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Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle.
BMC Genet. 2015 Nov 19; 16:134.BG

Abstract

BACKGROUND

Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data.

METHODS

In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design.

RESULTS

The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV.

CONCLUSION

The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured using denser SNPs and the prediction model accounted for MAF, but a large sample size is needed to increase the accuracy of GEBV under all QTL MAF categories.

Authors+Show Affiliations

National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. y0uemoto@nlbc.go.jp.National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. s1sasaki@nlbc.go.jp.National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. t0kojima@nlbc.go.jp.Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Nishigo, Fukushima, 961-8511, Japan. kazusugi@siag.or.jp.National Livestock Breeding Center, Nishigo, Fukushima, 961-8511, Japan. t4watanb@nlbc.go.jp.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26586567

Citation

Uemoto, Yoshinobu, et al. "Impact of QTL Minor Allele Frequency On Genomic Evaluation Using Real Genotype Data and Simulated Phenotypes in Japanese Black Cattle." BMC Genetics, vol. 16, 2015, p. 134.
Uemoto Y, Sasaki S, Kojima T, et al. Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle. BMC Genet. 2015;16:134.
Uemoto, Y., Sasaki, S., Kojima, T., Sugimoto, Y., & Watanabe, T. (2015). Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle. BMC Genetics, 16, 134. https://doi.org/10.1186/s12863-015-0287-8
Uemoto Y, et al. Impact of QTL Minor Allele Frequency On Genomic Evaluation Using Real Genotype Data and Simulated Phenotypes in Japanese Black Cattle. BMC Genet. 2015 Nov 19;16:134. PubMed PMID: 26586567.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle. AU - Uemoto,Yoshinobu, AU - Sasaki,Shinji, AU - Kojima,Takatoshi, AU - Sugimoto,Yoshikazu, AU - Watanabe,Toshio, Y1 - 2015/11/19/ PY - 2015/07/29/received PY - 2015/10/27/accepted PY - 2015/11/21/entrez PY - 2015/11/21/pubmed PY - 2016/6/2/medline SP - 134 EP - 134 JF - BMC genetics JO - BMC Genet. VL - 16 N2 - BACKGROUND: Genetic variance that is not captured by single nucleotide polymorphisms (SNPs) is due to imperfect linkage disequilibrium (LD) between SNPs and quantitative trait loci (QTLs), and the extent of LD between SNPs and QTLs depends on different minor allele frequencies (MAF) between them. To evaluate the impact of MAF of QTLs on genomic evaluation, we performed a simulation study using real cattle genotype data. METHODS: In total, 1368 Japanese Black cattle and 592,034 SNPs (Illumina BovineHD BeadChip) were used. We simulated phenotypes using real genotypes under different scenarios, varying the MAF categories, QTL heritability, number of QTLs, and distribution of QTL effect. After generating true breeding values and phenotypes, QTL heritability was estimated and the prediction accuracy of genomic estimated breeding value (GEBV) was assessed under different SNP densities, prediction models, and population size by a reference-test validation design. RESULTS: The extent of LD between SNPs and QTLs in this population was higher in the QTLs with high MAF than in those with low MAF. The effect of MAF of QTLs depended on the genetic architecture, evaluation strategy, and population size in genomic evaluation. In genetic architecture, genomic evaluation was affected by the MAF of QTLs combined with the QTL heritability and the distribution of QTL effect. The number of QTL was not affected on genomic evaluation if the number of QTL was more than 50. In the evaluation strategy, we showed that different SNP densities and prediction models affect the heritability estimation and genomic prediction and that this depends on the MAF of QTLs. In addition, accurate QTL heritability and GEBV were obtained using denser SNP information and the prediction model accounted for the SNPs with low and high MAFs. In population size, a large sample size is needed to increase the accuracy of GEBV. CONCLUSION: The MAF of QTL had an impact on heritability estimation and prediction accuracy. Most genetic variance can be captured using denser SNPs and the prediction model accounted for MAF, but a large sample size is needed to increase the accuracy of GEBV under all QTL MAF categories. SN - 1471-2156 UR - https://www.unboundmedicine.com/medline/citation/26586567/Impact_of_QTL_minor_allele_frequency_on_genomic_evaluation_using_real_genotype_data_and_simulated_phenotypes_in_Japanese_Black_cattle_ L2 - https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-015-0287-8 DB - PRIME DP - Unbound Medicine ER -