scholarly journals Allele-specific single-cell RNA sequencing reveals different architectures of intrinsic and extrinsic gene expression noises

2019 ◽  
Author(s):  
Mengyi Sun ◽  
Jianzhi Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Intrinsic Noise ◽  
Mouse Fibroblast ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

ABSTRACTGene expression noise refers to the variation of the expression level of a gene among isogenic cells in the same environment, and has two sources: extrinsic noise arising from the disparity of the cell state and intrinsic noise arising from the stochastic process of gene expression in the same cell state. Due to the low throughput of the existing method for measuring the two noise components, the architectures of intrinsic and extrinsic expression noises remain elusive. Using allele-specific single-cell RNA sequencing, we here estimate the two noise components of 3975 genes in mouse fibroblast cells. Our analyses verify predicted influences of several factors such as the TATA-box and microRNA targeting on intrinsic and extrinsic noises and reveal gene function-associated noise trends implicating the action of natural selection. These findings unravel differential regulations, optimizations, and biological consequences of intrinsic and extrinsic noises and can aid the construction of desired synthetic circuits.

scholarly journals Allele-specific single-cell RNA sequencing reveals different architectures of intrinsic and extrinsic gene expression noises

2019 ◽  
Vol 48 (2) ◽  
pp. 533-547 ◽  
Author(s):  
Mengyi Sun ◽  
Jianzhi Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Intrinsic Noise ◽  
Mouse Fibroblast ◽  
Extrinsic Noise ◽  
Gene Expression Noise ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

Abstract Gene expression noise refers to the variation of the expression level of a gene among isogenic cells in the same environment, and has two sources: extrinsic noise arising from the disparity of the cell state and intrinsic noise arising from the stochastic process of gene expression in the same cell state. Due to the low throughput of the existing method for measuring the two noise components, the architectures of intrinsic and extrinsic expression noises remain elusive. Using allele-specific single-cell RNA sequencing, we here estimate the two noise components of 3975 genes in mouse fibroblast cells. Our analyses verify predicted influences of several factors such as the TATA-box and microRNA targeting on intrinsic or extrinsic noises and reveal gene function-associated noise trends implicating the action of natural selection. These findings unravel differential regulations, optimizations, and biological consequences of intrinsic and extrinsic noises and can aid the construction of desired synthetic circuits.

scholarly journals SCALE: modeling allele-specific gene expression by single-cell RNA sequencing

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Yuchao Jiang ◽  
Nancy R. Zhang ◽  
Mingyao Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Scale Modeling ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

scholarly journals Single-cell RNA-sequencing of peripheral neuroblastic tumors reveals an aggressive transitional cell state at the junction of an adrenergic-mesenchymal transdifferentiation trajectory

2020 ◽  
Author(s):  
Xiaojun Yuan ◽  
Janith A. Seneviratne ◽  
Shibei Du ◽  
Ying Xu ◽  
Yijun Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Crest ◽  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Transitional Cell ◽  
Malignant Cell ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Neuroblastic Tumors

AbstractPeripheral neuroblastic tumors (PNTs) are the most common extracranial solid tumors in early childhood. They represent a spectrum of neural crest derived tumors including neuroblastoma, ganglioneuroblastoma and ganglioneuroma. PNTs exhibit heterogeneity due to interconverting malignant cell states described as adrenergic/nor-adrenergic or mesenchymal/neural crest cell in origin. The factors determining individual patient levels of tumor heterogeneity, their impact on the malignant phenotype, and the presence of other cell states are unknown. Here, single-cell RNA-sequencing analysis of 4267 cells from 7 PNTs demonstrated extensive transcriptomic heterogeneity. Trajectory modelling showed that malignant neuroblasts move between adrenergic and mesenchymal cell states via a novel state that we termed a “transitional” phenotype. Transitional cells are characterized by gene expression programs linked to a sympathoadrenal development, and aggressive tumor phenotypes such as rapid proliferation and tumor dissemination. Among primary bulk tumor patient cohorts, high expression of the transitional gene signature was highly predictive of poor prognosis when compared to adrenergic and mesenchymal expression patterns. High transitional gene expression in neuroblastoma cell lines identified a similar transitional H3K27-acetylation super-enhancer landscape, supporting the concept that PNTs have phenotypic plasticity and transdifferentiation capacity. Additionally, examination of PNT microenvironments, found that neuroblastomas contained low immune cell infiltration, high levels of non-inflammatory macrophages, and low cytotoxic T lymphocyte levels compared with more benign PNT subtypes. Modeling of cell-cell signaling in the tumor microenvironment predicted specific paracrine effects toward the various subtypes of malignant cells, suggesting further cell-extrinsic influences on malignant cell phenotype. Collectively, our study reveals the presence of a previously unrecognized transitional cell state with high malignant potential and an immune cell architecture which serve both as potential biomarkers and therapeutic targets.

scholarly journals Preparation of single-cell suspension from mouse breast cancer focusing on preservation of original cell state information and cell type composition

2019 ◽  
Author(s):  
Abaffy Pavel ◽  
Lettlova Sandra ◽  
Truksa Jaroslav ◽  
Kubista Mikael ◽  
Sindelka Radek
Keyword(s):  
Gene Expression ◽  
Cell Suspension ◽  
Single Cell ◽  
Rna Sequencing ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Single Cell Suspension ◽  
Cell State ◽  
Single Cell Rna Sequencing ◽  
Original Cell

SUMMARYSingle-cell analysis of gene expression has become a very popular method during the last decade. Unfortunately, appropriate standardization and workflow optimization remain elusive. The first step of the single cell analysis requires that the solid tissue be disassociated into a suspension of individual cells. However, during this step several technical bias can arise which can later result in the misinterpretation of the data. The goal of this study was to identify and quantify the effect of these technical factors on the quality of the single-cell suspension and the subsequent interpretation of the produced expression data. We tested the effects of various enzymes used for dissociation, several centrifugation forces, dissociation temperatures and the addition of Actinomycin D, a gene expression inhibitor. RT-qPCR was used to assess the effect from each parameter alteration, while a single-cell RNA sequencing experiment was used to confirm the optimized factors. Our concluding results provide a complete protocol for the tissue dissociation of mouse mammary tumour from 4T1 cells that preserves the original cell state and is suitable for any single-cell RNA sequencing analysis. Furthermore, our workflow may serve as a guide for the optimization of the dissociation procedure of any other tissue of interest, which would ultimately improve the reproducibility of the reported data.

scholarly journals Modeling allele-specific gene expression by single-cell RNA sequencing

2017 ◽  
Author(s):  
Yuchao Jiang ◽  
Nancy R Zhang ◽  
Mingyao Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Specific Gene ◽  
Burst Frequency ◽  
Specific Expression ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Allelic Differences ◽  
Allele Specific

AbstractAllele-specific expression is traditionally studied by bulk RNA sequencing, which measures average expression across cells. Single-cell RNA sequencing (scRNA-seq) allows the comparison of expression distribution between the two alleles of a diploid organism and thus the characterization of allele-specific bursting. We propose SCALE to analyze genome-wide allele-specific bursting, with adjustment of technical variability. SCALE detects genes exhibiting allelic differences in bursting parameters, and genes whose alleles burst non-independently. We apply SCALE to mouse blastocyst and human fibroblast cells and find that, globally, cis control in gene expression overwhelmingly manifests as differences in burst frequency.

scholarly journals Integrated single‐cell RNA sequencing analyses suggest developmental paths of cancer‐associated fibroblasts with gene expression dynamics

2021 ◽  
Vol 11 (7) ◽  
Author(s):  
Hee Chul Chung ◽  
Eun Jeong Cho ◽  
Hyeonjin Lee ◽  
Won‐Kyung Kim ◽  
Ji‐Hye Oh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cancer Associated Fibroblasts ◽  
Single Cell Rna Sequencing ◽  
Gene Expression Dynamics

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

scholarly journals Single-cell RNA sequencing of the mammalian pineal gland identifies two pinealocyte subtypes and cell type-specific daily patterns of gene expression

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205883 ◽  
Author(s):  
Joseph C. Mays ◽  
Michael C. Kelly ◽  
Steven L. Coon ◽  
Lynne Holtzclaw ◽  
Martin F. Rath ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pineal Gland ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Cell Type Specific ◽  
Mammalian Pineal Gland ◽  
Daily Patterns

scholarly journals Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽  
2020 ◽  
Vol 371 (6531) ◽  
pp. eaba5257 ◽  
Author(s):  
Anna Kuchina ◽  
Leandra M. Brettner ◽  
Luana Paleologu ◽  
Charles M. Roco ◽  
Alexander B. Rosenberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cell Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Growth Stages ◽  
High Throughput Analysis ◽  
Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

Sign in / Sign up

Export Citation Format

Share Document