Ferrero-Serrano Ángel, Chakravorty David, Kirven Kobie J, Assmann Sarah M
Biology Department, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA, 16802, USA.
Intercollege Graduate Degree Program in Bioinformatics and Genomics, Pennsylvania State University.
bioRxiv. 2023 Dec 21:2023.05.10.540241. doi: 10.1101/2023.05.10.540241.
Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To this end, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that allow the user to: i) explore the local environments of traditional rice varieties (landraces) in South-Eastern Asia, and; ii) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We exemplify the value of these resources, identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in and disrupted by a natural variant in . Prior QTL analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing Potential Evapotranspiration gradient and their regulation of key agronomic traits including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce crops that are climate resilient.
现代作物品种在其当前分布与当地气候对其生产力的适宜性之间存在一定程度的不匹配。为此,我们推出了水稻气候工具(https://gramene.org/CLIMtools/oryza_v1.0/),这是首个用于作物物种中与气候相关的遗传变异泛基因组预测的资源。水稻气候工具由基于网络的交互式数据库组成,用户可以:i)探索东南亚传统水稻品种(地方品种)的当地环境,以及;ii)通过对从地理参考当地环境收集并纳入3K水稻基因组计划的658个籼稻和283个粳稻地方品种种质的基因组关联来研究环境。我们举例说明了这些资源的价值,确定了当地环境中开花时间与温度之间的相互作用,这种相互作用由[具体基因1]中的适应性自然变异促成,并被[具体基因2]中的一个自然变异破坏。先前的数量性状位点分析表明异源三聚体G蛋白在控制农艺性状方面的重要性。因此,我们分析了不同异源三聚体G蛋白亚基中自然变异与气候的关联。我们确定了G蛋白在适应盛行潜在蒸散梯度以及调控包括株高、种子和穗长等关键农艺性状方面的协同作用。我们通过强调靶向异源三聚体G蛋白以培育具有气候适应性作物的前景来得出结论。