Multitrait genome‐wide association analysis of Populus trichocarpa identifies key polymorphisms controlling morphological and physiological traits. Issue 1 (8th April 2019)

• Record Type: Journal Article
• Authors: Chhetri, Hari B.; Macaya‐Sanz, David; Kainer, David; Biswal, Ajaya K.; Evans, Luke M.; Chen, Jin‐Gui; Collins, Cassandra; Hunt, Kimberly; Mohanty, Sushree S.; Rosenstiel, Todd; Ryno, David; Winkeler, Kim; Yang, Xiaohan; Jacobson, Daniel; Mohnen, Debra; Muchero, Wellington; Strauss, Steven H.; Tschaplinski, Timothy J.; Tuskan, Gerald A.; DiFazio, Stephen P.
• Is Part Of: New phytologist. Volume 223:Issue 1(2019)
• Page Start: 293
• Page End: 309
• Publication Date: 2019-04-08
• Subjects: adaptation -- drought tolerance -- genome‐wide association studies (GWAS) -- leaf morphology -- pleiotropy -- Populus; Botany -- Periodicals; 580
• DOI: 10.1111/nph.15777
• Languages: English
• ISSNs: 0028-646X

Abstract

Summary: Genome‐wide association studies (GWAS) have great promise for identifying the loci that contribute to adaptive variation, but the complex genetic architecture of many quantitative traits presents a substantial challenge. We measured 14 morphological and physiological traits and identified single nucleotide polymorphism (SNP)‐phenotype associations in a Populus trichocarpa population distributed from California, USA to British Columbia, Canada. We used whole‐genome resequencing data of 882 trees with more than 6.78 million SNPs, coupled with multitrait association to detect polymorphisms with potentially pleiotropic effects. Candidate genes were validated with functional data. Broad‐sense heritability ( H 2 ) ranged from 0.30 to 0.56 for morphological traits and 0.08 to 0.36 for physiological traits. In total, 4 and 20 gene models were detected using the single‐trait and multitrait association methods, respectively. Several of these associations were corroborated by additional lines of evidence, including co‐expression networks, metabolite analyses, and direct confirmation of gene function through RNAi. Multitrait association identified many more significant associations than single‐trait association, potentially revealing pleiotropic effects of individual genes. This approach can be particularly useful for challenging physiological traits such as water‐use efficiency or complex traits such as leaf morphology, for which we were able to identify credible candidate genes by combining multitrait association with gene co‐expression and co‐methylation data.