scholarly journals Graph–based integration of histone modifications profiles: haematopoietic cell differentiation as a case study

2020 ◽  
Author(s):  
Federica Baccini ◽  
Monica Bianchini ◽  
Filippo Geraci
Keyword(s):  
Histone Modification ◽  
Histone Modifications ◽  
Cell Types ◽  
Lymphoid Cells ◽  
Differential Analysis ◽  
Cell Type ◽  
Similarity Networks ◽  
Unique Cell ◽  
Per Gene

AbstractIn this paper, we show that quantifying histone modifications by counting the number of high– resolution peaks in each gene allows to build profiles of these epigenetic marks, associating them to a phenotype. The significance of this approach is verified by applying graph–cut techniques for assessing the differentiation between myeloid and lymphoid cells in haematopoiesis, i.e. the process through which all the different types of blood cells originate starting from a unique cell type. The experiments are conducted on a population of samples from 24 cell types involved in haematopoiesis. Six profiles are constructed for each cell type, based on a different histone modification signal. Following the experimentally verified idea that the peak number distribution per gene behaves similarly to gene expression, the profile computation employs standard differential analysis tools to find genes whose epigenetic modifications are related to a given phenotype. Next, six similarity networks of cell types are constructed, based on each histone modification, and then combined into a unique one through similarity network fusion. Finally, the similarity networks are transformed into dissimilarity graphs, to which two different cuts are applied and compared to evaluate the classic differentiation between myeloid and lymphoid cells. The results show that all histone modifications contribute almost equally to the myeloid/lymphoid differentiation, and this is also confirmed by the analysis of the fused network. However, they also suggest that histone modifications may not be the only mechanism for regulating the differentiation of hematopoietic cells.

scholarly journals Histone modifications form a cell-type-specific chromosomal bar code that persists through the cell cycle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Cell Types ◽  
Cell Type ◽  
Bar Code ◽  
Genes Encoding ◽  
Cell Type Specific ◽  
Rolling Windows

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

scholarly journals MTTFsite: cross-cell type TF binding site prediction by using multi-task learning

2019 ◽  
Vol 35 (24) ◽  
pp. 5067-5077 ◽  
Author(s):  
Jiyun Zhou ◽  
Qin Lu ◽  
Lin Gui ◽  
Ruifeng Xu ◽  
Yunfei Long ◽  
...  
Keyword(s):  
Gene Expression ◽  
Histone Modification ◽  
Prediction Method ◽  
Cell Types ◽  
Supplementary Information ◽  
Learning Approaches ◽  
Cell Type ◽  
Baseline Method ◽  
Common Features ◽  
Task Learning

AbstractMotivationThe prediction of transcription factor binding sites (TFBSs) is crucial for gene expression analysis. Supervised learning approaches for TFBS predictions require large amounts of labeled data. However, many TFs of certain cell types either do not have sufficient labeled data or do not have any labeled data.ResultsIn this paper, a multi-task learning framework (called MTTFsite) is proposed to address the lack of labeled data problem by leveraging on labeled data available in cross-cell types. The proposed MTTFsite contains a shared CNN to learn common features for all cell types and a private CNN for each cell type to learn private features. The common features are aimed to help predicting TFBSs for all cell types especially those cell types that lack labeled data. MTTFsite is evaluated on 241 cell type TF pairs and compared with a baseline method without using any multi-task learning model and a fully shared multi-task model that uses only a shared CNN and do not use private CNNs. For cell types with insufficient labeled data, results show that MTTFsite performs better than the baseline method and the fully shared model on more than 89% pairs. For cell types without any labeled data, MTTFsite outperforms the baseline method and the fully shared model by more than 80 and 93% pairs, respectively. A novel gene expression prediction method (called TFChrome) using both MTTFsite and histone modification features is also presented. Results show that TFBSs predicted by MTTFsite alone can achieve good performance. When MTTFsite is combined with histone modification features, a significant 5.7% performance improvement is obtained.Availability and implementationThe resource and executable code are freely available at http://hlt.hitsz.edu.cn/MTTFsite/ and http://www.hitsz-hlt.com:8080/MTTFsite/.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals An in vivo, neuron-specific approach for pairing translational and epigenetic signatures of early-life exercise

2021 ◽  
Author(s):  
Anthony Mark Raus ◽  
Tyson D Fuller ◽  
Nellie E Nelson ◽  
David A Valientes ◽  
Anita Bayat ◽  
...  
Keyword(s):  
Gene Expression ◽  
Histone Modifications ◽  
Early Life ◽  
Affinity Purification ◽  
Cell Types ◽  
Cell Type ◽  
Cell Type Specificity ◽  
Cell Type Specific ◽  
Induced Changes ◽  
Epigenetic Signatures

Aerobic exercise promotes physiological and molecular adaptations in neurons to influence brain function and behavior. The most well studied neurobiological consequences of exercise are those which underlie exercise-induced improvements in hippocampal memory, including the expression and regulation of the neurotrophic factor Bdnf. Whether aerobic exercise taking place during early-life periods of postnatal brain maturation has similar impacts on gene expression and its regulation remains to be investigated. Using unbiased next-generation sequencing we characterize gene expression programs and their regulation by specific, memory-associated histone modifications during juvenile-adolescent voluntary exercise (ELE). Traditional transcriptomic and epigenomic sequencing approaches have either used heterogeneous cell populations from whole tissue homogenates or flow cytometry for single cell isolation to distinguish cell types / subtypes. These methods fall short in providing cell-type specificity without compromising sequencing depth or procedure-induced changes to cellular phenotype. In this study, we use simultaneous isolation of translating mRNA and nuclear chromatin from a neuron-enriched cell population to more accurately pair ELE-induced changes in gene expression with epigenetic modifications. We employ a line of transgenic mice expressing the NuTRAP (Nuclear Tagging and Translating Ribosome Affinity Purification) cassette under the Emx1 promoter allowing for brain cell-type specificity. We then developed a technique that combines nuclear isolation using Isolation of Nuclei TAgged in Specific Cell Types (INTACT) with Translating Ribosomal Affinity Purification (TRAP) methods to determine cell type-specific epigenetic modifications influencing gene expression programs from a population of Emx1 expressing hippocampal neurons. Data from RNA-seq and CUT&RUN-seq were coupled to evaluate histone modifications influencing the expression of translating mRNA in neurons after early-life exercise (ELE). We also performed separate INTACT and TRAP isolations for validation of our protocol and demonstrate similar molecular functions and biological processes implicated by gene ontology (GO) analysis. Finally, as prior studies use tissue from opposite brain hemispheres to pair transcriptomic and epigenomic data from the same rodent, we take a bioinformatics approach to compare hemispheric differences in gene expression programs and histone modifications altered by by ELE. Our data reveal transcriptional and epigenetic signatures of ELE exposure and identify novel candidate gene-histone modification interactions for further investigation. Importantly, our novel approach of combined INTACT/TRAP methods from the same cell suspension allows for simultaneous transcriptomic and epigenomic sequencing in a cell-type specific manner.

scholarly journals Histone modifications form a cell-type-specific chromosomal bar code that modulates and maintains patterns of gene expression through the cell cycle

2020 ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Cell Types ◽  
Cell Type ◽  
Bar Code ◽  
Genes Encoding ◽  
Cell Type Specific ◽  
Rolling Windows

ABSTRACTBackgroundChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear.To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL) to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3.ResultsChromosome regions (bands) of 10-50Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. We show that they comprise 1-5Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely.We found little change between cell cycle phases, whether compared by 5Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains.Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription.ConclusionsModified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

scholarly journals Cell type–specific actions of Bcl11b in early T-lineage and group 2 innate lymphoid cells

2019 ◽  
Vol 217 (1) ◽  
Author(s):  
Hiroyuki Hosokawa ◽  
Maile Romero-Wolf ◽  
Qi Yang ◽  
Yasutaka Motomura ◽  
Ditsa Levanon ◽  
...  
Keyword(s):  
T Cells ◽  
Target Genes ◽  
Cell Types ◽  
Innate Lymphoid Cells ◽  
Lymphoid Cells ◽  
Cell Type ◽  
Distal Enhancer ◽  
Distinct Cell Type ◽  
Cell Type Specific ◽  
Group 2

The zinc finger transcription factor, Bcl11b, is expressed in T cells and group 2 innate lymphoid cells (ILC2s) among hematopoietic cells. In early T-lineage cells, Bcl11b directly binds and represses the gene encoding the E protein antagonist, Id2, preventing pro-T cells from adopting innate-like fates. In contrast, ILC2s co-express both Bcl11b and Id2. To address this contradiction, we have directly compared Bcl11b action mechanisms in pro-T cells and ILC2s. We found that Bcl11b binding to regions across the genome shows distinct cell type–specific motif preferences. Bcl11b occupies functionally different sites in lineage-specific patterns and controls totally different sets of target genes in these cell types. In addition, Bcl11b bears cell type–specific post-translational modifications and organizes different cell type–specific protein complexes. However, both cell types use the same distal enhancer region to control timing of Bcl11b activation. Therefore, although pro-T cells and ILC2s both need Bcl11b for optimal development and function, Bcl11b works substantially differently in these two cell types.

scholarly journals Repeated Passage of Wild-Type Woodchuck Hepatitis Virus in Lymphoid Cells Does Not Generate Cell Type-Specific Variants or Alter Virus Infectivity

2008 ◽  
Vol 82 (15) ◽  
pp. 7540-7550 ◽  
Author(s):  
Patricia M. Mulrooney-Cousins ◽  
Tomasz I. Michalak
Keyword(s):  
Lymphatic System ◽  
Hepatitis Virus ◽  
Cell Types ◽  
Lymphoid Cells ◽  
Wild Type Virus ◽  
Type Virus ◽  
Wild Type ◽  
Cell Type ◽  
Cell Type Specific ◽  
Repeated Passage

ABSTRACT Woodchuck hepatitis virus (WHV), which is closely related to human hepatitis B virus, infects the liver but also invariably establishes persistent infection in the lymphatic system. Although the dose of invading virus appears to be the main factor in determining whether WHV infection is restricted to the lymphatic system or also engages the liver, the nature of WHV lymphotropism remains unclear and a role for a specific lymphotropic variant was not excluded. The availability of woodchuck lymphocyte and hepatocyte cultures susceptible to WHV infection allows investigation of this issue in vitro. We hypothesized that repeated passage of wild-type WHV in lymphoid cells should lead to enrichment of a lymphotropic virus variant, if in fact such a variant exists. For this purpose, wild-type WHV with a homogeneous sequence was used as the inoculum, while lymphoid cells from a single healthy woodchuck donor and a normal woodchuck WCM-260 hepatocyte line served as infection targets. The serial passage of the wild-type virus repeated up to 13 times for both cell types did not lead to the emergence of cell type-specific WHV variants, as revealed by sequence analysis of the virus envelope and the core and X gene sequences. Moreover, the virus passaged in both cell types remained infectious for naive woodchucks, produced infection profiles that depended upon virus dose but not on virus cellular origin, and retained its initial DNA sequence. These results imply that WHV lymphotropism is a natural propensity of the wild-type virus and is not a consequence of infection with a viral variant.

scholarly journals Large-scale determination and characterization of cell type-specific regulatory elements in the human genome

2017 ◽  
Author(s):  
Can Wang ◽  
Shihua Zhang
Keyword(s):  
Histone Modifications ◽  
Large Scale ◽  
Chromatin Modification ◽  
Cell Types ◽  
Regulatory Elements ◽  
Cell Type ◽  
Cell Identity ◽  
Functional Roles ◽  
Cancer Occurrence ◽  
Cell Type Specific

AbstractHistone modifications have been widely elucidated to play vital roles in gene regulation and cell identity. The Roadmap Epigenomics Consortium generated a reference catalogue of several key histone modifications across >100s of human cell types and tissues. Decoding these epigenomes into functional regulatory elements is a challenging task in computational biology. To this end, we adopted a differential chromatin modification analysis framework to comprehensively determine and characterize cell type-specific regulatory elements (CSREs) and their histone modification codes in the human epigenomes of five histone modifications across 127 tissues or cell types. The CSREs show significant relevance with cell type-specific biological functions and diseases and cell identity. Clustering of CSREs with their specificity signals reveals diverse histone codes, demonstrating the diversity of functional roles of CSREs within the same cell or tissue. Last but not least, dynamics of CSREs from close cell types or tissues can give a detailed view of developmental processes such as normal tissue development and cancer occurrence.

scholarly journals Deconvolving multiplexed histone modifications in single cells

2021 ◽  
Author(s):  
Jake Yeung ◽  
Maria Florescu ◽  
Peter Zeller ◽  
Buys Anton de Barbanson ◽  
Alexander van Oudenaarden
Keyword(s):  
Bone Marrow ◽  
B Cells ◽  
Histone Modification ◽  
Histone Modifications ◽  
Blood Cells ◽  
Single Cells ◽  
Cell Types ◽  
Mouse Bone Marrow ◽  
Immunoglobulin Genes ◽  
Computational Framework

Recent advances have enabled mapping of histone modifications in single cells, but current methods are constrained to profile only one histone modification per cell. Here we present an integrated experimental and computational framework, scChIX (single-cell chromatin immunocleavage and unmixing), to map multiple histone modifications in single cells. We first validate this method using purified blood cells and show that although the two repressive marks, H3K27me3 and H3K9me3, are generally mutually exclusive, the transitions between the two regions can vary between cell types. Next we apply scChIX to a heterogenous cell population from mouse bone marrow to generate linked maps of active (H3K4me1) and repressive (H3K27me3) chromatin landscapes in single cells, where coordinates in the active modification map correspond to coordinates in the repressive map. Linked analysis reveals that immunoglobulin genes in the region are in a repressed chromatin state in pro-B cells, but become activated in B cells. Overall, scChIX unlocks systematic interrogation of the interplay between histone modifications in single cells.

scholarly journals Deciphering epigenomic code for cell differentiation using deep learning

2018 ◽  
Author(s):  
Pengyu Ni ◽  
Zhengchang Su
Keyword(s):  
Cell Differentiation ◽  
T Cell ◽  
Histone Modification ◽  
Cell Fate ◽  
Genomic Sequence ◽  
Cell Types ◽  
Cd4 T Cell ◽  
Cell Type ◽  
Functional Relationships ◽  
Histone Modification Patterns

ABSTRACTEpigenomic markers, such as histone modifications, play important roles in cell fate determination and type maintenance during cell differentiation. Although genomic sequence plays a crucial role in establishing the unique epigenome in each cell type produced during cell differentiation, little is known about the sequence determinants that lead to the unique epigenomes of the cells. Here, using a dataset of six histone markers measured in four human CD4+ T cell types produced at different stages of T cell development, we showed that two types of highly accurate deep convolutional neural networks (CNNs) constructed for each cell type and for each histone marker are a powerful strategy to uncover the sequence determinants of the various histone modification patterns in difference cell types. We found that sequence motifs learned by the CNN models are highly similar to known binding motifs of transcription factors known to play important roles in CD4+ T cell differentiation. Our results suggest that both the unique histone modification patterns in each cell type and the different patterns of the same histone marker in different cell types are determined by a set of motifs with unique combinations. Interestingly, the level of shared few motifs learned in the different cell models reflect the lineage relationships of the cells, while the level of few shared motifs learned in different histone marker models reflect their functional relationships. Furthermore, using these models, we can predict the importance of the learned motifs and their interactions in determining specific histone marker patterns in the cell types.

scholarly journals Cell-type–specific transcriptome and histone modification dynamics during cellular reprogramming in the Arabidopsis stomatal lineage

2019 ◽  
Vol 116 (43) ◽  
pp. 21914-21924 ◽  
Author(s):  
Laura R. Lee ◽  
Diego L. Wengier ◽  
Dominique C. Bergmann
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Histone Modifications ◽  
Developmental Plasticity ◽  
Plant Cells ◽  
Cell Types ◽  
Cellular Reprogramming ◽  
Cell Type ◽  
Chip Sequencing ◽  
Cell Type Specific

Plant cells maintain remarkable developmental plasticity, allowing them to clonally reproduce and to repair tissues following wounding; yet plant cells normally stably maintain consistent identities. Although this capacity was recognized long ago, our mechanistic understanding of the establishment, maintenance, and erasure of cellular identities in plants remains limited. Here, we develop a cell-type–specific reprogramming system that can be probed at the genome-wide scale for alterations in gene expression and histone modifications. We show that relationships among H3K27me3, H3K4me3, and gene expression in single cell types mirror trends from complex tissue, and that H3K27me3 dynamics regulate guard cell identity. Further, upon initiation of reprogramming, guard cells induce H3K27me3-mediated repression of a regulator of wound-induced callus formation, suggesting that cells in intact tissues may have mechanisms to sense and resist inappropriate dedifferentiation. The matched ChIP-sequencing (seq) and RNA-seq datasets created for this analysis also serve as a resource enabling inquiries into the dynamic and global-scale distribution of histone modifications in single cell types in plants.

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