Nucleic Acids ResearchBioinformaticsPeer-reviewed journal article
bpRNA: Large-scale Automated Annotation and Analysis of RNA Secondary Structure
Padideh Danaee, Mason N. RouchesiD, Michelle W. WileyiD, Dezhong Deng, Liang HuangiD, David A. HendrixiD
Abstract
While RNA secondary structure prediction from sequence data has made remarkable progress, there is a need for improved strategies for annotating the features of RNA secondary structures. Here we present bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with the positions, sequence, and flanking base pairs of each such structural feature. We also introduce several new informative representations of RNA structure types to improve structure visualization and interpretation. We have further used bpRNA to generate a web-accessible meta-database, \"bpRNA-1m\", of over 100,000 single-molecule, known secondary structures; this is both more fully and accurately annotated and over 20-times larger than existing databases. We use a subset of the database with highly similar ([≥]90% identical) sequences filtered out to report on statistical trends in sequence, flanking base pairs, and length. Both the bpRNA method and the bpRNA-1m database will be valuable resources both for specific analysis of individual RNA molecules and large-scale analyses such as are useful for updating RNA energy parameters for computational thermodynamic predictions, improving machine learning models for structure prediction, and for benchmarking structure-prediction algorithms.
- assay: long-read sequencing
- research focus: database / resource
- research focus: benchmarking
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 255
- FWCI
- 3.91
- Field percentile
- top 5%
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