Genome‐wide association implicates numerous genes underlying ecological trait variation in natural populations of Populus trichocarpa. Issue 2 (22nd April 2014)

• Record Type: Journal Article
• Authors: McKown, Athena D.; Klápště, Jaroslav; Guy, Robert D.; Geraldes, Armando; Porth, Ilga; Hannemann, Jan; Friedmann, Michael; Muchero, Wellington; Tuskan, Gerald A.; Ehlting, Jürgen; Cronk, Quentin C. B.; El‐Kassaby, Yousry A.; Mansfield, Shawn D.; Douglas, Carl J.
• Is Part Of: New phytologist. Volume 203:Issue 2(2014)
• Page Start: 535
• Page End: 553
• Publication Date: 2014-04-22
• Subjects: biomass -- ecophysiology -- genome‐wide association study (GWAS) -- phenology -- pleiotropy -- poplar -- single nucleotide polymorphisms (SNP) array -- Unified Mixed Model; Botany -- Periodicals; 580
• DOI: 10.1111/nph.12815
• Languages: English
• ISSNs: 0028-646X

Abstract

Summary: In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood ( Populus trichocarpa ) from much of its range in western North America. Extensive data from large‐scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome‐wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni‐corrected threshold ( P < 1.7 × 10 −6 ). Markers were found across 19 chromosomes, explained 1–13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.