ArticleQuantitative biology (Beijing, China)2018
ShapeShifter: a novel approach for identifying and quantifying stable lariat intronic species in RNAseq data.
Article in Quantitative biology (Beijing, China), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Defects in intron recycling suppress the antiviral response via a mechanism of intronic endogenous dsRNA.The Journal of experimental medicine · 2026Article
- DBR1 orchestrates the fate of lariat RNA: debranching-dependent turnover and function.Nucleic acids research · 2025Review
- The debranching enzyme Dbr1 regulates lariat turnover and intron splicing.Nature communications · 2024Article
- Circular stable intronic RNAs possess distinct biological features and are deregulated in bladder cancer.NAR cancer · 2023Article
- Metal content and kinetic properties of yeast RNA lariat debranching enzyme Dbr1.RNA (New York, N.Y.) · 2022Article
- Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data.GigaScience · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
backgroundMost intronic lariats are rapidly turned over after splicing. However, new research suggests that some introns may have additional post-splicing functions. Current bioinformatics methods used to identify lariats require a sequencing read that traverses the lariat branchpoint. This method provides precise branchpoint sequence and position information, but is limited in its ability to quantify abundance of stabilized lariat species in a given RNAseq sample. Bioinformatic tools are needed to better address these emerging biological questions.
methodsWe used an unsupervised machine learning approach on sequencing reads from publicly available ENCODE data to learn to identify and quantify lariats based on RNAseq read coverage shape.
resultsWe developed ShapeShifter, a novel approach for identifying and quantifying stable lariat species in RNAseq datasets. We learned a characteristic "lariat" curve from ENCODE RNAseq data and were able to estimate abundances for introns based on read coverage. Using this method we discovered new stable introns in these samples that were not represented using the older, branchpoint-traversing read method.
conclusionsShapeShifter provides a robust approach towards detecting and quantifying stable lariat species.
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Registered trials
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