Large scale dynamic integration of proteomics and genomics to support next-generation rice research

蛋白质组学和基因组学的大规模动态整合支持下一代水稻研究

• 批准号: BB/N013743/1
• 负责人: Andrew Jones
• 金额: $ 19.39万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FN013743%2F1
• 关键词: Large; scale; dynamic; integration; proteomics

Rice can be considered the most important worldwide crop for human nutrition, currently providing ~20% of worldwide daily dietary energy. Due to a growing worldwide population, and the effects of climate change, research into improvements in rice yield, resilience to drought and resistance to pathogens is urgently needed. Such research must be underpinned by public databases storing high-quality information about the rice genome, genetic variants carried by varieties with desirable traits, and information about the function of each gene/protein. This project is a collaboration between research teams based at the University of Liverpool, the Beijing Institute of Genomics and the BGI Education Centre. Our teams have considerable track record in the development of methods for studying the abundance of genes (transcriptomics) and proteins (proteomics) on a large scale for rice and other species, as well as computational approaches for interpreting and integrating data from these different techniques. At present, the public databases storing the rice genome and information known about gene/protein function are disconnected from experimental data (transcriptomics/proteomics) being collected in laboratories all over the world. These experimental data can be used directly to improve the annotation of the genome, by showing how strongly particular genes or proteins are expressed under particular growth conditions or for a given rice variety (which gives clues as to functional importance). These data also show how genes or proteins differ in a given variety from the "reference" genome contained in the database. Our groups are developing software tools for integrating and analysing these data in new ways, so that when laboratories submit their data to a public repository, it can be directly integrated and viewed alongside the genome - which at present is not possible. We are also going to generate and analyse new data sets for several important rice varieties, so we can study how these gene and protein sequences differ from the reference genome.Our results will help to improve the sequences and annotation of rice genes and proteins, and will be made easily available to all other rice researchers through the most widely accessed international public databases.

水稻可以被认为是世界上最重要的人类营养作物，目前为全世界提供约20%的每日膳食能量。由于世界人口的增长和气候变化的影响，迫切需要研究提高水稻产量、抗旱能力和抗病原体能力。这类研究必须以公共数据库为基础，这些数据库存储有关水稻基因组的高质量信息、具有理想性状的品种所携带的遗传变异以及每个基因/蛋白质的功能信息。该项目是由利物浦大学、北京基因组研究所和华大基因教育中心的研究团队合作完成的。我们的团队在开发水稻和其他物种的大规模基因（转录组学）和蛋白质（蛋白质组学）丰度研究方法以及用于解释和整合这些不同技术数据的计算方法方面有着相当大的记录。目前，储存水稻基因组和已知基因/蛋白质功能信息的公共数据库与世界各地实验室收集的实验数据（转录组学/蛋白质组学）是脱节的。这些实验数据可以直接用于改进基因组的注释，通过显示特定基因或蛋白质在特定生长条件下或特定水稻品种的表达强度（这为功能重要性提供了线索）。这些数据还显示了特定品种的基因或蛋白质与数据库中包含的“参考”基因组有何不同。我们的小组正在开发软件工具，以新的方式整合和分析这些数据，这样当实验室将他们的数据提交给公共存储库时，它可以直接整合并与基因组一起查看——这在目前是不可能的。我们还将生成和分析几个重要水稻品种的新数据集，这样我们就可以研究这些基因和蛋白质序列与参考基因组的不同之处。我们的研究结果将有助于改进水稻基因和蛋白质的序列和注释，并将通过最广泛访问的国际公共数据库方便所有其他水稻研究人员获得。

项目成果

Improvements to the Rice Genome Annotation Through Large-Scale Analysis of RNA-Seq and Proteomics Data Sets.

• DOI: 10.1074/mcp.ra118.000832
• 发表时间: 2019-01
• 期刊: Molecular & cellular proteomics : MCP
• 作者: Ren Z;Qi D;Pugh N;Li K;Wen B;Zhou R;Xu S;Liu S;Jones AR
• 通讯作者: Jones AR