Academic literature on the topic '3C-seq'

BackgroundChromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised.MethodsWe developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure.ResultsWhen all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance.DiscussionPreviously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development.

Abstract Motivation The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contact maps, but their potential application to prokaryotic data has not yet been evaluated. Results Here, we present a comparative analysis of domain calling algorithms using available single-microbe experimental data. We evaluated the algorithms’ intra-dataset reproducibility, concordance with other tools and sensitivity to coverage and resolution of contact maps. Using RNA-seq as an example, we showed how orthogonal biological data can be utilized to validate the reliability and significance of annotated domains. We also suggest that in silico simulations of contact maps can be used to choose optimal restriction enzymes and estimate theoretical map resolutions before the experiment. Our results provide guidelines for researchers investigating microbes and microbial communities using high-throughput 3C assays such as Hi-C and 3C-seq. Availability and implementation The code of the analysis is available at https://github.com/magnitov/prokaryotic_cids. Supplementary information Supplementary data are available at Bioinformatics online.

According to recent reports, bacterial chromosomes exhibit a hierarchical organization. The number of proteins that bind DNA are responsible for local and global organization of the DNA ensuring proper chromosome compaction. Advanced molecular biology techniques combined with high-throughput DNA sequencing methods allow a precise analysis of bacterial chromosome structures on a local and global scale. Methods such as in vivo footprinting and ChIP-seq allow to map binding sites of analyzed proteins in certain chromosomal regions or along the whole chromosome while analysis of the spatial interactions on global scale could be performed by 3C techniques. Additional insight into complex structures created by chromosome-organizing proteins is provided by high-resolution fluorescence microscopy techniques.

HLA-G, a nonclassical HLA molecule uniquely expressed in the placenta, is a central component of fetus-induced immune tolerance during pregnancy. The tissue-specific expression of HLA-G, however, remains poorly understood. Here, systematic interrogation of the HLA-G locus using massively parallel reporter assay (MPRA) uncovered a previously unidentified cis-regulatory element 12 kb upstream of HLA-G with enhancer activity, Enhancer L. Strikingly, clustered regularly-interspaced short palindromic repeats (CRISPR)/Cas9-mediated deletion of this enhancer resulted in ablation of HLA-G expression in JEG3 cells and in primary human trophoblasts isolated from placenta. RNA-seq analysis demonstrated that Enhancer L specifically controls HLA-G expression. Moreover, DNase-seq and chromatin conformation capture (3C) defined Enhancer L as a cell type-specific enhancer that loops into the HLA-G promoter. Interestingly, MPRA-based saturation mutagenesis of Enhancer L identified motifs for transcription factors of the CEBP and GATA families essential for placentation. These factors associate with Enhancer L and regulate HLA-G expression. Our findings identify long-range chromatin looping mediated by core trophoblast transcription factors as the mechanism controlling tissue-specific HLA-G expression at the maternal–fetal interface. More broadly, these results establish the combination of MPRA and CRISPR/Cas9 deletion as a powerful strategy to investigate human immune gene regulation.

Abstract Three quantitative trait loci (QTLs) modifying fetal hemoglobin (HbF) levels have been identified, and these have been shown to have a predictive value of disease severity in β thalassemia and sickle cell disease in diverse ethnic groups. One of the HbF QTLs which consists of a set of common intergenic single nucleotide polymorphisms (SNPs) in the HBS1L-MYB intergenic region on chromosome 6q23, has also been consistently identified as highly associated with clinically important human erythroid traits. Despite extensive genetic evidence, a clear mechanistic basis for the association between the intergenic SNPs and erythroid biology has remained elusive, although the two flanking genes (HBS1L and MYB) are candidate target genes. Here, we set out to characterize the regulatory potential of the human HBS1L-MYB intergenic region in detail and to investigate its functional impact on the erythroid phenotype-associated variants. We profiled chromatin occupancy of the key erythroid LDB1 transcription factor (TF) complex in primary human erythroid progenitors (HEPs) using chromatin immunoprecipitation coupled to high-throughput sequencing (ChIP-Seq) and quantitative PCR (ChIP-qPCR). We detected an intergenic cluster containing 7 binding sites for the LDB1–complex, characterized by strong binding and co-occupancy of core complex proteins LDB1, GATA1, TAL1 and ETO2. One of these sites was co-occupied by the erythroid-specific TF KLF1, a protein which was also found to bind the murine intergenic region. Depletion of LDB1, TAL1 and KLF1 in K562 cells using RNA interference resulted in a specific downregulation of MYB expression while leaving HBS1L levels unaffected, demonstrating that the erythroid TFs occupying the intergenic enhancers are required for MYB expression. Using chromosome conformation capture (3C) coupled to high-throughput sequencing (3C-Seq), we profiled higher order chromatin structure within the locus, and detected several strong chromatin co-associations between the MYB promoter and intergenic sequences, almost all of which correlated with TF binding. The binding activities were distributed over a conserved core region identical to a 24-kb interval containing genetic variants in strong genetic association with erythroid traits in human populations. This block of SNPs is referred to as HBS1L-MYB intergenic polymorphisms block-2 (HMIP-2). The SNPs within HMIP-2 clustered in 2 regions positioned directly under the 2 LDB1-complex ChIP-Seq peaks, at -84 and -71 kb from the MYB transcription start site. Using allele-specific ChIP in K562 cells, we observed diminished (25-50%) binding of LDB1, GATA1, TAL1 and KLF1 to the minor rs66650371 allele, showing that rs66650371 affects local TF binding. An allele-specific 3C analysis also showed reduced interactions between the minor rs66650371 allele at -84 and MYB. We validated and expanded observations made in K562 cells using primary human cells: 1. HEPs from high HbF individuals homozygous for all minor alleles of the phenotype-associated -84kb and -71kb intergenic variants in the conserved core (‘SNP/SNP’) showed consistently lower MYB levels throughout phase II of the culture as compared to wildtype control cells (‘WT/WT’); 37% lower MYB on average; 2. ChIP experiments on SNP/SNP and WT/WT HEPs showed reduced binding of GATA1 and KLF1 to the -84 and -71 regulatory elements (containing the associated variants), the results were further confirmed by allele-specific ChIP assays in SNP/WT HEPs; 3. 3C-qPCR assays on cultured SNP/SNP and WT/WT cells demonstrated diminished looping between the -84 element and the MYB promoter in SNP/SNP individuals; 4. SNP/WT HEPs also showed allelic imbalance of MYB but not HBS1L transcripts when compared to controls (WT/WT and SNP/SNP HEPs). In conclusion, we show that the HBS1L-MYB gene-free interval contains distal enhancer elements that interact with MYB, a critical regulator of erythroid development and HbF levels. Key variants in the intergenic interval affect MYB expression by reducing TF binding to its regulatory elements and disrupting long-range enhancer-gene interaction. Our study identifies the first causal link between the 6q23 HbF QTL and MYB regulation, provides novel insights into the molecular control of clinically important haematological traits and adds another layer of complexity to the regulation of MYB, suggesting potential targets for therapeutic intervention. Disclosures: Thein: Sangart: Consultancy; Shire: Research Funding; Novartis: Speakers Bureau.

AbstractSingle-cell Hi-C (scHi-C) analysis has been increasingly used to map chromatin architecture in diverse tissue contexts, but computational tools to define chromatin loops at high resolution from scHi-C data are still lacking. Here, we describe Single-Nucleus Analysis Pipeline for Hi-C (SnapHiC), a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. Using scHi-C data from 742 mouse embryonic stem cells, we benchmark SnapHiC against a number of computational tools developed for mapping chromatin loops and interactions from bulk Hi-C. We further demonstrate its use by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells, which uncovers cell type-specific chromatin loops and predicts putative target genes for noncoding sequence variants associated with neuropsychiatric disorders. Our results indicate that SnapHiC could facilitate the analysis of cell type-specific chromatin architecture and gene regulatory programs in complex tissues.

Abstract Gain-of-function NOTCH1 mutations are oncogenic drivers in a high fraction of T-cell lymphoblastic leukemia/lymphoma (T-LL). These mutations variously cause increased production or stabilization of the free intracellular domain of NOTCH1, which regulates gene expression by forming a transcription complex with the DNA-binding factor RBPJ and coactivators of the MAML family. Using expression profiling and ChIP-seq, we have shown that NOTCH1/RBPJ complexes activate most target genes by binding to super-enhancers, large regulatory elements that switch on transcription through long-range interactions with gene promoters. MYC is a critical target of Notch in normal and malignant pre-T cells, but how Notch regulates MYC is unknown. To understand which regulatory element(s) regulate MYC expression, we used chromatin conformation capture (3C) assays to test the interaction between putative enhancer(s) and the MYC promoter in T-LL cell lines, and reporter gene assays to confirm enhancer function of candidate sites. We identified a distal site located >1 Mb 3’ of human and murine MYC termed the Notch-dependent MYC enhancer (NDME) that binds Notch transcription complexes and physically interacts with the MYC proximal promoter. An ~1 kb DNA fragment containing this site activates a luciferase reporter gene in a Notch-dependent fashion in T-LL cells but not in heterologous cell types. The Notch binding site lies within a large enhancer region (>600 kb in breadth) containing multiple discrete H3K27ac peaks. Remarkably, acute changes in Notch activation produce rapid changes in H3K27 acetylation across the entire enhancer region and the MYC promoter that correlate with NOTCH1/RBPJ complex binding and MYC expression. T-LL cells selected for resistance to gamma-secretase inhibitors (GSIs) exhibit epigenetic silencing of the NDME and loss of NDME looping interactions with the MYC promoter, yet maintain MYC expression. 3C analysis of GSI resistant cells shows preferential interaction between the MYC promoter and a more 3’ enhancer element recently described as a BRD4-dependent regulator of MYC expression in acute myeloid leukemia cells. In line with this observation, BRD4 antagonists are potent inhibitors of MYC expression in GSI resistant T-LL cells but not GSI-sensitive cells. We also studied a case of Notch-mutated early T-cell progenitor acute lymphoblastic leukemia (ETP-ALL). ChIP-Seq analysis of the leukemic blasts revealed an “AML-like” MYC enhancer chromatin state, and as predicted from our analysis of cell lines, the blasts rapidly down-regulated MYC in response to BRD4 inhibitor but not in response to GSI. These findings suggest that specific MYC chromatin states predict responsiveness to Notch and BRD4 inhibitors, and provide a rationale for use of Notch and BRD4 inhibitor combinations in Notch-mutated leukemias. Disclosures No relevant conflicts of interest to declare.

L'ADN génomique des bactéries existe dans un complexe dynamique riche en protéines, le "nucléoïde'', très bien organisé à différentes échelles de longueur. Cette thèse décrit notre modélisation et analyse des données en mettant l'accent sur l'organisation du nucléoïde de \textit{E. coli}, et sur comment cette organisation affecte l'expression des gènes. La première partie du travail est une revue des progrès récents expérimentaux et théoriques quantifiant l'organisation physique (la géométrie et le compactage) du chromosome bactérien. En particulier, nous soulignons le rôle que la physique de la matière molle et la physique statistique jouent dans la description de ce système. Une deuxième partie de l'ouvrage traite d'un modèle de la physique des polymères inspiré par deux caractéristiques du nucléoïde: auto-adhérence osmotique et effet des protéines de pontage. Les résultats sont une caractérisation qualitative du diagramme de phase, qui montre que les nucléoïdes forment des domaines distincts sans interactions intra-spécifiques. La thèse couvre également plusieurs approches d'analyse de données pour tester les connexions entre l'organisation du nucléoïde avec l'expression des gènes (RNA-Seq) et des protéines (ChIP-Seq). Cette dernière partie contient une description de l'outil web NuST, qui permet d'effectuer de simples analyses statistiques sur de multiples échelles. En outre, nous présentons une étude de corrélation d'un grand nombre de mesures d'expression génomique dans différentes conditions de croissance, et nous le comparons avec les cartes d'interaction (Hi-C) spatiale entre le chromosome
The genomic DNA of bacteria exists in a complex and dynamic protein-rich state, which is highly organized at various lengthscales. This thesis describes a work of physical modeling and data analysis focused on the E. coli genome organization, in the form of the "nucleoid'', and on how nucleoid organization affects gene expression.The first part of the work is a review of the recent experimental andt heoretical advances quantifying the physical organization (compactionand geometry) of the bacterial chromosome with its complement of proteins (the nucleoid). In particular, we highlight the role that statistical and soft condensed matter physics play in describing this system of fundamental biological importance.A second part of the work discusses a simple polymer physics model inspired by two main features of the nucleoid: osmotic self-adhesion and protein bridging. Results are summarized by a qualitative characterization of the phase diagram of this model which shows the general feature that distinct domains may form without the need forintra-specific interactions.The thesis also covers several data analysis approaches to test possible connections between the physical organization of the nucleoid with gene expression (RNA-Seq) and protein binding (ChIP-Seq) datasets. This latter part contains a description of the NuST webtool, which consists of a database which collect datasets from past experiments and an implementation of simple multi scale statistical analysis tools. Additionally, we introduce a correlation study of a large number (about 300) of genome-wide expression data-sets, also compared to the outcome to the published genome interaction map (Hi-C)data

Over the last decade, development and application of a set of molecular genomic approaches based on the chromosome conformation capture method (3C), combined with increasingly powerful imaging approaches have enabled high resolution and genome-wide analysis of the spatial organization of chromosomes. The aim of this thesis is two-fold; 1), to provide guidelines for analyzing and interpreting data obtained from genome-wide 3C methods such as Hi-C and 3C-seq and 2), to leverage the 3C technology to solve genome function, structure, assembly, development and dosage problems across a broad range of organisms and disease models. First, through the introduction of cWorld, a toolkit for manipulating genome structure data, I accelerate the pace at which *C experiments can be performed, analyzed and biological insights inferred. Next I discuss a set of practical guidelines one should consider while planning an experiment to study the structure of the genome, a simple workflow for data processing unique to *C data and a set of considerations one should be aware of while attempting to gain insights from the data. Next, I apply these guidelines and leverage the cWorld toolkit in the context of two dosage compensation systems. The first is a worm condensin mutant which shows a reduction in dosage compensation in the hermaphrodite X chromosomes. The second is an allele-specific study consisting of genome wide Hi-C, RNA-Seq and ATAC-Seq which can measure the state of the active (Xa) and inactive (Xi) X chromosome. Finally I turn to studying specific gene – enhancer looping interactions across a panel of ENCODE cell-lines. These studies, when taken together, further our understanding of how genome structure relates to genome function.