Cited by 634Genomics and Phylogenetic StudiesGene expression and cancer classificationRNA Research and Splicing

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Using the transcriptome to annotate the genome

Saha, Saurabh, Sparks, Andrew B., Rago, Carlo, Akmaev, Viatcheslav, Wang, Clarence J., Vogelstein, Bert, Kinzler, Kenneth W., Velculescu, Victor E.·2002·Nature Biotechnology

DOI 10.1038/nbt0502-508

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Abstract

A remaining challenge for the human genome project involves the identification and annotation of expressed genes. The public and private sequencing efforts have identified approximately 15,000 sequences that meet stringent criteria for genes, such as correspondence with known genes from humans or other species, and have made another approximately 10,000-20,000 gene predictions of lower confidence, supported by various types of in silico evidence, including homology studies, domain searches, and ab initio gene predictions. These computational methods have limitations, both because they are unable to identify a significant fraction of genes and exons and because they are unable to provide definitive evidence about whether a hypothetical gene is actually expressed. As the in silico approaches identified a smaller number of genes than anticipated, we wondered whether high-throughput experimental analyses could be used to provide evidence for the expression of hypothetical genes and to reveal previously undiscovered genes. We describe here the development of such a method--called long serial analysis of gene expression (LongSAGE), an adaption of the original SAGE approach--that can be used to rapidly identify novel genes and exons.

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Authors: Saha, S., Sparks, A. B., Rago, C., Akmaev, V., Wang, C. J., Vogelstein, B., Kinzler, K. W., & Velculescu, V. E.
Affiliations: Howard Hughes Medical Institute (US)
Corresponding author: Kinzler, Kenneth W.
Velculescu, Victor E.
ORCID: Saha, Saurabh
Akmaev, Viatcheslav
Vogelstein, Bert
Kinzler, Kenneth W.
Velculescu, Victor E.
Venue: Nature Biotechnology
Publisher: Springer Science and Business Media LLC
Published: 2002-05
Volume: 20
Issue: 5
Pages: 508-512
ISSN: 0733-222X (ISSN-L)
1087-0156
1546-1696
DOI: 10.1038/nbt0502-508
OpenAlex: W2002982210
Cited by: 630
References: 20
Citations by year: 2026: 2 · 2025: 1 · 2024: 3 · 2023: 6 · 2022: 6 · 2021: 4 · 2020: 7 · 2019: 14 · 2018: 18 · 2017: 6 · 2016: 8 · 2015: 15 · 2014: 14 · 2013: 15 · 2012: 24
FWCI: 19.47
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Nature Biotechnology (publishedVersion)
PubMed (publishedVersion)
Funders: National Cancer Institute (CA 57345)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords: LongSAGE, serial analysis of gene expression, transcriptome, genome annotation, gene discovery, exon identification, expressed genes, human genome annotation, sage
MeSH terms: Genetic Techniques, Humans, Models, Genetic, RNA, Messenger, Software, Human Genome Project, Genome, DNA, Complementary, Reverse Transcriptase Polymerase Chain Reaction

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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Using the transcriptome to annotate the genome

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