Tuesday, December 7, 2010

3rd Semiannual Bay Area Population Genomics Conference


The schedule for BAPG III at Stanford is all set. This time and hopefully in the future BAPG is sponsored by the Ecology and Evolution Group at the Stanford Biology Department. We have an exceptional lineup of speakers from Berkeley, UC Santa Cruz and Stanford. The meeting will start at 9AM with coffee and will end with lunch and a poster session.
9:30 AM Rachel Brem, UC Berkeley
Pathway evolution in Saccharomyces
10:00 AM Dario Valenzano, Stanford
Genetic Architecture of longevity in the short-lived fish
Nothobranchius furzeri
10:30 AM Paul Jenkins, UC Berkeley
A new approach to computing likelihoods in population genetics models
with recombination
11:30 AM Jared Wenger, Stanford
Adaptive mutations effect minimal trade-offs across the yeast adaptive
landscape
12:00 PM Ed Green, UC Santa Cruz
Recent human evolution as revealed by ancient hominin genome
sequences

For additional information (schedule, parking, registration, poster lineup), the latest news and the videos of the presentation after the conference please go to
http://www.stanford.edu/group/petrov/BAPG.html

Saturday, December 4, 2010

Broker Genes in Human Disease


Genes that underlie human disease are important subjects of systems biology research. In a paper just published in GBE by James Cai, Elhanan Borenstein and Dmitri, we demonstrated that Mendelian and complex disease genes have distinct and consistent protein–protein interaction (PPI) properties. Disease genes have unusually high degree (number of connections to other proteins) and low clustering coefficients (their neighbor proteins tend not to be connected). We describe such genes as brokers in that they connect many proteins that would not be connected otherwise. In contrast, disease genes identified in genome-wide association study (GWAS) do not have these broker properties. We suggest that the mapping of the GWAS-identified SNPs onto the genes underlying disease is highly error prone. This research can be used to help improve this mapping and prioritize the identification of disease genes in GWAS studies.