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DCMB Seminar Series pres.

DCMB Seminar - Neurons in pathology through the lens of multi-omics and data analytics

Shankar Subramaniam, Ph.D. (UCSD)

Abstract:

Advances in stem cell engineering, omics technologies and data sciences offer a unique scope for deciphering the myriad ways molecular circuits dysfunction in pathologies of the brain. Recently, we have developed and explored iPSC-derived neurons from familial Alzheimer’s disease patients using a systems-level, multi-omics approach, identifying disease-related endotypes, which are commonly dysregulated in patient-derived neurons and patient brain tissue alike. By integrating RNA-Seq, ATAC-Seq, and ChIP-Seq approaches, we determined that the defining disease-causing mechanism of AD is de-differentiation of neurons, driven primarily through the REST-mediated repression of neuronal lineage specification gene programs and the activation of cell cycle reentry and non-specific germ layer precursor gene programs concomitant with modifications in chromatin accessibility. Strikingly, our reanalysis of previously-generated AD-patient brain tissue showed similar enrichment of neuronal repression and de-differentiation mechanisms. Surprisingly, our earlier work on glioblastoma also showed de-differentiation and initiation of some of the shared diseased endotypes as common features. We postulate that de-differentiation and reprogramming are hallmark mechanisms of numerous pathologies, arguably genetically evolved to serve as protection mechanisms.

Acknowledgements: This work was done in collaboration with the Laboratory of Dr. Wagner and his colleagues.

References:
Caldwell AB, Liu Q, Schroth GP, Tanzi RE, Galasko DR, Yuan SH, Wagner SL, Subramaniam S. Dedifferentiation orchestrated through remodeling of the chromatin landscape defines PSEN1 mutation-induced Alzheimer's Disease. 2019 (under revision in Nature) Available from: https://www.biorxiv.org/content/10.1101/531202v1.
Friedmann-Morvinski D, Bhargava V, Gupta S, Verma IM, Subramaniam S. Identification of therapeutic targets for glioblastoma by network analysis. Oncogene. 2016;35(5):608-20. PMCID: 4641815.
Bhargava V, Ko P, Willems E, Mercola M, Subramaniam S. Quantitative transcriptomics using designed primer-based amplification. Sci Rep. 2013;3:1740. PMCID: 3638165.
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