The differential expression of each of our ~25,000 genes in different tissues or under different conditions is critical for our proper development and function. Indeed, changes in differential gene expression caused by mutations in transcription factors (TFs) or the cis-regulatory genomic DNA elements they bind to (TF binding sites, or TFBSs) can result in a variety of human diseases, including several congenital disorders and cancer. In order to fully understand both normal development and pathologies, and to design effective therapeutics it is therefore critical to understand which TF regulates the expression of which gene, where and under which (developmental) conditions. In addition, it is essential to know the elements each TF binds to and where in the genome these TFBSs are located. This is a major challenge in genomic science as very little is known about the targets, binding sites, transcriptional activity and biological function for the majority of metazoan TFs. We use the nematode C. elegans as a model to address this challenge. Our long-term goal is to comprehensively map and characterize the protein-DNA interactions between all C. elegans TFs and all gene regulatory regions, and to identify all responsible TFBSs. Currently, ChIP is the most popular method to identify TF-DNA interactions. Although powerful, metazoan ChIP is limited to the few TFs that are widely and highly expressed, and for which suitable antibodies are available. To enable the identification of a wide variety of metazoan protein-DNA interactions in a condition-independent manner, we developed a high-throughput version of the yeast one-hybrid (Y1H) system. Our Y1H system can be used with several Gateway resources we created, including a promoterome that consists of 6,000 promoters, as well as ORF clones for ~80% of all 940 predicted worm TFs. Here, we propose to identify TFBSs throughout 30% of all C. elegans promoters by first mapping protein-DNA interactions between all available gene promoters and TFs by Y1H assays, and then to use these interactions to computationally delineate TFBSs. Project narrative The expression of each of our genes in different tissues or under different conditions is critical for our proper development and function. Indeed mutations in transcription factors or the genomic DNA sequences they bind to can result in a variety of human diseases, including several congenital disorders and cancer. We will identify which TF regulates the expression of which gene to gain insight into both normal development and disease, and to design effective therapeutics. Since such studies are not feasible at the genome scale in humans or mice, we have chosen the worm (C. elegans) as a model system.
| Reece-Hoyes, John S; Walhout, Albertha J M (2018) Gateway Recombinational Cloning. Cold Spring Harb Protoc 2018:pdb.top094912 |
| Reece-Hoyes, John S; Walhout, Albertha J M (2018) Propagating Gateway Vectors. Cold Spring Harb Protoc 2018:pdb.prot094920 |
| Reece-Hoyes, John S; Walhout, Albertha J M (2018) Generating an Open Reading Frame (ORF) Entry Clone and Destination Clone. Cold Spring Harb Protoc 2018:pdb.prot094938 |
| Reece-Hoyes, John S; Walhout, Albertha J M (2018) Using Multisite LR Cloning to Generate a Destination Clone. Cold Spring Harb Protoc 2018:pdb.prot094946 |
| Hu, Queenie; D'Amora, Dayana R; MacNeil, Lesley T et al. (2018) The Caenorhabditis elegans Oxidative Stress Response Requires the NHR-49 Transcription Factor. G3 (Bethesda) 8:3857-3863 |
| 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 |
| 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 |
| 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 |
| Yilmaz, L Safak; Walhout, Albertha Jm (2017) Metabolic network modeling with model organisms. Curr Opin Chem Biol 36:32-39 |
| 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 |
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