LncPlankton: a comprehensive database of candidate lncRNAs from marine microbial eukaryotes

Historically neglected or considered to be mere transcriptional noise, long non-coding RNAs (lncRNAs) are now emerging as central, regulatory molecules in a multitude of eukaryotic species, from animals to plants to fungi. Yet, our knowledge about the occurrence of these molecules in the marine environment is still elusive. To help fill this knowledge gap, we have developed LncPlankton, a comprehensive database of candidate marine lncRNAs. By integrating the predictions derived from 10 distinctive coding potential prediction tools in a majority voting setting, we have identified over 2M potential lncRNAs distributed across 414 marine plankton species from over nine different phyla. A user-friendly, open-access web interface of the database has been implemented to facilitate exploration (https://www.lncplankton.bio.ens.psl.eu/). We believe LncPlankton will serve as a rich resource for studies of lncRNAs, which will contribute to small- and large-scale analyses in a wide range of marine plankton species and allow comparative studies between them and well beyond the marine environment.

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Publication Details

Journal
NAR Genomics and Bioinformatics
Published
2025-10-07
DOI
https://doi.org/10.1093/nargab/lqaf159
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.00

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article

LncPlankton: a comprehensive database of candidate lncRNAs from marine microbial eukaryotes

Chris Bowler, Pierre Vincens, Helena Cruz de Carvalho, Ahmed Debit
NAR Genomics and Bioinformatics
Cancer-related molecular mechanisms research
article

LncPlankton: a comprehensive database of candidate lncRNAs from marine microbial eukaryotes

Chris Bowler, Pierre Vincens, Helena Cruz de Carvalho, Ahmed Debit
article en

Abstract

Historically neglected or considered to be mere transcriptional noise, long non-coding RNAs (lncRNAs) are now emerging as central, regulatory molecules in a multitude of eukaryotic species, from animals to plants to fungi. Yet, our knowledge about the occurrence of these molecules in the marine environment is still elusive. To help fill this knowledge gap, we have developed LncPlankton, a comprehensive database of candidate marine lncRNAs. By integrating the predictions derived from 10 distinctive coding potential prediction tools in a majority voting setting, we have identified over 2M potential lncRNAs distributed across 414 marine plankton species from over nine different phyla. A user-friendly, open-access web interface of the database has been implemented to facilitate exploration (https://www.lncplankton.bio.ens.psl.eu/). We believe LncPlankton will serve as a rich resource for studies of lncRNAs, which will contribute to small- and large-scale analyses in a wide range of marine plankton species and allow comparative studies between them and well beyond the marine environment.

NAR Genomics and BioinformaticsVol. 7(4)
Centre National de la Recherche Scientifique (FR), Inserm (FR), Université Paris-Est Créteil (FR), École Normale Supérieure - PSL (FR), Institut de Biologie de l'École Normale Supérieure (FR)
European Commission, Agence Nationale de la Recherche, Université de Recherche Paris Sciences et Lettres
Openalex Percentile: Top 57%
Cancer-related molecular mechanisms research
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