scholarly journals Genome-wide and single-cell analyses reveal a context dependent relationship between CBP recruitment and gene expression

2014 ◽  
Vol 42 (18) ◽  
pp. 11363-11382 ◽  
Author(s):  
Lawryn H. Kasper ◽  
Chunxu Qu ◽  
John C. Obenauer ◽  
Daniel J. McGoldrick ◽  
Paul K. Brindle
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Dependent Relationship ◽  
Genome Wide ◽  
Context Dependent

scholarly journals Exploring the Changing Landscape of Cell-to-Cell Variation After CTCF Knockdown via Single Cell RNA-seq

2019 ◽  
Author(s):  
Wei Wang ◽  
Gang Ren ◽  
Ni Hong ◽  
Wenfei Jin
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Cell ◽  
Zinc Finger ◽  
Ctcf Binding ◽  
Rna Seq ◽  
Expression Noise ◽  
Genome Wide ◽  
Cell Variation ◽  
Variable Genes

Abstract Background: CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation is unclear. Results: We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, Zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, indicating tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explain why knockdown of CTCF lead to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions: To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

scholarly journals Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue

Circulation ◽  
2020 ◽  
Vol 142 (14) ◽  
pp. 1374-1388
Author(s):  
Yanming Li ◽  
Pingping Ren ◽  
Ashley Dawson ◽  
Hernan G. Vasquez ◽  
Waleed Ageedi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Aortic Wall ◽  
Genome Wide Association ◽  
Aortic Tissue ◽  
Sequencing Data ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Differential Gene

Background: Ascending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues. Methods: We performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies. Results: We identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene( ERG ) exerts an important role in maintaining normal aortic wall function. Conclusions: Our study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression.

scholarly journals CHARTS: A web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq datasets

2020 ◽  
Author(s):  
Matthew N. Bernstein ◽  
Zijian Ni ◽  
Michael Collins ◽  
Mark E. Burkard ◽  
Christina Kendziorski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Web Application ◽  
Cellular Heterogeneity ◽  
Rna Seq ◽  
Individual Gene ◽  
Genome Wide ◽  
Progression Of Disease ◽  
Cell Subpopulations ◽  
Available Information

AbstractBackgroundSingle-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. Perhaps nowhere is this more important than in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer datasets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data.ResultsWe present CHARacterizing Tumor Subpopulations (CHARTS), a computational pipeline and web application for analyzing, characterizing, and integrating publicly available scRNA-seq cancer datasets. CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across multiple tumors and datasets.ConclusionCHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer datasets. CHARTS is freely available at charts.morgridge.org.

scholarly journals Cloudy with a Chance of Insights: Context Dependent Gene Regulation and Implications for Evolutionary Studies

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 492 ◽  
Author(s):  
Buchberger ◽  
Reis ◽  
Lu ◽  
Posnien
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Evolutionary Biology ◽  
Phenotypic Evolution ◽  
Specific Expression ◽  
Expression Studies ◽  
Genome Wide ◽  
Key Driver ◽  
Context Dependent ◽  
Genome Wide Expression

Research in various fields of evolutionary biology has shown that divergence in gene expression is a key driver for phenotypic evolution. An exceptional contribution of cis-regulatory divergence has been found to contribute to morphological diversification. In the light of these findings, the analysis of genome-wide expression data has become one of the central tools to link genotype and phenotype information on a more mechanistic level. However, in many studies, especially if general conclusions are drawn from such data, a key feature of gene regulation is often neglected. With our article, we want to raise awareness that gene regulation and thus gene expression is highly context dependent. Genes show tissue- and stage-specific expression. We argue that the regulatory context must be considered in comparative expression studies.

Single Cell Level Genome-Wide Gene Expression Analysis of Bone Marrow-Derived Oct-4+ very Small Embryonic-Like Stem Cells (VSELs) Revealed That a Polycomb Group Protein Ezh2 Regulates VSELs Pluripotency by Maintaining Bivalent Domains At Promoters of Important Homeodomain-Containing Developmental Transcription Factors

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2345-2345
Author(s):  
Magda Kucia ◽  
Rui Liu ◽  
Kasia Mierzejewska ◽  
Wan Wu ◽  
Janina Ratajczak ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Transcription Factors ◽  
Single Cell ◽  
Gene Expression Analysis ◽  
Polycomb Group ◽  
Polycomb Group Protein ◽  
Genome Wide ◽  
Group Protein ◽  
Genome Wide Gene Expression

Abstract Abstract 2345 Recently, we identified a population of very small embryonic-like (VSEL) stem cells (SCs) in adult bone marrow (BM) (Leukemia 2006:20;857). These Oct4+CXCR4+SSEA-1+Sca-1+CD45−Lin− VSELs are capable of differentiation in vitro into cells from all three germ lineages and in in vivo animal models they can be specified into mesenchymal stem cells (MSCs) (Stem Cells Dev 2010:19;1557), cardiomyocytes (Stem Cell 2008:26;1646), and long-term engrafting hematopoietic stem cells (HSCs) (Exp Hematol 2011:39;225). Be employing gene-expression and epigenetic profiling studies we reported that VSELs in BM have germ-line stem cell like epigenetic features including i) open/active chromatin structure in Oct4 promoter, ii) parent-of-origin specific reprogramming of genomic imprinting (Leukemia 2009, 23, 2042–2051), and iii) that they share several markers with epiblast-derived primordial germ cells (PGCs), in particular with migratory PGCs (Leukemia 2010, 24, 1450–1461). However, it was not clear how VSELs maintain pluripotent state. To address this issue we recently employed single cell-based genome-wide gene expression analysis and found that, Oct4+ VSELs i) express a similar, yet nonidentical, transcriptome as embryonic stem-cells (ESCs), ii) up-regulate cell-cycle checkpoint genes, and iii) down-regulate genes involved in protein turnover and mitogenic pathways. Interestingly, our single cell library studies also revelaed that Ezh2, a polycomb group protein, is highly expressed in VSELs. This protein is well known to be involved in maintaining a bivalent domains (BDs) at promoters of important homeodomain-containing developmental transcription factors. Of note a presence of BDs is characteristic for pluripotent stem cells (e.g., ESCs) and as result of Ezh2 overexpression, VSELs, like ESCs, exhibit BDs - bivalently modified nucleosomes (trimethylated H3K27 and H3K4) at promoters of important homeodomain-containing developmental transcription factors (Sox21 Nkx2.2 Dlx1 Zfpm2 Irx2 Lbx1h Hlxb9 Pax5 HoxA3). Of note, spontaneous (as seen during differentiation) or RNA interference-enforced down-regulation of Ezh2 removes BDs what, results in lose of their plurioptentiality and de-repression of several BD-regulated genes that control their tissue commitment. In conclusion, Our results show for first time that in addition to the expression of pluripotency core transcription factor Oct-4, VSELs, like other pluripotent stem-cells, maintain their pluripotent state through an Ezh2-dependent BD-mediated epigenetic mechanism. Based on this our genome-wide gene expression study not only advances our understanding of biological processes that govern VSELs pluripotency, differentiation, and quiescence but will also help to develop better protocols for ex vivo expansion of these promising cells for potential application in regenerative medicine. Disclosures: Ratajczak: Neostem Inc: Consultancy, Research Funding.

scholarly journals Cloudy with a Chance of Insights: Context Dependent Gene Regulation and Implications for the Evolution of Gene Expression

2019 ◽  
Author(s):  
Elisa Buchberger ◽  
Micael Reis ◽  
Ting-Hsuan Lu ◽  
Nico Posnien
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Evolutionary Biology ◽  
Expression Data ◽  
Regulatory Evolution ◽  
Specific Expression ◽  
Genome Wide ◽  
Key Driver ◽  
Context Dependent ◽  
Genome Wide Expression

Research in various fields of evolutionary biology has shown that divergence in gene expression is a key driver for phenotypic variation. An exceptional contribution of cis-regulatory evolution has for instance been found to contribute to morphological diversification. In the light of these findings, the analysis of genome-wide expression data has become one of the central tools to link genotype and phenotype information on a more mechanistic level. However, in many studies, especially if general conclusions are drawn from such data, a key feature of gene regulation is often neglected. With our article, we want to raise awareness that gene regulation and thus gene expression is highly context dependent. Genes show tissue- and developmental stage-specific expression. We argue that the regulatory context must be considered when studying evolution of gene expression.

scholarly journals Analysis of Clonal Evolution/Heterogeneity of MDS By Simultaneous Detection of Both Mutation and Gene Expression By Single Cell Sequencing

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 1800-1800
Author(s):  
Masahiro Marshall Nakagawa ◽  
Ryosaku Inagaki ◽  
Yasuhito Nannya ◽  
Lanying Zhao ◽  
Yutaka Kuroda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Profiles ◽  
Clonal Evolution ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Intratumor Heterogeneity ◽  
Single Cell Sequencing ◽  
Genome Wide ◽  
A Minor

Abstract Recent advances in single-cell sequencing (sc-Seq) technologies have enabled high-throughput transcriptome analysis in thousands of cells to understand the heterogeneity among cancer populations in terms of genome-wide gene expression. However, its application to the analysis of clonal evolution of cancer populations is largely limited by the lack of an efficient sc-Seq platform that allows for accurate detection of gene mutations at the same time with transcriptome analysis. The major challenge here is a frequent allele dropout of just two copies per single cell, which results in an inaccurate genotype assignment for many cells, preventing identification of relevant genotype-phenotype correlations. To overcome this, we developed a novel sc-Seq platform (scMutSeq) that allows for precise determination of both genotype and genome-wide gene expression simultaneously with negligible allele dropouts, on the basis of the Fluidigm C1 Single-Cell mRNA Seq HT system and applied it to the analysis of clonal evolution and intratumor heterogeneity of myelodysplastic syndromes (MDS) characterized by frequent clonal evolution to acute amyloid leukemia (AML). We first evaluated the performance of our plat form using an AML-derived cell line with heterozygous SF3B1K700E mutation, HNT-34, for which efficiency of the detection of both wild-type and mutant allele, together with global gene expression, was evaluated. Among 400 cells subjected to scMutSeq analysis, a total of 125 passed QC, in which cell viability was assessed in terms of expression of mitochondrial genes. Global gene expression and heterozygous SF3B1mutation were successfully detected in all the QC-confirmed cells with none of the cells showing the wild-type allele or homozygous SF3B1mutation, where evaluable transcript reads (unique molecular identifier >=1) were obtained for a median of 2,753 genes, designated as nGene. The performance was also tested for flow-sorted hematopoietic stem/progenitor cells (HSPCs) (Lin−CD34+) from an MDS patient positive for the SF3B1K700E mutation. Gene expression was successfully analyzed all the QC-confirmed cells (n=81) with a median nGene of 1,953. No substantial allele dropouts were suspected, because none of the cells genotyped had homozygous SF3B1mutation. We then applied scMutSeq to the analysis of TP53-mutated AML/MDS with complex karyotype, including del(5q) and del(7q), for which longitudinal samples were obtained for the assessment of clonal evolution. scMutSeq successfully analyzed the mutation status of TP53and global gene expression profiles at a single-cell level, where copy number abnormalities were also evaluated on the basis of gene expression. We identified two discrete clones in the HSPC fraction, carrying both del(5q) and del(7q) and del(5q) alone, respectively, even though the analysis of bulk DNA had failed to detect the latter clone, indicating that a minor clone having a distinct genotype came under detection with scMutSeq. Moreover, the HSPCs with both del(5q) and del(7q) showed aberrant expression of erythroid and megakaryocytic genes, increased expression of inflammatory signals and decreased expression of cell cycle-related genes, exhibiting a clear genotype phenotype correlation. Subsequent analysis of samples at later time points further disclosed evolution of clones having discrete del(5q) deletions and expression, revealing a complexity of clonal evolution in MDS. Next, to investigate the early process of MDS development, we analyzed clonal hematopoiesis found in a minor fraction (1.2-12%) of bone marrow samples from three elder individuals having hip replacement surgery, in which DNMT3A(n=1) (R882H) and TET2(n=2) (D905fs and Q1540fs) mutations had been detected by ddPCR or targeted deep sequencing, respectively. scMutSeq analysis of the HSPCs from these individuals revealed that mutant HSPCs showed distinct gene expression profiles, depending on the type of CHIP mutations. To summarize, our single-cell sequencing platform enables to detect both genetic and transcriptional heterogeneities, providing a powerful clue to understand clonal evolution and intratumor heterogeneity of MDS. Disclosures Nakagawa: Sumitomo Dainippon Pharma Co., Ltd.: Research Funding. Inagaki:Sumitomo Dainippon Pharma Co., Ltd.: Employment. Yoda:Chordia Therapeutics Inc.: Research Funding.

scholarly journals Exploring the changing landscape of cell-to-cell variation after CTCF knockdown via single cell RNA-seq

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Wei Wang ◽  
Gang Ren ◽  
Ni Hong ◽  
Wenfei Jin
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Single Cell ◽  
Zinc Finger ◽  
Ctcf Binding ◽  
Rna Seq ◽  
Expression Noise ◽  
Genome Wide ◽  
Cell Variation ◽  
Variable Genes

Abstract Background CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation remains unclear. Results We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating that gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, implying tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explains why knockdown of CTCF leads to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found that cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

scholarly journals Modeling allele-specific gene expression by single-cell RNA sequencing

2017 ◽  
Author(s):  
Yuchao Jiang ◽  
Nancy R Zhang ◽  
Mingyao Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Specific Gene ◽  
Burst Frequency ◽  
Specific Expression ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Allelic Differences ◽  
Allele Specific

AbstractAllele-specific expression is traditionally studied by bulk RNA sequencing, which measures average expression across cells. Single-cell RNA sequencing (scRNA-seq) allows the comparison of expression distribution between the two alleles of a diploid organism and thus the characterization of allele-specific bursting. We propose SCALE to analyze genome-wide allele-specific bursting, with adjustment of technical variability. SCALE detects genes exhibiting allelic differences in bursting parameters, and genes whose alleles burst non-independently. We apply SCALE to mouse blastocyst and human fibroblast cells and find that, globally, cis control in gene expression overwhelmingly manifests as differences in burst frequency.

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