2015 journal article
Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus (QTL) analysis and association studies
NEW PHYTOLOGIST, 209(3), 1067–1082.
author keywords: association genetics; epistatic networks; gene mapping; Populus reference genome; quantitative trait locus (QTL) dissection; transcriptome analysis
MeSH headings : Biomass; Chromosome Mapping; Epistasis, Genetic; Gene Expression Regulation, Plant; Gene Regulatory Networks; Genes, Plant; Genetic Association Studies; Genetic Linkage; Genome-Wide Association Study; Linkage Disequilibrium / genetics; Models, Genetic; Molecular Sequence Annotation; Plant Stems / genetics; Plant Stems / growth & development; Polymorphism, Single Nucleotide / genetics; Populus / genetics; Populus / growth & development; Quantitative Trait Loci / genetics; Quantitative Trait, Heritable; Species Specificity
TL;DR:
This study uses 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 of potential QTLs for growth traits in a Populus linkage population and a natural population.
(via Semantic Scholar)
open access via nph.onlinelibrary.wiley.com (publisher PDF)
UN Sustainable Development Goal Categories
2. Zero Hunger
(Web of Science)
13. Climate Action
(Web of Science)
15. Life on Land
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
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 QTLs for growth traits in a Populus linkage population (1200 progeny) and a natural population (435 individuals). Seventeen QTLs 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 (SNPs)) were selected from the segmental homology regions (SHRs) of 13 QTLs. Using multi‐gene association models, we observed 202 significant SNPs in 63 promising genes from 10 QTLs (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 QTLs. 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.