Methods

Human Disease Genes and Their Cloned Mouse Orthologs: Exploration of the FANTOM2 cDNA Sequence Data Set

    • 1National Center for Biotechnology Information, National Institutes of Health, Bethesda, Maryland 20894, USA
    • 2The Jackson Laboratory, Bar Harbor, Maine 04609, USA
    • 3Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
    • 4Departments of Pediatrics and Medicine, University of California, San Diego School of Medicine, San Diego, California 92093, USA
    • 5National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892-4472, USA
    • 6Applied Genomics, Inc., Sunnyvale, California 94085, USA
    • 7Department of Genetics, Boys Town National Research Hospital, Omaha, Nebraska 68131, USA
    • 8Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan
    • 9Genome Science Laboratory, RIKEN, Hirosawa, Wako, Saitama 351-0198, Japan
Published June 2, 2003. Vol 13 Issue 6b, pp. 1496-1500. https://doi.org/10.1101/gr.979503
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cover of Genome Research Vol 36 Issue 4
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April 2026, Vol. 36, No. 4
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Abstract

The FANTOM2 cDNA sequence data set is an excellent model to demonstrate the power of large-scale cDNA sequencing, with the goal of providing a full-length transcript sequence for each mouse gene. This data set enhances the use of the mouse as a model for human disease. Here we identify mouse cDNA sequences in the FANTOM2 data set for a set of 67 human disease genes that as of May 2002 had no corresponding mouse cDNA annotated in the Mouse Genome Informatics (MGI) database. These 67 human disease genes include genes related to neurological and eye disorders and cancer. We also present a list of the human disease genes and their cloned mouse orthologs found in two public databases, LocusLink and MGI. Allelic variant and gene functional information available in MGI provides additional information relative to these mouse models, whereas computed sequence-based connections at NCBI support facile navigation through multiple genomes.

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