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Biocomputational identification and validation of novel microRNAs predicted from bubaline whole genome shotgun sequences.

Abstract：

:MicroRNAs (miRNAs) are small (19-25 base long), non-coding RNAs that regulate post-transcriptional gene expression by cleaving targeted mRNAs in several eukaryotes. The miRNAs play vital roles in multiple biological and metabolic processes, including developmental timing, signal transduction, cell maintenance and differentiation, diseases and cancers. Experimental identification of microRNAs is expensive and lab-intensive. Alternatively, computational approaches for predicting putative miRNAs from genomic or exomic sequences rely on features of miRNAs viz. secondary structures, sequence conservation, minimum free energy index (MFEI) etc. To date, not a single miRNA has been identified in bubaline (Bubalus bubalis), which is an economically important livestock. The present study aims at predicting the putative miRNAs of buffalo using comparative computational approach from buffalo whole genome shotgun sequencing data (INSDC: AWWX00000000.1). The sequences were blasted against the known mammalian miRNA. The obtained miRNAs were then passed through a series of filtration criteria to obtain the set of predicted (putative and novel) bubaline miRNA. Eight miRNAs were selected based on lowest E-value and validated by real time PCR (SYBR green chemistry) using RNU6 as endogenous control. The results from different trails of real time PCR shows that out of selected 8 miRNAs, only 2 (hsa-miR-1277-5p; bta-miR-2285b) are not expressed in bubaline PBMCs. The potential target genes based on their sequence complementarities were then predicted using miRanda. This work is the first report on prediction of bubaline miRNA from whole genome sequencing data followed by experimental validation. The finding could pave the way to future studies in economically important traits in buffalo.

journal_name

Comput Biol Chem

journal_title

Computational biology and chemistry

authors

Manku HK,Dhanoa JK,Kaur S,Arora JS,Mukhopadhyay CS

doi

10.1016/j.compbiolchem.2017.08.005

subject

Has Abstract

pub_date

2017-10-01 00:00:00

pages

96-106

eissn

1476-9271

issn

1476-928X

pii

S1476-9271(16)30295-X

journal_volume

70

pub_type

杂志文章

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