Check out this paper in PNAS and the corresponding synopsis in the New York Times. The authors take a unique approach to finding genes likely to be associated with human traits using orthologous phenotypes in model organisms, or phenologs. The idea is simple. The authors have a database of ~2000 disease associated genes in humans. To this database they added another ~200,000 gene-trait associations in model organisms including mice, yeast, worm, and plants. Then they look for overlapping sets of orthologous genes from these organisms to identify phenotypes in the model organisms. The related genes causing orthologous phenotypes, or phenologs, are predictive of genes causing disease in humans. For example, the authors found genes responsible for angiogenesis using yeast, breast cancer associated genes in C. elegans, and even genes responsible for deafness using plants.
I remember seeing a talk about this at this year's Pacific Symposium in Biocomputing. You can learn more about the methodology at phenologs.org, and download all the original data used in the paper and build your own phenolog database, which could be very useful for disease gene prediction or prioritization of GWAS hits for followup.
PNAS: Systematic discovery of nonobvious human disease models through orthologous phenotypes
New York Times: The Search for Genes Leads to Unexpected Places
phenologs.org: Systematic discovery of non-obvious disease models and candidate genes