scholarly journals Characterization of Alzheimer’s Disease-Associated Excitatory Neurons via Single-Cell RNA Sequencing Analysis

2021 ◽  
Vol 13 ◽  
Author(s):  
Fanghong Shao ◽  
Meiting Wang ◽  
Qi Guo ◽  
Bowen Zhang ◽  
Xiangting Wang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Neuronal Cell ◽  
Cell Populations ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing ◽  
Excitatory Neurons

The detailed characteristics of neuronal cell populations in Alzheimer’s disease (AD) using single-cell RNA sequencing have not been fully elucidated. To explore the characterization of neuronal cell populations in AD, this study utilized the publicly available single-nucleus RNA-sequencing datasets in the transgenic model of 5X familial Alzheimer’s disease (5XFAD) and wild-type mice to reveal an AD-associated excitatory neuron population (C3:Ex.Neuron). The relative abundance of C3:Ex.Neuron increased at 1.5 months and peaked at 4.7 months in AD mice. Functional pathways analyses showed that the pathways positively related to neurodegenerative disease progression were downregulated in the C3:Ex.Neuron at 1.5 months in AD mice. Based on the differentially expressed genes among the C3:Ex.Neuron, four subtypes (C3.1–4) were identified, which exhibited distinct abundance regulatory patterns during the development of AD. Among these subtypes, the C3.1 neurons [marked by netrin G1 (Ntng1)] exhibited a similar regulatory pattern as the C3:Ex.Neuron in abundance during the development of AD. In addition, our gene set variation analysis (GSEA) showed that the C3.1 neurons, instead of other subtypes of the C3:Ex.Neuron, possessed downregulated AD pathways at an early stage (1.5 months) of AD mice. Collectively, our results identified a previously unidentified subset of excitatory neurons and provide a potential application of these neurons to modulate the disease susceptibility.

scholarly journals Single-cell RNA sequencing reveals B cell–related molecular biomarkers for Alzheimer’s disease

2021 ◽  
Author(s):  
Liu-Lin Xiong ◽  
Lu-Lu Xue ◽  
Ruo-Lan Du ◽  
Rui-Ze Niu ◽  
Li Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
B Cells ◽  
B Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Early Stage ◽  
Diagnostic Process ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing

AbstractIn recent years, biomarkers have been integrated into the diagnostic process and have become increasingly indispensable for obtaining knowledge of the neurodegenerative processes in Alzheimer’s disease (AD). Peripheral blood mononuclear cells (PBMCs) in human blood have been reported to participate in a variety of neurodegenerative activities. Here, a single-cell RNA sequencing analysis of PBMCs from 4 AD patients (2 in the early stage, 2 in the late stage) and 2 normal controls was performed to explore the differential cell subpopulations in PBMCs of AD patients. A significant decrease in B cells was detected in the blood of AD patients. Furthermore, we further examined PBMCs from 43 AD patients and 41 normal subjects by fluorescence activated cell sorting (FACS), and combined with correlation analysis, we found that the reduction in B cells was closely correlated with the patients’ Clinical Dementia Rating (CDR) scores. To confirm the role of B cells in AD progression, functional experiments were performed in early-stage AD mice in which fibrous plaques were beginning to appear; the results demonstrated that B cell depletion in the early stage of AD markedly accelerated and aggravated cognitive dysfunction and augmented the Aβ burden in AD mice. Importantly, the experiments revealed 18 genes that were specifically upregulated and 7 genes that were specifically downregulated in B cells as the disease progressed, and several of these genes exhibited close correlation with AD. These findings identified possible B cell-based AD severity, which are anticipated to be conducive to the clinical identification of AD progression.

scholarly journals The interplay between microglial states and major risk factors in Alzheimer’s disease through the eyes of single-cell RNA-sequencing: beyond black and white

2019 ◽  
Vol 122 (4) ◽  
pp. 1291-1296 ◽  
Author(s):  
Djuna von Maydell ◽  
Mehdi Jorfi
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Mechanisms ◽  
Black And White ◽  
Single Cell Rna Sequencing ◽  
Sequencing Studies ◽  
Integral Role

Microglia constitute ~10–20% of glial cells in the adult human brain. They are the resident phagocytic immune cells of the central nervous system and play an integral role as first responders during inflammation. Microglia are commonly classified as “HM” (homeostatic), “M1” (classically activated proinflammatory), or “M2” (alternatively activated). Multiple single-cell RNA-sequencing studies suggest that this discrete classification system does not accurately and fully capture the vast heterogeneity of microglial states in the brain. In fact, a recent single-cell RNA-sequencing study showed that microglia exist along a continuous spectrum of states. This spectrum spans heterogeneous populations of homeostatic and neuropathology-associated microglia in both healthy and Alzheimer’s disease (AD) mouse brains. Major risk factors, such as sex, age, and genes, modulate microglial states, suggesting that shifts along the trajectory might play a causal role in AD pathogenesis. This study provides important insight into the cellular mechanisms of AD and underlines the potential of novel cell-based therapies for AD.

scholarly journals Single cell RNA sequencing of human microglia uncovers a subset that is associated with Alzheimer’s disease

2020 ◽  
Vol 16 (S2) ◽  
Author(s):  
Marta Olah ◽  
Vilas Menon ◽  
Naomi Habib ◽  
Mariko Taga ◽  
Yiyi Ma ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Human Microglia ◽  
Single Cell Rna Sequencing

scholarly journals Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Marta Olah ◽  
Vilas Menon ◽  
Naomi Habib ◽  
Mariko F. Taga ◽  
Yiyi Ma ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Single Cell ◽  
Rna Sequencing ◽  
Independent Set ◽  
Neurosurgical Procedures ◽  
Human Microglia ◽  
Single Cell Rna Sequencing ◽  
Single Nucleus ◽  
Disease Related Genes

AbstractThe extent of microglial heterogeneity in humans remains a central yet poorly explored question in light of the development of therapies targeting this cell type. Here, we investigate the population structure of live microglia purified from human cerebral cortex samples obtained at autopsy and during neurosurgical procedures. Using single cell RNA sequencing, we find that some subsets are enriched for disease-related genes and RNA signatures. We confirm the presence of four of these microglial subpopulations histologically and illustrate the utility of our data by characterizing further microglial cluster 7, enriched for genes depleted in the cortex of individuals with Alzheimer’s disease (AD). Histologically, these cluster 7 microglia are reduced in frequency in AD tissue, and we validate this observation in an independent set of single nucleus data. Thus, our live human microglia identify a range of subtypes, and we prioritize one of these as being altered in AD.

scholarly journals Characterization of normal and cancer stem-like cell populations in murine lingual epithelial organoids using single-cell RNA sequencing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Erik Johansson ◽  
Hiroo Ueno
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Targeted Therapies ◽  
Tongue Cancer ◽  
Cell Populations ◽  
Specific Gene ◽  
Sequencing Analysis ◽  
Molecular Targeted Therapies ◽  
Single Cell Rna Sequencing

AbstractThe advances in oral cancer research and therapies have not improved the prognosis of patients with tongue cancer. The poor treatment response of tongue cancer may be attributed to the presence of heterogeneous tumor cells exhibiting stem cell characteristics. Therefore, there is a need to develop effective molecular-targeted therapies based on the specific gene expression profiles of these cancer stem-like cell populations. In this study, the characteristics of normal and cancerous organoids, which are convenient tools for screening anti-cancer drugs, were analyzed comparatively. As organoids are generally generated by single progenitors, they enable the exclusion of normal cell contamination from the analyses. Single-cell RNA sequencing analysis revealed that p53 signaling activation and negative regulation of cell cycle were enriched characteristics in normal stem-like cells whereas hypoxia-related pathways, such as HIF-1 signaling and glycolysis, were upregulated in cancer stem-like cells. The findings of this study improved our understanding of the common features of heterogeneous cell populations with stem cell properties in tongue cancers, that are different from those of normal stem cell populations; this will enable the development of novel molecular-targeted therapies for tongue cancer.

scholarly journals Characterization of Adipose Stem Cells through Single Cell RNA‐sequencing Analysis

2021 ◽  
Vol 35 (S1) ◽  
Author(s):  
Hahn Nahmgoong ◽  
Yong Geun Jeon ◽  
Eun Seo Park ◽  
Jong Kyoung Kim ◽  
Jae Bum Kim
Keyword(s):  
Stem Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Adipose Stem Cells ◽  
Sequencing Analysis ◽  
Single Cell Rna Sequencing

Molecular and Cellular Dynamics of Aortic Aneurysms Revealed by Single-Cell Transcriptomics

2021 ◽  
Author(s):  
Yanming Li ◽  
Scott A. LeMaire ◽  
Ying H. Shen
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Types ◽  
Cellular Level ◽  
Aortic Aneurysms ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Sequencing Analysis ◽  
Molecular Features ◽  
Single Cell Rna Sequencing

The aorta is highly heterogeneous, containing many different types of cells that perform sophisticated functions to maintain aortic homeostasis. Recently, single-cell RNA sequencing studies have provided substantial new insight into the heterogeneity of vascular cell types, the comprehensive molecular features of each cell type, and the phenotypic interrelationship between these cell populations. This new information has significantly improved our understanding of aortic biology and aneurysms at the molecular and cellular level. Here, we summarize these findings, with a focus on what single-cell RNA sequencing analysis has revealed about cellular heterogeneity, cellular transitions, communications among cell populations, and critical transcription factors in the vascular wall. We also review the information learned from single-cell RNA sequencing that has contributed to our understanding of the pathogenesis of vascular disease, such as the identification of cell types in which aneurysm-related genes and genetic variants function. Finally, we discuss the challenges and future directions of single-cell RNA sequencing applications in studies of aortic biology and diseases.

scholarly journals Isoform-level gene expression patterns in single-cell RNA-sequencing data

2016 ◽  
Author(s):  
Trung Nghia Vu ◽  
Quin F Wills ◽  
Krishna R Kalari ◽  
Nifang Niu ◽  
Liewei Wang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Pattern Analysis ◽  
Single Cells ◽  
Expression Patterns ◽  
Cell Populations ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Differential Pattern

RNA-sequencing of single-cells enables characterization of transcriptional heterogeneity in seemingly homogenous cell populations. In this study we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of pairs of isoforms from the same gene in single-cell isoform-level expression data. We define six principal patterns of isoform expression relationships and introduce the concept of differential pattern analysis. We applied ISOP for analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in two independent datasets. In the primary dataset we detected and assigned pattern type of 16562 isoform-pairs from 4929 genes. Our results showed that 78% of the isoform pairs displayed a mutually exclusive expression pattern, 14% of the isoform pairs displayed bimodal isoform preference and 8% isoform pairs displayed isoform preference. 26% of the isoform-pair patterns were significant, while remaining isoform-pair patterns can be understood as effects of transcriptional bursting, drop-out and biological heterogeneity. 32% of genes discovered through differential pattern analysis were novel and not detected by differential expression analysis. ISOP provides a novel approach for characterization of isoform-level expression in single-cell populations. Our results reveal a common occurrence of isoform-level preference, commitment and heterogeneity in single-cell populations.

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