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The complete sequencing of the human genome provides us with unprecedented opportunities to reveal many structural genetic variations amongst humans. These variations include duplications, deletions, inversions, and mutations of genomic segments.
Over the course of human history, some spontaneously arising genetic variations were so harmful to the survival of the individuals bearing them, that the individuals passed away before reaching sexual maturity. Consequently, the deleterious variants were not passed on. Other structural variants, however, did not induce immediate danger to the individuals and thus allowed the individuals to not only survive but also reproduce. Therefore, these variations were passed on to subsequent generations.
With Itsik Pe’er, I am exploring computational methods for disease association studies. We are hunting for variants that survived evolutionary pressures and try to find their link to complex medical diseases. We are using SNPs from the HapMap Project as genetic markers while relying on linkage disequilibrium between the SNPs that we use and the diseased loci.
Our focus is on admixed populations. These populations are defined as having their individuals composed of at least two ancestral populations. For example, African Americans are, on average, 80% of African descent and 20% of European descent. By stratifying an admixed individual’s genome to its ancestral components, we are able to take into account specific population variations and thus pinpoint to exact genomic sequences that statistically cause the complex disease in question.
Our vision, as we share it with other bioinformaticians, is that in the near future humans will enjoy personalized medicine, as our genome sequences will become an integral part of our EMR (Electronic Medical Record) -- a simple scan of the genome will reveal disease susceptibility, as well as shed some light as to the most appropriate treatments.
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