DISSERTATION RESEARCH: The Evolution of Plant Drought Tolerance and Gene Function Across Historic Frequency Gradients

论文研究：植物耐旱性和基因功能在历史频率梯度上的演变

• 批准号: 1701918
• 负责人: John McKay
• 金额: $ 1.98万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701918&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; Evolution; Plant; Drought

This research will investigate the function of genes possibly involved in drought adaptation in wild populations of the plant Arabidopsis thaliana. Droughts are one of nature?s most devastating forces, affecting millions of people each year. Yet as agents of strong selection on plant populations, they are also valuable for understanding basic evolutionary processes, such as discovering the genes involved in adaptation. Furthermore, studying plant evolution in the context of drought may produce the critical knowledge needed to develop drought tolerant crops. Using a global map of historic drought frequency based on remote sensing data, populations were identified that experience very different drought frequencies. From data on genetic differences among those populations, 20 genes were identified that will be studied for their molecular and phenotypic effects. This work is expected to yield key insight into the evolution of gene function, and to confirm genes underlying drought tolerance traits. The results of studying these genes may be of great value to breeding programs working to improve drought tolerance in crop species. In addition, the project will involve mentoring both undergraduate and high school students, including individuals from groups that are underrepresented in the sciences. Historic drought frequency significantly predicts important drought tolerance traits, flowering time and water use efficiency, among natural accessions of Arabidopsis thaliana. The project will investigate the effects of loss of function alleles on 20 genes involved in flowering time or water use efficiency. A reverse genetics approach based on T-DNA gene knockouts will be used to artificially induce mutations in these genes in a common genomic background. The project will quantify the effect sizes of these hypothesized genes on flowering time and water use efficiency. It will also characterize effects on whole genome expression profiles and abiotic signaling cascades using RNAseq.

本研究将研究拟南芥野生种群中可能参与干旱适应的基因的功能。干旱是自然界中最具破坏性的力量之一？S，每年影响数以百万计的人。然而，作为对植物种群进行强选择的媒介，它们对于理解基本的进化过程也是有价值的，例如发现与适应有关的基因。此外，在干旱的背景下研究植物进化可能会产生开发耐旱作物所需的关键知识。利用基于遥感数据的历史干旱频率全球地图，确定了经历非常不同干旱频率的人口。从这些群体之间的遗传差异数据中，确定了20个基因，这些基因将被研究其分子和表型效应。这项工作有望对基因功能的进化产生关键的洞察力，并确认耐旱性状的潜在基因。这些基因的研究结果可能对致力于提高作物品种抗旱性的育种计划具有重要价值。此外，该项目将涉及指导本科生和高中生，包括来自科学界代表性不足的群体的个人。历史干旱频率显著预测了拟南芥天然种质的重要耐旱性性状、开花时间和水分利用效率。该项目将调查20个与开花时间或水分利用效率有关的基因的功能等位基因丢失的影响。基于T-DNA基因敲除的反向遗传学方法将被用来在共同的基因组背景下人工诱导这些基因的突变。该项目将量化这些假想基因对开花时间和水分利用效率的影响大小。它还将利用RNAseq表征对整个基因组表达谱和非生物信号级联的影响。

项目成果

Drought adaptation in Arabidopsis thaliana by extensive genetic loss-of-function

• DOI: 10.7554/elife.41038
• 发表时间: 2018-12
• 期刊: eLife
• 影响因子: 7.7
• 作者: J. G. Monroe;T. Powell;Nicholas Price;J. Mullen;A. Howard;Kyle Evans;J. Lovell;J. McKay

Drought regimens predict life history strategies in Heliophila

干旱方案预测Heliophila的生活史策略

• DOI: 10.1111/nph.15919
• 发表时间: 2019
• 期刊: New Phytologist
• 影响因子: 9.4
• 作者: Monroe, J. Grey;Gill, Brian;Turner, Kathryn G.;McKay, John K.
• 通讯作者: McKay, John K.

Convergent Loss of an EDS1/PAD4 Signaling Pathway in Several Plant Lineages Reveals Coevolved Components of Plant Immunity and Drought Response

• DOI: 10.1105/tpc.19.00903
• 发表时间: 2020-07-01
• 期刊: PLANT CELL
• 影响因子: 11.6
• 作者: Baggs, Erin L.;Monroe, J. Grey;Krasileva, Ksenia, V
• 通讯作者: Krasileva, Ksenia, V

AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana

• DOI: 10.1093/nar/gkz925
• 发表时间: 2020-01-08
• 期刊: NUCLEIC ACIDS RESEARCH
• 影响因子: 14.9
• 作者: Togninalli, Matteo;Seren, Uemit;Grimm, Dominik G.
• 通讯作者: Grimm, Dominik G.