Whole Genome Association Strategy for Unbiased Candidate Gene Selection in Inflammatory Diseases

Susceptible individuals for inflammatory diseases could be targeted for either preventative measures or care if we could identify them by obtaining their genetic code. However, to date, there is no effective method of discovering which of the more than 5 million genetic variants are important in determining disease susceptibility. A common approach is to test every genetic variation, in every patient, for its correlation with some disease (called Whole Genome Association orWGA), but this is extremely expensive and slow. The intern will use a different approach that consists in conducting WGA analysis in tissue culture (rather than patients) where the response of every gene (rather than every disease) is measured. Therefore, thousands of WGA will be performed, one for each gene, using a cluster computer to run the analysis in parallel and speed up the process. By considering every gene included in a microarray chip, it will be possible to identify, in an unbiased way, candidate genes and single nucleotide polymorphisms (SNPs) that appear to regulate expression of important other genes in response to the prototype inflammatory stimulus. These candidate genes and SNPs will then be tested in critical ill human population in future studies.

Faculty Supervisor:

Dr. Mark Wilkinson

Student:

Rosalía Aguirre-Hernández

Partner:

Sirius Genomics Inc.

Discipline:

Medicine

Sector:

Life sciences

University:

University of British Columbia