RESEARCH-PGR: Systems Genomics of Rice Stress Adaptation

RESEARCH-PGR：水稻逆境适应的系统基因组学

• 批准号: 1546218
• 负责人: Michael Purugganan
• 金额: $ 399.54万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1546218&HistoricalAwards=false
• 关键词: RESEARCH; PGR; Systems; Genomics; Rice

Adaptation of crop plants like rice to environmental stress is an essential requirement to ensure high yields under those conditions. Salinity is among the major environmental stresses that crop plants face, and it is currently threatening rice cultivation due to increasing land pressure and climate change, which are pushing agriculture to marginal lands. Rice is a major world crop comprising two species: one from Asia (Oryza sativa), and one from Africa (O. glaberrima). This project aims to identify genes associated with adaptation to saline soils through comparative analyses of rice varieties that have contrasting adaptation to salt stress, within and between the two species. The discovery of more than one adaptive strategy will increase the options rice breeders could implement in their programs. This project will use several approaches to identify genes that have a uniquely coordinated pattern of expression when the plant is exposed to elevated salt, and at the same time are correlated with vigorous growth and productivity. This project will also undertake public outreach programs using the New York City BioBus. This is a transit bus equipped as a mobile educational laboratory that has been on the road reaching 115,000 people at more than 420 schools and communities. Plant biology laboratory modules will be developed for deployment across New York City on the BioBus. These modules will primarily target schoolchildren in underserved communities, and also the general public in street fairs.Salinity is one of the growing stress challenges crop plants face. In this systems genomics proposal, we will dissect the adaptive response of O. sativa (Asian rice) and O. glaberrima (African rice) to salt stress. First, we will infer the gene regulatory interaction network for salt stress in Asian and African rice using time-series transcriptome and chromatin accessibility data, coupled with state-of-the-art network inference methods. Second, we will use phenotypic selection analysis on gene expression levels to determine the strength and pattern of selection on stress response genes. Finally, we will map expression genome-wide association (GWAS) loci accompanying gene expression variation under salt stress, focusing on the genes that have been identified in phenotypic selection analysis as undergoing positive, stabilizing or disruptive selection. Moreover, we will also identity GWAS loci for plant fitness and fitness-related traits under saline conditions in both rice species, and integrate the results of these mapping analyses and phenotypic selection analyses with evidence for selective sweeps in whole genome sequence data from Asian and African rice. Our work will identify genes, genetic networks and genomic variants that affect gene expression differences in key loci in response to an environmental perturbation - salt stress -and explicitly connect gene regulatory variation to plant fitness.

使水稻等作物适应环境压力是确保在这些条件下高产的基本要求。 盐分是农作物面临的主要环境压力之一，由于土地压力和气候变化的增加，目前正威胁着水稻种植，这将农业推向边缘土地。水稻是一种主要的世界作物，包括两个物种：一个来自亚洲（Oryza sativa），一个来自非洲（O. glaberrima）。该项目旨在通过对两个物种内部和之间对盐胁迫具有不同适应性的水稻品种进行比较分析，确定与适应盐渍土相关的基因。一种以上适应策略的发现将增加水稻育种者在其计划中可以实施的选择。该项目将使用几种方法来鉴定当植物暴露于高盐时具有独特协调表达模式的基因，同时与旺盛的生长和生产力相关。该项目还将利用纽约市生物巴士开展公共外联方案。这是一辆配备了移动的教育实验室的公交车，已经在路上行驶，覆盖了420多所学校和社区的115 000人。将开发植物生物学实验室模块，以便在整个纽约市的BioBus上部署。这些模块将主要针对服务不足社区的学童，以及街头集市上的普通公众。盐分是作物面临的日益严重的压力挑战之一。在这个系统基因组学的建议中，我们将剖析O。sativa和O. glaberrima（非洲水稻）对盐胁迫的响应。首先，我们将使用时间序列转录组和染色质可及性数据，结合最先进的网络推理方法，推断亚洲和非洲水稻盐胁迫的基因调控相互作用网络。其次，我们将使用基因表达水平的表型选择分析，以确定胁迫反应基因的选择强度和模式。最后，我们将映射表达全基因组关联（GWAS）位点伴随着盐胁迫下的基因表达变化，专注于在表型选择分析中已被确定为正，稳定或破坏性选择的基因。此外，我们还将确定GWAS基因座的植物健身和健身相关的性状在盐条件下在两个水稻品种，并整合这些映射分析和表型选择分析的结果与证据的选择性扫描全基因组序列数据从亚洲和非洲水稻。我们的工作将确定影响关键位点基因表达差异的基因、遗传网络和基因组变异，以应对环境扰动-盐胁迫-并明确将基因调控变异与植物适应性联系起来。