Single cell transcriptomics to investigate monoallelic expression as a potential trigger of Alzheimer’s disease

• Applicant: Professorin Dr. Katja Nowick
• Subject Area: Molecular Biology and Physiology of Neurons and Glial Cells ; Bioinformatics and Theoretical Biology
• Term: from 2019 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 422051330

Alzheimer’s disease (AD) is one of the major diseases related to aging, currently affecting more than 35 million people worldwide, and expected to increase in incidences. Although being intensely investigated, the mechanisms of the onset of AD are still not fully understood. Some brain regions, such as the temporal lobe, are affected earlier by the disease than others, suggesting differences in sensitivity of certain neurons towards AD pathology. This observation might be explained by differences in gene expression between neurons leading to varying expressivity of the phenotype. Thus, investigations at the single cell level might reveal the trigger for the onset of AD. Random monoallelic expression (RMAE) is a mechanism, in which only one allele of a gene is expressed. Since the allele is randomly chosen, this gene expression mode can create variability between cells of the same cell type and might be one mechanism to render some neurons more sensitive than others to developing AD. RMAE has been shown to be involved in other cognitive diseases, such as schizophrenia and autism, and in neurodevelopmental disorders. AD-associated genes are significantly enriched among RMAE genes, suggesting a link between AD and RMAE. Moreover, the AD-characteristic amyloid precursor protein (APP) is expressed monoallelically, potentially leading to different amounts of APP in different cells. However, the extent of RMAE in human neurons, how RMAE is established in the cell, and consequences of dysregulation in RMAE have almost not been studied yet.To investigate the role of RMAE in late-onset AD, we propose to sequence for the first time the full-length transcripts of about 2000 single neurons from five healthy and five AD-affected individuals. Sequencing additionally the exomes of the respective individuals will allow us to discover heterozygous SNPs and RMAE. We will establish a computational pipeline for RMAE analysis and functional consequences of changes in RMAE. Utilizing the transcriptome data of about 2000 neurons, we will describe the transcriptional variability and the extent of RMAE in these cells. We will test the hypothesis, that patterns of RMAE are altered in neurons of individuals with AD. Using state-of-the-art comparative transcriptome and co-expression network analyses we aim to uncover functional consequences of changes in RMAE that might be related to AD. Importantly, we will investigate network differences for different neuron types to identify neuron-type specific alterations. In addition, integrating information of the epigenome, of transcription factors, and long non-coding RNAs, we also aim to provide important insights into mechanisms that establish RMAE and might lead to its dysregulation in AD. With our single neuron resolution, we expect to unravel new candidate genes and regulatory mechanisms involved in AD onset and progression, which so far were impossible to find by bulk sequencing of RNA from brain tissue.

• DFG Programme: Research Grants