Location: Plant, Soil and Nutrition ResearchTitle: The tomato expression Atlas
|FERNANDEZ, POZO - Boyce Thompson Institute
|ZHENG, YI - Boyce Thompson Institute
|SNYDER, STEPHEN - Boyce Thompson Institute
|NICOLAS, PHILIPPE - Boyce Thompson Institute
|FEI, ZHANGJUN - Boyce Thompson Institute
|ROSE, JOCELYN - Cornell University
|MUELLER, LUKAS - Cornell University
Submitted to: Bioinformatics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/31/2017
Publication Date: 11/12/2017
Citation: Fernandez, P., Zheng, Y., Snyder, S., Nicolas, P., Fei, Z., Giovannoni, J.J., Rose, J., Mueller, L. 2017. The tomato expression Atlas. Bioinformatics. 33:2397-2398.
Interpretive Summary: With the development of new high-throughput DNA sequencing technologies and decreasing costs, large gene expression datasets are being generated at an accelerating rate, but can be complex to visualize. New, more interactive and intuitive tools are needed to visualize the spatiotemporal context of expression data and help elucidate gene function. Using tomato fruit as a model, we have developed the Tomato Expression Atlas to facilitate effective data analysis, allowing the simultaneous visualization of groups of genes at a cell/tissue level of resolution within an organ, enhancing hypothesis development and testing in addition to candidate gene identification. This atlas can be adapted to different types of expression data from diverse species.
Technical Abstract: Large-scale transcriptome profiling has become widely adopted as a means to characterize the status and diversity of biological samples, and as a platform for functional genomic studies. Such analyses typically target whole organisms or specific organs; however, there is an increasing interest in using cell- or tissue-related transcriptome profiling to provide enhanced spatiotemporal understanding of gene function. The quantity and resolution of such gene expression information necessitates the development of new data visualization tools that are more interactive, intuitive and accessible. Tools such as the eFP browser or MapMan are available to visualize RNA-seq expression and metabolomics data in intuitive graphical formats. At the Sol Genomics Network (SGN, https://solgenomics.net/) we have developed the Tomato Expression Atlas (TEA), a web tool to store and display RNA-Seq data derived from complex organs/organisms down to the cell-type level of resolution, with the versatility to show different stages of development, genotypes, treatments, or other variables. TEA is currently based on expression data from tomato (Solanum spp.) fruit, but could be adapted for any multicellular organ/organism.