This article is part of the supplement: SNP-SIG 2012: Identification and annotation of SNPs in the context of structure, function, and disease
Multiscale modeling of the causal functional roles of nsSNPs in a genome-wide association study: application to hypoxia
1 Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA 92093, USA
2 Department of Computer Science, Hunter College, The City University of New York, New York City, NY 10065, USA
3 Department of Biological Sciences, Hunter College, The City University of New York, New York City, NY 10065, USA
4 Department of Psychology, Hunter College, The City University of New York, New York City, NY 10065, USA
5 Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
6 Department of Neuroscience, University of California, San Diego, La Jolla, CA 92093, USA
7 Rady Children's Hospital, San Diego, CA 92123, USA
8 Graduate Center, The City University of New York, New York City, NY 10016, USA
BMC Genomics 2013, 14(Suppl 3):S9 doi:10.1186/1471-2164-14-S3-S9Published: 28 May 2013
It is a great challenge of modern biology to determine the functional roles of non-synonymous Single Nucleotide Polymorphisms (nsSNPs) on complex phenotypes. Statistical and machine learning techniques establish correlations between genotype and phenotype, but may fail to infer the biologically relevant mechanisms. The emerging paradigm of Network-based Association Studies aims to address this problem of statistical analysis. However, a mechanistic understanding of how individual molecular components work together in a system requires knowledge of molecular structures, and their interactions.
To address the challenge of understanding the genetic, molecular, and cellular basis of complex phenotypes, we have, for the first time, developed a structural systems biology approach for genome-wide multiscale modeling of nsSNPs - from the atomic details of molecular interactions to the emergent properties of biological networks. We apply our approach to determine the functional roles of nsSNPs associated with hypoxia tolerance in Drosophila melanogaster. The integrated view of the functional roles of nsSNP at both molecular and network levels allows us to identify driver mutations and their interactions (epistasis) in H, Rad51D, Ulp1, Wnt5, HDAC4, Sol, Dys, GalNAc-T2, and CG33714 genes, all of which are involved in the up-regulation of Notch and Gurken/EGFR signaling pathways. Moreover, we find that a large fraction of the driver mutations are neither located in conserved functional sites, nor responsible for structural stability, but rather regulate protein activity through allosteric transitions, protein-protein interactions, or protein-nucleic acid interactions. This finding should impact future Genome-Wide Association Studies.
Our studies demonstrate that the consolidation of statistical, structural, and network views of biomolecules and their interactions can provide new insight into the functional role of nsSNPs in Genome-Wide Association Studies, in a way that neither the knowledge of molecular structures nor biological networks alone could achieve. Thus, multiscale modeling of nsSNPs may prove to be a powerful tool for establishing the functional roles of sequence variants in a wide array of applications.