Email updates

Keep up to date with the latest news and content from BMC Systems Biology and BioMed Central.

Open Access Highly Accessed Research article

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

Hsiang Ho1, Tijana Milenković2, Vesna Memišević2, Jayavani Aruri3, Nataša Pržulj4 and Anand K Ganesan13*

  • * Corresponding author: Anand K Ganesan aganesan@uci.edu

  • † Equal contributors

Author Affiliations

1 Department of Biological Chemistry, University of California, Irvine, CA 92697-1700, USA

2 Department of Computer Science, University of California, Irvine, CA 92697-3435, USA

3 Department of Dermatology, University of California, Irvine, CA 92697-2400, USA

4 Department of Computing, Imperial College London SW7 2AZ, UK

For all author emails, please log on.

BMC Systems Biology 2010, 4:84  doi:10.1186/1752-0509-4-84

Published: 15 June 2010

Abstract

Background

RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis.

Results

In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes.

Conclusions

We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.