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Extreme‐Phenotype Genome‐Wide Association Study (Xp‐Gwas): A Method For Identifying Trait‐Associated Variants By Sequencing Pools Of Individuals Selected From A Diversity Panel, Jinliang Yang, Haiying Jiang, Cheng-Ting Yeh, Jianming Yu, Jeffrey A. Jeddeloh, Dan Nettleton, Patrick S. Schnable
Extreme‐Phenotype Genome‐Wide Association Study (Xp‐Gwas): A Method For Identifying Trait‐Associated Variants By Sequencing Pools Of Individuals Selected From A Diversity Panel, Jinliang Yang, Haiying Jiang, Cheng-Ting Yeh, Jianming Yu, Jeffrey A. Jeddeloh, Dan Nettleton, Patrick S. Schnable
Dan Nettleton
Although approaches for performing genome‐wide association studies (GWAS) are well developed, conventional GWAS requires high‐density genotyping of large numbers of individuals from a diversity panel. Here we report a method for performing GWAS that does not require genotyping of large numbers of individuals. Instead XP‐GWAS (extreme‐phenotype GWAS) relies on genotyping pools of individuals from a diversity panel that have extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling discovery of associations between genetic variants and traits of interest. This method was evaluated in maize (Zea mays) using the well‐characterized kernel row number trait, which was …