Literature DB >> 26499329

Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus (QTL) analysis and association studies.

Qingzhang Du1,2, Chenrui Gong1,2, Qingshi Wang1,2, Daling Zhou1,2, Haijiao Yang1,2, Wei Pan1,2, Bailian Li1,2,3, Deqiang Zhang1,2.   

Abstract

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.
© 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Keywords:  Populus reference genome; association genetics; epistatic networks; gene mapping; quantitative trait locus (QTL) dissection; transcriptome analysis

Mesh:

Year:  2015        PMID: 26499329     DOI: 10.1111/nph.13695

Source DB:  PubMed          Journal:  New Phytol        ISSN: 0028-646X            Impact factor:   10.151


  24 in total

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