Discovery of novel human breast cancer micrornas from deep sequencing data by analysis of pri-microrna secondary structures

Ryu, S., Joshi, N., McDonnell, K., Woo, J., Choi, H., Gao, D., McCombie, W. R., Mittal, V. (2011) Discovery of novel human breast cancer micrornas from deep sequencing data by analysis of pri-microrna secondary structures. PLoS ONE, 6 (2).

[img]
Preview
PDF (Paper)
McCombie PLoS One 2011.pdf - Published Version

Download (868Kb) | Preview
URL: http://www.ncbi.nlm.nih.gov/pubmed/21346806
DOI: 10.1371/journal.pone.0016403

Abstract

MicroRNAs (miRNAs) are key regulators of gene expression and contribute to a variety of biological processes. Abnormal miRNA expression has been reported in various diseases including pathophysiology of breast cancer, where they regulate protumorigenic processes including vascular invasiveness, estrogen receptor status, chemotherapy resistance, invasion and metastasis. The miRBase sequence database, a public repository for newly discovered miRNAs, has grown rapidly with approximately >10,000 entries to date. Despite this rapid growth, many miRNAs have not yet been validated, and several others are yet to be identified. A lack of a full complement of miRNAs has imposed limitations on recognizing their important roles in cancer, including breast cancer. Using deep sequencing technology, we have identified 189 candidate novel microRNAs in human breast cancer cell lines with diverse tumorigenic potential. We further show that analysis of 500-nucleotide pri-microRNA secondary structure constitutes a reliable method to predict bona fide miRNAs as judged by experimental validation. Candidate novel breast cancer miRNAs with stem lengths of greater than 30 bp resulted in the generation of precursor and mature sequences in vivo. On the other hand, candidates with stem length less than 30 bp were less efficient in producing mature miRNA. This approach may be used to predict which candidate novel miRNA would qualify as bona fide miRNAs from deep sequencing data with approximately 90% accuracy. © 2011 Ryu et al.

Item Type: Paper
Subjects: diseases & disorders > cancer
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
diseases & disorders
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
diseases & disorders > cancer > cancer types > breast cancer
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > miRNA
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > miRNA

diseases & disorders > cancer > cancer types
CSHL Authors:
Communities: CSHL Cancer Center Shared Resources > DNA Sequencing Service
CSHL labs > McCombie lab
CSHL Cancer Center Program > Cancer Genetics
Depositing User: Matt Covey
Date Deposited: 06 Feb 2013 16:24
Last Modified: 14 Oct 2015 20:38
PMCID: PMC3035615
Related URLs:
URI: http://repository.cshl.edu/id/eprint/27169

Actions (login required)

Administrator's edit/view item Administrator's edit/view item
CSHL HomeAbout CSHLResearchEducationNews & FeaturesCampus & Public EventsCareersGiving