2010 journal article
Natural variation in expression of genes involved in xylem development in loblolly pine (Pinus taeda L.)
TREE GENETICS & GENOMES, 7(1), 193–206.
author keywords: Gene expression; Natural variation; Pinus taeda L; Xylem
TL;DR:
Genes encoding lignin biosynthetic enzymes and arabinogalactan proteins were more variable than those encoding cellulose synthases or those involved in signal transduction, and transcription factors that may be key regulators of xylem development in pine were identified.
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open access via link.springer.com (publisher PDF)
UN Sustainable Development Goal Categories
15. Life on Land
(OpenAlex)
Source: Web Of Science
Added: August 6, 2018
Gene expression analyses using native populations can contribute to the understanding of plant development and adaptation in multiple ways. These include the identification of candidate genes and genetic polymorphisms affecting expression and phenotypic traits and characterization of transcriptional networks. We analyzed the expression of 111 genes with probable roles in xylem/wood development in a population of loblolly pine (Pinus taeda L.) covering much of the natural range. Loblolly pine is one of the most commercially important forest tree species in the United States, and the discovery of genes and alleles contributing to desirable wood properties would be valuable. Of the 111 genes analyzed using quantitative reverse transcription–polymerase chain reaction, there were significant differences in gene expression between clones for 106 genes. Genes encoding lignin biosynthetic enzymes and arabinogalactan proteins were more variable than those encoding cellulose synthases or those involved in signal transduction. Several groups of genes with related functions form clusters. A network analysis identified transcription factors that may be key regulators of xylem development in pine. Secondary wall-associated NAC domain protein 1 (SND1) in particular appears to be involved in the regulation of many other genes. The cluster analysis using clones did not result in discrete populations but did identify some expression differences between regions. In the future, the gene expression data will be used for association analyses and promoter studies to understand how these gene expression differences are associated with specific genetic polymorphisms in other genes and promoters.