A Comprehensive Study of Target Prediction Algorithms for Animal MicroRNAs(miRNAs)

Abstract

The discovery of microRNAs has been a path-breaking step in understanding the full scope of post-transcriptional gene regulation. The microRNAs (miRNAs) are highly conserved, non-coding short ribonucleic acid (RNA) molecules, approximately 22 nucleotides long [6] and are found in all eukaryotic cells, except fungi and marine plants. MicroRNAs (miRNAs) post-transcriptionally regulate the expression of target genes by binding to complementary sequences on target messenger RNA transcripts, usually resulting in translational repression and thus inhibition of the expression of target mRNAs. Complete complementarity between miRNA:mRNA pairs is rare in mammals, but as little as a 6 bp match with the target mRNA can be sufficient to suppress the gene expression [8]. MicroRNAs, which were initially determined as moderate biological modifiers, have now emerged as powerful regulators of diverse cellular processes with important roles in tissue remodeling [9]. It throws light into the causes of diseases like lymphoma, leukemia, cancers and many cardiac problems where miRNA:mRNA pairing is found to play crucial roles [5]. Many computational methods are being developed to identify the relationship between the animal miRNAs and their target mRNAs. Here we study two of those recent methods to identify the target mRNAs of existing animal miRNAs.

Identification of microRNA-like RNAs from Trichoderma asperellum DQ-1 during its interaction with tomato roots using bioinformatic analysis and high-throughput sequencing

“…MicroRNAs (miRNAs), small non-coding RNAs and approximately 22 nt in length, can negatively regulate gene expression and have been discovered in animals and plants [1]. In animals, miRNAs interact with their target genes through imprecise base pairing, leading to inhibition of translation [2]. However, in plants, miRNAs often repress target mRNAs by interacting with their target genes through near-perfect complementarity [3].…”