Veley Kira M, Berry Jeffrey C, Fentress Sarah J, Schachtman Daniel P, Baxter Ivan, Bart Rebecca
Donald Danforth Plant Science Center Saint Louis MO USA.
Department of Agronomy and Horticulture and Center for Plant Science Innovation University of Nebraska-Lincoln Lincoln NE USA.
Plant Direct. 2017 Oct 25;1(4):e00023. doi: 10.1002/pld3.23. eCollection 2017 Oct.
Sorghum ( (L.) Moench) is a rapidly growing, high-biomass crop prized for abiotic stress tolerance. However, measuring genotype-by-environment (G x E) interactions remains a progress bottleneck. We subjected a panel of 30 genetically diverse sorghum genotypes to a spectrum of nitrogen deprivation and measured responses using high-throughput phenotyping technology followed by ionomic profiling. Responses were quantified using shape (16 measurable outputs), color (hue and intensity), and ionome (18 elements). We measured the speed at which specific genotypes respond to environmental conditions, in terms of both biomass and color changes, and identified individual genotypes that perform most favorably. With this analysis, we present a novel approach to quantifying color-based stress indicators over time. Additionally, ionomic profiling was conducted as an independent, low-cost, and high-throughput option for characterizing G x E, identifying the elements most affected by either genotype or treatment and suggesting signaling that occurs in response to the environment. This entire dataset and associated scripts are made available through an open-access, user-friendly, web-based interface. In summary, this work provides analysis tools for visualizing and quantifying plant abiotic stress responses over time. These methods can be deployed as a time-efficient method of dissecting the genetic mechanisms used by sorghum to respond to the environment to accelerate crop improvement.
高粱((L.) Moench)是一种生长迅速、生物量高的作物,因其对非生物胁迫的耐受性而备受青睐。然而,测量基因型与环境互作(G×E)仍然是一个进展瓶颈。我们对一组30个遗传多样性的高粱基因型进行了一系列氮素剥夺处理,并使用高通量表型技术随后进行离子组学分析来测量其响应。通过形状(16个可测量输出)、颜色(色调和强度)和离子组(18种元素)对响应进行量化。我们从生物量和颜色变化方面测量了特定基因型对环境条件的响应速度,并鉴定出表现最优良的个体基因型。通过这种分析,我们提出了一种随时间量化基于颜色的胁迫指标的新方法。此外,进行离子组学分析作为一种独立、低成本且高通量的选项来表征G×E,识别受基因型或处理影响最大的元素,并暗示对环境响应时发生的信号传导。整个数据集和相关脚本通过一个开放获取、用户友好的基于网络的界面提供。总之,这项工作提供了用于随时间可视化和量化植物非生物胁迫响应的分析工具。这些方法可作为一种高效省时的方法来剖析高粱用于响应环境的遗传机制,以加速作物改良。