Read-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets. We randomly selected up to 30 candidate read-through chimeras predicted from each software method and experimentally validated a total of 109 read-throughs and on this set, RTCpredictor outperformed all the other methods. In addition, RTCpredictor ( https://github.com/sandybioteck/RTCpredictor ) has less memory requirements and faster execution time.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9915620 | PMC |
http://dx.doi.org/10.1101/2023.02.02.526869 | DOI Listing |
Nat Commun
January 2025
Department of Medicinal Chemistry, University of Kansas, Lawrence, USA.
One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) which are often essential for viral replication, transcription, or translation. In this report, we discovered a series of coumarin derivatives that bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a sequencing-based method namely cgSHAPE-seq, in which an acylating probe was directed to crosslink with the 2'-OH group of ribose at the binding site to create read-through mutations during reverse transcription.
View Article and Find Full Text PDFBrief Bioinform
May 2024
Department of Pathology, School of Medicine, University of Virginia, Charlottesville, VA 22908, United States.
Read-through chimeric RNAs are being recognized as a means to expand the functional transcriptome and contribute to cancer tumorigenesis when mis-regulated. However, current software tools often fail to predict them. We have developed RTCpredictor, utilizing a fast ripgrep tool to search for all possible exon-exon combinations of parental gene pairs.
View Article and Find Full Text PDFFront Immunol
September 2023
Department of Biology & Biochemistry, University of Houston, Houston, TX, United States.
Introduction: We present here a strategy to identify immunogenic neoantigen candidates from unique amino acid sequences at the junctions of fusion proteins which can serve as targets in the development of tumor vaccines for the treatment of breastcancer.
Method: We mined the sequence reads of breast tumor tissue that are usually discarded as discordant paired-end reads and discovered cancer specific fusion transcripts using tissue from cancer free controls as reference. Binding affinity predictions of novel peptide sequences crossing the fusion junction were analyzed by the MHC Class I binding predictor, MHCnuggets.
bioRxiv
October 2023
Department of Medicinal Chemistry, University of Kansas, Lawrence, KS, USA.
One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) in their genomes. These conserved RNA structures are often essential for viral replication, transcription, or translation. In this report, we discovered and optimized a new type of coumarin derivatives, such as and , which bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome.
View Article and Find Full Text PDFRead-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!