TOMATOMICS: A Web Database for Integrated Omics Information in Tomato

Toru Kudo, Masaaki Kobayashi, Shin Terashima, Minami Katayama, Soichi Ozaki, Maasa Kanno, Misa Saito, Koji Yokoyama, Hajime Ohyanagi, Koh Aoki, Yasutaka Kubo, Kentaro Yano

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Solanum lycopersicum (tomato) is an important agronomic crop and a major model fruit-producing plant. To facilitate basic and applied research, comprehensive experimental resources and omics information on tomato are available following their development. Mutant lines and cDNA clones from a dwarf cultivar, Micro-Tom, are two of these genetic resources. Large-scale sequencing data for ESTs and full-length cDNAs from Micro-Tom continue to be gathered. In conjunction with information on the reference genome sequence of another cultivar, Heinz 1706, the Micro-Tom experimental resources have facilitated comprehensive functional analyses. To enhance the efficiency of acquiring omics information for tomato biology, we have integrated the information on the Micro-Tom experimental resources and the Heinz 1706 genome sequence. We have also inferred gene structure by comparison of sequences between the genome of Heinz 1706 and the transcriptome, which are comprised of Micro-Tom full-length cDNAs and Heinz 1706 RNA-seq data stored in the KaFTom and Sequence Read Archive databases. In order to provide large-scale omics information with streamlined connectivity we have developed and maintain a web database TOMATOMICS (http://bioinf.mind.meiji.ac.jp/tomatomics/). In TOMATOMICS, access to the information on the cDNA clone resources, full-length mRNA sequences, gene structures, expression profiles and functional annotations of genes is available through search functions and the genome browser, which has an intuitive graphical interface.
Original languageEnglish (US)
Pages (from-to)pcw207
JournalPlant and Cell Physiology
Volume58
Issue number1
DOIs
StatePublished - Jan 22 2017

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported in part by Grants-in-Aid for Scientific Research (No. 24113518 and No. 26113716 to K.Y.) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (MEXT) and for Scientific Research (B) (No. 16H04873 to Y.K.) from the Japan Society for Promotion of Science (JSPS). Support was also provided by the MEXT-Supported Program for the Strategic Research Foundation at Private Universities (2014–2018), Research Project Grant (A) by Institute of Science and Technology, Meiji University and by Research Funding for the Computational Software Supporting 70 Program from Meiji University to K.Y.

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