Gene expression
Cataloging mammalian circular RNAs
Open access · cc by · source: Europe PMC
Thousands of mammalian circRNAs arise by back-splicing and can be quantified across ENCODE cell types.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Protocol choice decides which molecules even appear. A computational pipeline on non-poly(A) RNA-seq was required to catalogue mammalian circular RNAs via back-splice junctions; most confident circRNAs used canonical GT-AG splice signals, and circular fractions varied by locus and cell type. A standard poly(A) mRNA-seq experiment would have missed them.
Evidence for the claim as stated.
Reference-guided counting and de novo assembly are not interchangeable products. CircRNA detection needed non-poly(A) libraries and back-splice calling; Aloe and sea bass papers assemble transcripts because a complete reference is missing or incomplete; LCL and tomato papers quantify against known genes. Treating every RNA-seq paper as a gene-count table hides those design choices.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Reference-guided counting and de novo assembly are not interchangeable products. CircRNA detection needed non-poly(A) libraries and back-splice calling; Aloe and sea bass papers assemble transcripts because a complete reference is missing or incomplete; LCL and tomato papers quantify against known genes. Treating every RNA-seq paper as a gene-count table hides those design choices.
- Supports · Aloe vera medicinal pathway transcriptome
- Supports · Genetics shapes methylation and expression
Discoveries this paper informs or conflicts with
- Seven matching bases were enough — and the leading predictors were looking for the wrong thing
This paper informs this development.
Study at a glance
- Design
- Computational / modelling — Computational detection of back-splice junctions in non-poly(A) RNA-seq
- N
- Multi-sample circRNA discovery pipeline — no single primary analytic N in stored summary
- Population
- Mammalian non-poly(A) RNA-seq libraries
- Outcome
- Expanded catalogue and splice features of circular RNAs
Structured fields used in claim comparison tables when every cited study has a complete layer.
Inspect source passages
Cataloging mammalian circular RNAs
These passages occur verbatim in the stored paper text. They support the points listed below; they do not verify every statement in the explanation.
Mammalian circular RNAs.
Background Many classes of non-protein-coding RNAs (ncRNAs) exist in cells [,], and members of each class play important roles in either regulating gene expression or other biological processes [–].
Back-splicing of pre-mRNA.
For example, microRNAs (miRNAs) pair to sites within messenger RNAs (mRNAs) to target the mRNAs for translational repression and/or mRNA destabilization [].
Key findings
Most confident circRNAs use canonical GT-AG splice signals; circular fractions vary by locus and cell type.
Methodology
Built a computational pipeline on non-poly(A) RNA-seq to detect back-splice junctions and circular fractions.
Limitations
Does not prove sponge function for most newly found circRNAs.
Related papers in this topic
Same topic cluster — not a recommendation engine.