title: Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology.
abstract: Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.|Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
authors.forename: Shi-Bo
authors.initials: SB
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Jian-Ying
authors.initials: JY
authors.lastname: Feng
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Wen-Long
authors.initials: WL
authors.lastname: Ren
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Huang
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Zhou
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Yang-Jun
authors.initials: YJ
authors.lastname: Wen
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Agriculture, Policy and Development, University of Reading, Reading RG6 6AR, United Kingdom.
authors.forename: Jim M
authors.initials: JM
authors.lastname: Dunwell
authors.affiliation: Department of Botany and Plant Science, University of California, Riverside 20705, USA.
authors.forename: Shizhong
authors.initials: S
authors.lastname: Xu
authors.affiliation: State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.|Statistical Genomics Lab, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
authors.forename: Yuan-Ming
authors.initials: YM
authors.lastname: Zhang
mesh_terms: D017360:Arabidopsis / Q000235:genetics; D003198:Computer Simulation; D017343:Genes, Plant; D056426:Genetic Loci; D055106:Genome-Wide Association Study / Q000379:methods; D016014:Linear Models; D020641:Polymorphism, Single Nucleotide; D019655:Quantitative Trait, Heritable; D012372:ROC Curve; D015203:Reproducibility of Results