While all of the cells in a human body share the same genome, different cell types have characteristic gene expression patterns that are controlled by elaborate gene regulatory networks. Understanding the encoding of these developmental programs in the genome and how they give rise to the diverse transcriptomes of differentiated cell types is the primary goal of functional genomics and one of the driving research themes of modern biomedical research in general. There is now ample evidence that the tight spatio-temporal regulation of the expression of thousands of genes is controlled by regulatory elements called enhancers that can be found far away from their cognate promoters via long-range looping interactions. With the development a multiple high-throughput assays to determine protein-DNA interactions, gene expression levels, and long- range interactions, we are on the cusp of sophisticated integrative studies where we can use combinations of these assays to ask fundamental questions about how protein-DNA interactions and enhancer-promoter interactions genome-wide account for changes in cell state across high-resolution differentiation time courses. We propose to develop several new experimental and computational methods to increase the resolution, applicability, and validation of protein-DNA interactions as well as long-range interactions to understand their role in controlling gene expression during differentiation from progenitor cells to differentiated cell types. Once developed, these methods will be widely applicable across a variety of studies in functional genomics. To demonstrate the power of these methods, we will apply them to study the differentiation of existing human, mouse, horse and dog stem cells into cardiomyocytes and neurons in order to understand the role, conservation and dynamics of these long-range interactions. The results will greatly expand our understanding of both the evolution and role of long-range interactions in homologous cell differentiation in mammals and whether particular long-range interactions are critical for the efficient differentiation of stem cells into fully- differentiated cell types.
| Serra, Lorrayne; Chang, Dennis Z; Macchietto, Marissa et al. (2018) Adapting the Smart-seq2 Protocol for Robust Single Worm RNA-seq. Bio Protoc 8: |
| Jiang, Shan; Mortazavi, Ali (2018) Integrating ChIP-seq with other functional genomics data. Brief Funct Genomics 17:104-115 |
| Ramirez, Ricardo N; El-Ali, Nicole C; Mager, Mikayla Anne et al. (2017) Dynamic Gene Regulatory Networks of Human Myeloid Differentiation. Cell Syst 4:416-429.e3 |
| Macchietto, Marissa; Angdembey, Dristi; Heidarpour, Negar et al. (2017) Comparative Transcriptomics of Steinernema and Caenorhabditis Single Embryos Reveals Orthologous Gene Expression Convergence during Late Embryogenesis. Genome Biol Evol 9:2681-2696 |
| Lu, Dihong; Macchietto, Marissa; Chang, Dennis et al. (2017) Activated entomopathogenic nematode infective juveniles release lethal venom proteins. PLoS Pathog 13:e1006302 |
| Plikus, Maksim V; Guerrero-Juarez, Christian F; Ito, Mayumi et al. (2017) Regeneration of fat cells from myofibroblasts during wound healing. Science 355:748-752 |
| Longabaugh, William J R; Zeng, Weihua; Zhang, Jingli A et al. (2017) Bcl11b and combinatorial resolution of cell fate in the T-cell gene regulatory network. Proc Natl Acad Sci U S A 114:5800-5807 |
| Hernandez, Michael X; Jiang, Shan; Cole, Tracy A et al. (2017) Prevention of C5aR1 signaling delays microglial inflammatory polarization, favors clearance pathways and suppresses cognitive loss. Mol Neurodegener 12:66 |
| Conesa, Ana; Madrigal, Pedro; Tarazona, Sonia et al. (2016) A survey of best practices for RNA-seq data analysis. Genome Biol 17:13 |
| Zeng, Weihua; Jiang, Shan; Kong, Xiangduo et al. (2016) Single-nucleus RNA-seq of differentiating human myoblasts reveals the extent of fate heterogeneity. Nucleic Acids Res 44:e158 |
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