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Ge, Z.

Publications and source records attributed to Ge, Z..

2 recordsLinked to original sources

Plumage redness signals mitochondrial function in the House Finch

Carotenoid coloration is widely recognized as a signal of individual condition in various animals, but despite decades of study, the mechanisms that link carotenoid coloration to condition remain unresolved. Most birds with red feathers convert yellow dietary carotenoids to red carotenoids in an oxidation process requiring the gene encoding the putative cytochrome P450 enzyme CYP2J19. Here, we tested the hypothesis that the process of carotenoid oxidation and feather pigmentation is functionally linked to mitochondrial performance. Consistent with this hypothesis, we observed high levels of red ketolated carotenoids associated with the hepatic mitochondria of molting wild house finches (Haemorhous mexicanus), and upon fractionation, we found the highest concentration of ketolated carotenoids in the inner mitochondrial membrane. We further found that the redness of growing feathers was positively related to the performance of liver mitochondria. Structural modeling of CYP2J19 supports a direct role of this protein in carotenoid ketolation that may be functionally linked to cellular respiration. These observations suggest that feather coloration serves as a signal of core functionality through inexorable links to cellular respiration in the mitochondria.

evolutionary biology

GRIPT: A novel case-control analysis method for Mendelian disease gene discovery

Despite rapid progress of next-generation sequencing (NGS) technologies, the disease-causing genes underpinning about 50% of Mendelian diseases remain elusive. One main challenge is the high genetic heterogeneity of Mendelian diseases in which similar phenotypes are caused by different genes and each gene only accounts for a small proportion of the patients. To overcome this gap, we developed a novel method, the Gene Ranking, Identification and Prediction Tool (GRIPT), for performing case-control analysis of NGS data. Analyses of simulated and real datasets show that GRIPT is well-powered for disease gene discovery, especially for diseases with high locus heterogeneity.

genomics