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Methods

Targeted discovery of novel human exons by comparative genomics

¹ Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853, USA; ² Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California 95064, USA; ³ Laboratory for Computational Genomics, Washington University, Saint Louis, Missouri 63130, USA; ⁴ Howard Hughes Medical Institute and Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA; ⁵ Departments of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73109, USA; ⁶ National Cancer Institute, Bethesda, Maryland 20892, USA; ⁷ National Human Genome Research Institute, Bethesda, Maryland 20892, USA; ⁸ Howard Hughes Medical Institute, University of California, Santa Cruz, California 95064, USA

A complete and accurate set of human protein-coding gene annotations is perhaps the single most important resource for genomic research after the human-genome sequence itself, yet the major gene catalogs remain incomplete and imperfect. Here we describe a genome-wide effort, carried out as part of the Mammalian Gene Collection (MGC) project, to identify human genes not yet in the gene catalogs. Our approach was to produce gene predictions by algorithms that rely on comparative sequence data but do not require direct cDNA evidence, then to test predicted novel genes by RT–PCR. We have identified 734 novel gene fragments (NGFs) containing 2188 exons with, at most, weak prior cDNA support. These NGFs correspond to an estimated 563 distinct genes, of which >160 are completely absent from the major gene catalogs, while hundreds of others represent significant extensions of known genes. The NGFs appear to be predominantly protein-coding genes rather than noncoding RNAs, unlike novel transcribed sequences identified by technologies such as tiling arrays and CAGE. They tend to be expressed at low levels and in a tissue-specific manner, and they are enriched for roles in motor activity, cell adhesion, connective tissue, and central nervous system development. Our results demonstrate that many important genes and gene fragments have been missed by traditional approaches to gene discovery but can be identified by their evolutionary signatures using comparative sequence data. However, they suggest that hundreds—not thousands—of protein-coding genes are completely missing from the current gene catalogs.

E-mail acs4{at}cornell.edu; fax (607) 255-4698.

[Supplemental material is available online at www.genome.org.]

Article published online before print. Article and publication date are online at http://www.genome.org/cgi/doi/10.1101/gr.7128207

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