Targeted discovery of novel human exons by comparative genomics

Adam Siepel, Mark Diekhans, Broňa Brejová, Laura Langton, Michael Stevens, Charles L.G. Comstock, Colleen Davis, Brent Ewing, Shelly Oommen, Christopher Lau, Hung Chun Yu, Jianfeng Li, Bruce A. Roe, Phil Green, Daniela S. Gerhard, Gary Temple, David Haussler, Michael R. Brent

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


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.

Original languageEnglish
Pages (from-to)1763-1773
Number of pages11
JournalGenome research
Issue number12
StatePublished - Dec 2007


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