基于比较基因组和ATAC-seq注释水稻基因组染色质开放区及其序列变异

We carried out large-scale genome-wide association studies in rice previously and mapped significant loci into narrow regions. However, many of the sequence variants that are significantly associated with phenotypic variation are located in noncoding regions. How to accurately assess their effects is the basis for further identifying candidate genes or causal variants. Open chromatins are the most important parts of regulatory noncoding regions, and contain a large number of transcription factor binding sites, which enrich critical sequence variants. In this project, we propose to obtain precise information of open chromatin based on ATAC-seq technology for several tissues of five species, such as rice. Combining with methods of comparative genomics, we expect that we can identify lots of regulatory elements for these species. We will then annotate sequence variants in the open chromatin regions, and pick some for experiments.

申请人及所在团队前期在水稻中进行了大量的全基因组关联分析研究，取得了一些成果。然而，很多与表型变异显著关联的序列变异位于非编码区，如何准确评估其效应是进一步确定候选基因和鉴定关键序列变异的基础。染色质开放区是已知最主要的非编码调控区，包含大量转录因子结合位点，是关键序列变异的富集区域。本申请拟使用ATAC-seq技术获得水稻等禾本科五个物种多个组织的染色质开放区信息，结合比较基因组鉴定水稻染色质开放区及其中的调控元件，并对水稻品种染色质开放区的序列变异进行注释，最后进行部分实验验证。

过去10年来水稻中进行了大量的全基因组关联分析研究，取得了丰硕的成果。然而，很多与表型变异显著关联的序列变异位于非编码区，如何准确评估其效应是进一步确定候选基因和鉴定关键序列变异的基础。染色质开放区是已知最主要的非编码调控区，包含大量转录因子结合位点，是关键序列变异的富集区域。本项目开发了UMI-ATAC-seq技术，获得了水稻等禾本科五个物种多个组织的染色质可及性数据。结合比较基因组研究鉴定了水稻染色质开放区及其中的调控元件；基于染色质可及性数据建立了深度学习模型，对水稻品种染色质开放区的序列变异进行了注释，发布了水稻基因组序列变异功能效应图谱（Impact Map），对预测的关键变异进行了部分实验验证；建立了植物中首个基于深度学习模型预测基因组序列变异调控效应的网络服务PlantDeepSEA。相关研究结果发表在Molecular Plant、Nucleic Acids Research等期刊上，完成了目标任务。