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Figure 1. Generation and Validation of scRNA-Seq Data from Breast Cancer Cells under Estrogen Stimulation (A) Workflow depicting the rapid and high-throughput isolation and RNA sequencing (RNA-seq) of single-cells from breast cancer cell lines under time course E2 treatment. (B) Correlation between single-cell profiles and bulk population profiles. (C) Scatterplot of gene expression values (log2[FPKM + 1]) between the 100k cell bulk profile and the 10k cell bulk profile (r = 0.948). (D) Scatterplot between two random single-cell profiles with low correlation (r = 0.587). (E) Scatterplot between the 10k cell bulk profile and a random single-cell profile showing low correlation (r = 0.63). (F) Scatterplot between the 10k cell bulk profile and the average of all single-cell profile (r = 0.865). (G) Violin plots showing the single-cell RNA sequencing (scRNA-seq) expression values (log2[FPKM + 1]) of estrogen-responsive marker genes TFF1, GREB1, and ESR1 from the time course E2 treatment of MCF-7 cells. (H) Violin plots showing single-cell <t>ddPCR</t> values (log2[count + 1]) of the marker genes from the same MCF-7 time course experiment. (I) Violin plots showing smRNA-FISH values (log2[count + 1]) of the marker genes in a time course E2 treatment of MCF-7 cells. Two hundred cells were counted for each time point. (J) Multiplexed smRNA-FISH images showing the mRNA copies of the marker genes in MCF-7 cells under time course E2 treatment with nuclei counter stained by DAPI.
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Figure 1. Generation and Validation of scRNA-Seq Data from Breast Cancer Cells under Estrogen Stimulation (A) Workflow depicting the rapid and high-throughput isolation and RNA sequencing (RNA-seq) of single-cells from breast cancer cell lines under time course E2 treatment. (B) Correlation between single-cell profiles and bulk population profiles. (C) Scatterplot of gene expression values (log2[FPKM + 1]) between the 100k cell bulk profile and the 10k cell bulk profile (r = 0.948). (D) Scatterplot between two random single-cell profiles with low correlation (r = 0.587). (E) Scatterplot between the 10k cell bulk profile and a random single-cell profile showing low correlation (r = 0.63). (F) Scatterplot between the 10k cell bulk profile and the average of all single-cell profile (r = 0.865). (G) Violin plots showing the single-cell RNA sequencing (scRNA-seq) expression values (log2[FPKM + 1]) of estrogen-responsive marker genes TFF1, GREB1, and ESR1 from the time course E2 treatment of MCF-7 cells. (H) Violin plots showing single-cell <t>ddPCR</t> values (log2[count + 1]) of the marker genes from the same MCF-7 time course experiment. (I) Violin plots showing smRNA-FISH values (log2[count + 1]) of the marker genes in a time course E2 treatment of MCF-7 cells. Two hundred cells were counted for each time point. (J) Multiplexed smRNA-FISH images showing the mRNA copies of the marker genes in MCF-7 cells under time course E2 treatment with nuclei counter stained by DAPI.
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DIAGENODE DIAGNOSTICS rabbit anti-human yy1
Figure 1. Generation and Validation of scRNA-Seq Data from Breast Cancer Cells under Estrogen Stimulation (A) Workflow depicting the rapid and high-throughput isolation and RNA sequencing (RNA-seq) of single-cells from breast cancer cell lines under time course E2 treatment. (B) Correlation between single-cell profiles and bulk population profiles. (C) Scatterplot of gene expression values (log2[FPKM + 1]) between the 100k cell bulk profile and the 10k cell bulk profile (r = 0.948). (D) Scatterplot between two random single-cell profiles with low correlation (r = 0.587). (E) Scatterplot between the 10k cell bulk profile and a random single-cell profile showing low correlation (r = 0.63). (F) Scatterplot between the 10k cell bulk profile and the average of all single-cell profile (r = 0.865). (G) Violin plots showing the single-cell RNA sequencing (scRNA-seq) expression values (log2[FPKM + 1]) of estrogen-responsive marker genes TFF1, GREB1, and ESR1 from the time course E2 treatment of MCF-7 cells. (H) Violin plots showing single-cell <t>ddPCR</t> values (log2[count + 1]) of the marker genes from the same MCF-7 time course experiment. (I) Violin plots showing smRNA-FISH values (log2[count + 1]) of the marker genes in a time course E2 treatment of MCF-7 cells. Two hundred cells were counted for each time point. (J) Multiplexed smRNA-FISH images showing the mRNA copies of the marker genes in MCF-7 cells under time course E2 treatment with nuclei counter stained by DAPI.
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Image Search Results


Figure 1. Generation and Validation of scRNA-Seq Data from Breast Cancer Cells under Estrogen Stimulation (A) Workflow depicting the rapid and high-throughput isolation and RNA sequencing (RNA-seq) of single-cells from breast cancer cell lines under time course E2 treatment. (B) Correlation between single-cell profiles and bulk population profiles. (C) Scatterplot of gene expression values (log2[FPKM + 1]) between the 100k cell bulk profile and the 10k cell bulk profile (r = 0.948). (D) Scatterplot between two random single-cell profiles with low correlation (r = 0.587). (E) Scatterplot between the 10k cell bulk profile and a random single-cell profile showing low correlation (r = 0.63). (F) Scatterplot between the 10k cell bulk profile and the average of all single-cell profile (r = 0.865). (G) Violin plots showing the single-cell RNA sequencing (scRNA-seq) expression values (log2[FPKM + 1]) of estrogen-responsive marker genes TFF1, GREB1, and ESR1 from the time course E2 treatment of MCF-7 cells. (H) Violin plots showing single-cell ddPCR values (log2[count + 1]) of the marker genes from the same MCF-7 time course experiment. (I) Violin plots showing smRNA-FISH values (log2[count + 1]) of the marker genes in a time course E2 treatment of MCF-7 cells. Two hundred cells were counted for each time point. (J) Multiplexed smRNA-FISH images showing the mRNA copies of the marker genes in MCF-7 cells under time course E2 treatment with nuclei counter stained by DAPI.

Journal: Cell reports

Article Title: Single-Cell Transcriptome Analysis Reveals Estrogen Signaling Coordinately Augments One-Carbon, Polyamine, and Purine Synthesis in Breast Cancer.

doi: 10.1016/j.celrep.2018.10.093

Figure Lengend Snippet: Figure 1. Generation and Validation of scRNA-Seq Data from Breast Cancer Cells under Estrogen Stimulation (A) Workflow depicting the rapid and high-throughput isolation and RNA sequencing (RNA-seq) of single-cells from breast cancer cell lines under time course E2 treatment. (B) Correlation between single-cell profiles and bulk population profiles. (C) Scatterplot of gene expression values (log2[FPKM + 1]) between the 100k cell bulk profile and the 10k cell bulk profile (r = 0.948). (D) Scatterplot between two random single-cell profiles with low correlation (r = 0.587). (E) Scatterplot between the 10k cell bulk profile and a random single-cell profile showing low correlation (r = 0.63). (F) Scatterplot between the 10k cell bulk profile and the average of all single-cell profile (r = 0.865). (G) Violin plots showing the single-cell RNA sequencing (scRNA-seq) expression values (log2[FPKM + 1]) of estrogen-responsive marker genes TFF1, GREB1, and ESR1 from the time course E2 treatment of MCF-7 cells. (H) Violin plots showing single-cell ddPCR values (log2[count + 1]) of the marker genes from the same MCF-7 time course experiment. (I) Violin plots showing smRNA-FISH values (log2[count + 1]) of the marker genes in a time course E2 treatment of MCF-7 cells. Two hundred cells were counted for each time point. (J) Multiplexed smRNA-FISH images showing the mRNA copies of the marker genes in MCF-7 cells under time course E2 treatment with nuclei counter stained by DAPI.

Article Snippet: REAGENT or RESOURCE SOURCE IDENTIFIER Chemicals, Peptides, and Recombinant Proteins 17b-estradiol (E2) Sigma Cat# 50-28-2 Critical Commercial Assays RNeasy Mini Kit QIAGEN Cat# 74106 SMARTer Ultra Low RNA Kit Clontech Cat# 634936 C1 Single-Cell mRNA Seq IFC Fluidigm Cat# 100-6041 C1 Single-Cell Reagent Kit for mRNA Seq Fluidigm Cat# 100-6201 C1 Single-Cell mRNA Seq HT IFC Fluidigm Cat# 101-4982 C1 Single-Cell mRNA Seq HT Reagent Kit v2 Fluidigm Cat# 101-3473 Nextera XT Sample Prep Kit Illumina Cat# FC-131-1096 Nextera XT DNA Sample Preparation Index Kit Illumina Cat# FC-131-1002 KAPA Library Quantification Kit KAPA Biosystems Cat# KR0405 Nextera XT Index Kit v2 Illumina Cat# FC-131-2001(set A) and FC-131-2002(set B). ddPCR Supermix for Probes (no dUTP) BioRad Cat# 186-3024 ddPCR Droplet Reader Oil BioRad Cat# 186-3004 DG8 Cartridges and Gaskets BioRad Cat# 186-4007 ddPCR 96-Well PCR Plates BioRad Cat# 12001925 RNAscope Multiplex Fluorescent v2 Kit ACDbio Cat# 323110 Cell apoptosis kit ThermoFisher Cat# V13245 MTT ThermoFisher Cat# M6494 Deposited Data Raw and analyzed data This paper GEO: GSE107864, GSE119455 Genome reference UCSC hg19 UCSC http://hgdownload.soe.ucsc.edu/goldenPath/ hg19/bigZips/ Gene annotation reference Gencode V18 Gencode database https://www.gencodegenes.org/18.html ERa ChIP-seq data Ross-Innes et al., 2012 GEO: GSE32222 Experimental Models: Cell Lines Human: MCF7 ATCC ATCC HTB-22 Human: T47D ATCC ATCC HTB-133 Oligonucleotides Primer sets and probes used in droplet digital PCR (Table S2) This paper N/A DsiRNAs used for knockdown assays (Table S3) This paper N/A Software and Algorithms Tophat v2.0.6 Kim et al., 2013 https://ccb.jhu.edu/software/tophat/index.shtml Cufflink v2.0.2 Trapnell et al., 2012 http://cole-trapnell-lab.github.io/cufflinks FastQC v0.11.5 https://www.bioinformatics. babraham.ac.uk/projects/fastqc/ https://www.bioinformatics.babraham.ac.uk/ projects/download.html#fastqc RSeQC v2.6.4 Wang et al., 2012 http://rseqc.sourceforge.net/ SIBER (OOMPA v2.1.0) Tong et al., 2013 http://bioinformatics.mdanderson.org/main/ OOMPA:Overview bc-GenExMiner 4.0 Jézéquel et al., 2012 http://bcgenex.centregauducheau.fr/BC-GEM/ GEM-Accueil.php?js=1 DAVID website v6.8 Huang et al., 2009 https://david.ncifcrf.gov/ GSEA software (MSigDB 6.2) Subramanian et al., 2005 http://software.broadinstitute.org/gsea/index.jsp Cell Reports 25, 2285–2298.e1–e4, November 20, 2018 e1

Techniques: Biomarker Discovery, High Throughput Screening Assay, Isolation, RNA Sequencing, Gene Expression, Expressing, Marker, Staining