1   Learning from Re-Sequencing Data: What To Do When the $1000 Genome Arrives?

Abstract:

Development of low cost sequencing technology is now paralleled by the simultaneous progress in collecting genetic material from large clinical populations. We investigated the potential of these two technological advances to enable fundamentally new ways for identification of genes underlying human complex phenotypes. We analyzed available systematic re-sequencing datasets to estimate effects of new mutations on fitness and parameters of demographic history. We further used a population genetics model informed by available data to simulate genome-wide re-sequencing studies. Our results suggest that genome-wide analysis of rare coding variation in individuals at phenotypic extremes will provide a powerful tool for discovery of new gene-phenotype associations.

However, these studies would require sequencing of very large population panels exceeding 10,000 individuals.

Host: Sergey Nuzhdin