Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India.
ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India.
Sci Rep. 2019 Sep 26;9(1):13917. doi: 10.1038/s41598-019-49915-2.
Drought is one of the major impediments in wheat productivity. Traditional breeding and marker assisted QTL introgression had limited success. Available wheat genomic and RNA-seq data can decipher novel drought tolerance mechanisms with putative candidate gene and marker discovery. Drought is first sensed by root tissue but limited information is available about how roots respond to drought stress. In this view, two contrasting genotypes, namely, NI5439 41 (drought tolerant) and WL711 (drought susceptible) were used to generate ~78.2 GB data for the responses of wheat roots to drought. A total of 45139 DEGs, 13820 TF, 288 miRNAs, 640 pathways and 435829 putative markers were obtained. Study reveals use of such data in QTL to QTN refinement by analysis on two model drought-responsive QTLs on chromosome 3B in wheat roots possessing 18 differentially regulated genes with 190 sequence variants (173 SNPs and 17 InDels). Gene regulatory networks showed 69 hub-genes integrating ABA dependent and independent pathways controlling sensing of drought, root growth, uptake regulation, purine metabolism, thiamine metabolism and antibiotics pathways, stomatal closure and senescence. Eleven SSR markers were validated in a panel of 18 diverse wheat varieties. For effective future use of findings, web genomic resources were developed. We report RNA-Seq approach on wheat roots describing the drought response mechanisms under field drought conditions along with genomic resources, warranted in endeavour of wheat productivity.
干旱是小麦生产力的主要障碍之一。传统的育种和标记辅助 QTL 导入在这方面的效果有限。现有的小麦基因组和 RNA-seq 数据可以通过潜在候选基因和标记的发现来破译新的耐旱机制。干旱首先由根组织感知，但关于根如何响应干旱胁迫的信息有限。在这种情况下，使用两个对比基因型，即 NI5439 41（耐旱）和 WL711（耐旱），生成了约 78.2GB 的小麦根对干旱响应的数据。共获得了 45139 个差异表达基因、13820 个转录因子、288 个 microRNA、640 个途径和 435829 个潜在标记。研究揭示了利用这些数据在 QTL 到 QTN 的细化分析中，对小麦根上的两个模型干旱响应 QTL 进行分析，这两个 QTL 上有 18 个差异调控基因，有 190 个序列变异（173 个 SNP 和 17 个 InDels）。基因调控网络显示了 69 个枢纽基因，它们整合了 ABA 依赖和非依赖途径，控制干旱感知、根生长、吸收调节、嘌呤代谢、硫胺素代谢和抗生素途径、气孔关闭和衰老。11 个 SSR 标记在 18 个不同的小麦品种中进行了验证。为了有效利用研究结果，开发了网络基因组资源。我们报告了小麦根的 RNA-Seq 方法，描述了田间干旱条件下的干旱响应机制，以及基因组资源，这是提高小麦生产力的努力的一部分。
