scholarly journals A conserved expression signature predicts growth rate and reveals cell & lineage-specific differences

2021 ◽  
Vol 17 (11) ◽  
pp. e1009582
Author(s):  
Zhisheng Jiang ◽  
Serena F. Generoso ◽  
Marta Badia ◽  
Bernhard Payer ◽  
Lucas B. Carey
Keyword(s):  
Growth Rate ◽  
Embryonic Stem ◽  
Cell Lineage ◽  
Proliferation Rate ◽  
Cell Type ◽  
Proliferating Cells ◽  
Mitochondria Membrane Potential ◽  
Transcriptional Signature ◽  
Expression Of Genes ◽  
Cell Type Specific

Isogenic cells cultured together show heterogeneity in their proliferation rate. To determine the differences between fast and slow-proliferating cells, we developed a method to sort cells by proliferation rate, and performed RNA-seq on slow and fast proliferating subpopulations of pluripotent mouse embryonic stem cells (mESCs) and mouse fibroblasts. We found that slowly proliferating mESCs have a more naïve pluripotent character. We identified an evolutionarily conserved proliferation-correlated transcriptomic signature that is common to all eukaryotes: fast cells have higher expression of genes for protein synthesis and protein degradation. This signature accurately predicted growth rate in yeast and cancer cells, and identified lineage-specific proliferation dynamics during development, using C. elegans scRNA-seq data. In contrast, sorting by mitochondria membrane potential revealed a highly cell-type specific mitochondria-state related transcriptome. mESCs with hyperpolarized mitochondria are fast proliferating, while the opposite is true for fibroblasts. The mitochondrial electron transport chain inhibitor antimycin affected slow and fast subpopulations differently. While a major transcriptional-signature associated with cell-to-cell heterogeneity in proliferation is conserved, the metabolic and energetic dependency of cell proliferation is cell-type specific.

scholarly journals Epigenetic mechanisms mediating cell state transitions in chondrocytes

2020 ◽  
Author(s):  
Manuela Wuelling ◽  
Christoph Neu ◽  
Andrea M. Thiesen ◽  
Simo Kitanovski ◽  
Yingying Cao ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Cell Lineage ◽  
Cell Types ◽  
State Transitions ◽  
Epigenetic Mechanisms ◽  
Cell Type ◽  
Transition Analysis ◽  
Lineage Differentiation ◽  
A Cell ◽  
Cell Type Specific

AbstractEpigenetic modifications play critical roles in regulating cell lineage differentiation, but the epigenetic mechanisms guiding specific differentiation steps within a cell lineage have rarely been investigated. To decipher such mechanisms, we used the defined transition from proliferating (PC) into hypertrophic chondrocytes (HC) during endochondral ossification as a model. We established a map of activating and repressive histone modifications for each cell type. ChromHMM state transition analysis and Pareto-based integration of differential levels of mRNA and epigenetic marks revealed that differentiation associated gene repression is initiated by the addition of H3K27me3 to promoters still carrying substantial levels of activating marks. Moreover, the integrative analysis identified genes specifically expressed in cells undergoing the transition into hypertrophy.Investigation of enhancer profiles detected surprising differences in enhancer number, location, and transcription factor binding sites between the two closely related cell types. Furthermore, cell type-specific upregulation of gene expression was associated with a shift from low to high H3K27ac decoration. Pathway analysis identified PC-specific enhancers associated with chondrogenic genes, while HC-specific enhancers mainly control metabolic pathways linking epigenetic signature to biological functions.

scholarly journals Cell Type-Specific Role of RNA Nuclease SMG6 in Neurogenesis

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3365
Author(s):  
Gabriela Maria Guerra ◽  
Doreen May ◽  
Torsten Kroll ◽  
Philipp Koch ◽  
Marco Groth ◽  
...  
Keyword(s):  
Stem Cells ◽  
Cell Fate ◽  
Cortical Neurons ◽  
Embryonic Stem ◽  
Normal Structure ◽  
Mutant Mice ◽  
Cell Type ◽  
Nonsense Mediated Mrna Decay ◽  
A Cell ◽  
Cell Type Specific

SMG6 is an endonuclease, which cleaves mRNAs during nonsense-mediated mRNA decay (NMD), thereby regulating gene expression and controling mRNA quality. SMG6 has been shown as a differentiation license factor of totipotent embryonic stem cells. To investigate whether it controls the differentiation of lineage-specific pluripotent progenitor cells, we inactivated Smg6 in murine embryonic neural stem cells. Nestin-Cre-mediated deletion of Smg6 in mouse neuroprogenitor cells (NPCs) caused perinatal lethality. Mutant mice brains showed normal structure at E14.5 but great reduction of the cortical NPCs and late-born cortical neurons during later stages of neurogenesis (i.e., E18.5). Smg6 inactivation led to dramatic cell death in ganglionic eminence (GE) and a reduction of interneurons at E14.5. Interestingly, neurosphere assays showed self-renewal defects specifically in interneuron progenitors but not in cortical NPCs. RT-qPCR analysis revealed that the interneuron differentiation regulators Dlx1 and Dlx2 were reduced after Smg6 deletion. Intriguingly, when Smg6 was deleted specifically in cortical and hippocampal progenitors, the mutant mice were viable and showed normal size and architecture of the cortex at E18.5. Thus, SMG6 regulates cell fate in a cell type-specific manner and is more important for neuroprogenitors originating from the GE than for progenitors from the cortex.

scholarly journals SnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C data

2020 ◽  
Author(s):  
Miao Yu ◽  
Armen Abnousi ◽  
Yanxiao Zhang ◽  
Guoqiang Li ◽  
Lindsay Lee ◽  
...  
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Target Genes ◽  
Embryonic Stem ◽  
Cell Type ◽  
Cortical Cells ◽  
Chromatin Loops ◽  
Chromatin Architecture ◽  
Prefrontal Cortical ◽  
Cell Type Specific

Single cell Hi-C (scHi-C) analysis has been increasingly used to map the chromatin architecture in diverse tissue contexts, but computational tools to define chromatin contacts at high resolution from scHi-C data are still lacking. Here, we describe SnapHiC, a method that can identify chromatin loops at high resolution and accuracy from scHi-C data. We benchmark SnapHiC against HiCCUPS, a common tool for mapping chromatin contacts in bulk Hi-C data, using scHi-C data from 742 mouse embryonic stem cells. We further demonstrate its utility by analyzing single-nucleus methyl-3C-seq data from 2,869 human prefrontal cortical cells. We uncover cell-type-specific chromatin loops and predict putative target genes for non-coding sequence variants associated with neuropsychiatric disorders. Our results suggest that SnapHiC could facilitate the analysis of cell-type-specific chromatin architecture and gene regulatory programs in complex tissues.

Cell type-specific endometrial transcriptome changes during initial recognition of pregnancy in the mare

2019 ◽  
Vol 31 (3) ◽  
pp. 496 ◽  
Author(s):  
Iside Scaravaggi ◽  
Nicole Borel ◽  
Rebekka Romer ◽  
Isabel Imboden ◽  
Susanne E. Ulbrich ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Information ◽  
Gene Expression Regulation ◽  
Cell Types ◽  
Rna Seq ◽  
Cell Type ◽  
Expression Of Genes ◽  
Prostaglandin F ◽  
Cell Type Specific ◽  
Gene Expression Studies

Previous endometrial gene expression studies during the time of conceptus migration did not provide final conclusions on the mechanisms of maternal recognition of pregnancy (MRP) in the mare. This called for a cell type-specific endometrial gene expression analysis in response to embryo signals to improve the understanding of gene expression regulation in the context of MRP. Laser capture microdissection was used to collect luminal epithelium (LE), glandular epithelium and stroma from endometrial biopsies from Day 12 of pregnancy and Day 12 of the oestrous cycle. RNA sequencing (RNA-Seq) showed greater expression differences between cell types than between pregnant and cyclic states; differences between the pregnant and cyclic states were mainly found in LE. Comparison with a previous RNA-Seq dataset for whole biopsy samples revealed the specific origin of gene expression differences. Furthermore, genes specifically differentially expressed (DE) in one cell type were found that were not detectable as DE in biopsies. Overall, this study revealed spatial information about endometrial gene expression during the phase of initial MRP. The conceptus induced changes in the expression of genes involved in blood vessel development, specific spatial regulation of the immune system, growth factors, regulation of prostaglandin synthesis, transport prostaglandin receptors, specifically prostaglandin F receptor (PTGFR) in the context of prevention of luteolysis.

Cell-type-specific consequences of nucleotide excision repair deficiencies: Embryonic stem cells versus fibroblasts

DNA Repair ◽  
2008 ◽  
Vol 7 (10) ◽  
pp. 1659-1669 ◽  
Author(s):  
H DEWAARD ◽  
E SONNEVELD ◽  
J DEWIT ◽  
R LANGE ◽  
J HOEIJMAKERS ◽  
...  
Keyword(s):  
Stem Cells ◽  
Embryonic Stem Cells ◽  
Nucleotide Excision Repair ◽  
Excision Repair ◽  
Embryonic Stem ◽  
Cell Type ◽  
Nucleotide Excision ◽  
Cell Type Specific

scholarly journals LMethyR-SVM: Predict human enhancers using low methylated regions based on weighted support vector machines

2016 ◽  
Author(s):  
Jingting Xu ◽  
Hong Hu ◽  
Yang Dai
Keyword(s):  
Dna Methylation ◽  
Histone Modification ◽  
Prediction Models ◽  
Large Fraction ◽  
Embryonic Stem ◽  
Fetal Lung ◽  
Support Vector ◽  
Cell Type ◽  
Enhancer Prediction ◽  
Cell Type Specific

AbstractBackgroundThe identification of enhancer is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning models. However, DNA methylation profiles generated from the whole genome bisulfate sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions.MethodIn this work we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles based on an unlabeled-negative learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive, and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is trained by solving a weighted support vector machine.ResultsWe demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the H1 human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers.ConclusionOur work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell type-specific enhancers.

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