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表型组学可以鉴定影响玉米气孔导度的基因组区域,这些区域受到水分亏缺和蒸散需求的条件影响。

Phenomics allows identification of genomic regions affecting maize stomatal conductance with conditional effects of water deficit and evaporative demand.

机构信息

LEPSE, INRA, Univ. Montpellier, 34060, Montpellier, France.

出版信息

Plant Cell Environ. 2018 Feb;41(2):314-326. doi: 10.1111/pce.13083. Epub 2017 Dec 11.

DOI:10.1111/pce.13083
PMID:29044609
Abstract

Stomatal conductance is central for the trades-off between hydraulics and photosynthesis. We aimed at deciphering its genetic control and that of its responses to evaporative demand and water deficit, a nearly impossible task with gas exchanges measurements. Whole-plant stomatal conductance was estimated via inversion of the Penman-Monteith equation from data of transpiration and plant architecture collected in a phenotyping platform. We have analysed jointly 4 experiments with contrasting environmental conditions imposed to a panel of 254 maize hybrids. Estimated whole-plant stomatal conductance closely correlated with gas-exchange measurements and biomass accumulation rate. Sixteen robust quantitative trait loci (QTLs) were identified by genome wide association studies and co-located with QTLs of transpiration and biomass. Light, vapour pressure deficit, or soil water potential largely accounted for the differences in allelic effects between experiments, thereby providing strong hypotheses for mechanisms of stomatal control and a way to select relevant candidate genes among the 1-19 genes harboured by QTLs. The combination of allelic effects, as affected by environmental conditions, accounted for the variability of stomatal conductance across a range of hybrids and environmental conditions. This approach may therefore contribute to genetic analysis and prediction of stomatal control in diverse environments.

摘要

气孔导度是权衡水分和光合作用的关键因素。我们旨在解析其遗传控制及其对蒸散需求和水分亏缺的响应,这是通过气体交换测量几乎不可能完成的任务。通过从蒸腾和植物结构收集的数据,利用彭曼-蒙特斯公式的反演,估算整株植物的气孔导度。我们联合分析了 4 个具有不同环境条件的实验,这些实验是对 254 个玉米杂交种进行的。估计的整株气孔导度与气体交换测量和生物量积累率密切相关。通过全基因组关联研究鉴定了 16 个稳健的数量性状位点(QTL),这些 QTL 与蒸腾和生物量的 QTL 共定位。光照、蒸气压亏缺或土壤水势在很大程度上解释了实验之间等位基因效应的差异,从而为气孔控制的机制提供了强有力的假设,并为在 QTL 所包含的 1-19 个基因中选择相关候选基因提供了一种方法。环境条件影响的等位基因效应的组合,解释了气孔导度在一系列杂交种和环境条件下的变异性。因此,这种方法可能有助于在不同环境下进行气孔控制的遗传分析和预测。

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