Premium
Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus ( QTL ) analysis and association studies
Author(s) -
Du Qingzhang,
Gong Chenrui,
Wang Qingshi,
Zhou Daling,
Yang Haijiao,
Pan Wei,
Li Bailian,
Zhang Deqiang
Publication year - 2016
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.13695
Subject(s) - quantitative trait locus , biology , family based qtl mapping , genetics , linkage disequilibrium , genetic architecture , association mapping , epistasis , single nucleotide polymorphism , genetic linkage , population , locus (genetics) , inclusive composite interval mapping , genetic association , gene , gene mapping , genotype , chromosome , demography , sociology
Summary Deciphering the genetic architecture underlying polygenic traits in perennial species can inform molecular marker‐assisted breeding. Recent advances in high‐throughput sequencing have enabled strategies that integrate linkage–linkage disequilibrium ( LD ) mapping in Populus . We used an integrated method of quantitative trait locus ( QTL ) dissection with a high‐resolution linkage map and multi‐gene association mapping to decipher the nature of genetic architecture (additive, dominant, and epistatic effects) of potential QTL s for growth traits in a Populus linkage population (1200 progeny) and a natural population (435 individuals). Seventeen QTL s for tree height, diameter at breast height, and stem volume mapped to 11 linkage groups (logarithm of odds ( LOD ) ≥ 2.5), and explained 2.7–18.5% of the phenotypic variance. After comparative mapping and transcriptome analysis, 187 expressed genes (10 046 common single nucleotide polymorphisms ( SNP s)) were selected from the segmental homology regions ( SHR s) of 13 QTL s. Using multi‐gene association models, we observed 202 significant SNP s in 63 promising genes from 10 QTL s ( P ≤ 0.0001; FDR ≤ 0.10) that exhibited reproducible associations with additive/dominant effects, and further determined 11 top‐ranked genes tightly linked to the QTL s. Epistasis analysis uncovered a uniquely interconnected gene–gene network for each trait. This study opens up opportunities to uncover the causal networks of interacting genes in plants using an integrated linkage– LD mapping approach.