Hansenula polymorpha: An attractive model organism for molecular studies of peroxisome biogenesis and function

In wild-type Hansenula polymorpha the proliferation of peroxisomes is induced by various unconventional carbon- and nitrogen sources. Highest induction levels, up to 80% of the cytoplasmic volume, are observed in cells grown in methanol-limited chemostat cultures. Based on our accumulated experience, we are now able to precisely adjust both the level of peroxisome induction as well as their protein composition by specific adaptations in growth conditions. During the last few years a series of peroxisome-deficient (per) mutants of H. polymorpha have been isolated and characterized. Phenotypically these mutants are characterized by the fact that they are not able to grow on methanol. Three mutant phenotypes were defined on the basis of morphological criteria, namely: (a) mutants completely lacking peroxisomes (Per-; 13 complementation groups); (b) mutants containing few small peroxisomes which are partly impaired in the peroxisomal import of matrix proteins (Pim-; five complementation groups); and (c) mutants with aberrations in the peroxisomal substructure (Pss-; two complementation groups). In addition, several conditional Per-, Pim- and Pss- mutants have been obtained. In all cases the mutant phenotype was shown to be caused by a recessive mutation in one gene. However, we observed that different mutations in one gene may cause different morphological mutant phenotypes. A detailed genetic analysis revealed that several PER genes, essential for peroxisome biogenesis, are tightly linked and organized in a hierarchical fashion. The use of both constitual and conditional per mutants in current and future studies of the molecular mechanisms controlling peroxisome biogenesis and function is discussed.

GemTools: A fast and efficient approach to estimating genetic ancestry

To uncover the genetic basis of complex disease, individuals are often measured at a large number of genetic variants (usually SNPs) across the genome. GemTools provides computationally efficient tools for modeling genetic ancestry based on SNP genotypes. The main algorithm creates an eigenmap based on genetic similarities, and then clusters subjects based on their map position. This process is continued iteratively until each cluster is relatively homogeneous. For genetic association studies, GemTools matches cases and controls based on genetic similarity.Comment: 5 pages, 1 figur