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  3. Alex LeNail Thesis Defense: Transcriptional Reprogramming to Reverse Aging-Associated Transcriptional Dysregulation in Neurons
Alex LeNail Thesis Defense: Transcriptional Reprogramming to Reverse Aging-Associated Transcriptional Dysregulation in Neurons
Department of Brain and Cognitive Sciences (BCS)

Alex LeNail Thesis Defense: Transcriptional Reprogramming to Reverse Aging-Associated Transcriptional Dysregulation in Neurons

Add to CalendarAmerica/New_YorkAlex LeNail Thesis Defense: Transcriptional Reprogramming to Reverse Aging-Associated Transcriptional Dysregulation in Neurons05/02/2025 2:00 pm05/02/2025 2:00 pmBuilding 46,Singleton
May 2, 2025
2:00 pm
Location
Building 46,Singleton
    Description

    Title: Transcriptional Reprogramming to Reverse Aging-Associated Transcriptional Dysregulation in Neurons

    Abstract:
    It is unclear what the mechanistic contribution of normal aging  is to the neurodegenerative diseases that present in advanced age. This motivates an investigation into the molecular characteristics of neuronal aging, as well as the pursuit of interventions that could reverse neuronal aging or increase neuronal resilience to degenerative mechanisms. We cataloged the molecular differences between young and old neurons of the mouse brain with single-nucleus paired transcriptional and epigenetic assays, forming a multi-omic atlas of brain aging, revealing deficits in mitochondrial biogenesis, proteostasis, and synaptic gene expression. To reverse these age-associated transcriptional profiles, we targeted endogenous homeostasis-maintenance genetic programs by increasing the dosage of relevant Transcription Factors (TFs). We computationally predicted a library of TFs most likely to engage the target genetic programs by integrating multiple lines of evidence and then produced a library of TFs that we administered in a pool to the aged mouse brain. Our single-nuclear RNA-seq readout describes the transcriptional consequences of each TF perturbation in each cell type in the aged motor cortex. Our results highlight certain under-studied TFs with promising rejuvenation potential and benchmark our algorithmic approaches to predict the effects of TF perturbations. 

    Thesis Advisor: Myriam Heiman (BCS, Picower)

    Thesis Defense Committee:

    Jonathan Weissman
    Manolis Kellis
    Hongkui Zeng

    Zoom Link: https://mit.zoom.us/j/4565992010?pwd=R1B3MVl2UkdOZzNZOFNSOGpoRFNodz09

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