An updated overview and classification of bioinformatics tools for MicroRNA analysis, which one to choose?

Highlights

• Many Tools for miRNAs have been developed.

• Best is to combine miRNA tools results.

• In this review, miRNA-related online tools are classified.

Abstract

The term ‘MicroRNA’ (miRNA) refers to a class of small endogenous non-coding RNAs (ncRNAs) regenerated from hairpin transcripts. Recent studies reveal miRNAs' regulatory involvement in essential biological processes through translational repression or mRNA degradation. Recently, there is a growing body of literature focusing on the importance of miRNAs and their functions. In this respect, several databases have been developed to manage the dispersed data produced. Therefore, it is necessary to know the parameters and characteristics of each database to benefit their data. Besides, selecting the correct database is of great importance to scientists who do not have enough experience in this field. A comprehensive classification along with an explanation of the information contained in each database leads to facilitating access to these resources. In this regard, we have classified relevant databases into several categories, including miRNA sequencing and annotation, validated/predicted miRNA targets, disease-related miRNA, SNP in miRNA sequence or target site, miRNA-related pathways, or gene ontology, and mRNA-miRNA interactions. Hence, this review introduces available miRNA databases and presents a convenient overview to inform researchers of different backgrounds to find suitable miRNA-related bioinformatics web tools and relevant information rapidly.

Introduction

Micro RNAs (miRNAs) are defined as a class of non-coding single-stranded RNAs about ~22 nucleotides in length. Computational predictions have evaluated that over 60% of transcripts in the human genome may be regulated by miRNAs [1]. MiRNAs can bind to specific target mRNAs by selective base–pairing, often in the 3′-untranslated region (3′UTR) and more rarely 5′-untranslated region (5′UTR) [2]. These molecules are involved in regulating gene expression at the post-transcriptional level through translational repression or degradation mechanisms [3]. A miRNA can regulate multiple mRNAs, and conversely, multiple miRNAs can modulate mutual mRNA targets [4,5]. The gene coding miRNAs are usually found in both intergenic and intragenic areas, as well as in sense or antisense strands within introns of genes, and are mostly transcribed by RNA polymerase II [3,6]. The RNA polymerase II (Pol II) produces primary (pri)-miRNA, which is cleaved into smaller stem-looped structures, known as a precursor (pre)–miRNA, by Drosha as an RNase III endonuclease, and its cofactor, DGCR8 [7]. Then, the pre-miRNA is transported from the nucleus to the cytoplasm by Exportin-5 protein and RAN GTPase [8]. Finally, in the cytoplasm, an RNA III-like enzyme called DICER produces mature miRNA from pre-miRNA. According to the complementary degree in connecting with targets, mature miRNAs perform their regulatory function by two posttranscriptional mechanisms: cleavage or repression of the translation of their targeted mRNAs (Fig. 1) [9]. The mechanism of translational repression by miRNAs is not entirely understood, but it is supposed that miRNAs inhibit translation in elongation or termination phases, or destroy the polypeptide released from the ribosome [10,11]. miRNAs might temporarily bind and modify mRNAs, or stably bind to their targets and employ factors mediating translational repression [12]. Also, transcription or splicing of transcripts in the nucleus can be regulated by miRNAs [13,14]. Based on the role of miRNAs in biological processes, disruption in their biogenesis or regulation can lead to diseases [15]. MiRNAs have been investigated in different diseases, including vascular diseases [16], neurological disorders [17,18], and cancers [[19], [20], [21]]. Therefore, identification of miRNAs and their targets can be considered as new diagnostic and therapeutic approaches [13,[22], [23], [24]]. According to technological developments, such as bioinformatics tools/software and sequencing methods, a large number of miRNAs have been identified in various organisms. Based on the latest version of the miRBase (V22), there are more than 48800 different mature miRNA sequences [25,26]. In the past decades, studies on miRNAs and their related fields have increased at a tremendous pace generating a large amount of scattered data. Several bioinformatics tools have been developed to manage these data. These databases can be categorized based on the information they provide for users. However, each database applies different algorithms and parameters that may be difficult to understand for users with little/no experience in this respect. In the present article, we aim to overview the significant classes of miRNA databases, explain essential features of each, and discuss how to select appropriately among them. Overall, we offer some important considerations on using the mentioned tools for miRNA analysis.