Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis

Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis
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DOI:
10.1111/pce.12595
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发表时间:
2016-01-01
影响因子:
7.3
通讯作者:
Vreugdenhil, Dick
Vreugdenhil, Dick
中科院分区:
生物学1区
文献类型:
--
作者:
Bac-Molenaar, Johanna A.;Granier, Christine;Vreugdenhil, Dick

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大面积耕地经常面临不规则降雨,导致部分生长季(S)的可用水有限,这就需要对植物的抗旱性进行研究。在受控中度干旱胁迫下,观察到324份拟南芥天然种质的生物量积累的自然变异。干旱胁迫下表现的改善与早花和缺乏春化需求相关,表明开花时间和干旱反应的调控网络重叠或这些性状对自然选择的相关反应。此外,植株大小与相对含水率(RWC)呈负相关,而与绝对含水率(WC)无关,说明可溶性化合物的作用显著。对照和干旱条件下的生长是随时间而决定的,并由指数函数建立模型。通过对时间植株大小数据和模型参数的全基因组关联(GWA)作图,检测到6个与干旱强烈相关的与时间相关的数量性状基因座(QTL)。如果在一个时间点上决定植株大小,大多数QTL都不会被识别出来。对早先报道的干旱时基因表达变化的分析使我们能够为每个QTL确定最可能的候选基因。
Large areas of arable land are often confronted with irregular rainfall resulting in limited water availability for part(s) of the growing seasons, which demands research for drought tolerance of plants. Natural variation was observed for biomass accumulation upon controlled moderate drought stress in 324 natural accessions of Arabidopsis. Improved performance under drought stress was correlated with early flowering and lack of vernalization requirement, indicating overlap in the regulatory networks of flowering time and drought response or correlated responses of these traits to natural selection. In addition, plant size was negatively correlated with relative water content (RWC) independent of the absolute water content (WC), indicating a prominent role for soluble compounds. Growth in control and drought conditions was determined over time and was modelled by an exponential function. Genome-wide association (GWA) mapping of temporal plant size data and of model parameters resulted in the detection of six time-dependent quantitative trait loci (QTLs) strongly associated with drought. Most QTLs would not have been identified if plant size was determined at a single time point. Analysis of earlier reported gene expression changes upon drought enabled us to identify for each QTL the most likely candidates.