Project description:Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq). The transient TF-target interactions captured uncover the early mode-of-action of NIN-LIKE PROTEIN 7 (NLP7), a master regulator of the nitrogen signaling pathway in plants. These transient NLP7 targets captured in root cells using temporal TF perturbation account for 50% of NLP7-regulated genes not detectably bound by NLP7 in planta. Rapid and transient NLP7 binding activates early nitrogen response TFs, which we validate to amplify the NLP7-initiated transcriptional cascade. Our approaches to capture transient TF-target interactions genome-wide can be applied to validate dynamic GRN models for any pathway or organism of interest.
Project description:The completion of whole genome sequencing projects has provided the genetic instructions of life. However, whereas the identification of gene coding regions has progressed, the mapping of transcriptional regulatory motifs has moved more slowly. To understand how distinct expression profiles can be established and maintained, a greater understanding of these sequences and their trans-acting factors is required. Herein we have used a combined in silico and biochemical approach to identify binding sites [repressor element 1/neuron-restrictive silencer element (RE1/NRSE)] and potential target genes of RE1 silencing transcription factor/neuron-restrictive silencing factor (REST/NRSF) within the human, mouse, and Fugu rubripes genomes. We have used this genome-wide analysis to identify 1,892 human, 1,894 mouse, and 554 Fugu RE1/NRSEs and present their location and gene linkages in a searchable database. Furthermore, we identified an in vivo hierarchy in which distinct subsets of RE1/NRSEs interact with endogenous levels of REST/NRSF, whereas others function as bona fide transcriptional control elements only in the presence of elevated levels of REST/NRSF. These data show that individual RE1/NRSE sites interact differentially with REST/NRSF within a particular cell type. This combined bioinformatic and biochemical approach serves to illustrate the selective manner in which a transcription factor interacts with its potential binding sites and regulates target genes. In addition, this approach provides a unique whole-genome map for a given transcription factor-binding site implicated in establishing specific patterns of neuronal gene expression.
Project description:An essential component of genome function is the syntax of genomic regulatory elements that determine how diverse transcription factors interact to orchestrate a program of regulatory control. A precise characterization of in vivo spacing constraints between key transcription factors would reveal key aspects of this genomic regulatory language. To discover novel transcription factor spatial binding constraints in vivo, we developed a new integrative computational method, genome wide event finding and motif discovery (GEM). GEM resolves ChIP data into explanatory motifs and binding events at high spatial resolution by linking binding event discovery and motif discovery with positional priors in the context of a generative probabilistic model of ChIP data and genome sequence. GEM analysis of 63 transcription factors in 214 ENCODE human ChIP-Seq experiments recovers more known factor motifs than other contemporary methods, and discovers six new motifs for factors with unknown binding specificity. GEM's adaptive learning of binding-event read distributions allows it to further improve upon previous methods for processing ChIP-Seq and ChIP-exo data to yield unsurpassed spatial resolution and discovery of closely spaced binding events of the same factor. In a systematic analysis of in vivo sequence-specific transcription factor binding using GEM, we have found hundreds of spatial binding constraints between factors. GEM found 37 examples of factor binding constraints in mouse ES cells, including strong distance-specific constraints between Klf4 and other key regulatory factors. In human ENCODE data, GEM found 390 examples of spatially constrained pair-wise binding, including such novel pairs as c-Fos:c-Jun/USF1, CTCF/Egr1, and HNF4A/FOXA1. The discovery of new factor-factor spatial constraints in ChIP data is significant because it proposes testable models for regulatory factor interactions that will help elucidate genome function and the implementation of combinatorial control.
Project description:The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. However, the use of high throughput experimental methods, such as ChIP-chip and ChIP-sequencing, is limited by their high cost and strong dependence on cellular type and context. We developed a computational method for the genome-wide identification of functional transcription factor binding sites based on positional weight matrices, comparative genomics, and gene expression profiling. The method was applied to Stat3, a transcription factor playing crucial roles in inflammation, immunity and oncogenesis, and able to induce distinct subsets of target genes in different cell types or conditions. A newly generated positional weight matrix enabled us to assign affinity scores of high specificity, as measured by EMSA competition assays. Phylogenetic conservation with 7 vertebrate species was used to select the binding sites most likely to be functional. Validation was carried out on predicted sites within genes identified as differentially expressed in the presence or absence of Stat3 by microarray analysis. Twelve of the fourteen sites tested were bound by Stat3 in vivo, as assessed by Chromatin Immunoprecipitation, allowing us to identify 9 Stat3 transcriptional targets. Given its high validation rate, and the availability of large transcription factor-dependent gene expression datasets obtained under diverse experimental conditions, our approach appears to be a valid alternative to high-throughput experimental assays for the discovery of novel direct targets of transcription factors.
Project description:The transcription factor E2F4 is a member of the E2F family of regulators which has critical roles in cell cycle control and differentiation. In order to fully understand the physiological roles of E2F4 and the regulatory networks it mediates, and to reveal its relationships with other members of the E2F family, it is essential to comprehensively identify E2F4 target sites throughout the genome. Here, we investigated genome-wide E2F4 targets in human lymphoblastoid cells using the recently developed unbiased target discovery technique of ChIP sequencing.
Project description:The transcription factor E2F4 is a member of the E2F family of regulators which has critical roles in cell cycle control and differentiation. In order to fully understand the physiological roles of E2F4 and the regulatory networks it mediates, and to reveal its relationships with other members of the E2F family, it is essential to comprehensively identify E2F4 target sites throughout the genome. Here, we investigated genome-wide E2F4 targets in human lymphoblastoid cells using the recently developed unbiased target discovery technique of ChIP sequencing. We sequecned E2F4 ChIP and corresponding Input
Project description:Secretion systems play a crucial role in microbe-microbe or host-microbe interactions. Among these systems, the extracellular contractile injection system (eCIS) is a unique bacterial and archaeal extracellular secretion system that injects protein toxins into target organisms. However, the specific proteins that eCISs inject into target cells and their functions remain largely unknown. Here, we developed a machine learning classifier to identify eCIS-associated toxins (EATs). The classifier combines genetic and biochemical features to identify EATs. We also developed a score for the eCIS N-terminal signal peptide to predict EAT loading. Using the classifier we classified 2,194 genes from 950 genomes as putative EATs. We validated four new EATs, EAT14-17, showing toxicity in bacterial and eukaryotic cells, and identified residues of their respective active sites that are critical for toxicity. Finally, we show that EAT14 inhibits mitogenic signaling in human cells. Our study provides insights into the diversity and functions of EATs and demonstrates machine learning capability of identifying novel toxins. The toxins can be employed in various applications dependently or independently of eCIS.
Project description:Stage-specific transcription is a fundamental biological process in the life cycle of the Plasmodium parasite. Proteins containing the AP2 DNA-binding domain are responsible for stage-specific transcriptional regulation and belong to the only known family of transcription factors in Plasmodium parasites. Comprehensive identification of their target genes will advance our understanding of the molecular basis of stage-specific transcriptional regulation and stage-specific parasite development. AP2-O is an AP2 family transcription factor that is expressed in the mosquito midgut-invading stage, called the ookinete, and is essential for normal morphogenesis of this stage. In this study, we identified the genome-wide target genes of AP2-O by chromatin immunoprecipitation-sequencing and elucidate how this AP2 family transcription factor contributes to the formation of this motile stage. The analysis revealed that AP2-O binds specifically to the upstream genomic regions of more than 500 genes, suggesting that approximately 10% of the parasite genome is directly regulated by AP2-O. These genes are involved in distinct biological processes such as morphogenesis, locomotion, midgut penetration, protection against mosquito immunity and preparation for subsequent oocyst development. This direct and global regulation by AP2-O provides a model for gene regulation in Plasmodium parasites and may explain how these parasites manage to control their complex life cycle using a small number of sequence-specific AP2 transcription factors.
Project description:BackgroundThe transcription factor Ets1 is highly expressed in B lymphocytes. Loss of Ets1 leads to premature B cell differentiation into antibody-secreting cells (ASCs), secretion of autoantibodies, and development of autoimmune disease. Despite the importance of Ets1 in B cell biology, few Ets1 target genes are known in these cells.ResultsTo obtain a more complete picture of the function of Ets1 in regulating B cell differentiation, we performed Ets1 ChIP-seq in primary mouse B cells to identify >10,000-binding sites, many of which were localized near genes that play important roles in B cell activation and differentiation. Although Ets1 bound to many sites in the genome, it was required for regulation of less than 5% of them as evidenced by gene expression changes in B cells lacking Ets1. The cohort of genes whose expression was altered included numerous genes that have been associated with autoimmune disease susceptibility. We focused our attention on four such Ets1 target genes Ptpn22, Stat4, Egr1, and Prdm1 to assess how they might contribute to Ets1 function in limiting ASC formation. We found that dysregulation of these particular targets cannot explain altered ASC differentiation in the absence of Ets1.ConclusionWe have identified genome-wide binding targets for Ets1 in B cells and determined that a relatively small number of these putative target genes require Ets1 for their normal expression. Interestingly, a cohort of genes associated with autoimmune disease susceptibility is among those that are regulated by Ets1. Identification of the target genes of Ets1 in B cells will help provide a clearer picture of how Ets1 regulates B cell responses and how its loss promotes autoantibody secretion.
Project description:Deep sequencing of size-selected DNase I-treated chromatin (DNase-seq) allows high-resolution measurement of chromatin accessibility to DNase I cleavage, permitting identification of de novo active cis-regulatory modules (CRMs) and individual transcription factor (TF) binding sites. We adapted DNase-seq to nuclei isolated from C. elegans embryos and L1 arrest larvae to generate high-resolution maps of TF binding. Over half of embryonic DNase I hypersensitive sites (DHSs) were annotated as noncoding, with 24% in intergenic, 12% in promoters, and 28% in introns, with similar statistics observed in L1 arrest larvae. Noncoding DHSs are highly conserved and enriched in marks of enhancer activity and transcription. We validated noncoding DHSs against known enhancers from myo-2, myo-3, hlh-1, elt-2, and lin-26/lir-1 and recapitulated 15 of 17 known enhancers. We then mined DNase-seq data to identify putative active CRMs and TF footprints. Using DNase-seq data improved predictions of tissue-specific expression compared with motifs alone. In a pilot functional test, 10 of 15 DHSs from pha-4, icl-1, and ceh-13 drove reporter gene expression in transgenic C. elegans Overall, we provide experimental annotation of 26,644 putative CRMs in the embryo containing 55,890 TF footprints, as well as 15,841 putative CRMs in the L1 arrest larvae containing 32,685 TF footprints.