Open Access Highly Accessed Research article

Dynamic recruitment of microRNAs to their mRNA targets in the regenerating liver

Jonathan Schug1, Lindsay B McKenna1, Gabriel Walton1, Nicholas Hand2, Sarmistha Mukherjee3, Kow Essuman3, Zhongjie Shi3, Yan Gao4, Karen Markley3, Momo Nakagawa3, Vasumathi Kameswaran1, Anastassios Vourekas5, Joshua R Friedman2, Klaus H Kaestner1 and Linda E Greenbaum1*

Author Affiliations

1 Department of Genetics and Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

2 Department of Pediatrics, The Children’s Hospital, University of Pennsylvania, Philadelphia, Pennsylvania, USA

3 Departments of Cancer Biology and Medicine, Thomas Jefferson University, 519 BLSB, 233 S. 10th Street, Philadelphia, PA, 19107, USA

4 Department of Cancer Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA

5 Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

For all author emails, please log on.

BMC Genomics 2013, 14:264  doi:10.1186/1471-2164-14-264

Published: 18 April 2013

Abstract

Background

Validation of physiologic miRNA targets has been met with significant challenges. We employed HITS-CLIP to identify which miRNAs participate in liver regeneration, and to identify their target mRNAs.

Results

miRNA recruitment to the RISC is highly dynamic, changing more than five-fold for several miRNAs. miRNA recruitment to the RISC did not correlate with changes in overall miRNA expression for these dynamically recruited miRNAs, emphasizing the necessity to determine miRNA recruitment to the RISC in order to fully assess the impact of miRNA regulation. We incorporated RNA-seq quantification of total mRNA to identify expression-weighted Ago footprints, and developed a microRNA regulatory element (MRE) prediction algorithm that represents a greater than 20-fold refinement over computational methods alone. These high confidence MREs were used to generate candidate ‘competing endogenous RNA’ (ceRNA) networks.

Conclusion

HITS-CLIP analysis provide novel insights into global miRNA:mRNA relationships in the regenerating liver.

Keywords:
Liver; Hepatectomy; HITS-CLIP; ceRNA; microRNA; Cell cycle