Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs
Open accessAbstract
Motivation: Several results in the literature suggest that biologically interesting RNAs have secondary structures that are more stable than expected by chance. Based on these observations, we developed a scanning algorithm for detecting noncoding RNA genes in genome sequences, using a fully probabilistic version of the Zuker minimum-energy folding algorithm. Results: Preliminary results were encouraging, but certain anomalies led us to do a carefully controlled investigation of this class of methods. Ultimately, our results argue that for the probabilistic model there is indeed a statistical effect, but it comes mostly from local base-composition bias and not from RNA secondary structure. For the thermodynamic implementation (which evaluates statistical significance by doing Monte Carlo shuffling in fixed-length sequence windows, thus eliminating the base-composition effect) the signals for noncoding RNAs are still usually indistinguishable from noise, especially when certain statistical artifacts resulting from local base-composition inhomogeneity are taken into account. We conclude that although a distinct, stable secondary structure is undoubtedly important in most noncoding RNAs, the stability of most noncoding RNA secondary structures is not sufficiently different from the predicted stability of a random sequence to be useful as a general genefinding approach. Contact: eddy@genetics.wustl.edu * To whom correspondence should be addressed.
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Compositional bias toward GC-rich sequences may be a reasonable criterion for identifying non-coding RNAs in the genome due to the effect on folding stability.
“For example, compositional bias toward GC-rich sequences may be a reasonable criterion for identifying non-coding RNAs in the genome due to the effect on folding stability (67)”
From Prebiotically plausible mechanisms increase compositional diversity of nucleic acid sequences (2012) · cites this paper as [67]
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Self-citation
- Authors
- Rivas, E., & Eddy, S. R.
- Affiliations
- Washington University in St. Louis (US)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2000-07-01
- Volume
- 16
- Issue
- 7
- Pages
- 583-605
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2088938573
- Cited by
- 279
- References
- 51
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 7 · 2020: 5 · 2019: 4 · 2018: 7 · 2017: 6 · 2016: 12 · 2015: 11 · 2014: 8 · 2013: 14 · 2012: 13
- FWCI
- 3.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Alfred P. Sloan Foundation
- National Institutes of Health
- National Human Genome Research Institute (HG01363, R01HG001363)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- 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
- Keywords
- RNA secondary structure, RNA folding, statistical significance, base composition bias
- MeSH terms
- Algorithms, Animals, Base Composition, Data Interpretation, Statistical, Nucleic Acid Conformation, RNA, Models, Statistical, Methanococcus, Caenorhabditis elegans, RNA, Helminth
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