The transcriptional regulation of gene expression is pivotal to all biological processes. Each of our ~20,000 protein-coding genes must be expressed at the right place, time and level, as well as under the right developmental or physiological circumstances. Consequently, inappropriate gene expression is implicated in a myriad of human diseases, including congenital disorders, cancer and obesity. Transcription has been studied intensively for decades, resulting in a detailed picture of the basic biochemical mechanisms of mRNA production. However, we know little about gene regulation at a 'systems level', i.e. how TFs function together in complex gene regulatory networks (GRNs) to faithfully orchestrate the expression of large sets of genes. Our long-term goal is to comprehensively characterize the structure, function and evolution of complex metazoan GRNs to gain insights into global mechanisms of gene regulation. It is becoming increasingly clear that textbook explanations of gene regulation in which a TF binds DNA in the genome and upon doing so regulates the most proximal gene are too simplistic because many physical TF binding events lack an apparent regulatory consequence. There are several explanations for this, ranging from technical (e.g. detection limits, attribution of a bindng event to the wrong gene) to biological (e.g. redundancy between TFs, condition-dependent effects). Conversely, regulatory interactions are not necessarily due to a direct effect. For instance, TFs can function in cascades to propagate functional regulation. A major challenge is to combine physical and regulatory interactions to increase our understanding of the mechanisms of gene regulation in the context of complex multicellular organisms. Many GRN studies focus either solely on physical TF interactions, whereas others focus primarily on regulatory interactions. However, integrated GRNs that combine both are scarce and, when available are relatively small in scale. If we had high-quality, large- scale physical and regulatoy interaction data, as well as spatiotemporal and conditional gene expression data, we could build increasingly precise GRNs. Here, we will continue our studies on the nematode C. elegans to map and integrate physical and regulatory GRNs, which will help us to go beyond mapping to understanding the regulatory mechanisms of gene expression at a systems level in a complex multicellular organism.

Public Health Relevance

The regulation of gene expression is vital for healthy development and homeostasis and many diseases are caused by or associated with severe changes in gene expression. In recent years, tremendous progress has been made in the identification of gene regulatory networks that describe physical interactions between regulators and their targets. This project will generate a large physical network, delineate regulatory interactions and combine the two types of interactions to gain insights into the mechanisms of gene regulation at a systems level.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM082971-06
Application #
8641704
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Sledjeski, Darren D
Project Start
2008-06-01
Project End
2017-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
6
Fiscal Year
2014
Total Cost
$720,869
Indirect Cost
$257,120
Name
University of Massachusetts Medical School Worcester
Department
Genetics
Type
Schools of Medicine
DUNS #
603847393
City
Worcester
State
MA
Country
United States
Zip Code
01655
Yilmaz, L Safak; Walhout, Albertha Jm (2017) Metabolic network modeling with model organisms. Curr Opin Chem Biol 36:32-39
Zhang, Jingyan; Holdorf, Amy D; Walhout, Albertha Jm (2017) C. elegans and its bacterial diet as a model for systems-level understanding of host-microbiota interactions. Curr Opin Biotechnol 46:74-80
Hu, Queenie; D'Amora, Dayana R; MacNeil, Lesley T et al. (2017) The Oxidative Stress Response in Caenorhabditis elegans Requires the GATA Transcription Factor ELT-3 and SKN-1/Nrf2. Genetics 206:1909-1922
García-González, Aurian P; Ritter, Ashlyn D; Shrestha, Shaleen et al. (2017) Bacterial Metabolism Affects the C. elegans Response to Cancer Chemotherapeutics. Cell 169:431-441.e8
Fuxman Bass, Juan I; Reece-Hoyes, John S; Walhout, Albertha J M (2016) Gene-Centered Yeast One-Hybrid Assays. Cold Spring Harb Protoc 2016:pdb.top077669
Fuxman Bass, Juan I; Pons, Carles; Kozlowski, Lucie et al. (2016) A gene-centered C. elegans protein-DNA interaction network provides a framework for functional predictions. Mol Syst Biol 12:884
Fuxman Bass, Juan I; Reece-Hoyes, John S; Walhout, Albertha J M (2016) Colony Lift Colorimetric Assay for ?-Galactosidase Activity. Cold Spring Harb Protoc 2016:pdb.prot088963
Fuxman Bass, Juan I; Reece-Hoyes, John S; Walhout, Albertha J M (2016) Zymolyase-Treatment and Polymerase Chain Reaction Amplification from Genomic and Plasmid Templates from Yeast. Cold Spring Harb Protoc 2016:pdb.prot088971
Fuxman Bass, Juan I; Reece-Hoyes, John S; Walhout, Albertha J M (2016) Performing Yeast One-Hybrid Library Screens. Cold Spring Harb Protoc 2016:pdb.prot088955
Fuxman Bass, Juan I; Reece-Hoyes, John S; Walhout, Albertha J M (2016) Generating Bait Strains for Yeast One-Hybrid Assays. Cold Spring Harb Protoc 2016:pdb.prot088948

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