LongSAGE analysis significantly improves genome annotation: identifications of novel genes and alternative transcripts in the mouse
Abstract
Motivation Owing to its increased tag length, LongSAGE tags are expected to be more reliable in direct assignment to genome sequences. Therefore, we evaluated the use of LongSAGE data in genome annotation by using our LongSAGE dataset of 202 015 tags (consisting of 41 718 unique tags), experimentally generated from mouse embryonic tail libraries. Results A fraction of LongSAGE tags could not be unambiguously assigned to its gene, due to the presence of widely conserved sequences downstream of particular CATG anchor sites. The presence of alternative forms of transcripts was confirmed in 45% of all detected genes. Surprisingly, a large fraction of LongSAGE tags with hits to the genome (66%) could not be assigned to any gene annotated in EnsEMBL. Among such cases, 2098 LongSAGE tags fell into a region containing a putative gene predicted by GenScan, providing experimental evidence for the presence of real genes, while 9112 genes were found out to be left out or wrongly annotated by the EnsEMBL pipeline. Conclusions LongSAGE transcriptome data can significantly improve the genome annotation by identifying novel genes and alternative transcripts, even in the case of thus far best-characterized organisms like the mouse. Contact imai@gsf.de.
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The longSAGE protocol generates tags that are 21 bp long and provides enhanced efficiency and accuracy of tag-to-gene mapping.
“SAGE has been improved by the development of a longSAGE protocol, which generates tags that are 21 bp long and provides enhanced efficiency and accuracy of tag-to-gene mapping [30-32].”
From A systematic screen for genes expressed in definitive endoderm by Serial Analysis of Gene Expression (SAGE) (2007) · cites this paper as [30]
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Using the transcriptome to annotate the genome
Saha, S., Sparks, A. B., Rago, C., Akmaev, V., Wang, C. J., Vogelstein, B., Kinzler, K. W., & Velculescu, V. E. (2002) · Nature Biotechnology · doi:10.1038/nbt0502-508 · Cited by 630 · see citing works
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Hou, J., Charters, A. M., Lee, S. C., Zhao, Y., Wu, M. K., Jones, S. J., Marra, M. A., & Hoodless, P. A. (2007) · BMC Developmental Biology · doi:10.1186/1471-213x-7-92 · Cited by 56 · see citing works
“SAGE has been improved by the development of a longSAGE protocol, which generates tags that are 21 bp long and provides enhanced efficiency and accuracy of tag-to-gene mapping [30-32].”
Method
- Authors
- Wahl, M. B., Heinzmann, U., & Imai, K.
- Affiliations
- Helmholtz Munich (DE)
- ORCID
- Heinzmann, U.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-12-10
- Volume
- 21
- Issue
- 8
- Pages
- 1393-1400
- ISSN
- 0266-7061 (ISSN-L)
- 1367-4803
- 1460-2059
- OpenAlex
- W2165640100
- Cited by
- 29
- References
- 1
- Citations by year
- 2020: 1 · 2015: 1 · 2013: 1 · 2012: 1
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer applications in the biosciences (publishedVersion)
- PubMed (publishedVersion)
- Site cant be reached (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- LongSAGE, genome annotation, gene discovery, splice variants, mice, transcriptome, Ensembl, GENSCAN, gene prediction
- MeSH terms
- Algorithms, Animals, Chromosome Mapping, Exons, Mice, Inbred C57BL, Transcription Factors, DNA, Antisense, Sequence Alignment, Alternative Splicing, Sequence Analysis, DNA, Gene Expression Profiling, Databases, Genetic, Mice
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