Coordinated Genetic Regulation of Growth and Lignin Revealed by Quantitative Trait Locus Analysis of cDNA Microarray Data in an Interspecific Backcross of Eucalyptus

Author:

Kirst Matias1,Myburg Alexander A.1,De León José P.G.1,Kirst Mariana E.1,Scott Jay1,Sederoff Ronald1

Affiliation:

1. Forest Biotechnology Group (M.K., R.S.), Functional Genomics and Genetics Graduate Program (M.K.), Botany Department (M.E.K.), and Department of Wood and Paper Sciences (J.S.), North Carolina State University, Raleigh, North Carolina 27695; Department of Genetics, Forestry and Agricultural Biotechnology Institute, University of Pretoria, 0002, South Africa (A.A.M.); and Cía. Forestal Oriental S.

Abstract

Abstract Phenotypic, genotypic, and transcript level (microarray) data from an interspecific backcross population of Eucalyptus grandis and Eucalyptus globulus were integrated to dissect the genetic and metabolic network underlying growth variation. Transcript abundance, measured for 2,608 genes in the differentiating xylem of a 91 (E. grandis × E. globulus) × E. grandis backcross progeny was correlated with diameter variation, revealing coordinated down-regulation of genes encoding enzymes of the lignin biosynthesis and associated methylation pathways in fast growing individuals. Lignin analysis of wood samples confirmed the content and quality predicted by the transcript levels measured on the microarrays. Quantitative trait locus (QTL) analysis of transcript levels of lignin-related genes showed that their mRNA abundance is regulated by two genetic loci, demonstrating coordinated genetic control over lignin biosynthesis. These two loci colocalize with QTLs for growth, suggesting that the same genomic regions are regulating growth, and lignin content and composition in the progeny. Genetic mapping of the lignin genes revealed that most of the key biosynthetic genes do not colocalize with growth and transcript level QTLs, with the exception of the locus encoding the enzyme S-adenosylmethionine synthase. This study illustrates the power of integrating quantitative analysis of gene expression data and genetic map information to discover genetic and metabolic networks regulating complex biological traits.

Publisher

Oxford University Press (OUP)

Subject

Plant Science,Genetics,Physiology

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