Computational Analysis Predicts Hundreds of Coding lncRNAs in Zebrafish.

Shital Kumar Mishra,Han Wang

doi:10.3390/biology10050371

Abstract

Simple SummaryNoncoding RNAs (ncRNAs) regulate a variety of fundamental life processes such as development, physiology, metabolism and circadian rhythmicity. RNA-sequencing (RNA-seq) technology has facilitated the sequencing of the whole transcriptome, thereby capturing and quantifying the dynamism of transcriptome-wide RNA expression profiles. However, much remains unrevealed in the huge noncoding RNA datasets that require further bioinformatic analysis. In this study, we applied six bioinformatic tools to investigate coding potentials of approximately 21,000 lncRNAs. A total of 313 lncRNAs are predicted to be coded by all the six tools. Our findings provide insights into the regulatory roles of lncRNAs and set the stage for the functional investigation of these lncRNAs and their encoded micropeptides.Recent studies have demonstrated that numerous long noncoding RNAs (ncRNAs having more than 200 nucleotide base pairs (lncRNAs)) actually encode functional micropeptides, which likely represents the next regulatory biology frontier. Thus, identification of coding lncRNAs from ever-increasing lncRNA databases would be a bioinformatic challenge. Here we employed the Coding Potential Alignment Tool (CPAT), Coding Potential Calculator 2 (CPC2), LGC web server, Coding-Non-Coding Identifying Tool (CNIT), RNAsamba, and MicroPeptide identification tool (MiPepid) to analyze approximately 21,000 zebrafish lncRNAs and computationally to identify 2730–6676 zebrafish lncRNAs with high coding potentials, including 313 coding lncRNAs predicted by all the six bioinformatic tools. We also compared the sensitivity and specificity of these six bioinformatic tools for identifying lncRNAs with coding potentials and summarized their strengths and weaknesses. These predicted zebrafish coding lncRNAs set the stage for further experimental studies.

Highlights

The classical view of the central dogma of molecular biology suggests that DNA makes RNA, and RNA makes proteins
LncRNAs do not code for proteins, they play regulatory roles in important biological processes, such as immune response [6,7], cellular growth and development [8]
We applied six state-of-the-art bioinformatic suites: Coding Potential Alignment Tool (CPAT) [27], Coding Potential Calculator 2 (CPC2) [28,29], LGC web server [30], Coding Identifying Tool (CNIT), RNAsamba [31], and MicroPeptide identification tool (MiPepid) [32] (Table 1) to classify more than 21,000 long-noncoding RNAs (lncRNAs) collected from the ZFLNC [33], Ensembl [34], NONCODE [35], and zflncRNApedia [36] databases

Summary

Introduction

The classical view of the central dogma of molecular biology suggests that DNA makes RNA, and RNA makes proteins. The messenger RNAs (mRNAs) code for proteins by conveying genetic information from the DNA. Approximately 1% of the whole length of a transcriptome encodes for proteins, and much of its nonprotein-coding region encodes various types of functional RNAs [3]. The noncoding RNAs longer than 200 nucleotide base pairs are termed long-noncoding RNAs (lncRNAs) [4]. This somewhat arbitrary limit distinguishes lncRNAs from the small noncoding RNAs (sRNAs) [5]. LncRNAs do not code for proteins, they play regulatory roles in important biological processes, such as immune response [6,7], cellular growth and development [8]

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Conclusion