ArticleNucleic acids research2018
The discovery potential of RNA processing profiles.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- lncRNA BC200 is processed into a stable Alu monomer.RNA (New York, N.Y.) · 2024Article
- Targeting the initiator to activate both ferroptosis and cuproptosis for breast cancer treatment: progress and possibility for clinical application.Frontiers in pharmacology · 2024Review
- Current Status of Regulatory Non-Coding RNAs Research in the Tritryp.Non-coding RNA · 2022Review
- A Novel Serum tsRNA for Diagnosis and Prediction of Nephritis in SLE.Frontiers in immunology · 2021Article
- Multiple information carried by RNAs: total eclipse or a light at the end of the tunnel?RNA biology · 2020Review
- Pathological significance of tRNA-derived small RNAs in neurological disorders.Neural regeneration research · 2020Article
- RNAs and RNA-Binding Proteins in Immuno-Metabolic Homeostasis and Diseases.Frontiers in cardiovascular medicine · 2019Review
- Transfer RNA-derived fragments and tRNA halves: biogenesis, biological functions and their roles in diseases.Journal of molecular medicine (Berlin, Germany) · 2018Review
- SPAR: small RNA-seq portal for analysis of sequencing experiments.Nucleic acids research · 2018Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.