The first intron of the myelin proteolipid protein gene confers cell type-specific expression by a transcriptional repression mechanism in non-expressing cell types

ABSTRACTBecause regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell-types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5,257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1Mb of genes was evaluated using linear regression models for unrelated subjects and linear mixed models for related subjects. Cell type-specific eQTL (ct-eQTL) models included an interaction term for expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2,533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell-types is supported by the observation that a large portion of GWS ct-eQTLs map within 1Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type specific analysis.

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Dynamics of gene expression in single root cells ofA. thaliana

10.1101/448514 ◽

2018 ◽

Cited By ~ 3

Author(s):

Ken Jean-Baptiste ◽

José L. McFaline-Figueroa ◽

Cristina M. Alexandre ◽

Michael W. Dorrity ◽

Lauren Saunders ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Developmental Trajectories ◽

Cell Types ◽

Cell Type ◽

Specific Expression ◽

Root Cells ◽

Cell Lineages ◽

Cell Type Specific Expression ◽

Cell Type Specific

ABSTRACTSingle-cell RNA-seq can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach toA. thalianaroot cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single-cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single-cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

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Cell-Type Specific Analysis of Selenium-Related Genes in Brain

Antioxidants ◽

10.3390/antiox8050120 ◽

2019 ◽

Vol 8 (5) ◽

pp. 120

Author(s):

Alexandru R. Sasuclark ◽

Vedbar S. Khadka ◽

Matthew W. Pitts

Keyword(s):

Neural Development ◽

Cortical Neurons ◽

Cell Types ◽

Inhibitory Neurons ◽

Brain Atlas ◽

Cell Type ◽

Specific Expression ◽

Rnaseq Data ◽

Cell Type Specific Expression ◽

Cell Type Specific

Selenoproteins are a unique class of proteins that play key roles in redox signaling in the brain. This unique organ is comprised of a wide variety of cell types that includes excitatory neurons, inhibitory neurons, astrocytes, microglia, and oligodendrocytes. Whereas selenoproteins are known to be required for neural development and function, the cell-type specific expression of selenoproteins and selenium-related machinery has yet to be systematically investigated. Due to advances in sequencing technology and investment from the National Institutes of Health (NIH)-sponsored BRAIN initiative, RNA sequencing (RNAseq) data from thousands of cortical neurons can now be freely accessed and searched using the online RNAseq data navigator at the Allen Brain Atlas. Hence, we utilized this newly developed tool to perform a comprehensive analysis of the cell-type specific expression of selenium-related genes in brain. Select proteins of interest were further verified by means of multi-label immunofluorescent labeling of mouse brain sections. Of potential significance to neural selenium homeostasis, we report co-expression of selenoprotein P (SELENOP) and selenium binding protein 1 (SELENBP1) within astrocytes. These findings raise the intriguing possibility that SELENBP1 may negatively regulate astrocytic SELENOP synthesis and thereby limit downstream Se supply to neurons.

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Single-Cell Regulatory Network Inference and Clustering Identifies Cell-Type Specific Expression Pattern of Transcription Factors in Mouse Sciatic Nerve

Frontiers in Cellular Neuroscience ◽

10.3389/fncel.2021.676515 ◽

2021 ◽

Vol 15 ◽

Author(s):

Mingchao Li ◽

Qing Min ◽

Matthew C. Banton ◽

Xinpeng Dun

Keyword(s):

Transcription Factors ◽

Sciatic Nerve ◽

Single Cell ◽

Cell Types ◽

Cell Type ◽

Specific Expression ◽

Single Cell Rna Sequencing ◽

Cell Type Specific Expression ◽

Cell Type Specific ◽

Different Cell Types

Advances in single-cell RNA sequencing technologies and bioinformatics methods allow for both the identification of cell types in a complex tissue and the large-scale gene expression profiling of various cell types in a mixture. In this report, we analyzed a single-cell RNA sequencing (scRNA-seq) dataset for the intact adult mouse sciatic nerve and examined cell-type specific transcription factor expression and activity during peripheral nerve homeostasis. In total, we identified 238 transcription factors expressed in nine different cell types of intact mouse sciatic nerve. Vascular smooth muscle cells have the lowest number of transcription factors expressed with 17 transcription factors identified. Myelinating Schwann cells (mSCs) have the highest number of transcription factors expressed, with 61 transcription factors identified. We created a cell-type specific expression map for the identified 238 transcription factors. Our results not only provide valuable information about the expression pattern of transcription factors in different cell types of adult peripheral nerves but also facilitate future studies to understand the function of key transcription factors in the peripheral nerve homeostasis and disease.

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Cell-Type-Specific Expression of Renin-Angiotensin-System Components in the Human Body and Its Relevance to SARS-CoV-2 Infection

10.1101/2020.04.11.034603 ◽

2020 ◽

Author(s):

Hemant Suryawanshi ◽

Pavel Morozov ◽

Thangamani Muthukumar ◽

Benjamin R. tenOever ◽

Masashi Yamaji ◽

...

Keyword(s):

Renin Angiotensin System ◽

Cell Types ◽

The Body ◽

Cell Type ◽

Specific Expression ◽

Angiotensin System ◽

Renin Angiotensin ◽

Viral Interference ◽

Cell Type Specific Expression ◽

Cell Type Specific

AbstractWe have analyzed the cell-type-specific expression of the renin-angiotensin system (RAS) components across 141 cell types or subtypes as defined by single-cell RNA-seq (scRNA-seq) analysis. ACE2, one of the components of RAS, also facilitates SARS-CoV-2 entry into cells in cooperation with its associated protease TMPRSS2. Therefore, our analysis also contributes to the understanding of SARS-CoV-2 infection, spreading of the virus throughout the body, and potential viral interference with RAS in COVID-19 patients.

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Changing Patterns of Gene Expression in Dictyostelium Prestalk Cell Subtypes Recognized by In Situ Hybridization with Genes from Microarray Analyses

Eukaryotic Cell ◽

10.1128/ec.2.3.627-637.2003 ◽

2003 ◽

Vol 2 (3) ◽

pp. 627-637 ◽

Cited By ~ 57

Author(s):

Mineko Maeda ◽

Haruyo Sakamoto ◽

Negin Iranfar ◽

Danny Fuller ◽

Toshinari Maruo ◽

...

Keyword(s):

Gene Expression ◽

In Situ Hybridization ◽

Cell Types ◽

Cell Type ◽

Developmentally Regulated ◽

Specific Expression ◽

Cell Type Specific Expression ◽

Changing Patterns ◽

Cell Type Specific

ABSTRACT We used microarrays carrying most of the genes that are developmentally regulated in Dictyostelium to discover those that are preferentially expressed in prestalk cells. Prestalk cells are localized at the front of slugs and play crucial roles in morphogenesis and slug migration. Using whole-mount in situ hybridization, we were able to verify 104 prestalk genes. Three of these were found to be expressed only in cells at the very front of slugs, the PstA cell type. Another 10 genes were found to be expressed in the small number of cells that form a central core at the anterior, the PstAB cell type. The rest of the prestalk-specific genes are expressed in PstO cells, which are found immediately posterior to PstA cells but anterior to 80% of the slug that consists of prespore cells. Half of these are also expressed in PstA cells. At later stages of development, the patterns of expression of a considerable number of these prestalk genes changes significantly, allowing us to further subdivide them. Some are expressed at much higher levels during culmination, while others are repressed. These results demonstrate the extremely dynamic nature of cell-type-specific expression in Dictyostelium and further define the changing physiology of the cell types. One of the signals that affect gene expression in PstO cells is the hexaphenone DIF-1. We found that expression of about half of the PstO-specific genes were affected in a mutant that is unable to synthesize DIF-1, while the rest appeared to be DIF independent. These results indicate that differentiation of some aspects of PstO cells can occur in the absence of DIF-1.

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Repression of myelin proteolipid protein gene expression is mediated through both general and cell type-specific negative regulatory elements in nonexpressing cells

Journal of Neurochemistry ◽

10.1046/j.1471-4159.2002.00962.x ◽

2002 ◽

Vol 82 (1) ◽

pp. 159-171 ◽

Cited By ~ 6

Author(s):

Shenyang Li ◽

Anna Dobretsova ◽

Natalia A. Kokorina ◽

Patricia A. Wight

Keyword(s):

Gene Expression ◽

Protein Gene ◽

Proteolipid Protein ◽

Regulatory Elements ◽

Cell Type ◽

Myelin Proteolipid Protein ◽

Cell Type Specific ◽

Myelin Proteolipid

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Cnidarian cell type diversity revealed by whole-organism single-cell RNA-seq analysis

10.1101/201103 ◽

2017 ◽

Author(s):

Arnau Sebé-Pedrós ◽

Elad Chomsky ◽

Baptiste Saudememont ◽

Marie-Pierre Mailhe ◽

Flora Pleisser ◽

...

Keyword(s):

Single Cell ◽

Cell Types ◽

Tissue Level ◽

Rna Seq ◽

Cell Type ◽

Specific Expression ◽

Animal Evolution ◽

Neuronal Markers ◽

Cell Type Specific Expression ◽

Cell Type Specific

A hallmark of animal evolution is the emergence and diversification of cell type-specific transcriptional states. But systematic and unbiased characterization of differentiated gene regulatory programs was so far limited to specific tissues in a few model species. Here, we perform whole-organism single cell transcriptomics to map cell types in the cnidarian Nematostella vectensis, a non-bilaterian animal that display complex tissue-level bodyplan organization. We uncover high diversity of transcriptional states in Nematostella, demonstrating cell type-specific expression for 35% of the genes and 51% of the transcription factors (TFs) detected. We identify eight broad cell clusters corresponding to cell classes such as neurons, muscles, cnidocytes, or digestive cells. These clusters comprise multiple cell modules expressing diverse and specific markers, uncovering in particular a rich repertoire of cells associated with neuronal markers. TF expression and sequence analysis defines the combinatorial code that underlies this cell-specific expression. It also reveals the existence of a complex regulatory lexicon of TF binding motifs encoded at both enhancer and promoters of Nematostella tissue-specific genes. Whole organism single cell RNA-seq is thereby established as a tool for comprehensive study of genome regulation and cell type evolution.

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Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue

Translational Psychiatry ◽

10.1038/s41398-021-01373-z ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Devanshi Patel ◽

Xiaoling Zhang ◽

John J. Farrell ◽

Jaeyoon Chung ◽

Thor D. Stein ◽

...

Keyword(s):

Gene Expression ◽

Quantitative Trait ◽

Expression Patterns ◽

Regulation Of Gene Expression ◽

Cell Types ◽

Eqtl Analysis ◽

Cell Type ◽

Specific Expression ◽

Cell Type Specific Expression ◽

Cell Type Specific

AbstractBecause regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.

Download Full-text