Author
Nancy M. Hannett
Bio: Nancy M. Hannett is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Transcription factor & Enhancer. The author has an hindex of 25, co-authored 29 publications receiving 15701 citations.
Papers
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TL;DR: This work determines how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells, and identifies network motifs, the simplest units of network architecture, and demonstrates that an automated process can use motifs to assemble a transcriptional regulatory network structure.
Abstract: We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiaeassociate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.
3,127 citations
TL;DR: It is found that PRC2 target genes are preferentially activated during ES cell differentiation and that the ES cell regulators OCT4, SOX2, and NANOG cooccupy a significant subset of these genes.
2,341 citations
TL;DR: An initial map of yeast's transcriptional regulatory code is constructed by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species.
Abstract: DNA-binding transcriptional regulators interpret the genome's regulatory code by binding to specific sequences to induce or repress gene expression. Comparative genomics has recently been used to identify potential cis-regulatory sequences within the yeast genome on the basis of phylogenetic conservation, but this information alone does not reveal if or when transcriptional regulators occupy these binding sites. We have constructed an initial map of yeast's transcriptional regulatory code by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species. The organization of regulatory elements in promoters and the environment-dependent use of these elements by regulators are discussed. We find that environment-specific use of regulatory elements predicts mechanistic models for the function of a large population of yeast's transcriptional regulators.
2,304 citations
TL;DR: It is postulated that super-enhancers are phase-separated multimolecular assemblies, also known as biomolecular condensates, which provide a means to compartmentalize and concentrate biochemical reactions within cells.
Abstract: Super-enhancers (SEs) are clusters of enhancers that cooperatively assemble a high density of transcriptional apparatus to drive robust expression of genes with prominent roles in cell identity. Here, we demonstrate that the SE-enriched transcriptional coactivators BRD4 and MED1 form nuclear puncta at SEs that exhibit properties of liquid-like condensates and are disrupted by chemicals that perturb condensates. The intrinsically disordered regions (IDRs) of BRD4 and MED1 can form phase-separated droplets and MED1-IDR droplets can compartmentalize and concentrate transcription apparatus from nuclear extracts. These results support the idea that coactivators form phase-separated condensates at SEs that compartmentalize and concentrate the transcription apparatus, suggest a role for coactivator IDRs in this process, and offer insights into mechanisms involved in control of key cell identity genes.
1,506 citations
TL;DR: These maps take into account changes in nucleosome occupancy at actively transcribed genes and, in doing so, revise previous assessments of the modifications associated with gene expression, providing the foundation for further understanding the roles of chromatin in gene expression and genome maintenance.
1,483 citations
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TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Abstract: Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
32,980 citations
TL;DR: The surface of nucleosomes is studded with a multiplicity of modifications that can dictate the higher-order chromatin structure in which DNA is packaged and can orchestrate the ordered recruitment of enzyme complexes to manipulate DNA.
10,046 citations
TL;DR: This work proposes an approach to measuring statistical significance in genomewide studies based on the concept of the false discovery rate, which offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted.
Abstract: With the increase in genomewide experiments and the sequencing of multiple genomes, the analysis of large data sets has become commonplace in biology. It is often the case that thousands of features in a genomewide data set are tested against some null hypothesis, where a number of features are expected to be significant. Here we propose an approach to measuring statistical significance in these genomewide studies based on the concept of the false discovery rate. This approach offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted. In doing so, a measure of statistical significance called the q value is associated with each tested feature. The q value is similar to the well known p value, except it is a measure of significance in terms of the false discovery rate rather than the false positive rate. Our approach avoids a flood of false positive results, while offering a more liberal criterion than what has been used in genome scans for linkage.
9,239 citations
TL;DR: This work states that rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize the view of biology and disease pathologies in the twenty-first century.
Abstract: A key aim of postgenomic biomedical research is to systematically catalogue all molecules and their interactions within a living cell. There is a clear need to understand how these molecules and the interactions between them determine the function of this enormously complex machinery, both in isolation and when surrounded by other cells. Rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize our view of biology and disease pathologies in the twenty-first century.
7,475 citations
TL;DR: High-resolution maps for the genome-wide distribution of 20 histone lysine and arginine methylations as well as histone variant H2A.Z, RNA polymerase II, and the insulator binding protein CTCF across the human genome using the Solexa 1G sequencing technology are generated.
6,488 citations