Resin biosynthesis in conifer is a complex process, controlled by multiple quantitative trait loci (QTLs). Quantifying resin components is traditionally expensive and labor-intensive. In this study, we employed near infrared (NIR) spectroscopy to quantify resin components in Slash pine using 240 genotypes. A partial least squares regression model was applied to identify the characteristic bands responsed to variations in Alpha and Beta pinene levels. Genome-wide association study (GWAS) identified 35 significant SNPs involved in terpenoid precursor biosynthesis, transport, modification, and abiotic stress resistance. eQTL mapping co-localized four candidate genes: PeCHITINASE (c166891.graph_c0), PeGLYCOSYLTRANSFERASE (c160167.graph_c0), PeASIL2 (c324347.graph_c0), and PeERF168 (c311225.graph_c0). Mutations in two SNPs increased the expression of PeASIL2 and PeERF168, leading to higher levels of Alpha and Beta pinene. Further heterologous transformation experiments confirmed that the PeERF168 gene regulates the concentration of both monoterpenes and sesquiterpenes. These findings provide valuable insights into the molecular mechanisms of resin biosynthesis, facilitating cost-effective gene discovery through high-throughput resin component detection and genomics integration, with substantial potential to enhance molecular breeding and improve resin yield and quality.
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http://dx.doi.org/10.1016/j.ijbiomac.2025.139728 | DOI Listing |
Int J Biol Macromol
January 2025
Umeå Plant Science Centre, Department Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-90183 Umeå, Sweden.
Resin biosynthesis in conifer is a complex process, controlled by multiple quantitative trait loci (QTLs). Quantifying resin components is traditionally expensive and labor-intensive. In this study, we employed near infrared (NIR) spectroscopy to quantify resin components in Slash pine using 240 genotypes.
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