International Mammalian Genome Society

logo18th International Mouse Genome Conference

17-22 October 2004, Seattle, USA


POSTER 99 - IN SILICO POSITIONAL CLONING: A WEB SYSTEM FOR EXPLORATION OF RESPONSIBLE GENES IN MONOGENIC AND MULTIGENIC TRAITS

Toyoda TT, Masuya HM, Kawashima TK, Hasegawa YH, Sezutsu HS, Kaminuma EK, Mochizuki YM, Hirosawa KH, Heida NH, Gondo YG, Kawai JK, Wakana SW, Konagaya AK, Hayashizaki YH, Shiroishi TS

RIKEN Genomic Sciences Center, Yokohama, Japan

RIKEN Genomic Sciences Center has been producing a wide range of bio-resources and comprehensive data collections from genomic-level to phenomic-level. Now, various sorts of large-scale datasets are available for the estimation of responsible genes in the forward-genetics approaches. Here we introduce a web-based system named “Genome ó Phenome Superhighway (GPS),” by which users can browse all the genes and the available bio-resources that exist in a genetic-mapped interval, and can select promising candidate genes based on the available omic datasets, such as literature-based network (LIBNET), gene expressions (READ), transcript annotations (FANTOM), genetic maps (TraitMap), and other species’ syntenic information. Thus, GPS integrates the genome, transcriptome, proteome, metabolome and phenome resources (large-scale ENU-mutant mice), and provides bioinformatics-based strategies for the gene hunting. By specifying a chromosomal interval and a keyword, for example “diabetes,” a user can obtain a ranking list of candidate genes from not only the diabetes-related genes that reportedly involve in the disease, but also from the diabetes-associated genes that is reportedly associated with other known diabetes-related genes. Then the user can pick up most promising candidates out of the list by checking their expression levels in the mouse organs. In addition to the monogenic cases, it is necessary for the system to be effective in multigenic cases, because most ordinary traits are controlled by multiple genes. GPS associates every combination of genetic loci to biomolecular networks, and thus helps us to estimate molecular-level candidate networks responsible for a given multigenic trait. GPS is open to public at http://omicspace.riken.jp/gps/.

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