Systematic reconstruction of genetic and molecular circuits in mammalian cells remains a significant, large-scale and unsolved challenge in genomics. The urgency to address it is underscored by the sizeable number of GWAS-derived disease genes whose functions remain largely obscure, limiting our progress towards biological understanding and therapeutic intervention. Recent advances in probing and manipulating cellular circuits on a genomic scale open the way for the development of a systematic method for circuit reconstruction. Here, we propose a Center for Cell Circuits to develop the reagents, technologies, algorithms, protocols and strategies needed to reconstruct molecular circuits. Our preliminary studies chart an initial path towards a universal strategy, which we will fully implement by developing a broad and integrated experimental and computational toolkit. We will develop methods for comprehensive profiling, genetic perturbations and mesoscale monitoring of diverse circuit layers (Aim 1). In parallel, we will develop a computational framework to analyze profiles, derive provisional models, use them to determine targets for perturbation and monitoring, and evaluate, refine and validate circuits based on those experiments (Aim 2). We will develop, test and refine this strategy in the context of two distinct and complementary mammalian circuits. First, we will produce an integrated, multi-layer circuit of the transcriptional response to pathogens in dendritic cells (Aim 3) as an example ofan acute environmental response. Second, we will reconstruct the the circuit of chromatin factors and non-coding RNAs that control chromatin organization and gene expression in mouse embryonic stem cells (Aim 4) as an example of the circuitry underlying stable cell states. These detailed datasets and models will reveal general principles of circuit organization, provide a resource for scientists in these two important fields, and allow computational biologists to test and develop algorithms. We will broadly disseminate our tools and methods to the community, enabling researchers to dissect any cell circuit of interest at unprecedented detail. Our work will open the way for reconstructing cellular circuits in human disease and individuals, to improve the accuracy of both diagnosis and treatment.

Public Health Relevance

While it is now possible to rapidly identify genes that contribute to human disease, it is remains a major challenge to explain how these genes work together to carry out their normal functions or cause disease. We propose to develop a universal way to discover how genes work together in circuits, eventually leading to better diagnosis and therapy.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Specialized Center (P50)
Project #
1P50HG006193-01
Application #
8116814
Study Section
Special Emphasis Panel (ZHG1-HGR-N (J1))
Program Officer
Felsenfeld, Adam
Project Start
2011-07-09
Project End
2016-04-30
Budget Start
2011-07-09
Budget End
2012-04-30
Support Year
1
Fiscal Year
2011
Total Cost
$3,674,343
Indirect Cost
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Charlton, Jocelyn; Downing, Timothy L; Smith, Zachary D et al. (2018) Global delay in nascent strand DNA methylation. Nat Struct Mol Biol 25:327-332
Ye, Chun Jimmie; Chen, Jenny; Villani, Alexandra-ChloƩ et al. (2018) Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection. Genome Res 28:1812-1825
Ichida, Justin K; Staats, Kim A; Davis-Dusenbery, Brandi N et al. (2018) Comparative genomic analysis of embryonic, lineage-converted and stem cell-derived motor neurons. Development 145:
Vian, Laura; P?kowska, Aleksandra; Rao, Suhas S P et al. (2018) The Energetics and Physiological Impact of Cohesin Extrusion. Cell 173:1165-1178.e20
Cheng, Ze; Otto, George Maxwell; Powers, Emily Nicole et al. (2018) Pervasive, Coordinated Protein-Level Changes Driven by Transcript Isoform Switching during Meiosis. Cell 172:910-923.e16
Mariani, Luca; Weinand, Kathryn; Vedenko, Anastasia et al. (2017) Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds. Cell Syst 5:187-201.e7
Prakadan, Sanjay M; Shalek, Alex K; Weitz, David A (2017) Scaling by shrinking: empowering single-cell 'omics' with microfluidic devices. Nat Rev Genet 18:345-361
Mariani, Luca; Weinand, Kathryn; Vedenko, Anastasia et al. (2017) Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds. Cell Syst 5:654
Mertins, Philipp; Przybylski, Dariusz; Yosef, Nir et al. (2017) An Integrative Framework Reveals Signaling-to-Transcription Events in Toll-like Receptor Signaling. Cell Rep 19:2853-2866
Villani, Alexandra-ChloƩ; Satija, Rahul; Reynolds, Gary et al. (2017) Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors. Science 356:

Showing the most recent 10 out of 100 publications