Methodological implementation of mixed linear models in multi-locus genome-wide association studies.
The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P-values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS.
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
Yang-Jun
YJ
Wen
Applied Science, University of British Columbia, Columbia, Canada.
Hanwen
H
Zhang
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
Yuan-Li
YL
Ni
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
Bo
B
Huang
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
Jin
J
Zhang
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.
Jian-Ying
JY
Feng
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China.
Shi-Bo
SB
Wang
School of Agriculture, Policy and Development, University of Reading, Berkshire, UK.
Jim M
JM
Dunwell
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China.|College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China.
Yuan-Ming
YM
Zhang
Public Health Sciences and Statistics and Center for Statistical Genetics, Pennsylvania State University, Hershey, PA, USA.|Center for Computational Biology, Beijing Forestry University, Beijing, China.
Rongling
R
Wu
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics*; D029681:Arabidopsis Proteins / Q000235:genetics*; D001499:Bayes Theorem; D003198:Computer Simulation; D055106:Genome-Wide Association Study / Q000379:methods*; D016014:Linear Models; D008957:Models, Genetic; D020412:Multifactorial Inheritance; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide
D029681:Arabidopsis Proteins