Rice-Map: a new-generation rice genome browser

• Main Authors: Luo Jingchu, Gu Xiaocheng, Li Zhe, Tang Liang, Zhang He, Zhao Shuqi, Kong Lei, Wang Jun, Gao Ge
• Format: Article
• Language: English
• Published: BMC 2011-03-01
• Series: BMC Genomics
• Online Access: http://www.biomedcentral.com/1471-2164/12/165

<p>Abstract</p> <p>Background</p> <p>The concurrent release of rice genome sequences for two subspecies (<it>Oryza sativa </it>L. ssp. <it>japonica </it>and <it>Oryza sativa </it>L. ssp. <it>indica</it>) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively.</p> <p>Description</p> <p>More than one hundred annotation tracks (81 for <it>japonica </it>and 82 for <it>indica</it>) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria.</p> <p>Conclusions</p> <p>Rice-Map delivers abundant up-to-date <it>japonica </it>and <it>indica </it>annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at <url>http://www.ricemap.org/</url>, with all data available for free downloading.</p>