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Genetic architecture of wood properties based on association analysis and co‐expression networks in white spruce
Author(s) -
Lamara Mebarek,
Raherison Elie,
Lenz Patrick,
Beaulieu Jean,
Bousquet Jean,
MacKay John
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.13762
Subject(s) - biology , genetic architecture , genetic association , trait , single nucleotide polymorphism , association mapping , gene , quantitative trait locus , computational biology , xylem , population , genetics , genome wide association study , expression quantitative trait loci , candidate gene , evolutionary biology , white (mutation) , botany , genotype , computer science , demography , sociology , programming language
Summary Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co‐expression networks. We tested single nucleotide polymorphisms ( SNP s) in 2652 candidate genes for statistical associations with wood density, stiffness, microfibril angle and ring width in a population of 1694 white spruce trees ( Picea glauca ). Associations mapping identified 229–292 genes per wood trait using a statistical significance level of P < 0.05 to maximize discovery. Over‐representation of genes associated for nearly all traits was found in a xylem preferential co‐expression group developed in independent experiments. A xylem co‐expression network was reconstructed with 180 wood associated genes and several known MYB and NAC regulators were identified as network hubs. The network revealed a link between the gene Pg NAC 8 , wood stiffness and microfibril angle, as well as considerable within‐season variation for both genetic control of wood traits and gene expression. Trait associations were distributed throughout the network suggesting complex interactions and pleiotropic effects. Our findings indicate that integration of association mapping and co‐expression networks enhances our understanding of complex wood traits.