Single cell RNA-seq by mostly-natural sequencing by synthesis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE197452 | GEO | 2022/05/31
REPOSITORIES: GEO
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Project description:Abstract: The recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we develop a BAyesian Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. BAMM-SC takes raw count data as input and accounts for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from applications of BAMM-SC to in-house experimental scRNA-seq datasets using blood and lung cells from humans or mice demonstrate that BAMM-SC outperformed existing clustering methods with considerable improved clustering accuracy, particularly in the presence of heterogeneity among individuals. Data purpose: To evaluate the performance of BAMM-SC for clustering droplet-based scRNA-seq data in population-based study, we performed single cell RNA-seq on peripheral blood mononuclear cells (PBMC) isolated from whole blood obtained from 4 healthy donors, and on lung cells isolated from streptococcus pneumonia (SP) infected and naïve mice.
2019-03-09 | GSE128066 | GEO
Project description:Existing protocols for full-length single-cell RNA sequencing (scRNA-seq) produce libraries of high complexity (thousands of distinct genes) with outstanding sensitivity and specificity of transcript quantification. These full-length libraries have the advantage of allowing probing of transcript isoforms, are informative regarding single nucleotide polymorphisms, and allow assembly of the VDJ region of the T- and B-cell receptor sequences. Since full length protocols are mostly plate-based at present, they are also suited to profiling cell types where cell numbers are limiting, such as rare cell types during development for instance. A disadvantage of these methods has been the scalability and cost of the experiments, which has limited their popularity as compared to droplet-based and nanowell approaches. Here, we describe an automated protocol for full-length scRNA-seq, including both an in-house automated SMART-seq2 protocol, and a commercial kit-based workflow. We discuss these two protocols in terms of ease-of-use, equipment requirements, running time, cost per sample and sequencing quality. By benchmarking the lysis buffers, reverse transcription enzymes and their combinations, we propose an optimized in-house automated protocol with dramatically reduced cost. These pipelines have been employed successfully for several research projects allied with the Human Cell Atlas initiative (www.humancellatlas.org) and are available on protocols.io.
2020-12-31 | E-MTAB-9345 | biostudies-arrayexpress
Project description:Pancreatic cancer is a complex disease with a desmoplastic stroma, extreme hypoxia, and inherent resistance to therapy. Understanding the signaling and adaptive response of such an aggressive cancer is key to making advances in therapeutic efficacy and understanding disease progression. Redox factor-1 (Ref-1), a redox signaling protein, regulates the DNA binding activity of several transcription factors, including HIF-1. The conversion of HIF-1 from an oxidized to reduced state leads to enhancement of its DNA binding. In our previously published work, knockdown of Ref-1 under normoxia resulted in altered gene expression patterns on pathways including EIF2, protein kinase A, and mTOR. In this study, single cell RNA sequencing (scRNA-seq) and proteomics were used to explore the effects of Ref-1 on metabolic pathways under hypoxia.Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions. Experimental Methods: scRNA-seq comparing pancreatic cancer cells expressing less than 20% of the Ref-1 protein was analyzed using left truncated mixture Gaussian model. Matched samples were also collected for bulk proteomic analysis of the four conditions. scRNA-seq data was validated using proteomics and qRT-PCR. Ref-1’s role in mitochondrial function was confirmed using mitochondrial function assays and qRT-PCR. Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions.
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2019-08-11 | E-MTAB-8192 | biostudies-arrayexpress
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2020-04-14 | E-MTAB-8735 | biostudies-arrayexpress
Project description:To profile the cell states of interacting natural killer (NK) cells and blood cancer cells, we cultured 26 different cell lines representing diverse hematologic neoplasms either alone or with NK cells derived from three healthy human donors. After 24 h co-culture, we labeled the cells from each monoculture or co-culture condition with oligonucleotide-conjugated antibodies against ubiquitously expressed surface proteins (with different oligonucleotide for each mono- or co-culture), enabling multiplexing in the scRNA-seq using the cell hashing method. We additionally performed pooled CRISPR screens with a single-cell transcriptome readout using the CROP-seq platform in blood cancer cells cultured either alone or in the presence of NK cells to study the effects of perturbing genes that influenced sensitivity to NK cell killing in genome-scale CRISPR screens.
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