Single-Cell mRNA Profiling Reveals Cell-Type-Specific Expression of Neurexin Isoforms

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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O4-10-01: CHARACTERIZING CELL TYPE-SPECIFIC EXPRESSION SIGNATURES IN BRAIN USING SINGLE CELL RNA SEQUENCING

Alzheimer s & Dementia ◽

10.1016/j.jalz.2019.06.4794 ◽

2019 ◽

Vol 15 ◽

pp. P1258-P1258 ◽

Cited By ~ 1

Author(s):

Tulsi Patel ◽

Troy Carnwath ◽

Laura Lewis-Tuffin ◽

Mariet Allen ◽

Sarah J. Lincoln ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Cell Type ◽

Specific Expression ◽

Single Cell Rna Sequencing ◽

Cell Type Specific Expression ◽

Cell Type Specific

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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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Single-cell transcriptomes identify human islet cell signatures and reveal cell-type–specific expression changes in type 2 diabetes

Genome Research ◽

10.1101/gr.212720.116 ◽

2016 ◽

Vol 27 (2) ◽

pp. 208-222 ◽

Cited By ~ 158

Author(s):

Nathan Lawlor ◽

Joshy George ◽

Mohan Bolisetty ◽

Romy Kursawe ◽

Lili Sun ◽

...

Keyword(s):

Type 2 Diabetes ◽

Single Cell ◽

Islet Cell ◽

Human Islet ◽

Cell Type ◽

Specific Expression ◽

Cell Type Specific Expression ◽

Cell Type Specific

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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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Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells

10.1101/2020.04.19.049254 ◽

2020 ◽

Cited By ~ 60

Author(s):

Christoph Muus ◽

Malte D. Luecken ◽

Gokcen Eraslan ◽

Avinash Waghray ◽

Graham Heimberg ◽

...

Keyword(s):

Epithelial Cells ◽

Single Cell ◽

Viral Entry ◽

Integrated Analysis ◽

Target Cells ◽

Specific Cell ◽

Cell Type ◽

Specific Expression ◽

Cell Type Specific Expression ◽

Cell Type Specific

ABSTRACTThe COVID-19 pandemic, caused by the novel coronavirus SARS-CoV-2, creates an urgent need for identifying molecular mechanisms that mediate viral entry, propagation, and tissue pathology. Cell membrane bound angiotensin-converting enzyme 2 (ACE2) and associated proteases, transmembrane protease serine 2 (TMPRSS2) and Cathepsin L (CTSL), were previously identified as mediators of SARS-CoV2 cellular entry. Here, we assess the cell type-specific RNA expression of ACE2, TMPRSS2, and CTSL through an integrated analysis of 107 single-cell and single-nucleus RNA-Seq studies, including 22 lung and airways datasets (16 unpublished), and 85 datasets from other diverse organs. Joint expression of ACE2 and the accessory proteases identifies specific subsets of respiratory epithelial cells as putative targets of viral infection in the nasal passages, airways, and alveoli. Cells that co-express ACE2 and proteases are also identified in cells from other organs, some of which have been associated with COVID-19 transmission or pathology, including gut enterocytes, corneal epithelial cells, cardiomyocytes, heart pericytes, olfactory sustentacular cells, and renal epithelial cells. Performing the first meta-analyses of scRNA-seq studies, we analyzed 1,176,683 cells from 282 nasal, airway, and lung parenchyma samples from 164 donors spanning fetal, childhood, adult, and elderly age groups, associate increased levels of ACE2, TMPRSS2, and CTSL in specific cell types with increasing age, male gender, and smoking, all of which are epidemiologically linked to COVID-19 susceptibility and outcomes. Notably, there was a particularly low expression of ACE2 in the few young pediatric samples in the analysis. Further analysis reveals a gene expression program shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues, including genes that may mediate viral entry, subtend key immune functions, and mediate epithelial-macrophage cross-talk. Amongst these are IL6, its receptor and co-receptor, IL1R, TNF response pathways, and complement genes. Cell type specificity in the lung and airways and smoking effects were conserved in mice. Our analyses suggest that differences in the cell type-specific expression of mediators of SARS-CoV-2 viral entry may be responsible for aspects of COVID-19 epidemiology and clinical course, and point to putative molecular pathways involved in disease susceptibility and pathogenesis.

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