scholarly journals NKCC1, an Elusive Molecular Target in Brain Development: Making Sense of the Existing Data

Cells ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2607
Author(s):  
Mari A. Virtanen ◽  
Pavel Uvarov ◽  
Christian A. Hübner ◽  
Kai Kaila
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Brain Cell ◽  
Specific Expression ◽  
Knock Out ◽  
Making Sense ◽  
Cell Type Specific Expression ◽  
Endogenous Proteins ◽  
Gaba Transmission

Ionotropic GABA transmission is mediated by anion (mainly Cl−)-permeable GABAA receptors (GABAARs). In immature neurons, GABA exerts depolarizing and sometimes functionally excitatory actions, based on active uptake of Cl− by the Na-K-2Cl cotransporter NKCC1. While functional evidence firmly shows NKCC1-mediated ion transport in immature and diseased neurons, molecular detection of NKCC1 in the brain has turned out to be extremely difficult. In this review, we describe the highly inconsistent data that are available on the cell type-specific expression patterns of the NKCC1 mRNA and protein in the CNS. We discuss the major technical caveats, including a lack of knock-out-controlled immunohistochemistry in the forebrain, possible effects of alternative splicing on the binding of antibodies and RNA probes, and the wide expression of NKCC1 in different cell types, which make whole-tissue analyses of NKCC1 useless for studying its neuronal expression. We also review novel single-cell RNAseq data showing that most of the NKCC1 in the adult CNS may, in fact, be expressed in non-neuronal cells, especially in glia. As future directions, we suggest single-cell NKCC1 mRNA and protein analyses and the use of genetically tagged endogenous proteins or systematically designed novel antibodies, together with proper knock-out controls, for the visualization of endogenous NKCC1 in distinct brain cell types and their subcellular compartments.

scholarly journals Cell-type Specific Expression Quantitative Trait Loci Associated with Alzheimer Disease in Blood and Brain Tissue

2020 ◽  
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 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.

scholarly journals Dynamics of gene expression in single root cells ofA. thaliana

2018 ◽  
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.

scholarly journals Differential induction of Pax genes by NGF and BDNF in cerebellar primary cultures.

1994 ◽  
Vol 125 (2) ◽  
pp. 417-425 ◽  
Author(s):  
C Kioussi ◽  
P Gruss
Keyword(s):  
Gene Family ◽  
Expression Patterns ◽  
Primary Cultures ◽  
Neuronal Cell ◽  
Cell Types ◽  
Early Gene ◽  
Specific Expression ◽  
Pax Genes ◽  
Cell Type Specific Expression

The Pax genes encode sequence-specific DNA binding transcription factors that are expressed in embryonic development of the nervous system. Primary neuronal cell cultures derived from the cerebellar cortex of embryonic day 14, newborn and 7-d old mice, were used to investigate the cell-type specific expression patterns of three members of the murine paired box containing gene family (Pax gene family), in vitro. Cell types which express Pax-2, Pax-3, and Pax-6 RNA in primary cultures correspond to those found in regions of the cerebellum which show RNA signals in sections of the developing mouse brain. To find mechanisms regulating Pax gene expression during cerebellar development, the differential regulation of Pax-2, Pax-3, and Pax-6 by NGF and BDNF, two structurally related neurotrophins, was studied in such primary cultures. Pax-2 and Pax-6 RNA increased slightly by 1 h and remained elevated throughout a 24-h treatment with BDNF and NGF. Pax-3 RNA was not detected in newborn cultures, but underwent a rapid (1 h) and transient (2 h) induction upon treatment with either BDNF or NGF. No response was seen with EGF or FGF. Cycloheximide treatment amplified Pax-3 induction and prolonged the signal. Thus, Pax-3 induction resembles that of the immediate-early gene c-fos, which transduces growth factor signals during the development of particular neuronal/glial cell types. The changes in Pax expression were inductive rather than trophic.

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

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.

scholarly journals Single-cell dissection of the human cerebrovasculature in health and disease

2021 ◽  
Author(s):  
Francisco J. Garcia ◽  
Na Sun ◽  
Hyeseung Lee ◽  
Brianna Godlewski ◽  
Kyriaki Galani ◽  
...  
Keyword(s):  
Single Cell ◽  
Ex Vivo ◽  
Expression Patterns ◽  
Cell Types ◽  
Normal Brain ◽  
Specific Expression ◽  
Fresh Tissue ◽  
Tissue Samples ◽  
Brain Physiology ◽  
Human Specific

SummaryDespite the importance of the blood-brain barrier in maintaining normal brain physiology and in understanding neurodegeneration and CNS drug delivery, human cerebrovascular cells remain poorly characterized due to their sparsity and dispersion. Here, we perform the first single-cell characterization of the human cerebrovasculature using both ex vivo fresh-tissue experimental enrichment and post mortem in silico sorting of human cortical tissue samples. We capture 31,812 cerebrovascular cells across 17 subtypes, including three distinct subtypes of perivascular fibroblasts as well as vasculature-coupled neurons and glia. We uncover human-specific expression patterns along the arteriovenous axis and determine previously uncharacterized cell type-specific markers. We use our newly discovered human-specific signatures to study changes in 3,945 cerebrovascular cells of Huntington’s disease patients, which reveal an activation of innate immune signaling in vascular and vasculature-coupled cell types and the concomitant reduction to proteins critical for maintenance of BBB integrity. Finally, our study provides a comprehensive resource molecular atlas of the human cerebrovasculature to guide future biological and therapeutic studies.

scholarly journals Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Jong Kyoung Kim ◽  
Aleksandra A. Kolodziejczyk ◽  
Tomislav Ilicic ◽  
Sarah A. Teichmann ◽  
John C. Marioni
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Large Fraction ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Technical Noise ◽  
Allele Specific ◽  
High Level

Abstract Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells, we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for lowly and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.

scholarly journals DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species

2021 ◽  
Author(s):  
Yanhui Hu ◽  
Sudhir Gopal Tattikota ◽  
Yifang Liu ◽  
Aram Comjean ◽  
Yue Gao ◽  
...  
Keyword(s):  
Single Cell ◽  
Expression Patterns ◽  
Model Organisms ◽  
Marker Genes ◽  
Specific Expression ◽  
Web Based ◽  
Manual Curation ◽  
Original Analysis ◽  
Cell Type Specific Expression ◽  
Cell Type Specific

AbstractWith the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, called DRscDB (https://www.flyrnai.org/tools/single_cell/web/) to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and the relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. DRscDB serves as a web-based user interface that allows users to mine, utilize and compare gene expression data pertaining to scRNA-seq datasets from the published literature.

scholarly journals Finding cell-specific expression patterns in the early Ciona embryo with single-cell RNA-seq

2017 ◽  
Author(s):  
Garth R. Ilsley ◽  
Ritsuko Suyama ◽  
Takeshi Noda ◽  
Nori Satoh ◽  
Nicholas M. Luscombe
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Stage ◽  
Specific Expression ◽  
Temporal Gene Expression

AbstractSingle-cell RNA-seq has been established as a reliable and accessible technique enabling new types of analyses, such as identifying cell types and studying spatial and temporal gene expression variation and change at single-cell resolution. Recently, single-cell RNA-seq has been applied to developing embryos, which offers great potential for finding and characterising genes controlling the course of development along with their expression patterns. In this study, we applied single-cell RNA-seq to the 16-cell stage of the Ciona embryo, a marine chordate and performed a computational search for cell-specific gene expression patterns. We recovered many known expression patterns from our single-cell RNA-seq data and despite extensive previous screens, we succeeded in finding new cell-specific patterns, which we validated by in situ and single-cell qPCR.

scholarly journals Molecular taxonomy of human ocular outflow tissues defined by single-cell transcriptomics

2020 ◽  
Vol 117 (23) ◽  
pp. 12856-12867 ◽  
Author(s):  
Gaurang Patel ◽  
Wen Fury ◽  
Hua Yang ◽  
Maria Gomez-Caraballo ◽  
Yu Bai ◽  
...  
Keyword(s):  
Single Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Molecular Taxonomy ◽  
Cell Types ◽  
Primary Component ◽  
Second Primary ◽  
Specific Expression ◽  
Component Structure ◽  
Outflow Pathway

The conventional outflow pathway is a complex tissue responsible for maintaining intraocular pressure (IOP) homeostasis. The coordinated effort of multiple cells with differing responsibilities ensures healthy outflow function and IOP maintenance. Dysfunction of one or more resident cell types results in ocular hypertension and risk for glaucoma, a leading cause of blindness. In this study, single-cell RNA sequencing was performed to generate a comprehensive cell atlas of human conventional outflow tissues. We obtained expression profiles of 17,757 genes from 8,758 cells from eight eyes of human donors representing the outflow cell transcriptome. Upon clustering analysis, 12 distinct cell types were identified, and region-specific expression of candidate genes was mapped in human tissues. Significantly, we identified two distinct expression patterns (myofibroblast- and fibroblast-like) from cells located in the trabecular meshwork (TM), the primary structural component of the conventional outflow pathway. We also located Schwann cell and macrophage signatures in the TM. The second primary component structure, Schlemm’s canal, displayed a unique combination of lymphatic/blood vascular gene expression. Other expression clusters corresponded to cells from neighboring tissues, predominantly in the ciliary muscle/scleral spur, which together correspond to the uveoscleral outflow pathway. Importantly, the utility of our atlas was demonstrated by mapping glaucoma-relevant genes to outflow cell clusters. Our study provides a comprehensive molecular and cellular classification of conventional and unconventional outflow pathway structures responsible for IOP homeostasis.

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

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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