Chhetri Hari B, Furches Anna, Macaya-Sanz David, Walker Alejandro R, Kainer David, Jones Piet, Harman-Ware Anne E, Tschaplinski Timothy J, Jacobson Daniel, Tuskan Gerald A, DiFazio Stephen P
Department of Biology, West Virginia University, Morgantown, WV, United States.
Biosciences Division, and The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.
Front Plant Sci. 2020 Sep 9;11:545748. doi: 10.3389/fpls.2020.545748. eCollection 2020.
To understand the genetic mechanisms underlying wood anatomical and morphological traits in , we used 869 unrelated genotypes from a common garden in Clatskanie, Oregon that were previously collected from across the distribution range in western North America. Using GEMMA mixed model analysis, we tested for the association of 25 phenotypic traits and nine multitrait combinations with 6.741 million SNPs covering the entire genome. Broad-sense trait heritabilities ranged from 0.117 to 0.477. Most traits were significantly correlated with geoclimatic variables suggesting a role of climate and geography in shaping the variation of this species. Fifty-seven SNPs from single trait GWAS and 11 SNPs from multitrait GWAS passed an FDR threshold of 0.05, leading to the identification of eight and seven nearby candidate genes, respectively. The percentage of phenotypic variance explained (PVE) by the significant SNPs for both single and multitrait GWAS ranged from 0.01% to 6.18%. To further evaluate the potential roles of candidate genes, we used a multi-omic network containing five additional data sets, including leaf and wood metabolite GWAS layers and coexpression and comethylation networks. We also performed a functional enrichment analysis on coexpression nearest neighbors for each gene model identified by the wood anatomical and morphological trait GWAS analyses. Genes affecting cell wall composition and transport related genes were enriched in wood anatomy and stomatal density trait networks. Signaling and metabolism related genes were also common in networks for stomatal density. For leaf morphology traits (leaf dry and wet weight) the networks were significantly enriched for GO terms related to photosynthetic processes as well as cellular homeostasis. The identified genes provide further insights into the genetic control of these traits, which are important determinants of the suitability and sustainability of improved genotypes for lignocellulosic biofuel production.
为了解[具体物种]木材解剖结构和形态特征背后的遗传机制，我们使用了来自俄勒冈州克拉茨卡尼一个共同种植园的869个无亲缘关系的基因型，这些基因型先前是从北美西部的分布范围内收集的。通过GEMMA混合模型分析，我们测试了25个表型性状和9个多性状组合与覆盖整个基因组的674.1万个单核苷酸多态性（SNP）之间的关联。广义性状遗传力范围为0.117至0.477。大多数性状与地理气候变量显著相关，表明气候和地理在塑造该物种的变异中起作用。单性状全基因组关联研究（GWAS）中的57个SNP和多性状GWAS中的11个SNP通过了0.05的错误发现率（FDR）阈值，分别导致鉴定出8个和7个附近的候选基因。单性状和多性状GWAS中显著SNP解释的表型变异百分比（PVE）范围为0.01%至6.18%。为了进一步评估候选基因的潜在作用，我们使用了一个包含五个额外数据集的多组学网络，包括叶片和木材代谢物GWAS层以及共表达和共甲基化网络。我们还对木材解剖结构和形态特征GWAS分析鉴定的每个基因模型的共表达最近邻进行了功能富集分析。影响细胞壁组成的基因和运输相关基因在木材解剖结构和气孔密度性状网络中富集。信号传导和代谢相关基因在气孔密度网络中也很常见。对于叶片形态性状（叶片干重和湿重），网络中与光合过程以及细胞内稳态相关的基因本体（GO）术语显著富集。鉴定出的基因进一步揭示了这些性状的遗传控制，这些性状是木质纤维素生物燃料生产中改良基因型适宜性和可持续性的重要决定因素。
