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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 (SNPs) 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 PgNAC8, 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.

Original publication

DOI

10.1111/nph.13762

Type

Journal article

Journal

New Phytol

Publication Date

04/2016

Volume

210

Pages

240 - 255

Keywords

association genetics, co-expression network, quantitative genetics, white spruce (Picea glauca), wood traits, Gene Expression Profiling, Gene Expression Regulation, Plant, Gene Ontology, Gene Regulatory Networks, Genes, Plant, Genetic Association Studies, Molecular Sequence Annotation, Phenotype, Picea, Polymorphism, Single Nucleotide, Protein Domains, Quantitative Trait, Heritable, Wood, Xylem