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Open Access Publications from the University of California

MicroRNA target site identification in helper T cell differentiation

  • Author(s): Kageyama, Robin
  • Advisor(s): Ansel, Karl M
  • Woodruff, Prescott
  • et al.
Abstract

MicroRNAs are important mediators in the control of helper T cell differentiation, where small perturbations in responses to extracellular signals leads to early polarization and specialization. Identifying gene targets of highly expressed helper T cell miRNAs can lead to identification of novel players in these networks. High-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) is a powerful tool for identifying these gene targets by pulling down the miRNA binding protein argonaute (Ago) and sequencing the co-immunoprecipitated miRNA and targeted cognate mRNA fragment.

We performed HITS-CLIP on mouse CD4+ helper T cells and identified miRNA binding sites. While a majority of these sites were in well annotated 3’ untranslated regions (UTRs), we also identified a number of miRNA sites in coding regions, downstream of annotated 3’UTRs and in difficult to annotate regions of the genome. We identified hundreds of binding sites that were dependent of the presence of miR-29a, a miRNA highly expressed in CD4 T cells and implicated for its roles in T cell differentiation. We also observed a role for miR-29 in IL-17 production, which led us to identify a number of miR-29 targeted genes with roles in Th17 differentiation, one of which, ICOS, was a new target that we found to be directly regulated by miR-29. Our study identifies Ago dependent miRNA binding sites important in Th17 biology and identifies a role for miR-29 in IL17 production.

Additionally, our lab has generated a tool that aims to create an easy to use interface for labs working with CLIP-Seq data to create high quality graphics that are easily edited in a vector based graphics program. ClipPlot is a webapp that can be run on a local server and used by all members of a lab simultaneously, requiring only the technical expertise of a single user. While this is not a replacement for sophisticated visualization tools like IGV, ClipPlot provides an easy to use platform for researchers working with CLIP-Seq or RNA-Seq data to quickly create presentable and easily manipulated graphics, visualizing the shape of sequencing data to defined regions.

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