Genetic modifiers of neurodegeneration in a drosophila model of parkinson’s disease

Sierra Lavoy, Vinita G. Chittoor-Vinod, Clement Y. Chow, Ian Martin

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Disease phenotypes can be highly variable among individuals with the same pathogenic mutation. There is increasing evidence that background genetic variation is a strong driver of disease variability in addition to the influence of environment. To understand the genotype–phenotype relationship that determines the expressivity of a pathogenic mutation, a large number of backgrounds must be studied. This can be efficiently achieved using model organism collections such as the Drosophila Genetic Reference Panel (DGRP). Here, we used the DGRP to assess the variability of locomotor dysfunction in a LRRK2 G2019S Drosophila melanogaster model of Parkinson’s disease (PD). We find substantial variability in the LRRK2 G2019S locomotor phenotype in different DGRP backgrounds. A genome-wide association study for candidate genetic modifiers reveals 177 genes that drive wide phenotypic variation, including 19 top association genes. Genes involved in the outgrowth and regulation of neuronal projections are enriched in these candidate modifiers. RNAi functional testing of the top association and neuronal projection-related genes reveals that pros, pbl, ct, and CG33506 significantly modify age-related dopamine neuron loss and associated locomotor dysfunction in the Drosophila LRRK2 G2019S model. These results demonstrate how natural genetic variation can be used as a powerful tool to identify genes that modify disease-related phenotypes. We report novel candidate modifier genes for LRRK2 G2019S that may be used to interrogate the link between LRRK2, neurite regulation and neuronal degeneration in PD.

Original languageEnglish (US)
Pages (from-to)1345-1356
Number of pages12
Issue number4
StatePublished - Aug 2018


  • D. melanogaster
  • Dopamine neurons
  • LRRK2
  • Parkinson’s disease

ASJC Scopus subject areas

  • Genetics


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