Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
Department of Biochemistry, Faculty of Science, King Abdulaziz University (KAU), Jeddah, Saudi Arabia.
Plant J. 2021 Jul;107(2):544-563. doi: 10.1111/tpj.15310. Epub 2021 Jun 2.
Salt stress decreases plant growth prior to significant ion accumulation in the shoot. However, the processes underlying this rapid reduction in growth are still unknown. To understand the changes in salt stress responses through time and at multiple physiological levels, examining different plant processes within a single set-up is required. Recent advances in phenotyping has allowed the image-based estimation of plant growth, morphology, colour and photosynthetic activity. In this study, we examined the salt stress-induced responses of 191 Arabidopsis accessions from 1 h to 7 days after treatment using high-throughput phenotyping. Multivariate analyses and machine learning algorithms identified that quantum yield measured in the light-adapted state (F /F ) greatly affected growth maintenance in the early phase of salt stress, whereas the maximum quantum yield (QY ) was crucial at a later stage. In addition, our genome-wide association study (GWAS) identified 770 loci that were specific to salt stress, in which two loci associated with QY and F /F were selected for validation using T-DNA insertion lines. We characterized an unknown protein kinase found in the QY locus that reduced photosynthetic efficiency and growth maintenance under salt stress. Understanding the molecular context of the candidate genes identified will provide valuable insights into the early plant responses to salt stress. Furthermore, our work incorporates high-throughput phenotyping, multivariate analyses and GWAS, uncovering details of temporal stress responses and identifying associations across different traits and time points, which are likely to constitute the genetic components of salinity tolerance.
盐胁迫会在植物地上部分离子大量积累之前降低其生长。然而,这种生长迅速下降的过程仍不清楚。为了在多个生理水平上随时间理解盐胁迫响应的变化,需要在单一设置中检查不同的植物过程。表型分析的最新进展允许基于图像的植物生长、形态、颜色和光合作用活性的估计。在这项研究中,我们使用高通量表型分析,在处理后 1 小时到 7 天的时间内,检查了 191 个拟南芥品系的盐胁迫诱导响应。多元分析和机器学习算法确定,在光适应状态下测量的量子产率(F/F)极大地影响了盐胁迫早期的生长维持,而最大量子产率(QY)在后期至关重要。此外,我们的全基因组关联研究(GWAS)鉴定了 770 个与盐胁迫特异性相关的基因座,其中与 QY 和 F/F 相关的两个基因座被选择用于使用 T-DNA 插入系进行验证。我们对 QY 基因座中发现的一个未知蛋白激酶进行了表征,该激酶在盐胁迫下降低了光合作用效率和生长维持。了解候选基因的分子背景将为早期植物对盐胁迫的响应提供有价值的见解。此外,我们的工作结合了高通量表型分析、多元分析和 GWAS,揭示了时间响应的细节,并鉴定了不同性状和时间点之间的关联,这些关联可能构成盐度耐受性的遗传成分。