高通量技术的广泛应用使得各类组学数据的产出速度越来越快,由此产生的海量数据蕴藏着大量的基因组变异和相关功能信息。如何对这些数据进行深度整合和利用将会是一个长期而艰巨的任务,这需要具备高效的数据存储、分析和挖掘的能力。在过去几年中,本课题组通过与所内外课题组的合作,在多个植物的基因组的组装、注释、比较基因组和群体基因组分析等方面进行了探索,同时也将大量的水稻种质信息和组学数据进行了整合,存储于结构化数据库中并开发了一些相应的网络查询展示和数据挖掘工具。本文对相关的研究成果及其进展进行了概括性介绍,并展望了下一步的目标：构建一个用于支持作物功能基因组学和分子设计育种研究的整合组学知识库。

The advances in high-throughput technologies have enabled high-speed accumulation of omics data, which contain a large amount of genetic variations and their functional information. The integration and deep utilization of those data will be a long-term and difficult task, which requires highly efficient data storage and powerful data analysis and mining tools. In the past several years, our group has conducted multi-level genomic analyses in several plants, including genome assembly and annotation, comparative and population genomic studies, through collaboration with other labs inside and outside of our institution. Meanwhile, we have integrated a large amount of rice germplasm information and omics data into a structural database and developed related data query, visual display and mining web tools. Here, we summarize some of those results and discuss our next goal to construct an integrated omics knowledgebase for crops to support functional genomics and molecular design breeding.