Poster Presentation 9th GeneMappers Conference 2012


Kaavya A Mohanasundaram 1 , Mani P Grover 1 , Sara Ballouz 2 , Richard A George 3 , Merridee A Wouters 1
  1. Faculty of Life and Environmental Sciences, Deakin University, Geelong, VIC, Australia
  2. School of computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia
  3. Victor Chang Cardiac Research Institute, NSW, Australia

The completion of human genome sequencing and breakthroughs in genotyping technologies has extensively enhanced research into the molecular basis of disease. The primary goal in human genetics is to identify causal  variants which are largely behind the inherited diseases and their associated phenotypes. Recent advances in population-based discovery such as Genome wide association studies (GWAS) are yielding novel disease genes for complex disease by testing a large number of SNP markers for disease association. Previously we showed how the candidate gene prediction system Gentrepid can be used to enhance this valuable but noisy GWA data (Ballouz et al., 2011). However, significant SNPs in GWAS may not be causal but simply in linkage disequilibrium with the causal SNP. Now, the system will be extended to facilitate molecular analysis of disease specific mutations from the gene level to the nucleotide level, providing a physicochemical bioinformatic approach to distinguish harmless polymorphisms from those likely to be pertinent to the phenotype in question. In the first phase, non-synonymous SNPs are primarily focussed since their involvement is generally characterised behind inherited genetic disorders. By analysing literature derived datasets, we present here the possible structural and functional consequences of non-synonymous polymorphisms which can be used a model set of features to predict the effect of AAS on the protein and score the most likely disease-causing mutation. This involves predicting the functional consequence of mutations at the amino acid level by identifying changes in sequence motifs such as phosphorylation sites, sites modified by reactive oxygen species (ROS). Rapid identification of inherited mutations in patients as well as somatic mutations in cancer can then be pursued by exome sequencing. 

  1. BALLOUZ, S., LIU, J., OTI, M., GAETA, B., FATKIN, D., BAHLO, M. & WOUTERS, M. 2011. Analysis of genome-wide association study data using the protein knowledge base. BMC Genetics, 12, 98.
  2. GEORGE, R. A., LIU, J. Y., FENG, L. L., BRYSON-RICHARDSON, R. J., FATKIN, D. & WOUTERS, M. A. 2006. Analysis of protein sequence and interaction data for candidate disease gene prediction. Nucleic Acids Research, 34, e130.