Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, 37831, TN, USA.
Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, 37831, TN, USA.
New Phytol. 2024 Oct;244(2):603-617. doi: 10.1111/nph.20026. Epub 2024 Aug 21.
Our study utilized genome-wide association studies (GWAS) to link nucleotide variants to traits in Populus trichocarpa, a species with rapid linkage disequilibrium decay. The aim was to overcome the challenge of interpreting statistical associations at individual loci without sufficient biological context, which often leads to reliance solely on gene annotations from unrelated model organisms. We employed an integrative approach that included GWAS targeting multiple traits using three individual techniques for lignocellulose phenotyping, expression quantitative trait loci (eQTL) analysis to construct transcriptional regulatory networks around each candidate locus and co-expression analysis to provide biological context for these networks, using lignocellulose biosynthesis in Populus trichocarpa as a case study. The research identified three candidate genes potentially involved in lignocellulose formation, including one previously recognized gene (Potri.005G116800/VND1, a critical regulator of secondary cell wall formation) and two genes (Potri.012G130000/AtSAP9 and Potri.004G202900/BIC1) with newly identified putative roles in lignocellulose biosynthesis. Our integrative approach offers a framework for providing biological context to loci associated with trait variation, facilitating the discovery of new genes and regulatory networks.
我们的研究利用全基因组关联研究(GWAS)将核苷酸变体与毛白杨(Populus trichocarpa)的性状联系起来,毛白杨是一种具有快速连锁不平衡衰减的物种。目的是克服在没有足够生物学背景的情况下解释单个基因座统计关联的挑战,这通常导致仅仅依赖于来自无关模型生物的基因注释。我们采用了一种综合方法,包括使用三种个体技术针对多个性状进行 GWAS,用于木质纤维素表型的鉴定、表达数量性状位点(eQTL)分析,以构建每个候选基因座周围的转录调控网络,以及共表达分析,为这些网络提供生物学背景,以毛白杨木质纤维素生物合成为案例研究。该研究确定了三个可能参与木质纤维素形成的候选基因,包括一个先前被识别的基因(Potri.005G116800/VND1,是次生细胞壁形成的关键调节因子)和两个基因(Potri.012G130000/AtSAP9 和 Potri.004G202900/BIC1),它们在木质纤维素生物合成中具有新发现的假定作用。我们的综合方法为与性状变异相关的基因座提供了生物学背景的框架,有助于发现新的基因和调控网络。