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A computational analysis of sequence features involved in recognition of short introns
Open accessAbstract
Splicing of short introns by the nuclear pre-mRNA splicing machinery is thought to proceed via an “intron definition” mechanism, in which the 5′ and 3′ splice sites (5′ss, 3′ss, respectively) are initially recognized and paired across the intron. Here, we describe a computational analysis of sequence features involved in recognition of short introns by using available transcript data from five eukaryotes with complete or nearly complete genomic sequences. The information content of five different transcript features was measured by using methods from information theory, and Monte Carlo simulations were used to determine the amount of information required for accurate recognition of short introns in each organism. We conclude: ( i ) that short introns in Drosophila melanogaster and Caenorhabditis elegans contain essentially all of the information for their recognition by the splicing machinery, and computer programs that simulate splicing specificity can predict the exact boundaries of ≈95% of short introns in both organisms; ( ii ) that in yeast, the 5′ss, branch signal, and 3′ss can accurately identify intron locations but do not precisely determine the location of 3′ cleavage in every intron; and ( iii ) that the 5′ss, branch signal, and 3′ss are not sufficient to accurately identify short introns in plant and human transcripts, but that specific subsets of candidate intronic enhancer motifs can be identified in both human and Arabidopsis that contribute dramatically to the accuracy of splicing simulators.
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Cites
Genome-wide bioinformatic and molecular analysis of introns in Saccharomyces cerevisiae
SPINGOLA, M., GRATE, L., HAUSSLER, D., & ARES, M. (1999) · RNA · doi:10.1017/s1355838299981682 · Cited by 316
Cited by
Korf, I. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-59 · Cited by 3,192
GMAP: A genomic mapping and alignment program for mRNA and EST sequences
Wu, T. D., & Watanabe, C. K. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti310 · Cited by 2,354
Intronic microRNA precursors that bypass Drosha processing
Ruby, J. G., Jan, C. H., & Bartel, D. P. (2007) · Nature · doi:10.1038/nature05983 · Cited by 1,722
Gene prediction with a hidden Markov model and a new intron submodel
Stanke, M., & Waack, S. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg1080 · Cited by 1,439
Non–coding RNA genes and the modern RNA world
Eddy, S. R. (2001) · Nature Reviews Genetics · doi:10.1038/35103511 · Cited by 1,426
Metadata
- Authors
- Lim, L. P., & Burge, C. B.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2001-09-25
- Volume
- 98
- Issue
- 20
- Pages
- 11193-11198
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2088440342
- Cited by
- 374
- References
- 1
- FWCI
- 6.73
- Type
- journal article
- Language
- en
- Open access
- green
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