Impact of QTL minor allele frequency on genomic evaluation using real genotype data and simulated phenotypes in Japanese Black cattle

BMC Genetics

Toshio Watanabe²  Yoshikazu Sugimoto¹  Takatoshi Kojima²  Shinji Sasaki²  Yoshinobu Uemoto² 

[1] Shirakawa Institute of Animal Genetics, Japan Livestock Technology Association, Nishigo 961-8511, Fukushima, Japan;National Livestock Breeding Center, Nishigo 961-8511, Fukushima, Japan

关键词: Simulation study;    Minor allele frequency;    Japanese Black cattle;    Heritability estimation;    Genomic prediction;    BovineHD;   

Others  :  1233826
DOI  :  10.1186/s12863-015-0287-8

 received in 2015-07-29, accepted in 2015-10-27,  发布年份 2015

【 摘 要 】

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.

【 授权许可】

   
2015 Uemoto et al.

【 图 表 】

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