e4029398-ec72-4498-9909-2d4b72407ed4
Combining QTL mapping and transcriptomics to decipher the genetic architecture of phenolic compounds metabolism in the conifer white spruce
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) progeny for two years. QTL detection was performed 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 a subset of 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 promising step towards resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.
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) progeny for two years. QTL detection was performed 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 a subset of 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 promising step towards resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.