Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce

Téléchargements

Téléchargements par mois depuis la dernière année

Lamara, Mebarek, Raherison, Elie, Lenz, Patrick, Beaulieu, Jean, Bousquet, Jean et MacKay, John (2016). Genetic architecture of wood properties based on association analysis and co-expression networks in white spruce. New Phytologist , 210 (1). pp. 240-255. doi:10.1111/nph.13762 Repéré dans Depositum à https://depositum.uqat.ca/id/eprint/1085

[thumbnail of lamaraetal_nph_2016.pdf]
Prévisualisation
PDF
Télécharger (759kB) | Prévisualisation

Résumé

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.

Type de document: Article
Informations complémentaires: Licence d'utilisation : CC-BY 4.0
Mots-clés libres: Association genetics; Co-expression network; Quantitative genetics; White spruce (Picea glauca); Wood traits
Divisions: Forêts
Date de dépôt: 01 juin 2020 16:00
Dernière modification: 01 juin 2020 16:00
URI: https://depositum.uqat.ca/id/eprint/1085

Gestion Actions (Identification requise)

Dernière vérification avant le dépôt Dernière vérification avant le dépôt