Literature DB >> 23384178

A simple high-throughput technology enables gain-of-function screening of human microRNAs.

Wen-Chih Cheng1, Tami J Kingsbury, Sarah J Wheelan, Curt I Civin.   

Abstract

MicroRNAs (miRs) regulate cellular processes by modulating gene expression. Although transcriptomic studies have identified numerous miRs differentially expressed in diseased versus normal cells, expression analysis alone cannot distinguish miRs driving a disease phenotype from those merely associated with the disease. To address this limitation, we developed miR-HTS, a method for unbiased high-throughput screening of the miRNome to identify functionally relevant miRs. Herein, we applied miR-HTS to simultaneously analyze the effects of 578 lentivirally transduced human miRs or miR clusters on growth of the IMR90 human lung fibroblast cell line. Growth-regulatory miRs were identified by quantitating the representation (i.e., relative abundance) of cells overexpressing each miR over a one-month culture of IMR90, using a panel of custom-designed quantitative real-time PCR (qPCR) assays specific for each transduced miR expression cassette. The miR-HTS identified 4 miRs previously reported to inhibit the growth of human lung-derived cell lines and 55 novel growth-inhibitory miR candidates. Nine of 12 (75%) selected candidate miRs were validated and shown to inhibit IMR90 cell growth. Thus, this novel lentiviral library- and qPCR-based miR-HTS technology provides a sensitive platform for functional screening that is straightforward and relatively inexpensive.

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Year:  2013        PMID: 23384178      PMCID: PMC3671589          DOI: 10.2144/000113991

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  46 in total

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Review 5.  MicroRNAs in development and disease.

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10.  Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis.

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4.  Regulation of RAB5C is important for the growth inhibitory effects of MiR-509 in human precursor-B acute lymphoblastic leukemia.

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5.  From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma.

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  5 in total

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