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Identification of active miRNA promoters from nuclear run-on RNA sequencing.
Liu, Qi; Wang, Jing; Zhao, Yue; Li, Chung-I; Stengel, Kristy R; Acharya, Pankaj; Johnston, Gretchen; Hiebert, Scott W; Shyr, Yu.
Afiliación
  • Liu Q; Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Wang J; Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.
  • Zhao Y; Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Li CI; Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Stengel KR; Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Acharya P; Department of Statistics, National Cheng Kung University, Tainan 70101, Taiwan.
  • Johnston G; Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Hiebert SW; Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
  • Shyr Y; Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
Nucleic Acids Res ; 45(13): e121, 2017 Jul 27.
Article en En | MEDLINE | ID: mdl-28460090
ABSTRACT
The genome-wide identification of microRNA transcription start sites (miRNA TSSs) is essential for understanding how miRNAs are regulated in development and disease. In this study, we developed mirSTP (mirna transcription Start sites Tracking Program), a probabilistic model for identifying active miRNA TSSs from nascent transcriptomes generated by global run-on sequencing (GRO-seq) and precision run-on sequencing (PRO-seq). MirSTP takes advantage of characteristic bidirectional transcription signatures at active TSSs in GRO/PRO-seq data, and provides accurate TSS prediction for human intergenic miRNAs at a high resolution. MirSTP performed better than existing generalized and experiment specific methods, in terms of the enrichment of various promoter-associated marks. MirSTP analysis of 27 human cell lines in 183 GRO-seq and 28 PRO-seq experiments identified TSSs for 480 intergenic miRNAs, indicating a wide usage of alternative TSSs. By integrating predicted miRNA TSSs with matched ENCODE transcription factor (TF) ChIP-seq data, we connected miRNAs into the transcriptional circuitry, which provides a valuable source for understanding the complex interplay between TF and miRNA. With mirSTP, we not only predicted TSSs for 72 miRNAs, but also identified 12 primary miRNAs with significant RNA polymerase pausing alterations after JQ1 treatment; each miRNA was further validated through BRD4 binding to its predicted promoter. MirSTP is available at http//bioinfo.vanderbilt.edu/mirSTP/.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Regiones Promotoras Genéticas / Análisis de Secuencia de ARN / MicroARNs Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Regiones Promotoras Genéticas / Análisis de Secuencia de ARN / MicroARNs Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos