scholarly journals Comprehensive RNA sequencing in primary murine keratinocytes and fibroblasts identifies novel biomarkers and provides potential therapeutic targets for skin-related diseases

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Tiancheng Wang ◽  
Zhenwei Zhou ◽  
Enjing Luo ◽  
Jinghong Zhong ◽  
Daqing Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Growth Factors ◽  
Collagen Type ◽  
Therapeutic Targets ◽  
Cell Types ◽  
Rna Seq ◽  
Lymphocyte Antigen ◽  
Genes Encoding ◽  
Complex Locus

Abstract Background Keratinocytes and fibroblasts represent the major cell types in the epidermis and dermis of the skin and play a significant role in maintenance of skin homeostasis. However, the biological characteristics of keratinocytes and fibroblasts remain to be elucidated. The purpose of this study was to compare the gene expression pattern between keratinocytes and fibroblasts and to explore novel biomarker genes so as to provide potential therapeutic targets for skin-related diseases such as burns, wounds, and aging. Methods Skin keratinocytes and fibroblasts were isolated from newborn mice. To fully understand the heterogeneity of gene expression between keratinocytes and fibroblasts, differentially expressed genes (DEGs) between the two cell types were detected by RNA-seq technology. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the known genes of keratinocytes and fibroblasts and verify the RNA-seq results. Results Transcriptomic data showed a total of 4309 DEGs (fold-change > 1.5 and q-value < 0.05). Among them, 2197 genes were highly expressed in fibroblasts and included 10 genes encoding collagen, 16 genes encoding transcription factors, and 14 genes encoding growth factors. Simultaneously, 2112 genes were highly expressed in keratinocytes and included 7 genes encoding collagen, 14 genes encoding transcription factors, and 8 genes encoding growth factors. Furthermore, we summarized 279 genes specifically expressed in keratinocytes and 33 genes specifically expressed in fibroblasts, which may represent distinct molecular signatures of each cell type. Additionally, we observed some novel specific biomarkers for fibroblasts such as Plac8 (placenta-specific 8), Agtr2 (angiotensin II receptor, type 2), Serping1 (serpin peptidase inhibitor, clade G, member 1), Ly6c1 (lymphocyte antigen 6 complex, locus C1), Dpt (dermatopontin), and some novel specific biomarkers for keratinocytes such as Ly6a (lymphocyte antigen 6 complex, locus A) and Lce3c (late cornified envelope 3C), Ccer2 (coiled-coil glutamate-rich protein 2), Col18a1 (collagen, type XVIII, alpha 1) and Col17a1 (collagen type XVII, alpha 1). In summary, these data provided novel identifying biomarkers for two cell types, which can provide a resource of DEGs for further investigations.

scholarly journals Alterations of mesenchymal stromal cells in cerebrospinal fluid: insights from transcriptomics and an ALS clinical trial

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ashley A. Krull ◽  
Deborah O. Setter ◽  
Tania F. Gendron ◽  
Sybil C. L. Hrstka ◽  
Michael J. Polzin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cerebrospinal Fluid ◽  
Growth Factors ◽  
Mesenchymal Stromal Cells ◽  
Stromal Cells ◽  
Large Scale ◽  
Therapeutic Benefit ◽  
Protein Levels ◽  
Genes Encoding ◽  
Intrathecal Space

Abstract Background Mesenchymal stromal cells (MSCs) have been studied with increasing intensity as clinicians and researchers strive to understand the ability of MSCs to modulate disease progression and promote tissue regeneration. As MSCs are used for diverse applications, it is important to appreciate how specific physiological environments may stimulate changes that alter the phenotype of the cells. One need for neuroregenerative applications is to characterize the spectrum of MSC responses to the cerebrospinal fluid (CSF) environment after their injection into the intrathecal space. Mechanistic understanding of cellular biology in response to the CSF environment may predict the ability of MSCs to promote injury repair or provide neuroprotection in neurodegenerative diseases. Methods In this study, we characterized changes in morphology, metabolism, and gene expression occurring in human adipose-derived MSCs cultured in human (hCSF) or artificial CSF (aCSF) as well as examined relevant protein levels in the CSF of subjects treated with MSCs for amyotrophic lateral sclerosis (ALS). Results Our results demonstrated that, under intrathecal-like conditions, MSCs retained their morphology, though they became quiescent. Large-scale transcriptomic analysis of MSCs revealed a distinct gene expression profile for cells cultured in aCSF. The aCSF culture environment induced expression of genes related to angiogenesis and immunomodulation. In addition, MSCs in aCSF expressed genes encoding nutritional growth factors to expression levels at or above those of control cells. Furthermore, we observed a dose-dependent increase in growth factors and immunomodulatory cytokines in CSF from subjects with ALS treated intrathecally with autologous MSCs. Conclusions Overall, our results suggest that MSCs injected into the intrathecal space in ongoing clinical trials remain viable and may provide a therapeutic benefit to patients.

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 Single-nucleus RNA-seq and FISH identify coordinated transcriptional activity in mammalian myofibers

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Matthieu Dos Santos ◽  
Stéphanie Backer ◽  
Benjamin Saintpierre ◽  
Brigitte Izac ◽  
Muriel Andrieu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Transcription Factors ◽  
Neuromuscular Junction ◽  
Heavy Chain ◽  
Transcriptional Activity ◽  
Rna Seq ◽  
Hybrid Fibers ◽  
Adult Mice ◽  
Single Nucleus

Abstract Skeletal muscle fibers are large syncytia but it is currently unknown whether gene expression is coordinately regulated in their numerous nuclei. Here we show by snRNA-seq and snATAC-seq that slow, fast, myotendinous and neuromuscular junction myonuclei each have different transcriptional programs, associated with distinct chromatin states and combinations of transcription factors. In adult mice, identified myofiber types predominantly express either a slow or one of the three fast isoforms of Myosin heavy chain (MYH) proteins, while a small number of hybrid fibers can express more than one MYH. By snRNA-seq and FISH, we show that the majority of myonuclei within a myofiber are synchronized, coordinately expressing only one fast Myh isoform with a preferential panel of muscle-specific genes. Importantly, this coordination of expression occurs early during post-natal development and depends on innervation. These findings highlight a previously undefined mechanism of coordination of gene expression in a syncytium.

MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Yong Zhong ◽  
Xiangcheng Xiao
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Signaling Pathways ◽  
Iga Nephropathy ◽  
Molecular Mechanisms ◽  
Mesangial Cells ◽  
Therapeutic Targets ◽  
Cell Types ◽  
Receptor Crosstalk ◽  
Overt Proteinuria

Abstract Background and Aims The exact molecular mechanisms underlying IgA nephropathy (IgAN) remains incompletely defined. Therefore, it is necessary to further elucidate the mechanism of IgA nephropathy and find novel therapeutic targets. Method Single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from 4 IgAN and 1 control subjects to define the transcriptomic landscape at the single-cell resolution. Unsupervised clustering analysis of kidney specimens was used to identify distinct cell clusters. Differentially expressed genes and potential signaling pathways involved in IgAN were also identified. Results Our analysis identified 14 cell subsets in kidney biopsies from IgAN patients, and analyzed changing gene expression in distinct renal cell types. We found increased mesangial expression of several novel genes including MALAT1, GADD45B, SOX4 and EDIL3, which were related to proliferation and matrix accumulation and have not been reported in IgAN previously. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling and NOD-like receptor signaling. Moreover, the receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. Specifically, IgAN with overt proteinuria displayed elevated genes participating in several signaling pathways which may be involved in pathogenesis of progression of IgAN. Conclusion The comprehensive analysis of kidney biopsy specimen demonstrated different gene expression profile, potential pathologic ligand-receptor crosstalk, signaling pathways in human IgAN. These results offer new insight into pathogenesis and identify new therapeutic targets for patients with IgA nephropathy.

scholarly journals RNA-Seq Data-Mining Allows the Discovery of Two Long Non-Coding RNA Biomarkers of Viral Infection in Humans

2020 ◽  
Vol 21 (8) ◽  
pp. 2748 ◽  
Author(s):  
Ruth Barral-Arca ◽  
Alberto Gómez-Carballa ◽  
Miriam Cebey-López ◽  
María José Currás-Tuala ◽  
Sara Pischedda ◽  
...  
Keyword(s):  
Gene Expression ◽  
Viral Infections ◽  
Umbilical Vein ◽  
Cell Types ◽  
Dermal Fibroblasts ◽  
Learning Approaches ◽  
Rna Seq ◽  
Wide Range ◽  
Healthy Control ◽  
Umbilical Vein Endothelial Cells

There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections.

scholarly journals Molecular hallmarks of heterochronic parabiosis at single cell resolution

2020 ◽  
Author(s):  
Róbert Pálovics ◽  
Andreas Keller ◽  
Nicholas Schaum ◽  
Weilun Tan ◽  
Tobias Fehlmann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Disease Risk ◽  
Global Gene Expression ◽  
Cell Types ◽  
The Body ◽  
Hematopoietic Stem ◽  
Gene Sets ◽  
Genes Encoding ◽  
Systemic Understanding

Slowing or reversing biological ageing would have major implications for mitigating disease risk and maintaining vitality. While an increasing number of interventions show promise for rejuvenation, the effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. We performed single-cell RNA-sequencing on 13 organs to reveal cell type specific responses to young or aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, hematopoietic stem cells, hepatocytes, and endothelial cells from multiple tissues appear especially responsive. On the pathway level, young blood invokes novel gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. Intriguingly, we observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it. Altogether, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

scholarly journals Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

2019 ◽  
Author(s):  
Marcus Alvarez ◽  
Elior Rahmani ◽  
Brandon Jew ◽  
Kristina M. Garske ◽  
Zong Miao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Cell Types ◽  
Supervised Machine Learning ◽  
Data Sets ◽  
Rna Seq ◽  
Novel Approach ◽  
Single Nucleus ◽  
Downstream Analysis

AbstractSingle-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. Contrary to single-cell RNA seq (scRNA-seq), we observe that snRNA-seq is commonly subject to contamination by high amounts of extranuclear background RNA, which can lead to identification of spurious cell types in downstream clustering analyses if overlooked. We present a novel approach to remove debris-contaminated droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: 1) human differentiating preadipocytes in vitro, 2) fresh mouse brain tissue, and 3) human frozen adipose tissue (AT) from six individuals. All three data sets showed various degrees of extranuclear RNA contamination. We observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq data, we also successfully applied DIEM to single-cell data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem.

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.

Abstract 191: Transcriptional Regulation of Renin by Nuclear Receptors Co-regulated With Renin

Hypertension ◽  
2013 ◽  
Vol 62 (suppl_1) ◽  
Author(s):  
Ko-Ting Lu ◽  
Eric T Weatherford ◽  
Pimonrat Ketsawatsomkron ◽  
Justin L Grobe ◽  
Curt D Sigmund
Keyword(s):  
Gene Expression ◽  
Nuclear Receptors ◽  
Estrogen Receptor Alpha ◽  
Hormone Receptors ◽  
Cell Types ◽  
Negative Control ◽  
Sirna Duplex ◽  
Expression Of Genes ◽  
Renin Gene ◽  
Genes Encoding

Expression of the renin gene is required to maintain normal morphological and physiological identity of renal juxtaglomerular (JG) cells, yet the mechanisms regulating renin gene transcription remain elusive. We re-examined data from Brunskill et. al (JASN 22:2213, 2011), investigating genome-wide gene expression in JG and other renal cell types. Based on our previous data implicating nuclear receptors (RAR, RXR, VDR, PPARG, Nr2f2 and Nr2f6) in the regulation of mouse and human renin gene expression, we focused our analysis on the expression of genes encoding the 48 nuclear hormone receptors and their co-regulation with renin. Several nuclear receptors have an expression pattern emulating that of renin, that is, they were similarly enriched in JG cells but not in other cell types. These include Esr1, Nr1h4, Ppara, VDR, Nr1i2, Ppard, Hnf4g, Nr1h3, Thrb, Hnf4a, Esrrg, Nr4a3, Nr3c2, and Ar. We tested the hypothesis that a nuclear receptor that is co-regulated with renin may participate in renin gene regulation. To accomplish this, endogenous renin expression was evaluated in renin-expressing As4.1 cells after siRNA-mediated knock down of selected nuclear receptors. Each experiment included a negative control siRNA duplex (NC) that does not target any known genes. By way of example, siRNA-mediated inhibition of estrogen receptor alpha (Esr1) by 70-80% resulted in a 2-fold decrease in renin mRNA (fold change ± SEM: siEsr1: 0.4±0.2, p<0.001 vs NC). Similar results were obtained with a different siRNA targeting Esr1. Interestingly, loss of Esr1 also caused up-regulation of vitamin D receptor (VDR, 2.8±0.7 fold, p<0.001 vs NC) and Nr2f6 (2.0±0.2 fold, p<0.05 vs NC), both of which are known to be negative regulators of renin. Similarly, both renin (0.1±0.02, p<0.001 vs untreated) and Esr1 (0.3±0.1, p<0.05 vs untreated) mRNA were reduced in the kidney from mice treated with deoxycorticosterone acetate (50mg) and receiving 0.15 M NaCl in drinking water for 21 days (DOCA-salt). These data suggest Esr1 may regulate renin expression. Studies are in progress to assess if Esr1 stimulates renin expression on its own or acts by affecting the level of other nuclear receptors; and to determine if other co-regulated nuclear receptors also regulate expression of the renin gene.

scholarly journals Identifying inaccuracies in gene expression estimates from unstranded RNA-seq data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail Pomaznoy ◽  
Ashu Sethi ◽  
Jason Greenbaum ◽  
Bjoern Peters
Keyword(s):  
Gene Expression ◽  
Differential Expression Analysis ◽  
Cell Types ◽  
Library Preparation ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Machine Learning Model ◽  
Specific Manner ◽  
Library Preparation Protocol

Abstract RNA-seq methods are widely utilized for transcriptomic profiling of biological samples. However, there are known caveats of this technology which can skew the gene expression estimates. Specifically, if the library preparation protocol does not retain RNA strand information then some genes can be erroneously quantitated. Although strand-specific protocols have been established, a significant portion of RNA-seq data is generated in non-strand-specific manner. We used a comprehensive stranded RNA-seq dataset of 15 blood cell types to identify genes for which expression would be erroneously estimated if strand information was not available. We found that about 10% of all genes and 2.5% of protein coding genes have a two-fold or higher difference in estimated expression when strand information of the reads was ignored. We used parameters of read alignments of these genes to construct a machine learning model that can identify which genes in an unstranded dataset might have incorrect expression estimates and which ones do not. We also show that differential expression analysis of genes with biased expression estimates in unstranded read data can be recovered by limiting the reads considered to those which span exonic boundaries. The resulting approach is implemented as a package available at https://github.com/mikpom/uslcount.

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