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Title: Multitrait genome–wide association analysis of Populus trichocarpa identifies key polymorphisms controlling morphological and physiological traits

Journal Article · · New Phytologist
DOI: https://doi.org/10.1111/nph.15777 · OSTI ID:1545212
ORCiD logo [1];  [1];  [2];  [3];  [1];  [2];  [4];  [4];  [3];  [5];  [3];  [4]; ORCiD logo [2]; ORCiD logo [2];  [3]; ORCiD logo [2];  [6]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [1]
  1. West Virginia Univ., Morgantown, WV (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Univ. of Georgia, Athens, GA (United States)
  4. ArborGen, Inc., Ridgeville, SC (United States)
  5. Portland State Univ., Portland, OR (United States)
  6. Oregon State Univ., Corvallis, OR (United States)

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 (H2) 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. Furthermore, 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.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE
Grant/Contract Number:
AC05-00OR22725; AC05‐00OR22725
OSTI ID:
1545212
Alternate ID(s):
OSTI ID: 1505666
Journal Information:
New Phytologist, Vol. 223, Issue 1; ISSN 0028-646X
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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