Computational annotation of miRNA transcription start sites

Author:

Wang Saidi1,Talukder Amlan1,Cha Mingyu1,Li Xiaoman2,Hu Haiyan1

Affiliation:

1. Computer Science, University of Central Florida, Orlando, FL-32816, US

2. Burnett School of Biomedical Science, University of Central Florida, Orlando, FL-32816, US

Abstract

Abstract Motivation MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. Results In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. Contact xiaoman@mail.ucf.edu, haihu@cs.ucf.edu

Funder

National Science Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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