Next Generation Approach of Biological Data Analysis through in silico Prediction and Analysis of Small ncRNA-RNA Interactions in Human Tissues

Sep 11, 2026

This study investigates small non-coding RNA analysis by identifying micro RNAs (miRNAs) and other sncRNAs to reveal tissue-specific RNA-RNA interactions linked to particular diseases. miRNAs are detected using miRDeep2, while sncRNAs are obtained through DASHR for information and high-throughput validation. Tissue interaction profiling across six healthy human tissues is derived from RAID. Results include 777 miRNAs with tissue-level expression, 1560 sncRNAs across all tissues, and 502 interactions with 229 liver-specific interactions.

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Abstract

Introduction

Small ncRNAs and long non-coding RNAs

Rationale for in-silico interaction analysis

Materials and Methods

Datasets of human tissues

Next Generation Approach of Biological Data Analysis through in silico Prediction and Analysis of Small ncRNA-RNA Interactions in Human Tissues Imon Chakraborty 1 and Shohini Chakraborty2, * 1 School of Bioscience and Engineering, Jadavpur University, Kolkata, WB, 700032; 2 Botany Department, University of Gour Banga, Malda, 732103, West Bengal, India Received November 25, 2018; Revised January 1, 2019; Accepted January 15, 2019 Abstract This study investigates the analysis of small non-coding RNAs based on the identification of micro RNAs (miRNAs) and other small non-coding RNAs (sncRNAs) to study tissue-specific interactions which lead to specific diseases. The RNARNA interaction revealed the tissue specificity to understand the impact on human health. miRNAs were identified using miRDeep2, and other sncRNAs were identified using the Database of Small Human non-coding RNAs (DASHR) which gave the information on sncRNAs and a high throughput validation. Moreover, the RNA Association Interaction Database (RAID) gave the profiled interactions data of sncRNAs for six different healthy human tissues. The results show the identification of a total of 777 miRNAs and their level of expression in each tissue. In the DASHR analysis, 1560 small ncRNAs were found in all of the tissues. miRNAs and other small ncRNAs expressions were visualized using the R software-based Heatmap. RAID detailed 502 interactions with 229 tissue-specific interactions in the liver from 85 miRNAsand 102 small ncRNAs. The In silico analysis was suggested to describe the non-coding RNAs tissue-specific interactions during healthy conditions which might be associated with disease conditions. Keywords: Biological data analysis, In-silico, miRNA, non-coding RNA, RNA-RNA interaction. 1. Introduction Ribonucleic acid (RNA) is one of the three major biological macromolecules that are fundamental for all known forms of life (along with DNA and proteins) (Baker et al., 2003) . RNA is a significant macromolecule for cells because it relays information encoded in DNA within the cell as a coding and non-coding segment. The coding part of RNA molecule is translated into proteins according to the RNA's instructions followed by a translation mechanism (Hutvágner et al., 2001) . A non-coding RNA is an RNA molecule that is transcribed from DNA, but is not translated into proteins (Anastasiadou et al., 2018) . In general, non-coding RNAs regulate gene expression at the transcriptional and posttranscriptional levels. These non-coding RNAs can be divided into two main groups: the small ncRNAs (small ncRNAs) and the long non-coding RNAs. The major classes of small ncRNAs are micro RNAs (miRNAs), small nucleolar RNAs (snoRNAs), short interfering RNAs (siRNAs) and PIWI interacting RNAs (piRNAs) (Esteller, 2011) . Small ncRNAs play a role in heterochromatin formation, histone modification, DNA methylation targeting, and gene silencing. Long non-coding RNAs are responsible for chromatin remodeling, transcriptional regulation, post-transcriptional regulation, and as precursors for siRNAs. miRNAs are exigent regulators for many basic cellular processes (Pritchard et al., 2012), hence, a little alteration or deviation in the amount, timing or location of miRNA expression can have larger effects on cell and organisms’ growth. The analyses of primary, precursor, and mature miRNA levels as well as the identification and characterization of miRNA targets are crucial for determining the biogenesis or functional changes of miRNAs due to a particular mutant or disease (Van Wynsberghe et al., 2011) . Small nucleolar RNAs (snoRNAs) primarily guide chemical modifications of other RNAs. They are also associated with small nucleolar ribonucleoprotein particles (snoRNPs) where they serve as guide molecules in the post-transcriptional modification of ribosomal RNA (rRNA) and small nuclear RNA (snRNA) . siRNAs function in an analogous way to miRNAs to mediate posttranscriptional

FAQs

How are miRNAs identified in this study?

miRNAs are identified using miRDeep2, which applies a probabilistic model of miRNA biogenesis to score sequenced RNA compatibility with miRNA precursor secondary structure.

Which databases are used for sncRNA identification and interaction profiling?

DASHR is used to identify and validate other sncRNAs, and RAID is used to profile RNA-RNA interactions across healthy human tissues.

What main results are reported for human tissues?

The study reports 777 miRNAs with tissue-specific expression levels, 1560 sncRNAs found across all tissues, and 502 total interactions including 229 tissue-specific interactions in the liver.

Sep 11, 2026

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