Combining QTL mapping and transcriptomics to decipher the genetic
architecture of phenolic compounds metabolism in a conifer
Abstract
Conifer forests worldwide are becoming increasingly vulnerable to the
effects of climate change. Although phenolic compounds (PCs) have been
shown to be modulated by biotic and abiotic stresses, the genetic basis
underlying the variation in their basal composition remains poorly
documented in conifers. We used QTL mapping and RNA-Seq to explore the
complex polygenic network underlying the constitutive production of PCs
in white spruce (Picea glauca) full-sib progeny for two years. QTL
detection was conducted for nine PCs and differentially expressed genes
(DEGs) were identified between individuals with high and low PC contents
for five PCs exhibiting stable QTLs across time. A total of 17 QTLs were
detected for eight metabolites, including one major QTL explaining up to
91.3% of the neolignan-2 variance. The RNA-Seq analysis highlighted 50
DEGs associated with phenylpropanoid biosynthesis, several key
transcription factors, and 137 genes showing opposite expression
patterns in individuals with high levels of the flavonoids gallocatechin
and taxifolin glucoside. A total of 19 DEGs co-localised with QTLs. Our
findings represent a significant step towards resolving the genomic
architecture of PC production in spruce and enhancing the functional
characterization of genes and transcriptional networks responsible for
differences in constitutive production of PCs in conifers.