scholarly journals TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation

2021 ◽  
Author(s):  
Martin Fischer ◽  
Konstantin Riege ◽  
Robert Schwarz ◽  
James A. DeCaprio ◽  
Steve Hoffmann
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Expression Profiling ◽  
Regulatory Mechanisms ◽  
Cell Type ◽  
Specific Effects ◽  
Binding Data ◽  
Cycle Dependent ◽  
Cell Cycle Signaling ◽  
Common Cell

AbstractIn recent years, our web-atlas at www.TargetGeneReg.org has enabled many researchers to uncover new biological insights and to identify novel regulatory mechanisms that affect p53 and the cell cycle – signaling pathways that are frequently dysregulated in diseases like cancer. Here, we provide a substantial upgrade of the database that comprises an extension to include non-coding genes and the transcription factors ΔNp63 and RFX7. TargetGeneReg 2.0 combines gene expression profiling and transcription factor DNA binding data to determine, for each gene, the response to p53, ΔNp63, and cell cycle signaling. It can be used to dissect common, cell type, and treatment-specific effects, identify the most promising candidates, and validate findings. We demonstrate the increased power and more intuitive layout of the resource using realistic examples.

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 The DREAM complex: master coordinator of cell cycle-dependent gene expression

2013 ◽  
Vol 13 (8) ◽  
pp. 585-595 ◽  
Author(s):  
Subhashini Sadasivam ◽  
James A. DeCaprio
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cycle Dependent

scholarly journals Genetic influences on cell type specific gene expression and splicing during neurogenesis elucidate regulatory mechanisms of brain traits

2020 ◽  
Author(s):  
Nil Aygün ◽  
Angela L. Elwell ◽  
Dan Liang ◽  
Michael J. Lafferty ◽  
Kerry E. Cheek ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Elements ◽  
Regulatory Mechanisms ◽  
Specific Gene ◽  
Cell Type ◽  
Specific Expression ◽  
Risk Variants ◽  
Allele Specific ◽  
Cell Type Specific ◽  
Regulatory Effects

SummaryInterpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing is mainly performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements of cells present during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs and allele specific expression in primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74). Using colocalization and TWAS, we uncover cell-type specific regulatory mechanisms underlying risk for these traits.

scholarly journals Microarray gene expression profiling in colorectal (HCT116) and hepatocellular (HepG2) carcinoma cell lines treated withMelicope ptelefolialeaf extract reveals transcriptome profiles exhibiting anticancer activity

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5203 ◽  
Author(s):  
Mohammad Faujul Kabir ◽  
Johari Mohd Ali ◽  
Onn Haji Hashim
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Dna Replication ◽  
Cell Lines ◽  
Microarray Data ◽  
Expression Profiling ◽  
Cell Cycle Progression ◽  
Anticancer Activities ◽  
Microarray Gene Expression ◽  
Cycle Progression

BackgroundWe have previously reported anticancer activities ofMelicope ptelefolia(MP) leaf extracts on four different cancer cell lines. However, the underlying mechanisms of actions have yet to be deciphered. In the present study, the anticancer activity of MP hexane extract (MP-HX) on colorectal (HCT116) and hepatocellular carcinoma (HepG2) cell lines was characterized through microarray gene expression profiling.MethodsHCT116 and HepG2 cells were treated with MP-HX for 24 hr. Total RNA was extracted from the cells and used for transcriptome profiling using Applied Biosystem GeneChip™ Human Gene 2.0 ST Array. Gene expression data was analysed using an Applied Biosystems Expression Console and Transcriptome Analysis Console software. Pathway enrichment analyses was performed using Ingenuity Pathway Analysis (IPA) software. The microarray data was validated by profiling the expression of 17 genes through quantitative reverse transcription PCR (RT-qPCR).ResultsMP-HX induced differential expression of 1,290 and 1,325 genes in HCT116 and HepG2 cells, respectively (microarray data fold change, MA_FC ≥ ±2.0). The direction of gene expression change for the 17 genes assayed through RT-qPCR agree with the microarray data. In both cell lines, MP-HX modulated the expression of many genes in directions that support antiproliferative activity. IPA software analyses revealed MP-HX modulated canonical pathways, networks and biological processes that are associated with cell cycle, DNA replication, cellular growth and cell proliferation. In both cell lines, upregulation of genes which promote apoptosis, cell cycle arrest and growth inhibition were observed, while genes that are typically overexpressed in diverse human cancers or those that promoted cell cycle progression, DNA replication and cellular proliferation were downregulated. Some of the genes upregulated by MP-HX include pro-apoptotic genes (DDIT3, BBC3, JUN), cell cycle arresting (CDKN1A, CDKN2B), growth arrest/repair (TP53, GADD45A) and metastasis suppression (NDRG1). MP-HX downregulated the expression of genes that could promote anti-apoptotic effect, cell cycle progression, tumor development and progression, which include BIRC5, CCNA2, CCNB1, CCNB2, CCNE2, CDK1/2/6, GINS2, HELLS, MCM2/10 PLK1, RRM2 and SKP2. It is interesting to note that all six top-ranked genes proposed to be cancer-associated (PLK1, MCM2, MCM3, MCM7, MCM10 and SKP2) were downregulated by MP-HX in both cell lines.DiscussionThe present study showed that the anticancer activities of MP-HX are exerted through its actions on genes regulating apoptosis, cell proliferation, DNA replication and cell cycle progression. These findings further project the potential use of MP as a nutraceutical agent for cancer therapeutics.

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

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