PIWI-interacting RNAs in human diseases: databases and computational models

Author:

Zhang Tianjiao1,Chen Liang2ORCID,Li Rongzhen1,Liu Ning1,Huang Xiaobing1,Wong Garry1ORCID

Affiliation:

1. Faculty of Health Sciences, University of Macau , Taipa, Macau S.A.R. 999078, China

2. Department of Computer Science, School of Engineering, Shantou University , Shantou, China

Abstract

Abstract PIWI-interacting RNAs (piRNAs) are short 21–35 nucleotide molecules that comprise the largest class of non-coding RNAs and found in a large diversity of species including yeast, worms, flies, plants and mammals including humans. The most well-understood function of piRNAs is to monitor and protect the genome from transposons particularly in germline cells. Recent data suggest that piRNAs may have additional functions in somatic cells although they are expressed there in far lower abundance. Compared with microRNAs (miRNAs), piRNAs have more limited bioinformatics resources available. This review collates 39 piRNA specific and non-specific databases and bioinformatics resources, describes and compares their utility and attributes and provides an overview of their place in the field. In addition, we review 33 computational models based upon function: piRNA prediction, transposon element and mRNA-related piRNA prediction, cluster prediction, signature detection, target prediction and disease association. Based on the collection of databases and computational models, we identify trends and potential gaps in tool development. We further analyze the breadth and depth of piRNA data available in public sources, their contribution to specific human diseases, particularly in cancer and neurodegenerative conditions, and highlight a few specific piRNAs that appear to be associated with these diseases. This briefing presents the most recent and comprehensive mapping of piRNA bioinformatics resources including databases, models and tools for disease associations to date. Such a mapping should facilitate and stimulate further research on piRNAs.

Funder

Faculty of Health Sciences, University of Macau

National Natural Science Foundation of China

Li Ka Shing Foundation Cross-Disciplinary Research

STU Scientific Research Foundation for Talents

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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