Targeted discovery of novel human exons by comparative genomics
Author(s) -
Adam Siepel,
Mark Diekhans,
Broňa Brejová,
Laura Langton,
Michael Stevens,
Charles L.G. Comstock,
Colleen Davis,
Brent Ewing,
Shelly Oommen,
Christopher Lau,
HungChun Yu,
Jianfeng Li,
Bruce A. Roe,
Phil Green,
Daniela S. Gerhard,
Gary Temple,
David Haussler,
Michael R. Brent
Publication year - 2007
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.7128207
Subject(s) - biology , gene , genetics , exon , gene prediction , genome , human genome , comparative genomics , coding region , computational biology , genomics , pair rule gene , complementary dna , functional genomics , gene expression , regulator gene
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.
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