scholarly journals Varied interactions between proviruses and adjacent host chromatin.

1986 ◽  
Vol 6 (11) ◽  
pp. 3999-4007 ◽  
Author(s):  
K F Conklin ◽  
M Groudine

Retroviruses integrated at unique locations in the host genome can be expressed at different levels. We have analyzed the preintegration sites of three transcriptionally competent avian endogenous proviruses (evs) to determine whether the various levels of provirus expression correlate with their location in active or inactive regions of chromatin. Our results show that in three of four cell types, the chromatin conformation (as defined by relative nuclease sensitivity) of virus preintegration sites correlates with the level of expression of the resident provirus in ev+ cells: two inactive proviruses (ev-1 and ev-2) reside in nuclease-resistant chromatin domains and one active provirus (ev-3) resides in a nuclease-sensitive domain. Nuclear runoff transcription assays reveal that the preintegration sites of the active and inactive viruses are not transcribed. However, in erythrocytes of 15-day-old chicken embryos (15d RBCs), the structure and activity of the ev-3 provirus is independent of the conformation of its preintegration site. In this cell type, the ev-3 preintegration site is organized in a nuclease-resistant conformation, while the ev-3 provirus is in a nuclease-sensitive conformation and is transcribed. In addition, the nuclease sensitivity of host sequences adjacent to ev-3 is altered in ev-3+ 15d RBCs relative to that found in 15d RBCs that lack ev-3. These data suggest that the relationship between preintegration site structure and retrovirus expression is more complex than previously described.

1986 ◽  
Vol 6 (11) ◽  
pp. 3999-4007
Author(s):  
K F Conklin ◽  
M Groudine

Retroviruses integrated at unique locations in the host genome can be expressed at different levels. We have analyzed the preintegration sites of three transcriptionally competent avian endogenous proviruses (evs) to determine whether the various levels of provirus expression correlate with their location in active or inactive regions of chromatin. Our results show that in three of four cell types, the chromatin conformation (as defined by relative nuclease sensitivity) of virus preintegration sites correlates with the level of expression of the resident provirus in ev+ cells: two inactive proviruses (ev-1 and ev-2) reside in nuclease-resistant chromatin domains and one active provirus (ev-3) resides in a nuclease-sensitive domain. Nuclear runoff transcription assays reveal that the preintegration sites of the active and inactive viruses are not transcribed. However, in erythrocytes of 15-day-old chicken embryos (15d RBCs), the structure and activity of the ev-3 provirus is independent of the conformation of its preintegration site. In this cell type, the ev-3 preintegration site is organized in a nuclease-resistant conformation, while the ev-3 provirus is in a nuclease-sensitive conformation and is transcribed. In addition, the nuclease sensitivity of host sequences adjacent to ev-3 is altered in ev-3+ 15d RBCs relative to that found in 15d RBCs that lack ev-3. These data suggest that the relationship between preintegration site structure and retrovirus expression is more complex than previously described.


2021 ◽  
Author(s):  
Saumya Agrawal ◽  
Tanvir Alam ◽  
Masaru Koido ◽  
Ivan V. Kulakovskiy ◽  
Jessica Severin ◽  
...  

AbstractTranscription of the human genome yields mostly long non-coding RNAs (lncRNAs). Systematic functional annotation of lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. Currently, 95% of human lncRNAs have no functional characterization. Using chromatin conformation and Cap Analysis of Gene Expression (CAGE) data in 18 human cell types, we systematically located genomic regions in spatial proximity to lncRNA genes and identified functional clusters of interacting protein-coding genes, lncRNAs and enhancers. Using these clusters we provide a cell type-specific functional annotation for 7,651 out of 14,198 (53.88%) lncRNAs. LncRNAs tend to have specialized roles in the cell type in which it is first expressed, and to incorporate more general functions as its expression is acquired by multiple cell types during evolution. By analyzing RNA-binding protein and RNA-chromatin interaction data in the context of the spatial genomic interaction map, we explored mechanisms by which these lncRNAs can act.


Author(s):  
Zhong Wang ◽  
Alexandra G. Chivu ◽  
Lauren A. Choate ◽  
Edward J. Rice ◽  
Donald C. Miller ◽  
...  

AbstractWe trained a sensitive machine learning tool to infer the distribution of histone marks using maps of nascent transcription. Transcription captured the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. The relationship between active histone marks and transcription was conserved in all cell types examined, allowing individual labs to annotate active functional elements in mammals with similar richness as major consortia. Using imputation as an interpretative tool uncovered cell-type specific differences in how the PRC2-dependent repressive mark, H3K27me3, corresponds to transcription, and revealed that transcription initiation requires both chromatin accessibility and an active chromatin environment demonstrating that initiation is less promiscuous than previously thought.


2016 ◽  
Author(s):  
Enrique Carrillo-de-Santa-Pau ◽  
David Juan ◽  
Vera Pancaldi ◽  
Felipe Were ◽  
Ignacio Martin-Subero ◽  
...  

AbstractHematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify forty-two human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Nicholas D. Johnson ◽  
Xiumei Wu ◽  
Christopher D. Still ◽  
Xin Chu ◽  
Anthony T. Petrick ◽  
...  

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is characterized by changes in cell composition that occur throughout disease pathogenesis, which includes the development of fibrosis in a subset of patients. DNA methylation (DNAm) is a plausible mechanism underlying these shifts, considering that DNAm profiles differ across tissues and cell types, and DNAm may play a role in cell-type differentiation. Previous work investigating the relationship between DNAm and fibrosis in NAFLD has been limited by sample size and the number of CpG sites interrogated. Results Here, we performed an epigenome-wide analysis using Infinium MethylationEPIC array data from 325 individuals with NAFLD, including 119 with severe fibrosis and 206 with no histological evidence of fibrosis. After adjustment for latent confounders, we identified 7 CpG sites whose DNAm associated with fibrosis (p < 5.96 × 10–8). Analysis of RNA-seq data collected from a subset of individuals (N = 56) revealed that gene expression at 288 genes associated with DNAm at one or more of the 7 fibrosis-related CpGs. DNAm-based estimates of cell-type proportions showed that estimated proportions of natural killer cells increased, while epithelial cell proportions decreased with disease stage. Finally, we used an elastic net regression model to assess DNAm as a biomarker of fibrotic stage and found that our model predicted fibrosis with a sensitivity of 0.93 and provided information beyond a model based solely on cell-type proportions. Conclusion These findings are consistent with DNAm as a mechanism underpinning or marking fibrosis-related shifts in cell composition and demonstrate the potential of DNAm as a possible biomarker of NAFLD fibrosis.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1305-1305
Author(s):  
Vincent P Schulz ◽  
Laurie A. Steiner ◽  
Yelena Maksimova ◽  
Patrick G. Gallagher

Abstract Abstract 1305 CTCF and cohesion are critical regulators of cellular growth, development and differentiation. CTCF has multiple functions including acting at gene promoters as a transcriptional activator or repressor, mediating long-range chromatin interactions, and acting as a chromatin insulator element. The cohesin complex is also multifunctional, participating in chromosome segregation during cell division, facilitating DNA-promoter interactions through cell-type specific DNA-looping, participating in DNA repair, and participating with CTCF in enhancer blocking. The cohesin complex is composed of 4 proteins Smc1, Smc3, Scc1, and either SA1 or SA2. The presence of SA1 or SA2 is mutually excusive, leading to 2 related, but distinct complexes, cohesinSA1 and cohesin.SA2. The SA1 component of the complex directly interacts with CTCF. To gain insight into how CTCF and cohesin regulate genes in erythroid development, chromatin immunoprecipitation coupled with high throughput sequencing (ChIP-seq) and mRNA transcriptome analyses were performed in human CD34+ hematopoietic stem and progenitor cells and cultured primary human erythroid (R3/R4 stage) cells, the results combined, and the interactomes compared. The MACS program identified 26,330 sites of CTCF and 23,396 sites of cohesinSA1 occupancy in CD34+ and 39,782 sites of CTCF and 33,497 sites of cohesinSA1 occupancy in erythroid cell chromatin (p<10e-5, fold enrichment>5). In CD34+ cells, the majority of CTCF and cohesinSA1 binding sites were located in intergenic regions (56 and 57%,) and introns (33 and 34%). In contrast, in erythroid cells, CTCF and cohesinSA1 binding had migrated to gene promoters (16% vs 2% and 24% vs 2%, respectively) with less binding in intergenic regions and introns. Sites of binding in erythroid cells were similar to that observed in fibroblasts, another differentiated cell-type. CTCF has sites of both cell-type specific and cell-type invariant binding. The Galaxy tool was utilized to compare sites of CTCF occupancy in 7 additional cell types. In CD34+ cells, only 5% sites of CTCF binding were CD34+ cell-type specific. In erythroid cells, 36% of CTCF binding sites were erythroid-specific. These unique sites were located primarily in enhancers and introns and were rarely seen in promoters. Refseq genes within 3kb of erythroid cell-specific CTCF sites were highly significantly enriched for the following GO terms: induction of apoptosis by extracellular signals, cytoskeleton organization, cellular response to stress, and macromolecule catabolic process. In both cell types, RefSeq genes within 3kb of an invariant CTCF site were consistently expressed at lower levels c.f. genes within 3kb of CD34+- or erythroid cell-specific CTCF sites. Analyzing CTCF-cohesinSA1 co-occupancy, there were 17,755 sites of CTCF and cohesinSA1 co-occupancy in CD34+ cells, accounting for 75% of CTCF sites and 67% of cohesinSA1 sites. In erythroid cells, 19,933 sites of occupancy were shared between CTCF and cohesinSA1, representing 50% of CTCF sites and 60% of cohesinSA1 sites. Finally, it has been suggested that CTCF marks chromatin domains in a cell-type specific manner. To determine whether CTCF and cohesinSA1 are present at domain boundaries in erythropoiesis, ChIP-seq for H3K27me3, a repressive chromatin mark, was performed. Chromatin domains were predicted using the Rseg program. 9,480 and 18,511 H3K27me3 chromatin domains were identified in CD34+ and erythroid cells, respectively, with average domain lengths of 31kb in CD34+ and 28kb in erythroid cells. There were 692 and 2,096 CTCF sites that marked domain boundaries in CD34+ and erythroid cells, respectively. These CTCF sites were cell-type specific, as only 75 of these CTCF sites were shared between CD34+ and erythroid cells. In both cell types, the majority of CTCF sites marking domain boundaries were found in distal intergenic regions and introns. CohesinSA1 was also frequently found at domain boundaries, present at 566 and 1830 domain boundaries in CD34+ and erythroid cells, respectively. Co-localization of CTCF with cohesinSA1 at domain boundaries was also common, with 66% of CTCF sites and 58% of CTCF sites binding both CTCF and cohesionSA1 in CD34+ and erythroid cells, respectively. These data indicate that CTCF and cohesin have multiple roles in regulating gene expression in erythropoiesis. Disclosures: No relevant conflicts of interest to declare.


2017 ◽  
Author(s):  
Aparna Bhaduri ◽  
Tomasz J. Nowakowski ◽  
Alex A. Pollen ◽  
Arnold R. Kriegstein

AbstractHigh throughput methods for profiling the transcriptomes of single cells have recently emerged as transformative approaches for large-scale population surveys of cellular diversity in heterogeneous primary tissues. Efficient generation of such an atlas will depend on sufficient sampling of the diverse cell types while remaining cost-effective to enable a comprehensive examination of organs, developmental stages, and individuals. To examine the relationship between cell number and transcriptional heterogeneity in the context of unbiased cell type classification, we explicitly explored the population structure of a publically available 1.3 million cell dataset from the E18.5 mouse brain. We propose a computational framework for inferring the saturation point of cluster discovery in a single cell mRNA-seq experiment, centered around cluster preservation in downsampled datasets. In addition, we introduce a “complexity index”, which characterizes the heterogeneity of cells in a given dataset. Using Cajal-Retzius cells as an example of a limited complexity dataset, we explored whether biological distinctions relate to technical clustering. Surprisingly, we found that clustering distinctions carrying biologically interpretable meaning are achieved with far fewer cells (20,000). Together, these findings suggest that most of the biologically interpretable insights from the 1.3 million cells can be recapitulated by analyzing 50,000 randomly selected cells, indicating that instead of profiling few individuals at high “cellular coverage”, the much anticipated cell atlasing studies may instead benefit from profiling more individuals, or many time points at lower cellular coverage.Recent efforts seek to create a comprehensive cell atlas of the human body1,2 Current technology, however, makes it precipitously expensive to perform analysis of every cell. Therefore, designing effective sampling strategies be critical to generate a working atlas in an efficient, cost-effective, and streamlined manner. The advent of single cell and single nucleus mRNA sequencing (RNAseq) in droplet format3,4 now enables large scale sampling of cells from any tissue, and a recently released publicly available dataset of 1.3 million single cells from the E18.5 mouse brain generated with the 10X Chromium5 provides an opportunity to explore the relationship between population structure and the number of sampled cells necessary to reveal the underlying diversity of cell types. Here, we present a framework for how researchers can evaluate whether a dataset has reached saturation, and we estimate how many cells would be required to generate an atlas of the sample analyzed here. This framework can be applied to any organ or cell type specific atlas for any organism.


2021 ◽  
Author(s):  
Marine Louarn ◽  
Anne Siegel ◽  
Thierry Fest ◽  
Olivier Dameron ◽  
Fabrice Chatonnet

The Regulatory Circuits project is among the most recent and the most complete attempts to identify cell-type specific regulatory networks in Human. It is one of the largest efforts of public genomics data integration, based on data from the major consortia FANTOM5, ENCODE and Roadmap Epigenomics. This project is a main provider of biological data, cited more than 224 times (Google Scholar) and its resulting networks were used in at least 42 other articles. For such a general resource, reproducibility of both the outputs (regulation networks) and methods (data integration pipeline) is a major issue, since biological data are updated regularly. In addition, users may want to introduce new data into the Regulatory Circuits framework to provide networks about previously uncharacterized cell types or to add information about specific regulators, which require to re-execute the whole pipeline on the new data. In this article, we analyze the various factors limiting reproducibility of the Regulatory Circuits data and methods. Starting from a factual description of our understanding of the methods used in Regulatory Circuits, our contribution is two-fold: we propose (1) a characterization of the different levels of reusability, reproducibility and conceptual issues in the original workflow and (2) a new implementation of the workflow ensuring its consistency with the published description and allowing for an easier reuse and reproduction of the published outputs. Both are applicable beyond the case of Regulatory Circuits.


1984 ◽  
Vol 37 (4) ◽  
pp. 237 ◽  
Author(s):  
Donald FG Orwin ◽  
Joy L Woods ◽  
Stephen L Ranford

A method of determining cell types in wool fibres by methylene-blue staining has been extended to allow relationships between cortical cell type and cortical diameter to be studied in wools from individual sheep. Application of the method to wools from 12 sheep from six breeds showed that orthocortical cells were the predominant cell type produced. The percentage area occupied by orthocortical cells in a fibre cross-section increased with increasing cortical diameter in either a curvilinear (log-linear) or a linear manner. Nutritional stress or season may have affected the relationship in some sheep.


2017 ◽  
Author(s):  
Todd H. Oakley

AbstractNovelty and innovation are fundamental yet relatively understudied concepts in evolution. We may study novelty phylogenetically, with a key question of whether evolution occurs by tree-like branching, or through exchange of distantly related parts in processes akin to horizontal transfer. Here, I argue that except at the lowest levels of biological organization, evolution is not usually tree-like. Perfectly vertical inheritance, an assumption of evolutionary trees, requires simultaneous co-duplication of all the parts of a duplicating or speciating (which I collectively call 'furcating') biological feature. However, simultaneous co-duplication of many parts usually requires variational processes that are rare. Therefore, instead of being perfectly tree-like, evolution often involves events that incorporate or fuse more distantly related parts into new units during evolution, which herein I call 'fusion'. Exon shuffling, horizontal gene transfer, introgression and co-option are such fusion processes at different levels of organization. In addition to co-duplication, units under phylogenetic study must individuate (gaining evolutionary independence) before they can diverge. A lack of individuation erases evolutionary history, and provides another challenge to tree-like evolution. In particular, biological units in the same organism that are the products of development always share the same genome, perhaps making full individuation difficult. The ubiquity of processes that fuse distantly related parts or oppose individuation has wide ranging implications for the study of macroevolution. For one, the central metaphor of a tree of life will often be violated, to the point where we may need a different metaphor, such as economic public goods, or a ‘web of life’. Secondly, we may need to expand current models. For example, even under the prevailing model of cell-type evolution, the sister-cell-type model, a lack of complete individuation and evolution by co-option will often be involved in forming new cell-types. Finally, these processes highlight a need for an expansive toolkit for studying evolutionary history. Multivariate methods are particularly critical to discover co-variation, the hallmark of an absence of complete individuation. In addition to studying phylogenetic trees, we may often need to analyze and visualize phylogenetic networks. Even though furcation - the splitting and individuation of biological features - does happen, fusion of distant events is just as critical for the evolution of novelties, and must formally be incorporated into the metaphors, models, and visualization of evolutionary history.


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