Nagle Michael F, Yuan Jialin, Kaur Damanpreet, Ma Cathleen, Peremyslova Ekaterina, Jiang Yuan, Zahl Bahiya, Niño de Rivera Alexa, Muchero Wellington, Fuxin Li, Strauss Steven H
Department of Forest Ecosystems and Society, Oregon State University, 3180 SW Jefferson Way, Corvallis, OR, 97331, United States.
Department of Electrical Engineering and Computer Science, Oregon State University, 110 SW Park Terrace, Corvallis, OR, 97331, United States.
Hortic Res. 2023 Jun 14;10(8):uhad125. doi: 10.1093/hr/uhad125. eCollection 2023 Aug.
Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of . GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.
不定根形成对树木的繁殖、育种和基因工程至关重要。植物进行这一过程的能力具有高度遗传性且为多基因性质；然而，其遗传变异的基础在很大程度上尚未得到表征。为了鉴定不定根形成的遗传调控因子，我们使用1148个……基因型进行了全基因组关联研究（GWAS）。GWAS通常受到研究人员在高通量规模上收集精确表型数据能力的限制；为了帮助克服这一限制，我们开发了一个计算机视觉系统来测量一系列与杨树不定根发育相关的性状，包括侧根和基部根长度及面积的时间测量值。使用多种方法和显著性阈值进行GWAS，以处理非正态表型统计数据并提高统计效力。这些分析总共产生了277个独特的关联，表明控制生根的基因包括激素信号传导、细胞分裂和结构、活性氧信号传导以及其他在根发育中具有已知作用的过程的调控因子。还鉴定出了许多功能未表征和/或具有隐秘作用的基因。这些候选基因提供了功能分析的靶点，包括生理和上位性分析，以更好地表征不定根形成复杂的多基因调控。
