scholarly journals Genomic meta-analysis of the interplay between 3D chromatin organization and gene expression programs under basal and stress conditions

2018 ◽  
Author(s):  
Idan Nurick ◽  
Ron Shamir ◽  
Ran Elkon
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Cell Lines ◽  
Meta Analysis ◽  
Cell Types ◽  
Chromatin Organization ◽  
Cell Type ◽  
Differential Gene ◽  
Different Cell Types

AbstractBackgroundOur appreciation of the critical role of the 3D organization of the genome in gene regulation is steadily increasing. Recent 3C-based deep sequencing techniques elucidated a hierarchy of structures that underlie the spatial organization of the genome in the nucleus. At the top of this hierarchical organization are chromosomal territories and the megabase-scale A/B compartments that correlate with transcriptional activity within cells. Below them are the relatively cell-type invariant topologically associated domains (TADs), characterized by high frequency of physical contacts between loci within the same TAD and are assumed to function as regulatory units. Within TADs, chromatin loops bring enhancers and target promoters to close spatial proximity. Yet, we still have only rudimentary understanding how differences in chromatin organization between different cell types affect cell-type specific gene expression programs that are executed under basal and challenged conditions.ResultsHere, we carried out a large-scale meta-analysis that integrated Hi-C data from thirteen different cell lines and dozens of ChIP-seq and RNA-seq datasets measured on these cells, either under basal conditions or after treatment. Pairwise comparisons between cell lines demonstrated the strong association between modulation of A/B compartmentalization, differential gene expression and transcription factor (TF) binding events. Furthermore, integrating the analysis of transcriptomes of different cell lines in response to various challenges, we show that 3D organization of cells under basal conditions constrains not only gene expression programs and TF binding profiles that are active under the basal condition but also those induced in response to treatment.ConclusionsOur results further elucidate the role of dynamic genome organization in regulation of differential gene expression between different cell types, and indicate the impact of intra-TAD enhancer-promoter interactions that are established under basal conditions on both the basal and treatment-induced gene expression programs.

scholarly journals Single cell analysis of the effects of developmental lead (Pb) exposure on the hippocampus

2019 ◽  
Author(s):  
Kelly M. Bakulski ◽  
John F. Dou ◽  
Robert C. Thompson ◽  
Christopher Lee ◽  
Lauren Y. Middleton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Differential Gene Expression ◽  
Cell Types ◽  
Marker Genes ◽  
Cell Type ◽  
Cell Clusters ◽  
Differential Gene ◽  
Pb Exposure ◽  
And Behavior

AbstractBackgroundLead (Pb) exposure is ubiquitous and has permanent developmental effects on childhood intelligence and behavior and adulthood risk of dementia. The hippocampus is a key brain region involved in learning and memory, and its cellular composition is highly heterogeneous. Pb acts on the hippocampus by altering gene expression, but the cell type-specific responses are unknown.ObjectiveExamine the effects of perinatal Pb treatment on adult hippocampus gene expression, at the level of individual cells, in mice.MethodsIn mice perinatally exposed to control water (n=4) or a human physiologically-relevant level (32 ppm in maternal drinking water) of Pb (n=4), two weeks prior to mating through weaning, we tested for gene expression and cellular differences in the hippocampus at 5-months of age. Analysis was performed using single cell RNA-sequencing of 5,258 cells from the hippocampus by 10x Genomics Chromium to 1) test for gene expression differences averaged across all cells by treatment; 2) compare cell cluster composition by treatment; and 3) test for gene expression and pathway differences within cell clusters by treatment.ResultsGene expression patterns revealed 12 cell clusters in the hippocampus, mapping to major expected cell types (e.g. microglia, astrocytes, neurons, oligodendrocytes). Perinatal Pb treatment was associated with 12.4% more oligodendrocytes (P=4.4×10−21) in adult mice. Across all cells, differential gene expression analysis by Pb treatment revealed cluster marker genes. Within cell clusters, differential gene expression with Pb treatment (q<0.05) was observed in endothelial, microglial, pericyte, and astrocyte cells. Pathways up-regulated with Pb treatment were protein folding in microglia (P=3.4×10−9) and stress response in oligodendrocytes (P=3.2×10−5).ConclusionBulk tissue analysis may be confounded by changes in cell type composition and may obscure effects within vulnerable cell types. This study serves as a biological reference for future single cell studies of toxicant or neuronal complications, to ultimately characterize the molecular basis by which Pb influences cognition and behavior.

scholarly journals Cell type-specific differential expression for spatial transcriptomics

2021 ◽  
Author(s):  
Dylan M Cable ◽  
Evan Murray ◽  
Vignesh Shanmugam ◽  
Simon Zhang ◽  
Michael Z Diao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Type ◽  
Unified Framework ◽  
Wide Range ◽  
Cell Type Specific ◽  
Differential Gene

Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed across tissue context for cell types of interest. However, changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type introduce complex statistical challenges. Here, we introduce a statistical method, Robust Cell Type Differential Expression (RCTDE), that estimates cell type-specific patterns of differential gene expression while accounting for localization of other cell types. By using general log-linear models, we provide a unified framework for defining and identifying gene expression changes for a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MERFISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimer's mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our RCTDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr.

scholarly journals Methods to increase reproducibility in differential gene expression via meta-analysis

2016 ◽  
Vol 45 (1) ◽  
pp. e1-e1 ◽  
Author(s):  
Timothy E. Sweeney ◽  
Winston A. Haynes ◽  
Francesco Vallania ◽  
John P. Ioannidis ◽  
Purvesh Khatri
Keyword(s):  
Gene Expression ◽  
Differential Gene Expression ◽  
Meta Analysis ◽  
Differential Gene

scholarly journals A resampling-based meta-analysis for detection of differential gene expression in breast cancer

BMC Cancer ◽  
2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Bala Gur-Dedeoglu ◽  
Ozlen Konu ◽  
Serkan Kir ◽  
Ahmet Rasit Ozturk ◽  
Betul Bozkurt ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Differential Gene Expression ◽  
Meta Analysis ◽  
Differential Gene

Exploiting Endogenous Micro-RNAs to Avoid off-Target Transgene Expression

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3296-3296
Author(s):  
Raul Teruel Montoya ◽  
Xianguo Kong ◽  
Shaji Abraham ◽  
Lin Ma ◽  
Leonard C. Edelstein ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Cell Lines ◽  
Binding Sites ◽  
Transgene Expression ◽  
Cell Types ◽  
Jurkat Cells ◽  
Cell Type ◽  
Hematological Disorders

Abstract Abstract 3296 Genetic modification of hematopoietic stem cells (HSCs) has the potential to benefit acquired and congenital hematological disorders. Despite the use of so-called “tissue-specific” promoters to drive expression of the desired transgene, off-target (and consequent deleterious) effects have been observed. MicroRNAs (miRNAs) are important regulators of gene expression. They associate with Argonaute proteins and most typically target 3'UTRs, where complementary base-pairing results in repressed gene expression via RNA decay and translation inhibition. Most miRNAs are ubiquitously expressed, and although some are claimed to be “tissue specific,” such claims have generally not been rigorously validated. The long-term goal of this work is identifying “cell preferential” miRNA expression that could be exploited in expression vectors to minimize off-target transgene expression in HSCs. Initially, total RNA was extracted with Trizol from the megakaryocyte and T-lymphocyte cell lines, Meg-01 and Jurkat, and miRNAs were profiled by Nanostring technology (Nanostring Technologies, Denver, CO). MiR-495 was determined to be highly expressed in Meg-01 and very low in Jurkat cells. A luciferase reporter construct was generated with four canonical binding sites for miR-495 in the 3'UTR and transfected into both cell lines. Compared to control vector without miR-495 binding sites, luciferase expression showed a 50% reduction in Meg-01 cells, but no knock down in Jurkat cells. These experiments indicated that different levels of endogenous miRNA levels can regulate transgene expression through a novel design in the 3'UTR. We next turned our attention to human hematopoietic cells. We reasoned that the long-term goal of minimal off-target transgene expression in HSCs would require knowledge of miRNAs that had little or no detectable expression (“selectively reduced [SR]”) in one cell type and were highly expressed in other cell types. In this manner, the transgene expression would be dampened only in the non-target cells. As a surrogate for bone marrow progenitors and as proof of principle, we used primary cells in normal human peripheral blood. T-cells, B-cells, platelets and granulocytes were purified by density centrifugation followed by immunoselection from five healthy human donors. Flow cytometry using membrane specific markers demonstrate >97% purity of each specific cell preparation. Total RNA was extracted and miRNAs were profiled as above. First, we identified 277 miRNAs that were differentially expressed between any pair of cell types (p-value<0.05 by ANOVA). Second, we performed ranked pair-wise comparisons across all cell types to determine SR miRNAs. This analysis revealed 5 platelet SR-miRNAs, 6 B-cell SR-miRNAs, 2 T-cell SR-miRNAs and 4 granulocyte SR-miRNAs. Lastly, we considered which of these 17 SR-miRNAs would be the best single SR-miRNA within and across cell types. SR-miRNAs were normalized to let-7b, a miRNA we determined to be equivalently expressed across all cell types, and hence, an ideal normalizer. Lineage-specific SR-miRNAs were selected based on extremely low expression in only one cell type and highest fold change of expression compared to the other cell types. The best SR-miRNAs were miR-29b (SR in platelets), miR-125a-5p (SR in B-cells) and miR-146a (SR in granulocytes). The SR expression levels of these 3 miRNAs were validated by qRT-PCR. Our analysis identified no good SR-miRNAs in T-cells. On-going experiments are testing the selective effects of the SR miRNAs in lentiviral vector infection of cord blood CD34+ cells differentiated along specific lineages. In summary, we have demonstrated in hematopoietic cell lines that SR endogenous miRNAs can regulate the expression of transgenes via tandem arrangement of their target sites in the 3'UTR. Additionally, we have identified miRNAs that are specifically expressed at a very low level in one blood cell type and at high levels in other cell types. These miRNAs could potentially be utilized as new biological tools in gene therapy for hematological disorders to restrict transgene expression and avoid the negative consequences of off-target expression. Disclosures: No relevant conflicts of interest to declare.

Sign in / Sign up

Export Citation Format

Share Document