Pavi Ramachandran and Johnny Cruz Corchado Will Present Their Research on November 14, 2013
RNAi therapy in a spinocerebellar ataxia type 7 mouse model
Spinocerebellar ataxia type 7 (SCA7) is an autosomal dominant neurodegenerative disease characterized by cerebellar ataxia and vision loss with no effective treatments currently in the clinic. SCA7 is one of nine known polyglutamine (polyQ) diseases and is caused by an expansion of >37 CAG repeats in exon 1 of ATXN7.
Mutant polyQ ATXN7 gains a dominant negative function disrupting the normal function of ATXN7. Reducing the levels of mutant polyQ ATXN7 could thus reduce the downstream toxic effects of mutant ATXN7 that lead to the disease. However, for therapy in human patients, identifying methods to reduce only the mutant allele expression will be challenging. To overcome this hurdle, we hypothesized silencing of ATXN7 by RNA interference (RNAi) would alleviate phenotypes in a SCA7 mouse model.
We tested our hypothesis in a SCA7 mouse model, which expresses human ataxin-7 cDNA containing 92 pathogenic CAG repeats. The onset of PC degeneration is ~20 weeks of age, following which motor abnormalities start to develop. Unfortunately retinal degeneration is not pronounced in this model even though the transgene is expressed as seen by the presence of nuclear inclusions and QPCR. We thus tested the therapeutic efficacy and safety of reducing ATXN7 expression in the SCA7 cerebellum and evaluated the safety of reducing ATXN7 in the SCA7 retina.
How Good Are Population Genetics models to Estimate Recombination in DROSOPHILA?
Recombination is a crucial biological process that shapes evolutionary change within and between species. Developing whole-genome genetic maps is important to understand the molecular mechanism of recombination variation across genomes but also essential for accurate inferences in phenotype-genotype analyses. The generation of high-resolution, whole-genome genetic maps based on experimental crosses is cost- and labor-intensive. Therefore, it is favorable to have more practical approaches to study recombination variability across genomes that, ideally, could be applied to model and non-model species. Population genetics analyses use coalescent models and incorporate patterns of Linkage Disequilibrium (LD) to estimate recombination rates. These LD-based genetic maps provide a quick way to survey recombination variability across the whole genome based on (now cheap) genomic sequences. We sought to generate whole-genome genetic maps for populations of Drosophila melanogaster using LD mapping and sought to test their accuracy. We tested the reliability of two population genetics methods (LDhat and LDhelmet) to construct whole-genome recombination maps in Drosophila. Our preliminary results show that both LDhat and LDhelmet are good approaches to estimate the ancestral recombination rate in D. melanogaster, with LDhat presenting a more accurate model. Our data suggest there have been recent, and significant, changes in the recombination rate landscape across the D. melanogaster genome.