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PreprintCited by 0RNA Research and SplicingGenomics and Phylogenetic StudiesRNA and protein synthesis mechanisms

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PRIME-BSPre: A genome-wide protein-RNA binding sites prediction method based on templates

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Wei, Xinhang, Duan, Yingtian, Li, Danyang, Liu, Xudong, Xie, Juan, Liu, Shiyong·2023·BMC Genomics
DOI 10.1101/2023.10.08.561403PMC PMC13032426

Preprint — published as 10.1186/s12864-026-12657-3 · Paper page

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Abstract

Identification of RNA binding sites that potentially interact with RNA-binding proteins facilitates a comprehensive analysis of protein-RNA interactions and enables further investigation into the mechanisms underlying RNA splicing and modification. However, the current experimental data remains limited in comparison to the vast family of RBPs, and deep learning prediction methods are inadequate for those RBPs lacking sufficient interaction data for training. Therefore, we present PRIME-BSPre, a genome-wide method for predicting protein-RNA binding sites based on templates that incorporate both RNA sequence and secondary structure as well as the tertiary structure of corresponding RBPs. We have successfully benchmarked our method on the human genome, demonstrating excellent prediction performance on RBP datasets beyond our library and robustness across cell lines. Additionally, we are pioneers in introducing the low Shannon entropy algorithm to describe binding preferences of RNA motifs. Our predicted results further support the hypothesis that RBPs preferentially bind RNA motifs with low complexity.

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Fig. 1 Workflow of PRIME-BSPre. The input target is aligned with all the templates in template library. Tertiary structure similarity of RBPs, binding preference of binding sites, global and local similarity of RNA sequences and secondary structure are considered in PRIME-BSPre scoring methods. The alignment results are initially ranked by the LS-Scores and five best alignments are finally selected by the LS-PEAK as the prediction results
Fig. 1 Workflow of PRIME-BSPre. The input target is aligned with all the templates in template library. Tertiary structure similarity of RBPs, binding preference of binding sites, global and local similarity of RNA sequences and secondary structure are considered in PRIME-BSPre scoring methods. The alignment results are initially ranked by the LS-Scores and five best alignments are finally selected by the LS-PEAK as the prediction resultsCC BY · PubMed Central
Fig. 2 Local secondary structure and sequence features extracted on RNA binding sites. The pink-shaded region in the RNA secondary structure represents the binding sites, while LS-Score quantitatively assesses sequence and secondary structure similarities within this area between templates and targets. A The secondary structure HAIRPIN LOOP, which exhibits typical characteristics, is depicted along with its quantitative features. B The secondary structure MULTIPLE LOOP, which exhibits another characteristic feature, is depicted along with its corresponding quantitative attributes. C shows the Sequence features of native and predicted RNA binding sites: Motif Structure, Motif Sequence and Motif Set. Among them, Motif Structure is the Position Probability Matrices (PPMs) generated by serialized secondary structure features: B (Bulge), E (External strand), H (Hairpin loop), M (Multiple loop) and S (Stem); Motif set is a sequential description of all binding preference motifs, where each base represents the base enriched in motifs
Fig. 2 Local secondary structure and sequence features extracted on RNA binding sites. The pink-shaded region in the RNA secondary structure represents the binding sites, while LS-Score quantitatively assesses sequence and secondary structure similarities within this area between templates and targets. A The secondary structure HAIRPIN LOOP, which exhibits typical characteristics, is depicted along with its quantitative features. B The secondary structure MULTIPLE LOOP, which exhibits another characteristic feature, is depicted along with its corresponding quantitative attributes. C shows the Sequence features of native and predicted RNA binding sites: Motif Structure, Motif Sequence and Motif Set. Among them, Motif Structure is the Position Probability Matrices (PPMs) generated by serialized secondary structure features: B (Bulge), E (External strand), H (Hairpin loop), M (Multiple loop) and S (Stem); Motif set is a sequential description of all binding preference motifs, where each base represents the base enriched in motifsCC BY · PubMed Central
Fig. 3 LS-PEAK on ATF4_ENST00000680748.1 with native seCLIP-seq binding sites. The upper blue histogram shows the base-resolution LS-Score along ATF4_ENST00000680748.1, where the height of each blue bar represents the LS-Score at the corresponding nucleotide position (higher bars indicate higher inferred binding preference). The gray shaded vertical window indicates the LS-PEAK region selected in this example: it is defined as a contiguous segment where LS-Scores exceed the mean LS-Score of this transcript (used here as the cutoff), and it corresponds to the candidate region carried forward for template screening. Protein labels above the histogram (e.g., PRPF39, BUD13) mark the RBPs whose native binding sites are shown for comparison at the corresponding genomic positions. The lower track displays the seCLIP-seq-supported native binding site intervals on the same transcript/locus (shown as the labeled binding segment aligned to the coordinate axis), enabling direct visual comparison between the predicted LS-PEAK window (gray shaded) and the experimentally observed binding locations
Fig. 3 LS-PEAK on ATF4_ENST00000680748.1 with native seCLIP-seq binding sites. The upper blue histogram shows the base-resolution LS-Score along ATF4_ENST00000680748.1, where the height of each blue bar represents the LS-Score at the corresponding nucleotide position (higher bars indicate higher inferred binding preference). The gray shaded vertical window indicates the LS-PEAK region selected in this example: it is defined as a contiguous segment where LS-Scores exceed the mean LS-Score of this transcript (used here as the cutoff), and it corresponds to the candidate region carried forward for template screening. Protein labels above the histogram (e.g., PRPF39, BUD13) mark the RBPs whose native binding sites are shown for comparison at the corresponding genomic positions. The lower track displays the seCLIP-seq-supported native binding site intervals on the same transcript/locus (shown as the labeled binding segment aligned to the coordinate axis), enabling direct visual comparison between the predicted LS-PEAK window (gray shaded) and the experimentally observed binding locationsCC BY · PubMed Central
Fig. 4 Prediction results compared with other methods on different cell lines. MCC of the prediction results of PRIME-BSPre, compared with PRIME-3D2D, PrismNet on the cell line K562 and the cell line HepG2 over 158 RBP-RNA test pairs. The box line plot shows overall results on different methods
Fig. 4 Prediction results compared with other methods on different cell lines. MCC of the prediction results of PRIME-BSPre, compared with PRIME-3D2D, PrismNet on the cell line K562 and the cell line HepG2 over 158 RBP-RNA test pairs. The box line plot shows overall results on different methodsCC BY · PubMed Central
Fig. 5 Comparison with PrismNet on different cell lines. A-B Comparison of PRIME-BSPre with PrismNet in different cell lines. Dot plots depict the performance of all RNAs in each RBP, as predicted by PRIME-BSPre and PrismNet
Fig. 5 Comparison with PrismNet on different cell lines. A-B Comparison of PRIME-BSPre with PrismNet in different cell lines. Dot plots depict the performance of all RNAs in each RBP, as predicted by PRIME-BSPre and PrismNetCC BY · PubMed Central

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Research works printed but not linked: 41

  1. 10.1186/gb-2009-10-3-r30 · DOI
  2. 10.1038/nbt.3300 · DOI · Paper page
  3. 10.1016/j.molcel.2012.05.021 · DOI
  4. 10.1038/s41596-022-00680-z · DOI
  5. 10.1093/bfgp/elu047 · DOI
  6. 2017, RNAcompete-S: Combined RNA sequence/structure preferences for RNA binding proteins derived from a single-step in vitro selection, Methods, 126, 18, 10.1016/j.ymeth.2017.06.024 · DOI
  7. 10.1093/NAR/GKAB1049 · DOI · Paper page
  8. Danecek P , Bonfield JK , Liddle J , Marshall J , Ohan V , Pollard MO , Whitwham A , Keane T , McCarthy SA , Davies RM et al. 2021. Twelve years of SAMtools and BCFtools. Gigascience 10. · DOI
  9. 10.1371/journal.pgen.1002384 · DOI
  10. 10.1093/nar/gkg938 · DOI
  11. 10.1016/j.molcel.2018.05.001 · DOI · Paper page
  12. 10.1093/nar/gkac243 · DOI
  13. 10.1038/nrg3778 · DOI · Paper page
  14. 2021, Repetitive DNA: genomic dark matter matters, Nat Rev Genet, 22, 342, 10.1038/s41576-021-00354-8 · DOI
  15. 10.1038/nrg3813 · DOI · Paper page
  16. 10.1016/j.cell.2010.03.009 · DOI · Paper page
  17. 10.1093/nar/gkl544 · DOI
  18. 10.1371/journal.pcbi.1000832 · DOI
  19. 10.1038/nsmb.1838 · DOI · Paper page
  20. 10.1016/j.molcel.2014.04.016 · DOI
  21. 10.1038/35057062 · DOI · Paper page
  22. 2022, PRIESSTESS: interpretable, high-performing models of the sequence and structure preferences of RNA-binding proteins, Nucleic Acids Res, 50, e111, 10.1093/nar/gkac694 · DOI
  23. 2022, Systematic identification of NF90 target RNAs by iCLIP analysis, Sci Rep, 12, 364, 10.1038/s41598-021-04101-1 · DOI
  24. 10.1093/nar/gkz1062 · DOI
  25. 10.1186/gb-2014-15-1-r17 · DOI
  26. 10.1093/bioinformatics/btw259 · DOI
  27. 10.1093/nar/gku406 · DOI
  28. 10.1038/nature12311 · DOI · Paper page
  29. 10.1186/1471-2105-11-129 · DOI
  30. 2015, Erratum: Structural imprints in vivo decode RNA regulatory mechanisms, Nature, 527, 264, 10.1038/nature15717 · DOI
  31. 10.1038/nature14263 · DOI
  32. 10.1038/sj.embor.7400325 · DOI · Paper page
  33. 2021, Predicting dynamic cellular protein-RNA interactions by deep learning using in vivo RNA structures, Cell Res, 31, 495, 10.1038/s41422-021-00476-y · DOI
  34. 2016, RNA Sequence Context Effects Measured In Vitro Predict In Vivo Protein Binding and Regulation, Mol Cell, 64, 294, 10.1016/j.molcel.2016.08.035 · DOI
  35. 10.1038/s41586-020-2077-3 · DOI · Paper page
  36. 10.1038/nmeth.3810 · DOI · Paper page
  37. 10.1093/NAR/GKAB1061 · DOI · Paper page
  38. 10.1261/rna.029041.111 · DOI
  39. 2020, PRIME-3D2D is a 3D2D model to predict binding sites of protein-RNA interaction, Commun Biol, 3, 384, 10.1038/s42003-020-1114-y · DOI
  40. 10.1093/nar/gkad353 · DOI
  41. 10.1093/nar/gki524 · DOI · Paper page

Metadata

Authors
Wei, X., Duan, Y., Li, D., Liu, X., Xie, J., & Liu, S.
Affiliations
Huazhong University of Science and Technology (CN)
Corresponding author
Liu, Shiyong
ORCID
Venue
BMC Genomics
Publisher
openRxiv
Published
2023-10-10
Volume
27
Issue
1
ISSN
1471-2164 (ISSN-L)
DOI
10.1101/2023.10.08.561403
PMC
PMC13032426
OpenAlex
W7130849569
Cited by
0
References
1
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • BMC Genomics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (32271267)
  • Huazhong University of Science and Technology
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
Keywords
RNA-binding proteins, template-based modeling, RNA secondary structure, RNA tertiary structure, RNA motifs, genomic prediction, human genome
MeSH terms
Prediction Algorithms, Algorithms, Binding Sites, Humans, Nucleic Acid Conformation, Protein Binding, RNA, Genome, Human, RNA-Binding Proteins, Computational Biology, Genomics

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CoChat. (2026). Citation check: PRIME-BSPre: A genome-wide protein-RNA binding sites prediction method based on templates. https://app.cochat.ai/papers/10.1101/2023.10.08.561403
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Wei, X., Duan, Y., Li, D., Liu, X., Xie, J., & Liu, S. (2023). PRIME-BSPre: A genome-wide protein-RNA binding sites prediction method based on templates. BMC Genomics. https://doi.org/10.1101/2023.10.08.561403