LCSB R³
Responsible and Reproducible Research

The Parkinson’s disease associated mutation LRRK2-G2019S alters dopaminergic differentiation dynamics via NR2F1#

Authors#

Jonas Walter, Silvia Bolognin, Suresh K Poovathingal, Stefano Magni, Deborah Gérard, Paul MA Antony, Sarah L Nickels, Luis Salamanca, Emanuel Berger, Lisa M Smits, Kamil Grzyb, Rita Perfeito, Fredrik Hoel, Xiaobing Qing, Jochen Ohnmacht, Michele Bertacchi, Javier Jarazo, Tomasz Ignac, Anna S Monzel, Laura Gonzalez-Cano, Rejko Krüger, Thomas Sauter, Michèle Studer, Luis Pereira de Almeida, Karl J Tronstad, Lasse Sinkkonen, Alexander Skupin, Jens C Schwamborn

Abstract#

Increasing evidence suggests that neurodevelopmental alterations might contribute to increase the susceptibility to develop neurodegenerative diseases. We investigate the occurrence of developmental abnormalities in dopaminergic neurons in a model of Parkinson’s disease (PD). We monitor the differentiation of human patient-specific neuroepithelial stem cells (NESCs) into dopaminergic neurons. Using high-throughput image analyses and single-cell RNA sequencing, we observe that the PD-associated LRRK2-G2019S mutation alters the initial phase of neuronal differentiation by accelerating cell-cycle exit with a concomitant increase in cell death. We identify the NESC-specific core regulatory circuit and a molecular mechanism underlying the observed phenotypes. The expression of NR2F1, a key transcription factor involved in neurogenesis, decreases in LRRK2-G2019S NESCs, neurons, and midbrain organoids compared to controls. We also observe accelerated dopaminergic differentiation in vivo in NR2F1-deficient mouse embryos. This suggests a pathogenic mechanism involving the LRRK2-G2019S mutation, where the dynamics of dopaminergic differentiation are modified via NR2F1.

Raw data#

The complete Dataset is available from LCSB File Storage. It is subdivided into originals (raw data) and partials (analysis) specific to each figure and supplementary present in the manuscript.

Sequencing data#

The complete RNA-seq dataset is available from NCBI website.

Scripts#

The scripts used to analyse the data are available from GitLab.