The human genome is segmented into topologically associating domains (TADs), but the role of this conserved organization during transient changes in gene expression is not known. Here we describe the ...distribution of progestin-induced chromatin modifications and changes in transcriptional activity over TADs in T47D breast cancer cells. Using ChIP-seq (chromatin immunoprecipitation combined with high-throughput sequencing), Hi-C (chromosome capture followed by high-throughput sequencing), and three-dimensional (3D) modeling techniques, we found that the borders of the ∼ 2000 TADs in these cells are largely maintained after hormone treatment and that up to 20% of the TADs could be considered as discrete regulatory units where the majority of the genes are either transcriptionally activated or repressed in a coordinated fashion. The epigenetic signatures of the TADs are homogeneously modified by hormones in correlation with the transcriptional changes. Hormone-induced changes in gene activity and chromatin remodeling are accompanied by differential structural changes for activated and repressed TADs, as reflected by specific and opposite changes in the strength of intra-TAD interactions within responsive TADs. Indeed, 3D modeling of the Hi-C data suggested that the structure of TADs was modified upon treatment. The differential responses of TADs to progestins and estrogens suggest that TADs could function as "regulons" to enable spatially proximal genes to be coordinately transcribed in response to hormones.
Abstract
The three-dimensional conformation of genomes is an essential component of their biological activity. The advent of the Hi-C technology enabled an unprecedented progress in our understanding ...of genome structures. However, Hi-C is subject to systematic biases that can compromise downstream analyses. Several strategies have been proposed to remove those biases, but the issue of abnormal karyotypes received little attention. Many experiments are performed in cancer cell lines, which typically harbor large-scale copy number variations that create visible defects on the raw Hi-C maps. The consequences of these widespread artifacts on the normalized maps are mostly unexplored. We observed that current normalization methods are not robust to the presence of large-scale copy number variations, potentially obscuring biological differences and enhancing batch effects. To address this issue, we developed an alternative approach designed to take into account chromosomal abnormalities. The method, called OneD, increases reproducibility among replicates of Hi-C samples with abnormal karyotype, outperforming previous methods significantly. On normal karyotypes, OneD fared equally well as state-of-the-art methods, making it a safe choice for Hi-C normalization. OneD is fast and scales well in terms of computing resources for resolutions up to 5 kb.
Lamins (A/C and B) are major constituents of the nuclear lamina (NL). Structurally conserved lamina-associated domains (LADs) are formed by genomic regions that contact the NL. Lamins are also found ...in the nucleoplasm, with a yet unknown function. Here we map the genome-wide localization of lamin B1 in an euchromatin-enriched fraction of the mouse genome and follow its dynamics during the epithelial-to-mesenchymal transition (EMT). Lamin B1 associates with actively expressed and open euchromatin regions, forming dynamic euchromatin lamin B1-associated domains (eLADs) of about 0.3 Mb. Hi-C data link eLADs to the 3D organization of the mouse genome during EMT and correlate lamin B1 enrichment at topologically associating domain (TAD) borders with increased border strength. Having reduced levels of lamin B1 alters the EMT transcriptional signature and compromises the acquisition of mesenchymal traits. Thus, during EMT, the process of genome reorganization in mouse involves dynamic changes in eLADs.
Dynamic changes in the three-dimensional (3D) organization of chromatin are associated with central biological processes, such as transcription, replication and development. Therefore, the ...comprehensive identification and quantification of these changes is fundamental to understanding of evolutionary and regulatory mechanisms. Here, we present Comparison of Hi-C Experiments using Structural Similarity (CHESS), an algorithm for the comparison of chromatin contact maps and automatic differential feature extraction. We demonstrate the robustness of CHESS to experimental variability and showcase its biological applications on (1) interspecies comparisons of syntenic regions in human and mouse models; (2) intraspecies identification of conformational changes in Zelda-depleted Drosophila embryos; (3) patient-specific aberrant chromatin conformation in a diffuse large B-cell lymphoma sample; and (4) the systematic identification of chromatin contact differences in high-resolution Capture-C data. In summary, CHESS is a computationally efficient method for the comparison and classification of changes in chromatin contact data.
Genome discoveries at the core of biology are made by visual description and exploration of the cell, from microscopic sketches and biochemical mapping to computational analysis and spatial modeling. ...We outline the experimental and visualization techniques that have been developed recently which capture the three-dimensional interactions regulating how genes are expressed. We detail the challenges faced in integration of the data to portray the components and organization and their dynamic landscape. The goal is more than a single data-driven representation as interactive visualization for de novo research is paramount to decipher insights on genome organization in space.
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•Integrated research reveals multiscale, multifaceted, dynamic genome architecture.•Current tools are challenged by the multivariant 3D data and spatial models.•Visualization research can help explore novel visual grammar and interactions.•These integrative, predictive tools will transform analysis and communication.
Target identification is essential for drug design, drug-drug interaction prediction, dosage adjustment and side effect anticipation. Specifically, the knowledge of structural details is essential ...for understanding the mode of action of a compound on a target protein. Here, we present nAnnoLyze, a method for target identification that relies on the hypothesis that structurally similar binding sites bind similar ligands. nAnnoLyze integrates structural information into a bipartite network of interactions and similarities to predict structurally detailed compound-protein interactions at proteome scale. The method was benchmarked on a dataset of 6,282 pairs of known interacting ligand-target pairs reaching a 0.96 of area under the Receiver Operating Characteristic curve (AUC) when using the drug names as an input feature for the classifier, and a 0.70 of AUC for "anonymous" compounds or compounds not present in the training set. nAnnoLyze resulted in higher accuracies than its predecessor, AnnoLyze. We applied the method to predict interactions for all the compounds in the DrugBank database with each human protein structure and provide examples of target identification for known drugs against human diseases. The accuracy and applicability of our method to any compound indicate that a comparative docking approach such as nAnnoLyze enables large-scale annotation and analysis of compound-protein interactions and thus may benefit drug development.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Cohesin exists in two variants containing STAG1 or STAG2. STAG2 is one of the most mutated genes in cancer and a major bladder tumor suppressor. Little is known about how its inactivation ...contributes to tumorigenesis. Here, we analyze the genomic distribution of STAG1 and STAG2 and perform STAG2 loss-of-function experiments using RT112 bladder cancer cells; we then analyze the genomic effects by integrating gene expression and chromatin interaction data. Functional compartmentalization exists between the cohesin complexes: cohesin-STAG2 displays a distinctive genomic distribution and mediates short and mid-ranged interactions that engage genes at higher frequency than those established by cohesin-STAG1. STAG2 knockdown results in down-regulation of the luminal urothelial signature and up-regulation of the basal transcriptional program, mirroring differences between STAG2-high and STAG2-low human bladder tumors. This is accompanied by rewiring of DNA contacts within topological domains, while compartments and domain boundaries remain refractive. Contacts lost upon depletion of STAG2 are assortative, preferentially occur within silent chromatin domains, and are associated with de-repression of lineage-specifying genes. Our findings indicate that STAG2 participates in the DNA looping that keeps the basal transcriptional program silent and thus sustains the luminal program. This mechanism may contribute to the tumor suppressor function of STAG2 in the urothelium.
Discovering and classifying long noncoding RNAs (lncRNAs) across all mammalian tissues and cell lines remains a major challenge. Previously, mouse lncRNAs were identified using transcriptome ...sequencing (RNA-seq) data from a limited number of tissues or cell lines. Additionally, associating a few hundred lncRNA promoters with chromatin states in a single mouse cell line has identified two classes of chromatin-associated lncRNA. However, the discovery and classification of lncRNAs is still pending in many other tissues in mouse. To address this, we built a comprehensive catalog of lncRNAs by combining known lncRNAs with high-confidence novel lncRNAs identified by mapping and de novo assembling billions of RNA-seq reads from eight tissues and a primary cell line in mouse. Next, we integrated this catalog of lncRNAs with multiple genome-wide chromatin state maps and found two different classes of chromatin state-associated lncRNAs, including promoter-associated (plncRNAs) and enhancer-associated (elncRNAs) lncRNAs, across various tissues. Experimental knockdown of an elncRNA resulted in the downregulation of the neighboring protein-coding Kdm8 gene, encoding a histone demethylase. Our findings provide 2,803 novel lncRNAs and a comprehensive catalog of chromatin-associated lncRNAs across different tissues in mouse.
Functional characterization of a protein sequence is a common goal in biology, and is usually facilitated by having an accurate three-dimensional (3-D) structure of the studied protein. In the ...absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described.
Chromosome conformation capture techniques, such as Hi-C, are fundamental in characterizing genome organization. These methods have revealed several genomic features, such as chromatin loops, whose ...disruption can have dramatic effects in gene regulation. Unfortunately, their detection is difficult; current methods require that the users choose the resolution of interaction maps based on dataset quality and sequencing depth. Here, we introduce Binless, a resolution-agnostic method that adapts to the quality and quantity of available data, to detect both interactions and differences. Binless relies on an alternate representation of Hi-C data, which leads to a more detailed classification of paired-end reads. Using a large-scale benchmark, we demonstrate that Binless is able to call interactions with higher reproducibility than other existing methods. Binless, which is freely available, can thus reliably be used to identify chromatin loops as well as for differential analysis of chromatin interaction maps.
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