Nucleotide diversity in lignification genes and QTNs for lignin quality in a multi-parental population of Eucalyptus urophylla

Eric Mandrou,Frédéric Mortier,Christophe Plomion,Marie Denis,Franck Salin,Jean-Marc Gion

doi:10.1007/s11295-014-0760-y

Abstract

Lignin is a major chemical compound of wood and one of the most abundant organic biopolymers on earth. It accumulates in the secondary cell wall of xylem cells and is a major target for tree breeders because of its foreseen role in the emerging bioeconomy. In this study, we paved the way toward an accelerated domestication of a widely grown tree species, Eucalyptus urophylla, by molecular breeding. To this end, we first described the pattern of nucleotide variation occurring at seven structural and regulatory genes of the lignin biosynthesis pathway and found high levels of average nucleotide and haplotype diversity per gene (π = 0.0065 and Hd = 0.853). Then, taking advantage of a pre-existing factorial mating design, a candidate-gene-based quantitative trait locus (QTL) detection strategy was used to compare the variation of lignin quality (syringyl by guaiacyl ratio (S/G)) with the nucleotidic variability in these seven genes in 304 genotypes belonging to 33 connected full-sib families. Two genes, encoding cinnamoyl-CoA reductase (CCR) and a Rho-like GTPase (ROP1), were shown to be linked to the variation of S/G through different single and multi-locus single-nucleotide polymorphism (SNP)- and haplotype-based association methods. Providing that relevant candidate genes are selected and their patterns of nucleotide diversity is accurately described, we showed that quantitative trait nucleotides (QTNs) can be detected taking advantage of pre-existing field experiments and trait measurements gathered in the framework of a forest tree breeding program.

Highlights

Surveying structural variations (i.e., single-nucleotide polymorphisms (SNPs), deletion-insertion polymorphisms (DIPs), copy-number variations (CNVs), duplications, and other rearrangements) in whole genomes or specific genomic regions is currently a key step in research undertaken to decipher the genetic basis of phenotypic variation and to identify causative variants in complex evolutionary processes such as speciation, selection, and local adaptation (Barton and Keightley 2002)
Smaller scale studies aiming to describe the landscape of nucleotide variation from a limited number of loci or subgenic regions are still appropriate for peculiar applications, e.g., genetic identification, population structure analysis, and management of breeding populations, as well as for the analysis of genes involved in specific biosynthesis pathways or belonging to specific gene families
The average nucleotide diversity of these seven genes was 0.0065, with values ranging from 0.0131 in cinnamoylCoA reductase (CCR) to 0.0027 in caffeate O-methyltransferase 2 (COMT2). This average was lower in nonsynonymous positions (0.0016) with estimated values ranging from 0.0024 in COMT2 to 0.0008 in CAD2 and higher in silent positions (0.0094) with values ranging from 0.0173 in CCR to 0.0029 in COMT2

Summary

Introduction

Surveying structural variations (i.e., single-nucleotide polymorphisms (SNPs), deletion-insertion polymorphisms (DIPs), copy-number variations (CNVs), duplications, and other rearrangements) in whole genomes or specific genomic regions is currently a key step in research undertaken to decipher the genetic basis of phenotypic variation and to identify causative variants in complex evolutionary processes such as speciation, selection, and local adaptation (Barton and Keightley 2002). The main objective of these studies was to understand evolutionary processes (demographic history, imprint of natural selection) underlying patterns of nucleotide variation They revealed high levels of genetic variation and rapid decay of linkage disequilibrium, declining to negligible levels in less than 500 bp (Brown et al 2004; Ingvarsson 2005; Heuertz et al 2006), as expected in allogamous species with large population sizes and efficient gene flow. These studies provided the first data to conduct association mapping in trees which, given the mating characteristics and life history of those species, was believed to have great potential to accurately map mutations that contribute to trait variation (Neale and Savolainen 2004; Neale and Ingvarsson 2008). Because of the rather small populations generally used to estimate QTL effects (in general between 100 and 300 genotypes), percentages of explained variance are certainly biased upward, and the power to detect associations is extremely low (Lepoittevin et al 2012)

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