Gene signatures linked to the cell biological phenotypes of familial PD

Mclean Hospital, Belmont MA

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Abstract

DESCRIPTION (provided by applicant): High throughput sequencing of the genome-wide transcriptome will generate many new hypotheses regarding the genetic interactions underlying neurodegenerative mechanisms. We expect that marker genes of biologically relevant pathways are needed to efficiently interrogate the large sets of raw data produced by the experiments. The goal of this new R21 proposal is to help validate the neuronal transcriptome as a tool for the study of Parkinson's disease. Cells from well-defined familial cases of Parkinson's disease, although rare, provide an excellent starting point for such analyses. We and others have shown that cells from Parkinson's disease patients carrying LRRK2 or PINK1 mutations demonstrate mitochondrial deficits. Importantly, the molecular mechanisms that connect LRRK2 or PINK1 mutations to the mitochondrial deficits remain unclear. Using an innovative approach to interpreting the neuronal transcriptome, we aim to generate new hypotheses regarding the molecular mechanisms of LRRK2 or PINK1 associated mitochondrial deficits. We will link the functional mitochondrial deficits of human neurons carrying Parkinson's disease associated LRRK2 and PINK1 mutations that we have observed to the RNA sequences expressed by the neurons. By combining high- throughput transcriptome sequencing with new quantitative PCR arrays, we propose to determine the expression level and sequence signatures of mitochondrial DNA (SA1) and nuclear DNA (SA2) encoded genes that mark the mitochondrial deficits of patient-derived neurons. Multiple clones of age-matched, sibling and isogenic control iPSCs will be used to minimize the influence of genomic variation across neuronal samples. In a first step towards our goal, RNA molecules from induced pluripotent stem cell (iPSC)-derived neurons carrying LRRK2, PINK1 mutations and showing mitochondrial deficits or healthy subjects were sequenced. Preliminary analyses of the RNAseq data confirmed the presence of the LRRK2 and PINK1 mutations in the neuronal transcriptome. Furthermore, our analysis suggests that the functional mitochondrial deficits are associated with aberrant processing of mitochondrial DNA-encoded transcripts. These data from human neurons can be used to establish a reasonable and coherent framework of cell biological responses to interpret a patient's transcriptome. Our results will be instructive and critical to future attempts to effectively analyze human cell biological phenotypes with the multiple underlying genetic interactions of sporadic forms of Parkinson's disease.