P) models for MY and FY, and 3) to compare the estimates of variance components, genetic parameters, accuracies of prediction, and rankings of genomic-polygenic animal estimated breeding value (EBV) for MY and FY in the Thai multibreed dairy population computed using five sets of SNPs from GeneSeek Genomic Profile (GGP) 80k chip. The dataset consisted of pedigree and phenotypes of 8,361 first lactation cows calved during 1989 to 2014. Models and assumptions were defined and used differently based on the objectives. Genotyped information from 2,661 animals with GGP9K (n = 1,412), GGP20K (n = 570), GGP26K (n = 540) were imputed to GGP80K (n = 139). After imputation, five SNP sets were constructed; the complete (SNP100), top 75% (SNP75), top 50% (SNP50), top 25% (SNP25), and top 5% (SNP5) sets. The heritability estimates using P model were 0.22 ± 0.06 for MY, 0.17 ± 0.06 for FY and 0.24 ± 0.07 for FP. Genetic correlations form P model were 0.47 ± 0.16 for MY and FY, -0.30 ± 0.20 for MY and FP, and 0.30 ± 0.21 for FY and FP. However, the heritability estimates from GP model (0.38 for MY; 0.40 for FY) were higher than P model (0.28 for MY and 0.30 for FY). Fraction of the additive genetic variance explained by the SNP markers were 50% for MY, and 48% for FY. Rank correlations between GP and G models were the highest for both MY and FY (0.99; P<0.01), while rank correlations between G and P models were the lowest for MY (0.89; P<0.01) and FY (0.73; P<0.01). These results indicated that the accuracy of prediction and selection of Thai dairy population would be improved using GP model. The estimates of additive genetic variances and heritability for MY and FY obtained from GP models were higher for SNP25, SNP50 and SNP75 than SNP100, except SNP5 subsets. Prediction accuracies for MY and FY were higher for SNP25 than SNP5, SNP50, SNP75 and SNP100. All rank correlations between SNP100 and other SNP subsets were above 0.98 for both traits, except for the correlation between SNP100 and SNP5 (0.93 for MY; 0.92 for FY). These results indicated that genotyping animals with an SNP25 dedicated chip would be a suitable alternative way to maintain genotyping costs low, while speeding up genetic progress for MY and FY in Thai multibreed dairy cattle population.

Kasetsart University. Office of the University Library

Address: Bangkok

Email: tdckulib@ku.ac.th

Name: Skorn Koonawootrittriron

Role: Thesis Advisor

Name: Mauricio A. Elzo

Role: Thesis CO-Advisor

Name: Thanathip Suwanasopee

Role: Thesis CO-Advisor

Created: 2018

Modified: 2025-07-01

Issued: 2025-07-01

วิทยานิพนธ์/Thesis

application/pdf

URL: https://www.lib.ku.ac.th/KUthesis/2561/bodin-won-all.pdf

CallNumber: SF208 .B63

eng

DegreeName: Doctor of Philosophy

Level: Doctoral Degree

Descipline: Animal Science

Grantor: Kasetsart University

©copyrights Kasetsart University

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