• 제목/요약/키워드: Missing Heritability Problem

검색결과 4건 처리시간 0.015초

Genome-wide Association Study (GWAS) and Its Application for Improving the Genomic Estimated Breeding Values (GEBV) of the Berkshire Pork Quality Traits

  • Lee, Young-Sup;Jeong, Hyeonsoo;Taye, Mengistie;Kim, Hyeon Jeong;Ka, Sojeong;Ryu, Youn-Chul;Cho, Seoae
    • Asian-Australasian Journal of Animal Sciences
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    • 제28권11호
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    • pp.1551-1557
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    • 2015
  • The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single nucleotide polymorphisms (SNPs) were obtained using GWAS results with p value <0.01. BLUP analyzed with significant SNPs was much more accurate than that with total genotyped SNPs in terms of narrow-sense heritability. It implies that genomic estimated breeding values (GEBVs) of pork quality traits can be calculated by BLUP via GWAS. The GWAS model was the linear regression using PLINK and BLUP model was the G-BLUP and SNP-GBLUP. The SNP-GBLUP uses SNP-SNP relationship matrix. The BLUP analysis using preprocessing of GWAS can be one of the possible alternatives of solving the missing heritability problem and it can provide alternative BLUP method which can find more accurate GEBVs.

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method

  • Lee, Seungyeoun;Son, Donghee;Yu, Wenbao;Park, Taesung
    • Genomics & Informatics
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    • 제14권4호
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    • pp.166-172
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    • 2016
  • Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

Heritability Estimated Using 50K SNPs Indicates Missing Heritability Problem in Holstein Breeding

  • Shin, Donghyun;Park, Kyoung-Do;Ka, Sojoeng;Kim, Heebal;Cho, Kwang-hyeon
    • Genomics & Informatics
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    • 제13권4호
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    • pp.146-151
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    • 2015
  • Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip ($h^2_G$). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.

생존시간과 연관된 유전자 간의 교호작용에 관한 다중차원축소방법의 확장 (An extension of multifactor dimensionality reduction method for detecting gene-gene interactions with the survival time)

  • 오진석;이승연
    • Journal of the Korean Data and Information Science Society
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    • 제25권5호
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    • pp.1057-1067
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    • 2014
  • 인간게놈 프로젝트 이후 질병과 연관된 변이유전자를 탐색하기 위해 유전형질의 차이에 영향을 주는 단일 유전자를 중심으로 전장유전체 연관성 연구가 활발하게 진행되어왔다. 그러나 전장유전체 연관성 연구에서 접근한 단일유전자 분석방법에 한계점이 발견되면서 최근에는 다중유전자 분석방법이나 유전자-유전자간의 상호작용에 대한 연구들이 활발하게 진행 중이다. 이 중 다중차원축소방법은 유전자-유전자간의 상호작용의 연관성을 찾아내기 위하여 고차원을 일차원으로 축소하는 방법으로 이진형 반응변수를 기반으로 크게 활용되고 있다. 본 논문에서는 이 방법을 생존시간으로 확장하여 생존시간과 연관된 유전자-유전자간의 상호작용을 찾아내는 방법을 제안하고자 한다. 구체적으로 가속화 고장시간 회귀모형 하에서 표준화잔차 스코어를 분류기준으로 사용하여 다중차원축소방법을 적용하는 방법으로 AFT-MDR이라고 지칭하였다. 시뮬레이션 연구를 통하여 기존에 제안된 Surv-MDR과 Cox-MDR과의 검정력을 비교하였으며 국내의 백혈병환자 자료분석에 적용하였다. 시뮬레이션 결과로부터 AFT-MDR은 유전율이 높을수록 검정력이 커지며 회귀모형에 기반하여 공변량의 효과를 고려할 수 있다는 장점이 있으나 센서링 비율이 높아지면서 검정력이 매우 떨어진다는 단점이 발견되었다. 따라서 이를 보완하기 위한 추후연구의 필요성이 요구된다.