What is LncPlankton?

An integrated extensive database of long non-coding RNAs in marine protists including Dinoflagelattes, Bacillaryophyta (Diatoms), Haptophytes, Chlorophytes, Bolidophytes, Dictyochophytes and Pelagophytes, to name a few. The aim of LncPlankton is two-fold: first, to explore qualitatively the transcriptome landscape of a broad range of marine planktonic species by predicting the nature of the transcripts and classifying them into three classes: coding-like, lncRNA-like, and sncRNA-like. Second, to provide open information of planktonic lncRNAs such as their coding potential status, nucleotide sequences, expression values, and predicted secondary structure.

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How were lncRNAs predicted?

Data With the aim to do an in depth screen of potential marine lncRNAs, we used several public sources, the major one being the assembled transcriptomic data of 406 eukaryotic microorganisms species representing all major branches of the eukaryotic tree life provided by the Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP) assembling a total of 650 transcriptomes. More details ...

Workflow The majority voting procedure is an ensemble machine learning method combining the predictions of 10 coding potential tools including CPC2, CPAT, LncFinder, LncADeep... The aim is to increase the confidence/robustness of lncRNA prediction, and most importantly to promote the diversity of the ensemble model. Briefly, the nature of the transcripts is predicted by each tool and labeled as “coding” or “non-coding”, and the class with highest number of votes is the outcome. Then, two other filters are applied in order to discriminate between lncRNA-like, sncRNA-like, and coding-like transcripts (transcript length and putative ORF length) More details ...

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Motivation

To fill the gap of knowledge of the lack of information concerning marine lncRNA, we developed LncPlankton V1.0 which is the first comprehensive extensive database of planktonic lncRNAs. A user-friendly Shiny application was also implemented and integrated to LncPlankton V1.0 allowing the user to customize the screening and identification of lncRNAs. In addition, a BLAST service to query LncPlankton V1.0 based on sequence similarity is provided.