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Research article - Peer-reviewed, 2022

A transcriptome-based association study of growth, wood quality, and oleoresin traits in a slash pine breeding population

Ding, Xianyin; Diao, Shu; Luan, Qifu; Wu, Harry; Zhang, Yini; Jiang, Jingmin

Abstract

Slash pine (Pinus elliottii Engelm.) is an important timber and resin species in the United States, China, Brazil and other countries. Understanding the genetic basis of these traits will accelerate its breeding progress. We carried out a genome-wide association study (GWAS), transcriptome-wide association study (TWAS) and weighted gene co-expression network analysis (WGCNA) for growth, wood quality, and oleoresin traits using 240 unrelated individuals from a Chinese slash pine breeding population. We developed high quality 53,229 single nucleotide polymorphisms (SNPs). Our analysis reveals three main results: (1) the Chinese breeding population can be divided into three genetic groups with a mean inbreeding coefficient of 0.137; (2) 32 SNPs significantly were associated with growth and oleoresin traits, accounting for the phenotypic variance ranging from 12.3% to 21.8% and from 10.6% to 16.7%, respectively; and (3) six genes encoding PeTLP, PeAP2/ERF, PePUP9, PeSLP, PeHSP, and PeOCT1 proteins were identified and validated by quantitative real time polymerase chain reaction for their association with growth and oleoresin traits. These results could be useful for tree breeding and functional studies in advanced slash pine breeding program.

Published in

PLoS Genetics
2022, volume: 18, number: 2, article number: e1010017

Authors' information

Ding, Xianyin
Chinese Academy of Forestry
Diao, Shu
Chinese Academy of Forestry
Luan, Qifu
Chinese Academy of Forestry
Swedish University of Agricultural Sciences, Department of Forest Genetics and Plant Physiology
Commonwealth Scientific and Industrial Research Organisation (CSIRO)
National Forestry and Grassland Engineering Technology Research Center of Exotic Pine Cultivation
Zhang, Yini
Chinese Academy of Forestry
Jiang, Jingmin
Chinese Academy of Forestry

UKÄ Subject classification

Forest Science

Publication Identifiers

DOI: https://doi.org/10.1371/journal.pgen.1010017

URI (permanent link to this page)

https://res.slu.se/id/publ/118834