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Current Bioinformatics

Editor-in-Chief

ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

Delineating Characteristic Sequence and Structural Features of Precursor and Mature Piwi-interacting RNAs of Epithelial Ovarian Cancer

Author(s): Garima Singh, Arpit Chandan Swain and Bibekanand Mallick*

Volume 16, Issue 4, 2021

Published on: 15 July, 2020

Page: [541 - 552] Pages: 12

DOI: 10.2174/1574893615999200715164755

Price: $65

Abstract

Background: Piwi-interacting RNAs (piRNAs) are an amazing class of small noncoding RNAs (sncRNAs) known for its promising role in germline and somatic cells. Myriad functional studies have been performed to unveil the true potential of this class of ncRNAs; however, global features encoded in their sequence and structure have not been explored.

Objectives: We aim to identify the sequence and structural level characteristic features of piRNAs of normal ovary (NO), and two subtypes of epithelial ovarian cancer (EOCa)- endometrioid (ENOCa), and serous ovarian cancer (SOCa) that we had reported earlier and their precursors.

Methods: We have performed sequence analysis of mature piRNAs and their upstream/downstream regions as well as structural analysis of precursor piRNAs (pre-piRNAs) by examining their minimal folding energy (MFE), adjusted minimal folding energy (AMFE) and minimal folding energy index (MFEI) etc. using in silico approaches.

Results: We observed enrichment of U at first position and G at several other positions of mature piRNAs, which might be associated with the processing of mature piRNAs similar to what is seen in the case of miRNAs and strong target binding, respectively. In addition, we found the richness of AU in and around 20 nts upstream and downstream of precursor piRNAs (pre-piRNAs). This characteristic feature of pre-piRNAs possibly contributes to lower MFE compared to random sequences and make its secondary structure less stable which decides biogenesis of piRNAs. We also noticed that MFE, AMFE and MFEI of pre-piRNAs are comparatively less than pre-miRNAs of metazoans, plants and viruses reported in other studies, which clearly discriminate pre-piRNAs from other RNA sequences including pre-miRNAs of other organisms.

Conclusion: In summary, the present study reveals key characteristic features encoded within and around mature piRNAs as well as pre-piRNAs of NO and EOCa samples that distinguish piRNAs from miRNAs and other random RNA sequences. These findings might act as a cornerstone for a better understanding of biogenesis and function of piRNAs as well as will aid in easier identification of new piRNAs from unknown stretch of sequences using the characteristic features.

Keywords: piRNA, miRNA, pre-piRNA, genomics, delineating, ovarian cancer.

Graphical Abstract

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