CyanOmics: an integrated database of omics for the model cyanobacterium Synechococcus sp PCC 7002

被引:11
|
作者
Yang, Yaohua [1 ,2 ]
Feng, Jie [1 ,2 ]
Li, Tao [1 ]
Ge, Feng [1 ]
Zhao, Jindong [1 ,3 ]
机构
[1] Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Peking Univ, Coll Life Sci, Beijing 100871, Peoples R China
基金
中国国家自然科学基金;
关键词
OXIDATIVE STRESS; HIGH-LIGHT; GENERATION; SEQUENCE; GROWTH; MUTANT; ROLES;
D O I
10.1093/database/bau127
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cyanobacteria are an important group of organisms that carry out oxygenic photosynthesis and play vital roles in both the carbon and nitrogen cycles of the Earth. The annotated genome of Synechococcus sp. PCC 7002, as an ideal model cyanobacterium, is available. A series of transcriptomic and proteomic studies of Synechococcus sp. PCC 7002 cells grown under different conditions have been reported. However, no database of such integrated omics studies has been constructed. Here we present CyanOmics, a database based on the results of Synechococcus sp. PCC 7002 omics studies. CyanOmics comprises one genomic dataset, 29 transcriptomic datasets and one proteomic dataset and should prove useful for systematic and comprehensive analysis of all those data. Powerful browsing and searching tools are integrated to help users directly access information of interest with enhanced visualization of the analytical results. Furthermore, Blast is included for sequence-based similarity searching and Cluster 3.0, as well as the R hclust function is provided for cluster analyses, to increase CyanOmics's usefulness. To the best of our knowledge, it is the first integrated omics analysis database for cyanobacteria. This database should further understanding of the transcriptional patterns, and proteomic profiling of Synechococcus sp. PCC 7002 and other cyanobacteria. Additionally, the entire database framework is applicable to any sequenced prokaryotic genome and could be applied to other integrated omics analysis projects.
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页数:9
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