Stable recombination hotspots in birds.

The DNA-binding protein PRDM9 has a critical role in specifying meiotic recombination hotspots in mice and apes, but it appears to be absent from other vertebrate species, including birds. To study the evolution and determinants of recombination in species lacking the gene that encodes PRDM9, we inferred fine-scale genetic maps from population resequencing data for two bird species: the zebra finch, Taeniopygia guttata, and the long-tailed finch, Poephila acuticauda. We found that both species have recombination hotspots, which are enriched near functional genomic elements. Unlike in mice and apes, most hotspots are shared between the two species, and their conservation seems to extend over tens of millions of years. These observations suggest that in the absence of PRDM9, recombination targets functional features that both enable access to the genome and constrain its evolution.

Convergence of genetic influences in comorbidity.

BACKGROUND: Predisposition to complex diseases is explained in part by genetic variation, and complex diseases are frequently comorbid, consistent with pleiotropic genetic variation influencing comorbidity. Genome Wide Association (GWA) studies typically assess association between SNPs and a single-disease phenotype. Fisher meta-analysis combines evidence of association from single-disease GWA studies, assuming that each study is an independent test of the same hypothesis. The Rank Product (RP) method overcomes limitations posed by Fisher assumptions, though RP was not designed for GWA data. METHODS: We modified RP to accommodate GWA data, and we call it modRP. Using p-values output from GWA studies, we aggregate evidence for association between SNPs and related phenotypes. To assess significance, RP randomly samples the observed ranks to develop the null distribution of the RP statistic, and then places the observed RPs into the null distribution. ModRP eliminates the effect of linkage disequilibrium and controls for differences in power at tested SNPs, to meet RP assumptions in application to GWA data. RESULTS: After validating modRP based on both positive and negative control studies, we searched for pleiotropic influences on comorbid substance use disorders in a novel study, and found two SNPs to be significantly associated with comorbid cocaine, opium, and nicotine dependence. Placing these SNPs into biological context, we developed a protein network modeling the interaction of cocaine, nicotine, and opium with these variants. CONCLUSIONS: ModRP is a novel approach to identifying pleiotropic genetic influences on comorbid complex diseases. It can be used to assess association for related phenotypes where raw data is unavailable or inappropriate for analysis using other approaches. The method is conceptually simple and produces statistically significant, biologically relevant results.