We propose to further our understanding of the molecular mechanisms that direct stem cells during neural development with the ultimate goal of enabling stem cell based regenerative medicine for neurodegenerative diseases. We will study the etiology of Spinal Muscular Atrophy (SMA) in the context of the mechanisms that we elucidate with the goal of developing clues to potential therapeutic targets for this developmental disease. To understand how external cues direct development, we will elucidate the transcriptional regulatory networks underlying neural development and represent this understanding in predictive computational models. Our studies will begin with undifferentiated embryonic stem (ES) cells, and using protocols that we have pioneered, we will elucidate the mechanism of ES cell development and fate commitment in specific neuron subtypes. Our work is structured into three projects. Project 1 will identify the transcription factors potentially involved in motor neuron identity, iteratively define transcriptional networks, and characterize the transcriptional consequences of SMA. Drawing upon these results, Project 2 will discover how key transcriptional and chromatin regulators control the gene expression programs of mouse and human embryonic stem cells and discover how this regulatory circuitry changes upon differentiation into spinal progenitor cells and then specific classes of central nervous system cells such as motor neurons. Using data from both of these projects, Project 3 will build a model of transcriptional regulation during neural development that integrates expression data, factor binding data, chromatin data, shRNA knock down data, and genome sequence in both human and mouse, examine the gene expression consequences of our SMA model in the context of the deduced regulatory networks, and explore the validity of the mouse model for human ES cell differentiation. Both Project 1 and 2 will test the models produced in Project 3.

Public Health Relevance

We will build predictive regulatory models of neural development to help us understand what goes wrong in neural pathologies. Using our models we will explore why specific groups of motor neurons die in Spinal Muscular Atrophy (SMA), develop clues for therapeutic targets that might help individuals with SMA, and study how stem cells respond to external cues that could lead to methods of programming stem cells for therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Program Projects (P01)
Project #
5P01NS055923-05
Application #
7920094
Study Section
National Institute of Neurological Disorders and Stroke Initial Review Group (NSD)
Program Officer
Owens, David F
Project Start
2006-09-15
Project End
2013-02-28
Budget Start
2010-09-01
Budget End
2013-02-28
Support Year
5
Fiscal Year
2010
Total Cost
$1,285,247
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02139
Zeng, Haoyang; Edwards, Matthew D; Liu, Ge et al. (2016) Convolutional neural network architectures for predicting DNA-protein binding. Bioinformatics 32:i121-i127
Arbab, Mandana; Sherwood, Richard I (2016) Self-Cloning CRISPR. Curr Protoc Stem Cell Biol 38:5B.5.1-5B.5.16
Hashimoto, Tatsunori; Sherwood, Richard I; Kang, Daniel D et al. (2016) A synergistic DNA logic predicts genome-wide chromatin accessibility. Genome Res 26:1430-1440
Barkal, Amira A; Srinivasan, Sharanya; Hashimoto, Tatsunori et al. (2016) Cas9 Functionally Opens Chromatin. PLoS One 11:e0152683
Arbab, Mandana; Srinivasan, Sharanya; Hashimoto, Tatsunori et al. (2015) Cloning-free CRISPR. Stem Cell Reports 5:908-917
Mahony, Shaun; Edwards, Matthew D; Mazzoni, Esteban O et al. (2014) An integrated model of multiple-condition ChIP-Seq data reveals predeterminants of Cdx2 binding. PLoS Comput Biol 10:e1003501
Sherwood, Richard I; Hashimoto, Tatsunori; O'Donnell, Charles W et al. (2014) Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape. Nat Biotechnol 32:171-178
Wichterle, Hynek; Gifford, David; Mazzoni, Esteban (2013) Neuroscience. Mapping neuronal diversity one cell at a time. Science 341:726-7
Mazzoni, Esteban O; Mahony, Shaun; Closser, Michael et al. (2013) Synergistic binding of transcription factors to cell-specific enhancers programs motor neuron identity. Nat Neurosci 16:1219-27
Arbab, Mandana; Mahony, Shaun; Cho, Hyunjii et al. (2013) A multi-parametric flow cytometric assay to analyze DNA-protein interactions. Nucleic Acids Res 41:e38

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