4.6 Article

Discovery of Novel MicroRNAs in Female Reproductive Tract Using Next Generation Sequencing

Journal

PLOS ONE
Volume 5, Issue 3, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0009637

Keywords

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Funding

  1. Ovarian Cancer Research Fund
  2. Young Texans Against Cancer
  3. National Institutes of Health [CA60651, P30 CA125123, K12 HD01426-02]
  4. Specialized Cooperative Centers in Reproductive & Infertility Research [U54HD07495]

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MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional gene silencing. Over 700 human miRNAs have currently been identified, many of which are mutated or de-regulated in diseases. Here we report the identification of novel miRNAs through deep sequencing the small RNAome (<30 nt) of over 100 tissues or cell lines derived from human female reproductive organs in both normal and disease states. These specimens include ovarian epithelium and ovarian cancer, endometrium and endometriomas, and uterine myometrium and uterine smooth muscle tumors. Sequence reads not aligning with known miRNAs were each mapped to the genome to extract flanking sequences. These extended sequence regions were folded in silico to identify RNA hairpins. Sequences demonstrating the ability to form a stem loop structure with low minimum free energy (<-225 kcal) and predicted Drosha and Dicer cut sites yielding a mature miRNA sequence matching the actual sequence were considered putative novel miRNAs. Additional confidence was achieved when putative novel hairpins assembled a collection of sequences highly similar to the putative mature miRNA but with heterogeneous 3'-ends. A confirmed novel miRNA fulfilled these criteria and had its star sequence in our collection. We found 7 distinct confirmed novel miRNAs, and 51 additional novel miRNAs that represented highly confident predictions but without detectable star sequences. Our novel miRNAs were detectable in multiple samples, but expressed at low levels and not specific to any one tissue or cell type. To date, this study represents the largest set of samples analyzed together to identify novel miRNAs.

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