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    Structured Review

    Thermo Fisher ns1 mutants
    The 103L and 106I residues in the H5N1- NS gene antagonize poly I: C induced IFN- β and IRF -3 promoter transcriptional activation but differ in CPSF- 30 F2F3 binding. a . <t>H5N1-NS1</t> proteins (wt and mutants) as well as CPSF30-F2F3-FLAG were expressed by coupled in vitro transcription and translation of expression plasmids or empty vector in the presence of 35 S labeled methionine and cysteine with detection by autoradiography. Radiolabeled NS1 proteins or empty vector were mixed with radiolabeled CPSF30- F2F3-FLAG and subject to pull-down using α-FLAG M2 antibody and detected by SDS-PAGE and autoradiography. b . Representative pull-down of 2 independent replicates showing that the I106 mutation abrogated binding but L103 maintained binding. c . IFN-β promoter activation was measured in human 293-T cells in triplicate biological replicates for the H5N1-NS-wt and the three NS mutant (L103F, I106M and L103F+I106M) expression plasmids using a dual-luciferase reporter assay. Each of the NS expression plasmids along with the firefly luciferase p125 under the control of the human IFN-β promoter as well as the renilla luciferase control pRL-SV40 reporter plasmids were transfected in 293T cells. Sixteen hours following transfection, IFN-β promoter activation was stimulated by poly I:C transfection. The luciferase activities were measured following a 24h incubation period and are shown as the ratio relative to the internal renilla luciferase control. d . The same experiment was repeated using the firefly luviferase reporter plasmid under the control of the human IRF-3 promoter. Data represent the means of n = 3 values ± SD (*p
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    1) Product Images from "Influenza A/Hong Kong/156/1997(H5N1) virus NS1 gene mutations F103L and M106I both increase IFN antagonism, virulence and cytoplasmic localization but differ in binding to RIG-I and CPSF30"

    Article Title: Influenza A/Hong Kong/156/1997(H5N1) virus NS1 gene mutations F103L and M106I both increase IFN antagonism, virulence and cytoplasmic localization but differ in binding to RIG-I and CPSF30

    Journal: Virology Journal

    doi: 10.1186/1743-422X-10-243

    The 103L and 106I residues in the H5N1- NS gene antagonize poly I: C induced IFN- β and IRF -3 promoter transcriptional activation but differ in CPSF- 30 F2F3 binding. a . H5N1-NS1 proteins (wt and mutants) as well as CPSF30-F2F3-FLAG were expressed by coupled in vitro transcription and translation of expression plasmids or empty vector in the presence of 35 S labeled methionine and cysteine with detection by autoradiography. Radiolabeled NS1 proteins or empty vector were mixed with radiolabeled CPSF30- F2F3-FLAG and subject to pull-down using α-FLAG M2 antibody and detected by SDS-PAGE and autoradiography. b . Representative pull-down of 2 independent replicates showing that the I106 mutation abrogated binding but L103 maintained binding. c . IFN-β promoter activation was measured in human 293-T cells in triplicate biological replicates for the H5N1-NS-wt and the three NS mutant (L103F, I106M and L103F+I106M) expression plasmids using a dual-luciferase reporter assay. Each of the NS expression plasmids along with the firefly luciferase p125 under the control of the human IFN-β promoter as well as the renilla luciferase control pRL-SV40 reporter plasmids were transfected in 293T cells. Sixteen hours following transfection, IFN-β promoter activation was stimulated by poly I:C transfection. The luciferase activities were measured following a 24h incubation period and are shown as the ratio relative to the internal renilla luciferase control. d . The same experiment was repeated using the firefly luviferase reporter plasmid under the control of the human IRF-3 promoter. Data represent the means of n = 3 values ± SD (*p
    Figure Legend Snippet: The 103L and 106I residues in the H5N1- NS gene antagonize poly I: C induced IFN- β and IRF -3 promoter transcriptional activation but differ in CPSF- 30 F2F3 binding. a . H5N1-NS1 proteins (wt and mutants) as well as CPSF30-F2F3-FLAG were expressed by coupled in vitro transcription and translation of expression plasmids or empty vector in the presence of 35 S labeled methionine and cysteine with detection by autoradiography. Radiolabeled NS1 proteins or empty vector were mixed with radiolabeled CPSF30- F2F3-FLAG and subject to pull-down using α-FLAG M2 antibody and detected by SDS-PAGE and autoradiography. b . Representative pull-down of 2 independent replicates showing that the I106 mutation abrogated binding but L103 maintained binding. c . IFN-β promoter activation was measured in human 293-T cells in triplicate biological replicates for the H5N1-NS-wt and the three NS mutant (L103F, I106M and L103F+I106M) expression plasmids using a dual-luciferase reporter assay. Each of the NS expression plasmids along with the firefly luciferase p125 under the control of the human IFN-β promoter as well as the renilla luciferase control pRL-SV40 reporter plasmids were transfected in 293T cells. Sixteen hours following transfection, IFN-β promoter activation was stimulated by poly I:C transfection. The luciferase activities were measured following a 24h incubation period and are shown as the ratio relative to the internal renilla luciferase control. d . The same experiment was repeated using the firefly luviferase reporter plasmid under the control of the human IRF-3 promoter. Data represent the means of n = 3 values ± SD (*p

    Techniques Used: Activation Assay, Binding Assay, In Vitro, Expressing, Plasmid Preparation, Labeling, Autoradiography, SDS Page, Mutagenesis, Luciferase, Reporter Assay, Transfection, Incubation

    Linear plot of relative gene expression of host genes between NS1 HK - wt and mutants in human A459 cells. The host gene expression relative to HK-wt was plotted with the line of best fit for dysregulated genes in human A459 cells shown in Figure 7 a. The slope of each line is indicated relative to the HK-wt line with slope = 1. Insert. A box plot of dysregulated gens from Figure 7 a shown relative to the gene expression of HK-wt relative to mock infected M1 cells.
    Figure Legend Snippet: Linear plot of relative gene expression of host genes between NS1 HK - wt and mutants in human A459 cells. The host gene expression relative to HK-wt was plotted with the line of best fit for dysregulated genes in human A459 cells shown in Figure 7 a. The slope of each line is indicated relative to the HK-wt line with slope = 1. Insert. A box plot of dysregulated gens from Figure 7 a shown relative to the gene expression of HK-wt relative to mock infected M1 cells.

    Techniques Used: Expressing, Infection

    Host gene expression is differentially affected by 103L and 106I mutation in human and mouse cells. Mouse M1 cells and human A459 cells were wither mock infected with PBS of infected with rHK1-wt, or NS1 F103L, M106I, M106V and F103L + M106I mutants at MOI = 2 in triplicate with extraction of total RNA at 8 hpi. Genes that were significantly increased or decreased 2 fold (≥ 2 1 or ≤ 2 -1 ) by Affymetrix microarray analysis relative to mock infected cells for any individual virus were analyzed among the viruses. Host genes are represented in heat maps with red and blue according to with the indicated scales for the log 2 values ( panels a , b and c) . a) Effect of virus infection on gene regulation in mouse M1 cells showing hierarchical cluster analysis of dys regulated genes as well as hierarchical clustering among viruses. b) Effect of virus infection on gene regulation in human A549 cells showing hierarchical clustering of genes and viruses as represented in panel a. Relative to HK-wt the 242 dysregulated genes were significantly upregulated for M106I, M106V and F103L + M106I (** p ≤ 0.01, *** p ≤ 0.001 by t-test) but not F103L (not significantly different (nsd)). c) Transcriptional abundance analysis of genes that are common between human and mouse cells were analyzed as described in panel a. d) Bar graph of up (red bars) and down (blue bars) regulated gene transcripts detected by microarray analysis relative to mock infected M1 and A459 cells infected with the indicated viruses. The number of significantly up and down regulated genes relative to mock infected A549 cells was significantly different for M106I, M106V and F103L + M106I (*p ≤ 0.05 by Chi-squared test), versus HK-wt (reference, r) but not F103L that was not significantly different.
    Figure Legend Snippet: Host gene expression is differentially affected by 103L and 106I mutation in human and mouse cells. Mouse M1 cells and human A459 cells were wither mock infected with PBS of infected with rHK1-wt, or NS1 F103L, M106I, M106V and F103L + M106I mutants at MOI = 2 in triplicate with extraction of total RNA at 8 hpi. Genes that were significantly increased or decreased 2 fold (≥ 2 1 or ≤ 2 -1 ) by Affymetrix microarray analysis relative to mock infected cells for any individual virus were analyzed among the viruses. Host genes are represented in heat maps with red and blue according to with the indicated scales for the log 2 values ( panels a , b and c) . a) Effect of virus infection on gene regulation in mouse M1 cells showing hierarchical cluster analysis of dys regulated genes as well as hierarchical clustering among viruses. b) Effect of virus infection on gene regulation in human A549 cells showing hierarchical clustering of genes and viruses as represented in panel a. Relative to HK-wt the 242 dysregulated genes were significantly upregulated for M106I, M106V and F103L + M106I (** p ≤ 0.01, *** p ≤ 0.001 by t-test) but not F103L (not significantly different (nsd)). c) Transcriptional abundance analysis of genes that are common between human and mouse cells were analyzed as described in panel a. d) Bar graph of up (red bars) and down (blue bars) regulated gene transcripts detected by microarray analysis relative to mock infected M1 and A459 cells infected with the indicated viruses. The number of significantly up and down regulated genes relative to mock infected A549 cells was significantly different for M106I, M106V and F103L + M106I (*p ≤ 0.05 by Chi-squared test), versus HK-wt (reference, r) but not F103L that was not significantly different.

    Techniques Used: Expressing, Mutagenesis, Infection, Microarray

    Analysis of NS1 protein 103 and 106 residue mutation in natural human and animal isolates. a . Phylogenetic trees based on the NS1 protein sequence of influenza A viruses isolated from subtypes H1N1, H3N2, H5N1, H6N1and H9N2. Know subtypes and amino acid at position 103 and 106 are indicated. Different 103/106 residue motifs (FM, YM, LI) are represented by a grey square. Full trees and a list of GenBank accession numbers of the viruses used are provided in supplementary information. Independent selection of F103L occurred in the FM lineage and are indicated with a square (■) and independent selection of M106I is shown for 2 H9N2 isolates representative of a Middle Eastern lineage. b . Variability found at position 103 and 106 in different IAV subtypes. H1N1, H3N2, H5N1, H6N1 and H9N2 viruses were analyzed for the frequency of different amino acid compositions at position 103, 106 and 103/106.
    Figure Legend Snippet: Analysis of NS1 protein 103 and 106 residue mutation in natural human and animal isolates. a . Phylogenetic trees based on the NS1 protein sequence of influenza A viruses isolated from subtypes H1N1, H3N2, H5N1, H6N1and H9N2. Know subtypes and amino acid at position 103 and 106 are indicated. Different 103/106 residue motifs (FM, YM, LI) are represented by a grey square. Full trees and a list of GenBank accession numbers of the viruses used are provided in supplementary information. Independent selection of F103L occurred in the FM lineage and are indicated with a square (■) and independent selection of M106I is shown for 2 H9N2 isolates representative of a Middle Eastern lineage. b . Variability found at position 103 and 106 in different IAV subtypes. H1N1, H3N2, H5N1, H6N1 and H9N2 viruses were analyzed for the frequency of different amino acid compositions at position 103, 106 and 103/106.

    Techniques Used: Mutagenesis, Sequencing, Isolation, Selection

    The 103L and 106I residues in the H5N1- NS gene are associated with increased cytoplasmic localization of NS1 protein in mouse epithelial cells. Monolayers of mouse epithelial cells were infected with rPR8-H5N1-NS-103L+106I (n=3) and the three mutants rPR8-NS-L103F+106I, rPR8-NS-103L+I106M and rPR8-NS-L103F+I106M (n=2) at MOI=2 and compared to mock uninfected cells. NS1, NP and M1 proteins localization was detected by western blots using rabbit protein specific antibodies. Rabbit anti-tubulin and mouse anti-histone antibodies were used as controls for cytoplasmic and nuclear fractions respectively. a . The nuclear and cytoplasmic accumulation of NS1 protein is shown for one analysis. The whole cell lysate is designated as “W”, nuclear fraction as “N” and the cytoplsmic fraction as “C”. b . Western blots showing the H5N1-NS1 protein nuclear and cytoplasmic fractions in parallel for 2–3 replicates of infected M1 cells.
    Figure Legend Snippet: The 103L and 106I residues in the H5N1- NS gene are associated with increased cytoplasmic localization of NS1 protein in mouse epithelial cells. Monolayers of mouse epithelial cells were infected with rPR8-H5N1-NS-103L+106I (n=3) and the three mutants rPR8-NS-L103F+106I, rPR8-NS-103L+I106M and rPR8-NS-L103F+I106M (n=2) at MOI=2 and compared to mock uninfected cells. NS1, NP and M1 proteins localization was detected by western blots using rabbit protein specific antibodies. Rabbit anti-tubulin and mouse anti-histone antibodies were used as controls for cytoplasmic and nuclear fractions respectively. a . The nuclear and cytoplasmic accumulation of NS1 protein is shown for one analysis. The whole cell lysate is designated as “W”, nuclear fraction as “N” and the cytoplsmic fraction as “C”. b . Western blots showing the H5N1-NS1 protein nuclear and cytoplasmic fractions in parallel for 2–3 replicates of infected M1 cells.

    Techniques Used: Infection, Western Blot

    The H5N1 NS1 L103 and I106 mutations affect binding of NS1 to human RIG- I CARD, helicase and RD domains in the bacterial reverse 2- hybrid system. a . Drop spotting of the H5N1 influenza NS1 RTHS strains on selective media. Serial dilutions (2.5 μL of each sample containing ~10 n cells/mL is indicated) of the NS1 RTHS strains (and controls), were drop spotted onto selective media containing 0, 25 or 50 μM IPTG. In the absence of IPTG, there is no expression of the targeted fusion proteins; all strains therefore grow normally (top row of plates). Upon addition of IPTG (2nd and 3rd row of plates), the functional 434.P22 repressor will be reconstituted in those RTHS that contain interacting proteins (Additional file 1 : Figure S1), leading to cell death. The strains containing proteins that do not interact (e.g. L103F, I106M) continue to grow normally in the presence of IPTG. b . Dose response for IPTG induction of proteins for RIGI domain binding of H5N1 and H3N2 NS1 L103 and I106 mutants as well as H1N1 and H3N2 wt NS1 proteins. RTHS constructs that possessed each of the wt H5N1 (A/HK/156/1997), H3N2 (A/HK/1/68) and H1N1 (/Brevig Mission/1/1918) or indicated 103 and 106 mutant for the H5N1 and H3N2 viruses were tested for survival under selective medium on induction with 0, 5, 10, 25 and 50 μM IPTG. The number of surviving bacterial colonies were determined by serial dilution as shown in panel A and plotted as bar graphs. NS1 proteins that do not bind the indicated RIG-I domain baits (CARD, helicase and RD) were not reduced in survival relative to the non-induced controls (0 μM IPTG).
    Figure Legend Snippet: The H5N1 NS1 L103 and I106 mutations affect binding of NS1 to human RIG- I CARD, helicase and RD domains in the bacterial reverse 2- hybrid system. a . Drop spotting of the H5N1 influenza NS1 RTHS strains on selective media. Serial dilutions (2.5 μL of each sample containing ~10 n cells/mL is indicated) of the NS1 RTHS strains (and controls), were drop spotted onto selective media containing 0, 25 or 50 μM IPTG. In the absence of IPTG, there is no expression of the targeted fusion proteins; all strains therefore grow normally (top row of plates). Upon addition of IPTG (2nd and 3rd row of plates), the functional 434.P22 repressor will be reconstituted in those RTHS that contain interacting proteins (Additional file 1 : Figure S1), leading to cell death. The strains containing proteins that do not interact (e.g. L103F, I106M) continue to grow normally in the presence of IPTG. b . Dose response for IPTG induction of proteins for RIGI domain binding of H5N1 and H3N2 NS1 L103 and I106 mutants as well as H1N1 and H3N2 wt NS1 proteins. RTHS constructs that possessed each of the wt H5N1 (A/HK/156/1997), H3N2 (A/HK/1/68) and H1N1 (/Brevig Mission/1/1918) or indicated 103 and 106 mutant for the H5N1 and H3N2 viruses were tested for survival under selective medium on induction with 0, 5, 10, 25 and 50 μM IPTG. The number of surviving bacterial colonies were determined by serial dilution as shown in panel A and plotted as bar graphs. NS1 proteins that do not bind the indicated RIG-I domain baits (CARD, helicase and RD) were not reduced in survival relative to the non-induced controls (0 μM IPTG).

    Techniques Used: Binding Assay, Expressing, Functional Assay, Construct, Mutagenesis, Serial Dilution

    Virulence is increased by each of the 103L and 106I NS1 mutations in the H5N1- NS gene on human and mouse adapted virus backbones as well as for 103S and 106I PR8 NS1 gene mutations in PR8 virus. a and b . Groups of 3 CD-1 mice were infected intranasally with 5 × 10 6 pfu of rHK viruses possessing wt (103L + 106I) or mutant H5N1 NS1 genes that differed due to the indicated mutations at positions 103 and 106. c and d . Groups of 3 CD-1 mice were infected intranasally with 1 × 10 4 pfu with the different rPR8 viruses possessing wt (103L + 106I) or mutant H5N1 NS1 genes that differed due to the indicated mutations at positions 103 and 106. e and f , Groups of 5 BALB/c mice were infected intranasally with 1 × 10 4 pfu with wt rPR8 or mutants that differed due to the indicated mutations at positions 103 and 106. The percent of body weight loss was calculated as the mice body weight loss was recorded daily throughout the whole course of the experiment. Values are shown as average +/− standard deviation (*p
    Figure Legend Snippet: Virulence is increased by each of the 103L and 106I NS1 mutations in the H5N1- NS gene on human and mouse adapted virus backbones as well as for 103S and 106I PR8 NS1 gene mutations in PR8 virus. a and b . Groups of 3 CD-1 mice were infected intranasally with 5 × 10 6 pfu of rHK viruses possessing wt (103L + 106I) or mutant H5N1 NS1 genes that differed due to the indicated mutations at positions 103 and 106. c and d . Groups of 3 CD-1 mice were infected intranasally with 1 × 10 4 pfu with the different rPR8 viruses possessing wt (103L + 106I) or mutant H5N1 NS1 genes that differed due to the indicated mutations at positions 103 and 106. e and f , Groups of 5 BALB/c mice were infected intranasally with 1 × 10 4 pfu with wt rPR8 or mutants that differed due to the indicated mutations at positions 103 and 106. The percent of body weight loss was calculated as the mice body weight loss was recorded daily throughout the whole course of the experiment. Values are shown as average +/− standard deviation (*p

    Techniques Used: Mouse Assay, Infection, Mutagenesis, Standard Deviation

    2) Product Images from "Epigallocatechin-3-gallate (EGCG) protects against chromate-induced toxicity in vitro"

    Article Title: Epigallocatechin-3-gallate (EGCG) protects against chromate-induced toxicity in vitro

    Journal: Toxicology and Applied Pharmacology

    doi: 10.1016/j.taap.2011.10.018

    EGCG reduces Cr(VI)-induced cytotoxicity. A, BEAS-2B cells were exposed to 10 μM Cr(VI) and increasing concentrations of EGCG (5–100 μM) for 24 h. MTT assay showed EGCG dose-dependently increased cell viability in Cr(VI)-treated
    Figure Legend Snippet: EGCG reduces Cr(VI)-induced cytotoxicity. A, BEAS-2B cells were exposed to 10 μM Cr(VI) and increasing concentrations of EGCG (5–100 μM) for 24 h. MTT assay showed EGCG dose-dependently increased cell viability in Cr(VI)-treated

    Techniques Used: MTT Assay

    EGCG inhibits Cr(VI)-induced apoptosis. BEAS-2B cells were treated with 10 μM Cr(VI) and increasing concentrations of EGCG (5–25 μM) for 24 h. A, The cells were collected and stained with propidium iodide. DNA content was analyzed
    Figure Legend Snippet: EGCG inhibits Cr(VI)-induced apoptosis. BEAS-2B cells were treated with 10 μM Cr(VI) and increasing concentrations of EGCG (5–25 μM) for 24 h. A, The cells were collected and stained with propidium iodide. DNA content was analyzed

    Techniques Used: Staining

    EGCG inhibits Cr(VI)-induced intracellular ROS generation. A, BEAS-2B cells were simultaneously treated with Cr(VI) and EGCG for 2 h and fluorescence micrographs were taken. (a) negative control, (b) positive control (100 μM H 2 O 2 ), (c) 5 μM
    Figure Legend Snippet: EGCG inhibits Cr(VI)-induced intracellular ROS generation. A, BEAS-2B cells were simultaneously treated with Cr(VI) and EGCG for 2 h and fluorescence micrographs were taken. (a) negative control, (b) positive control (100 μM H 2 O 2 ), (c) 5 μM

    Techniques Used: Fluorescence, Negative Control, Positive Control

    Confirmation of expression levels of selected genes by quantitative RT-PCR. BEAS-2B cells were treated with 10 μM Cr(VI) in the presence of absence of 25 μM EGCG for 24 h. Total RNA was extracted and expression levels of (a) EGR1, (b)
    Figure Legend Snippet: Confirmation of expression levels of selected genes by quantitative RT-PCR. BEAS-2B cells were treated with 10 μM Cr(VI) in the presence of absence of 25 μM EGCG for 24 h. Total RNA was extracted and expression levels of (a) EGR1, (b)

    Techniques Used: Expressing, Quantitative RT-PCR

    3) Product Images from "Engineered Zinc-Finger Proteins Can Compensate Genetic Haploinsufficiency by Transcriptional Activation of the Wild-Type Allele: Application to Willams-Beuren Syndrome and Supravalvular Aortic Stenosis"

    Article Title: Engineered Zinc-Finger Proteins Can Compensate Genetic Haploinsufficiency by Transcriptional Activation of the Wild-Type Allele: Application to Willams-Beuren Syndrome and Supravalvular Aortic Stenosis

    Journal: Human Gene Therapy

    doi: 10.1089/hum.2011.201

    Validation of ELN -ZFP clones. (A) HEK293 cells were transiently transfected with plasmids encoding select ELN -ZFPs and the indicated controls. Total RNA was harvested 48 hours later and q-RT-PCR performed for elastin, VEGF-A, and HIF-1α. q-RT-PCR
    Figure Legend Snippet: Validation of ELN -ZFP clones. (A) HEK293 cells were transiently transfected with plasmids encoding select ELN -ZFPs and the indicated controls. Total RNA was harvested 48 hours later and q-RT-PCR performed for elastin, VEGF-A, and HIF-1α. q-RT-PCR

    Techniques Used: Transfection, Reverse Transcription Polymerase Chain Reaction

    4) Product Images from "A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples"

    Article Title: A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples

    Journal: BMC Genomics

    doi: 10.1186/1471-2164-15-879

    Exon expression and gene expression. Calculation of exon expression versus gene expression using the standard splicing index and the residual regression score proposed in this work. (A) Plot of the exon expression signal versus the gene expression signal of gene RGN measured in 11 human tissue samples by exon microarrays (3 replicates per sample). The exon signal is calculated using the probes that map to the specific exon ENSE00001527616 and the gene signal is calculated using the probes that map to the common conserved exons included in the long transcripts of the gene. A linear regression is applied to the data to calculate the expression of the gene-exon pair. The 3 samples corresponding to cerebellum (labeled as “cer”) are placed in a circle to show that the average expression of these samples shows a significant deviation from the linear regression calculated for the whole gene. (B) Expression signal profile of gene RGN (ENSG00000130988) across the 33 samples (red line with dots) compared to the profile of exon ENSE00001527616 (black line) and the profiles of the rest of the exons (grey lines). (C) Plot of the residual regression scores calculated for each sample for the gene-exon pair ENSG00000130988-ENSE00001527616. (D) Plot of the splicing index es calculated for each sample for the gene-exon pair ENSG00000130988-ENSE00001527616.
    Figure Legend Snippet: Exon expression and gene expression. Calculation of exon expression versus gene expression using the standard splicing index and the residual regression score proposed in this work. (A) Plot of the exon expression signal versus the gene expression signal of gene RGN measured in 11 human tissue samples by exon microarrays (3 replicates per sample). The exon signal is calculated using the probes that map to the specific exon ENSE00001527616 and the gene signal is calculated using the probes that map to the common conserved exons included in the long transcripts of the gene. A linear regression is applied to the data to calculate the expression of the gene-exon pair. The 3 samples corresponding to cerebellum (labeled as “cer”) are placed in a circle to show that the average expression of these samples shows a significant deviation from the linear regression calculated for the whole gene. (B) Expression signal profile of gene RGN (ENSG00000130988) across the 33 samples (red line with dots) compared to the profile of exon ENSE00001527616 (black line) and the profiles of the rest of the exons (grey lines). (C) Plot of the residual regression scores calculated for each sample for the gene-exon pair ENSG00000130988-ENSE00001527616. (D) Plot of the splicing index es calculated for each sample for the gene-exon pair ENSG00000130988-ENSE00001527616.

    Techniques Used: Expressing, Labeling

    5) Product Images from "The Heterotrimeric Laminin Coiled-Coil Domain Exerts Anti-Adhesive Effects and Induces a Pro-Invasive Phenotype"

    Article Title: The Heterotrimeric Laminin Coiled-Coil Domain Exerts Anti-Adhesive Effects and Induces a Pro-Invasive Phenotype

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0039097

    Representative gelatin zymogram showing MMP9 and MMP2 activities in HT1080 cells were cultured under serum free conditions for 72 hours under substrate-independent conditions on uncoated wells (1) or on LM111 (2) or rLCC111 (3) coated wells (A). Densitometric evaluation of MMP-9 (B) and latent MMP-2 (C).
    Figure Legend Snippet: Representative gelatin zymogram showing MMP9 and MMP2 activities in HT1080 cells were cultured under serum free conditions for 72 hours under substrate-independent conditions on uncoated wells (1) or on LM111 (2) or rLCC111 (3) coated wells (A). Densitometric evaluation of MMP-9 (B) and latent MMP-2 (C).

    Techniques Used: Cell Culture

    FACS profiles and representative microscopy images of HT1080 cells labeled with LM111 (A, C) or rLC111 (B, D), followed by incubation with rabbit anti-laminin antibody for the detection of LM111 (green line in FACS histogram A, and C) or anti-His mAb for the detection of rLC111 (green line in FACS histogram B, and D). To rule out the binding of anti-laminin antibody to endogenous laminin, HT1080 cells were incubated with the anti-laminin antibody in the absence of added LM111 (blue line in FACS histogram A, and inset C). A similar control was performed with the anti-His mAb in the absence of added rLC111 (blue line in FACS histogram B, and inset D).
    Figure Legend Snippet: FACS profiles and representative microscopy images of HT1080 cells labeled with LM111 (A, C) or rLC111 (B, D), followed by incubation with rabbit anti-laminin antibody for the detection of LM111 (green line in FACS histogram A, and C) or anti-His mAb for the detection of rLC111 (green line in FACS histogram B, and D). To rule out the binding of anti-laminin antibody to endogenous laminin, HT1080 cells were incubated with the anti-laminin antibody in the absence of added LM111 (blue line in FACS histogram A, and inset C). A similar control was performed with the anti-His mAb in the absence of added rLC111 (blue line in FACS histogram B, and inset D).

    Techniques Used: FACS, Microscopy, Labeling, Incubation, Binding Assay

    rLCC111 substrates do not support cell attachment. Adhesion of HT0180 cells to plastic-coated LM111 or rLCC111 (ranging from 0.08 to 20 μg/ml), or BSA was measured by bioluminescence. (A). Data are plotted as the log of fold change in adhesion relative to BSA. The coating efficiency of LM111 and rLCC111 was monitored by ELISA using a polyclonal anti-laminin antibody (B). Soluble rLCC111 (5 to 20 mg/ml) inhibits adhesion of HT1080 cells (C) to plastic immobilized intact LM111 (10 mg/ml). Data shown are from a representative experiment out of three independent ones. (*, p
    Figure Legend Snippet: rLCC111 substrates do not support cell attachment. Adhesion of HT0180 cells to plastic-coated LM111 or rLCC111 (ranging from 0.08 to 20 μg/ml), or BSA was measured by bioluminescence. (A). Data are plotted as the log of fold change in adhesion relative to BSA. The coating efficiency of LM111 and rLCC111 was monitored by ELISA using a polyclonal anti-laminin antibody (B). Soluble rLCC111 (5 to 20 mg/ml) inhibits adhesion of HT1080 cells (C) to plastic immobilized intact LM111 (10 mg/ml). Data shown are from a representative experiment out of three independent ones. (*, p

    Techniques Used: Cell Attachment Assay, Enzyme-linked Immunosorbent Assay

    Morphology of HT1080 cells cultured on tissue culture plates coated with BSA, intact LM111 or rLCC111 (10 mg/ml). Cells were allowed to attach for 6 hours, followed by fixation and staining with Alexa Fluor 594 phalloidin (A). Scale bar is 10 µm. Spread and non-spread cells were counted and percentages of non-spread cells are indicated (B). Spread cells were defined as large cells with extensive visible lamellipodia, whereas non-spread cells were defined as round cells with little or no membrane protrusions. Spread and non-spread cells were counted in four high-power fields and represented as mean±SD for each condition and time point. The data were evaluated by t test and were considered to be statistically significant when p ≤0.05. (*, p
    Figure Legend Snippet: Morphology of HT1080 cells cultured on tissue culture plates coated with BSA, intact LM111 or rLCC111 (10 mg/ml). Cells were allowed to attach for 6 hours, followed by fixation and staining with Alexa Fluor 594 phalloidin (A). Scale bar is 10 µm. Spread and non-spread cells were counted and percentages of non-spread cells are indicated (B). Spread cells were defined as large cells with extensive visible lamellipodia, whereas non-spread cells were defined as round cells with little or no membrane protrusions. Spread and non-spread cells were counted in four high-power fields and represented as mean±SD for each condition and time point. The data were evaluated by t test and were considered to be statistically significant when p ≤0.05. (*, p

    Techniques Used: Cell Culture, Staining

    6) Product Images from "Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits"

    Article Title: Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits

    Journal: American Journal of Human Genetics

    doi: 10.1016/j.ajhg.2017.02.003

    Work Flow and Results Summary 42,271 SNPs associated with 1,960 traits were obtained from GRASP (at p ≤ 5 × 10 −8 ). Whole blood samples were collected from 5,257 FHS participants. Genome-wide genotyping and mRNA expression levels were assayed. We correlated 39,165 GWAS SNPs (after filtering) with expression levels of 17,873 genes to identify expression quantitative trait loci (eQTLs). For SNPs having both local ( cis ) and remote ( trans ) regulation effects, we then tested whether the effect of trans -eQTLs was mediated through cis -eGenes. Finally, integrating genotype, gene expression, and phenotype data, we conducted causal inference testing to identify causal variants for eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, fasting blood glucose).
    Figure Legend Snippet: Work Flow and Results Summary 42,271 SNPs associated with 1,960 traits were obtained from GRASP (at p ≤ 5 × 10 −8 ). Whole blood samples were collected from 5,257 FHS participants. Genome-wide genotyping and mRNA expression levels were assayed. We correlated 39,165 GWAS SNPs (after filtering) with expression levels of 17,873 genes to identify expression quantitative trait loci (eQTLs). For SNPs having both local ( cis ) and remote ( trans ) regulation effects, we then tested whether the effect of trans -eQTLs was mediated through cis -eGenes. Finally, integrating genotype, gene expression, and phenotype data, we conducted causal inference testing to identify causal variants for eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, fasting blood glucose).

    Techniques Used: Flow Cytometry, Genome Wide, Expressing, GWAS

    7) Product Images from "The miR-183 family cluster alters zinc homeostasis in benign prostate cells, organoids and prostate cancer xenografts"

    Article Title: The miR-183 family cluster alters zinc homeostasis in benign prostate cells, organoids and prostate cancer xenografts

    Journal: Scientific Reports

    doi: 10.1038/s41598-017-07979-y

    miR-183-FC expression lowered intra-tumoural zinc and increased tumour size in vivo . ( A ) Expression of miRs-183, 96 and 182 in RWPE2 prostate cancer cells compared to benign RWPE1 by RT-qPCR. Relative quantity to RWPE1 cells and normalized to RNU44. ( B ) RWPE2 cells were transduced with CTRL or 183FC lentivirus and FACS sorted. ( C ) Absolute quantitation of miRs-183, 96 and 182 by RT-qPCR analysis, and ( D ) respective reduction of miR-specific luc-3′ UTR plasmids compared to empty vector (EV) after 24 hours in RWPE2-CTRL and RWPE2-183FC cells (mean and SEM shown, n = 2). ( E ) hZIP1 gene expression normalized to HPRT in CTRL and 183FC RWPE2 cells. ( F ) 48 hour cell proliferation assay comparison between CTRL and 183FC RWPE2 cells in vitro . Bar graph shows mean with SEM for n = 3 experiments. ( G ) tumor volume of RWPE2-CTRL and 183FC xenografts in nude mice; n = 3 grafts for each cell type. Mean with SEM at each week. *p
    Figure Legend Snippet: miR-183-FC expression lowered intra-tumoural zinc and increased tumour size in vivo . ( A ) Expression of miRs-183, 96 and 182 in RWPE2 prostate cancer cells compared to benign RWPE1 by RT-qPCR. Relative quantity to RWPE1 cells and normalized to RNU44. ( B ) RWPE2 cells were transduced with CTRL or 183FC lentivirus and FACS sorted. ( C ) Absolute quantitation of miRs-183, 96 and 182 by RT-qPCR analysis, and ( D ) respective reduction of miR-specific luc-3′ UTR plasmids compared to empty vector (EV) after 24 hours in RWPE2-CTRL and RWPE2-183FC cells (mean and SEM shown, n = 2). ( E ) hZIP1 gene expression normalized to HPRT in CTRL and 183FC RWPE2 cells. ( F ) 48 hour cell proliferation assay comparison between CTRL and 183FC RWPE2 cells in vitro . Bar graph shows mean with SEM for n = 3 experiments. ( G ) tumor volume of RWPE2-CTRL and 183FC xenografts in nude mice; n = 3 grafts for each cell type. Mean with SEM at each week. *p

    Techniques Used: Expressing, In Vivo, Quantitative RT-PCR, Transduction, FACS, Quantitation Assay, Plasmid Preparation, Proliferation Assay, In Vitro, Mouse Assay

    ZIP1 mRNA, hZIP1 protein and zinc levels were lower in miR-183-FC cells. ( A ) hZIP1 mRNA gene expression measured by RT-qPCR in RWPE1-CTRL and RWPE1-183FC cells. ( B ) ZIP1 protein levels measured by immunoblot and quantified. ( C ) Chromogenic zinc assay in RWPE1-CTRL and 183FC cells (n = 3 experiments). Mean shown with SEM. ( D ) Zinquin (blue) fluorescence in RWPE1-CTRL and RWPE1-183FC cells was imaged with confocal microscopy. Naïve RWPE1 cells were mixed with GFP+ cells. Arrows indicate GFP+ transduced RWPE1 cells. ( E ) Zinquin intensity quantified per cell by inForm™ image analysis in RWPE1-CTRL and RWPE1-183FC cells. N = 3 experiments were analyzed as percentage of CTRL mean per experiment. Data from all 3 experiments were analyzed together by Mann-Whitney nonparametric test and are shown as boxplots with mean (line), 25–75% (box) and 95% confidence intervals (whiskers) and individual cell outliers. *p
    Figure Legend Snippet: ZIP1 mRNA, hZIP1 protein and zinc levels were lower in miR-183-FC cells. ( A ) hZIP1 mRNA gene expression measured by RT-qPCR in RWPE1-CTRL and RWPE1-183FC cells. ( B ) ZIP1 protein levels measured by immunoblot and quantified. ( C ) Chromogenic zinc assay in RWPE1-CTRL and 183FC cells (n = 3 experiments). Mean shown with SEM. ( D ) Zinquin (blue) fluorescence in RWPE1-CTRL and RWPE1-183FC cells was imaged with confocal microscopy. Naïve RWPE1 cells were mixed with GFP+ cells. Arrows indicate GFP+ transduced RWPE1 cells. ( E ) Zinquin intensity quantified per cell by inForm™ image analysis in RWPE1-CTRL and RWPE1-183FC cells. N = 3 experiments were analyzed as percentage of CTRL mean per experiment. Data from all 3 experiments were analyzed together by Mann-Whitney nonparametric test and are shown as boxplots with mean (line), 25–75% (box) and 95% confidence intervals (whiskers) and individual cell outliers. *p

    Techniques Used: Expressing, Quantitative RT-PCR, Zinc Assay, Fluorescence, Confocal Microscopy, MANN-WHITNEY

    Overexpression of 183FC alters gene expression in RWPE1 and regulates motility and adhesion of prostate cells. ( A ) Heatmap of suppressed genes between RWPE1-CTRL and RWPE1-183FC cells. Affymetrix HT 1.0 Arrays were run on biological triplicates of lentivirus transduced RWPE1 cells sorted for GFP expression. Log 2 of the gene expression is shown and grouped by gene function. GSEA and DAVID Pathways are in shown in Supplemental Table 1 . Full data were deposited into GEO (GSE99134). ( B ) Adhesion of cells at 30 minutes for RWPE1-CTRL, RWPE1-183FC, RWPE2-CTRL, RWPE2-183FC, PC3-CTRL and PC3-183KD. Bar graph shows mean and SEM for n = 4. ( C ) Migration of PC3-CTRL and PC3-183KD by scratch assay shown as bar graph for mean and SEM for n = 4, and, ( D ) Representative images of the scratch closure. ( E ) Respective levels of miR-specific luc-3′ UTR plasmids compared to empty vector (EV) after 24 hours in PC3-CTRL and PC3-183KD cells. Mean and SEM are shown, (n = 2). Student’s paired 2-sided t-test, *p
    Figure Legend Snippet: Overexpression of 183FC alters gene expression in RWPE1 and regulates motility and adhesion of prostate cells. ( A ) Heatmap of suppressed genes between RWPE1-CTRL and RWPE1-183FC cells. Affymetrix HT 1.0 Arrays were run on biological triplicates of lentivirus transduced RWPE1 cells sorted for GFP expression. Log 2 of the gene expression is shown and grouped by gene function. GSEA and DAVID Pathways are in shown in Supplemental Table 1 . Full data were deposited into GEO (GSE99134). ( B ) Adhesion of cells at 30 minutes for RWPE1-CTRL, RWPE1-183FC, RWPE2-CTRL, RWPE2-183FC, PC3-CTRL and PC3-183KD. Bar graph shows mean and SEM for n = 4. ( C ) Migration of PC3-CTRL and PC3-183KD by scratch assay shown as bar graph for mean and SEM for n = 4, and, ( D ) Representative images of the scratch closure. ( E ) Respective levels of miR-specific luc-3′ UTR plasmids compared to empty vector (EV) after 24 hours in PC3-CTRL and PC3-183KD cells. Mean and SEM are shown, (n = 2). Student’s paired 2-sided t-test, *p

    Techniques Used: Over Expression, Expressing, Migration, Wound Healing Assay, Plasmid Preparation

    Overexpression of the miR-183 family cluster in benign prostate epithelial cells. ( A ) The gene for the miR-183 family cluster was isolated from male genomic DNA using nested PCR and cloned into CD511B-1 Lentiviral plasmid. ( B ) Sorting of GFP+ RWPE1-CTRL and RWPE1-183FC cells for homogeneous polyclonal population. ( C ) Expression of mature miRs-183, -96 and -182 by RT-qPCR in RWPE1 cells. Absolute quantitation from a standard curve and normalized to RNU44. Mean of N = 6 shown with SEM. ( D ) luciferase levels of plasmids containing the miR consensus sequences in the 3′ UTR transiently transfected in RWPE1-CTRL and RWPE1-183FC. Graphs show mean data −/+ SEM (n = 2) relative to empty vector without miR sites in the 3′ UTR (EV). *p
    Figure Legend Snippet: Overexpression of the miR-183 family cluster in benign prostate epithelial cells. ( A ) The gene for the miR-183 family cluster was isolated from male genomic DNA using nested PCR and cloned into CD511B-1 Lentiviral plasmid. ( B ) Sorting of GFP+ RWPE1-CTRL and RWPE1-183FC cells for homogeneous polyclonal population. ( C ) Expression of mature miRs-183, -96 and -182 by RT-qPCR in RWPE1 cells. Absolute quantitation from a standard curve and normalized to RNU44. Mean of N = 6 shown with SEM. ( D ) luciferase levels of plasmids containing the miR consensus sequences in the 3′ UTR transiently transfected in RWPE1-CTRL and RWPE1-183FC. Graphs show mean data −/+ SEM (n = 2) relative to empty vector without miR sites in the 3′ UTR (EV). *p

    Techniques Used: Over Expression, Isolation, Nested PCR, Clone Assay, Plasmid Preparation, Expressing, Quantitative RT-PCR, Quantitation Assay, Luciferase, Transfection

    8) Product Images from "Medulloblastoma subgroups remain stable across primary and metastatic compartments"

    Article Title: Medulloblastoma subgroups remain stable across primary and metastatic compartments

    Journal: Acta neuropathologica

    doi: 10.1007/s00401-015-1389-0

    (a) Unsupervised hierarchical clustering of human 2.0 exon array (Affymetrix GeneChip Human Gene 2.0 ST Array) expression data from 22 medulloblastoma samples (9 matched primary-metastasis patients) using 1,000 most differentially expressed genes. (b)
    Figure Legend Snippet: (a) Unsupervised hierarchical clustering of human 2.0 exon array (Affymetrix GeneChip Human Gene 2.0 ST Array) expression data from 22 medulloblastoma samples (9 matched primary-metastasis patients) using 1,000 most differentially expressed genes. (b)

    Techniques Used: Expressing

    9) Product Images from "ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks"

    Article Title: ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks

    Journal: Nature neuroscience

    doi: 10.1038/nn.4345

    spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values
    Figure Legend Snippet: spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values

    Techniques Used: Preserving

    10) Product Images from "Characterization of a P-Rex1 gene signature in breast cancer cells"

    Article Title: Characterization of a P-Rex1 gene signature in breast cancer cells

    Journal: Oncotarget

    doi: 10.18632/oncotarget.10285

    Changes in gene expression induced by HRG in T-47D cells T-47D cells were treated with HRG (20 ng/ml) or vehicle for 6 h. Total RNA from three replicates was extracted and reverse transcribed to cDNA. Gene expression profiling was carried out using an Affymetrix GeneChip Human Gene 1.0 ST Array. ( A ) Heatmap of the microarray data showing changes in gene expression by HRG ( p -values
    Figure Legend Snippet: Changes in gene expression induced by HRG in T-47D cells T-47D cells were treated with HRG (20 ng/ml) or vehicle for 6 h. Total RNA from three replicates was extracted and reverse transcribed to cDNA. Gene expression profiling was carried out using an Affymetrix GeneChip Human Gene 1.0 ST Array. ( A ) Heatmap of the microarray data showing changes in gene expression by HRG ( p -values

    Techniques Used: Expressing, Microarray

    Effect of P-Rex1 RNAi on the expression of genes regulated by HRG T-47D cells were transfected with two different P-Rex1 RNAi sequences ( P-Rex #1 and P-Rex #2 ), or a non-target control RNAi ( NTC ). After 16 h, cells were serum starved for 48 h and stimulated with HRG (20 ng/ml) or vehicle for 6 h. Gene expression profiling was carried out using an Affymetrix GeneChip Human Gene 1.0 ST Array. P-Rex1-regulated genes were defined as those in which both P-Rex1 RNAi duplexes (#1 and #2) caused a statistically significant change ( p
    Figure Legend Snippet: Effect of P-Rex1 RNAi on the expression of genes regulated by HRG T-47D cells were transfected with two different P-Rex1 RNAi sequences ( P-Rex #1 and P-Rex #2 ), or a non-target control RNAi ( NTC ). After 16 h, cells were serum starved for 48 h and stimulated with HRG (20 ng/ml) or vehicle for 6 h. Gene expression profiling was carried out using an Affymetrix GeneChip Human Gene 1.0 ST Array. P-Rex1-regulated genes were defined as those in which both P-Rex1 RNAi duplexes (#1 and #2) caused a statistically significant change ( p

    Techniques Used: Expressing, Transfection

    11) Product Images from "Powerful Complex Immunoadjuvant Based on Synergistic Effect of Combined TLR4 and NOD2 Activation Significantly Enhances Magnitude of Humoral and Cellular Adaptive Immune Responses"

    Article Title: Powerful Complex Immunoadjuvant Based on Synergistic Effect of Combined TLR4 and NOD2 Activation Significantly Enhances Magnitude of Humoral and Cellular Adaptive Immune Responses

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0155650

    Combination of MPLA and MDP strongly enhances the transcriptional response in THP-1 cells in comparison to individual PRR agonists. (A) Venn diagram demonstrating overlap in the sets of genes found to be MDP-, MPLA- and/or MDP+MPLA-induced in THP-1 cells. Cells were treated with MDP (20μg/ml) and MPLA (1μg/ml) individually or in combination or left unstimulated. RNA was harvested after 3 h and analyzed by hybridization to Affymetrix Human Gene 1.0 ST genechip microarrays. Genes induced by MDP (white circle), MPLA (gray circle) or their combination (black circle) by at least 3-fold over untreated cells are shown. (B) List of MDP+MPLA-induced genes with potentiated expression in comparison to gene expression levels in untreated cells and cells treated with either MPLA or MDP alone. Cells were left untreated or treated with MDP (20μg/ml) and MPLA (1μg/ml) individually or in combination. RNA was harvested after 3 h and analyzed by hybridization to Affymetrix Human Gene 1.0 ST Genechip microarrays. The figure lists 72 genes that showed potentiated expression with MDP+MPLA treatment compared to MPLA or MDP alone (potentiated = fold induction of gene expression level with combined treatment over the untreated control was greater than the sum of the fold induction seen with MPLA alone and MDP alone). Statistical significance was determined by a random-variance t-test with P
    Figure Legend Snippet: Combination of MPLA and MDP strongly enhances the transcriptional response in THP-1 cells in comparison to individual PRR agonists. (A) Venn diagram demonstrating overlap in the sets of genes found to be MDP-, MPLA- and/or MDP+MPLA-induced in THP-1 cells. Cells were treated with MDP (20μg/ml) and MPLA (1μg/ml) individually or in combination or left unstimulated. RNA was harvested after 3 h and analyzed by hybridization to Affymetrix Human Gene 1.0 ST genechip microarrays. Genes induced by MDP (white circle), MPLA (gray circle) or their combination (black circle) by at least 3-fold over untreated cells are shown. (B) List of MDP+MPLA-induced genes with potentiated expression in comparison to gene expression levels in untreated cells and cells treated with either MPLA or MDP alone. Cells were left untreated or treated with MDP (20μg/ml) and MPLA (1μg/ml) individually or in combination. RNA was harvested after 3 h and analyzed by hybridization to Affymetrix Human Gene 1.0 ST Genechip microarrays. The figure lists 72 genes that showed potentiated expression with MDP+MPLA treatment compared to MPLA or MDP alone (potentiated = fold induction of gene expression level with combined treatment over the untreated control was greater than the sum of the fold induction seen with MPLA alone and MDP alone). Statistical significance was determined by a random-variance t-test with P

    Techniques Used: Hybridization, Expressing

    12) Product Images from "Shambhala: a platform-agnostic data harmonizer for gene expression data"

    Article Title: Shambhala: a platform-agnostic data harmonizer for gene expression data

    Journal: BMC Bioinformatics

    doi: 10.1186/s12859-019-2641-8

    Averaged expression profile for samples of type A before (upper row, panels  a  to  d ) and after (lower row, panels  e  to  h ) the Shambhala harmonization. The profiles were obtained using the platforms Illumina HiSeq 2000, GPL11154 (panels  a  and  e ), Illumina HumanHT-12 V4.0 expression beadchip, GPL10558 ( b  and  f ), Affymetrix Human Gene 2.0 ST Array, GPL17930 ( c  and  g ), and Affymetrix GeneChip PrimeView Human Gene Expression Array, GPL16043 ( d  and  h )
    Figure Legend Snippet: Averaged expression profile for samples of type A before (upper row, panels a to d ) and after (lower row, panels e to h ) the Shambhala harmonization. The profiles were obtained using the platforms Illumina HiSeq 2000, GPL11154 (panels a and e ), Illumina HumanHT-12 V4.0 expression beadchip, GPL10558 ( b and f ), Affymetrix Human Gene 2.0 ST Array, GPL17930 ( c and g ), and Affymetrix GeneChip PrimeView Human Gene Expression Array, GPL16043 ( d and h )

    Techniques Used: Expressing

    13) Product Images from "VEGF‐B signaling impairs endothelial glucose transcytosis by decreasing membrane cholesterol content"

    Article Title: VEGF‐B signaling impairs endothelial glucose transcytosis by decreasing membrane cholesterol content

    Journal: EMBO Reports

    doi: 10.15252/embr.201949343

    VEGF‐B signaling does not change expression of genes involved in endothelial cell metabolism RNA from primary human brain microvascular endothelial cells (HBMEC) stimulated with VEGF‐B 167 , VEGF‐B 186 , or vehicle (Control) for 6 h ( n = 3 cell dishes/condition) were subjected to microarray hybridization using Affymetrix GeneChip ® Human Gene 1.0 ST chips. Shown is a heat map over selected genes involved in intermediary metabolism (listed in Appendix Table S3 ). The three differentially expressed genes in response to VEGF‐B stimulation are indicated with arrow heads.
    Figure Legend Snippet: VEGF‐B signaling does not change expression of genes involved in endothelial cell metabolism RNA from primary human brain microvascular endothelial cells (HBMEC) stimulated with VEGF‐B 167 , VEGF‐B 186 , or vehicle (Control) for 6 h ( n = 3 cell dishes/condition) were subjected to microarray hybridization using Affymetrix GeneChip ® Human Gene 1.0 ST chips. Shown is a heat map over selected genes involved in intermediary metabolism (listed in Appendix Table S3 ). The three differentially expressed genes in response to VEGF‐B stimulation are indicated with arrow heads.

    Techniques Used: Expressing, Microarray, Hybridization

    14) Product Images from "Influenza A/Hong Kong/156/1997(H5N1) virus NS1 gene mutations F103L and M106I both increase IFN antagonism, virulence and cytoplasmic localization but differ in binding to RIG-I and CPSF30"

    Article Title: Influenza A/Hong Kong/156/1997(H5N1) virus NS1 gene mutations F103L and M106I both increase IFN antagonism, virulence and cytoplasmic localization but differ in binding to RIG-I and CPSF30

    Journal: Virology Journal

    doi: 10.1186/1743-422X-10-243

    Linear plot of relative gene expression of host genes between NS1 HK - wt and mutants in human A459 cells.  The host gene expression relative to HK-wt was plotted with the line of best fit for dysregulated genes in human A459 cells shown in Figure   7 a. The slope of each line is indicated relative to the HK-wt line with slope = 1. Insert. A box plot of dysregulated gens from Figure   7 a shown relative to the gene expression of HK-wt relative to mock infected M1 cells.
    Figure Legend Snippet: Linear plot of relative gene expression of host genes between NS1 HK - wt and mutants in human A459 cells. The host gene expression relative to HK-wt was plotted with the line of best fit for dysregulated genes in human A459 cells shown in Figure  7 a. The slope of each line is indicated relative to the HK-wt line with slope = 1. Insert. A box plot of dysregulated gens from Figure  7 a shown relative to the gene expression of HK-wt relative to mock infected M1 cells.

    Techniques Used: Expressing, Infection

    Host gene expression is differentially affected by 103L and 106I mutation in human and mouse cells. Mouse M1 cells and human A459 cells were wither mock infected with PBS of infected with rHK1-wt, or NS1 F103L, M106I, M106V and F103L + M106I mutants at MOI = 2 in triplicate with extraction of total RNA at 8 hpi. Genes that were significantly increased or decreased 2 fold (≥ 2 1 or ≤ 2 -1 ) by Affymetrix microarray analysis relative to mock infected cells for any individual virus were analyzed among the viruses. Host genes are represented in heat maps with red and blue according to with the indicated scales for the log 2 values ( panels a , b and c) . a) Effect of virus infection on gene regulation in mouse M1 cells showing hierarchical cluster analysis of dys regulated genes as well as hierarchical clustering among viruses. b) Effect of virus infection on gene regulation in human A549 cells showing hierarchical clustering of genes and viruses as represented in panel a. Relative to HK-wt the 242 dysregulated genes were significantly upregulated for M106I, M106V and F103L + M106I (** p ≤ 0.01, *** p ≤ 0.001 by t-test) but not F103L (not significantly different (nsd)). c) Transcriptional abundance analysis of genes that are common between human and mouse cells were analyzed as described in panel a. d) Bar graph of up (red bars) and down (blue bars) regulated gene transcripts detected by microarray analysis relative to mock infected M1 and A459 cells infected with the indicated viruses. The number of significantly up and down regulated genes relative to mock infected A549 cells was significantly different for M106I, M106V and F103L + M106I (*p ≤ 0.05 by Chi-squared test), versus HK-wt (reference, r) but not F103L that was not significantly different.
    Figure Legend Snippet: Host gene expression is differentially affected by 103L and 106I mutation in human and mouse cells. Mouse M1 cells and human A459 cells were wither mock infected with PBS of infected with rHK1-wt, or NS1 F103L, M106I, M106V and F103L + M106I mutants at MOI = 2 in triplicate with extraction of total RNA at 8 hpi. Genes that were significantly increased or decreased 2 fold (≥ 2 1 or ≤ 2 -1 ) by Affymetrix microarray analysis relative to mock infected cells for any individual virus were analyzed among the viruses. Host genes are represented in heat maps with red and blue according to with the indicated scales for the log 2 values ( panels a , b and c) . a) Effect of virus infection on gene regulation in mouse M1 cells showing hierarchical cluster analysis of dys regulated genes as well as hierarchical clustering among viruses. b) Effect of virus infection on gene regulation in human A549 cells showing hierarchical clustering of genes and viruses as represented in panel a. Relative to HK-wt the 242 dysregulated genes were significantly upregulated for M106I, M106V and F103L + M106I (** p ≤ 0.01, *** p ≤ 0.001 by t-test) but not F103L (not significantly different (nsd)). c) Transcriptional abundance analysis of genes that are common between human and mouse cells were analyzed as described in panel a. d) Bar graph of up (red bars) and down (blue bars) regulated gene transcripts detected by microarray analysis relative to mock infected M1 and A459 cells infected with the indicated viruses. The number of significantly up and down regulated genes relative to mock infected A549 cells was significantly different for M106I, M106V and F103L + M106I (*p ≤ 0.05 by Chi-squared test), versus HK-wt (reference, r) but not F103L that was not significantly different.

    Techniques Used: Expressing, Mutagenesis, Infection, Microarray

    The 103L and 106I residues in the H5N1- NS gene are associated with increased cytoplasmic localization of NS1 protein in mouse epithelial cells.  Monolayers of mouse epithelial cells were infected with rPR8-H5N1-NS-103L+106I (n=3) and the three mutants rPR8-NS-L103F+106I, rPR8-NS-103L+I106M and rPR8-NS-L103F+I106M (n=2) at MOI=2 and compared to mock uninfected cells. NS1, NP and M1 proteins localization was detected by western blots using rabbit protein specific antibodies. Rabbit anti-tubulin and mouse anti-histone antibodies were used as controls for cytoplasmic and nuclear fractions respectively.  a . The nuclear and cytoplasmic accumulation of NS1 protein is shown for one analysis. The whole cell lysate is designated as “W”, nuclear fraction as “N” and the cytoplsmic fraction as “C”.  b . Western blots showing the H5N1-NS1 protein nuclear and cytoplasmic fractions in parallel for 2–3 replicates of infected M1 cells.
    Figure Legend Snippet: The 103L and 106I residues in the H5N1- NS gene are associated with increased cytoplasmic localization of NS1 protein in mouse epithelial cells. Monolayers of mouse epithelial cells were infected with rPR8-H5N1-NS-103L+106I (n=3) and the three mutants rPR8-NS-L103F+106I, rPR8-NS-103L+I106M and rPR8-NS-L103F+I106M (n=2) at MOI=2 and compared to mock uninfected cells. NS1, NP and M1 proteins localization was detected by western blots using rabbit protein specific antibodies. Rabbit anti-tubulin and mouse anti-histone antibodies were used as controls for cytoplasmic and nuclear fractions respectively. a . The nuclear and cytoplasmic accumulation of NS1 protein is shown for one analysis. The whole cell lysate is designated as “W”, nuclear fraction as “N” and the cytoplsmic fraction as “C”. b . Western blots showing the H5N1-NS1 protein nuclear and cytoplasmic fractions in parallel for 2–3 replicates of infected M1 cells.

    Techniques Used: Infection, Western Blot

    15) Product Images from "Natriuretic peptides promote glucose uptake in a cGMP-dependent manner in human adipocytes"

    Article Title: Natriuretic peptides promote glucose uptake in a cGMP-dependent manner in human adipocytes

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-19619-0

    Human adipose tissue gene expression from microarrays of GC-A ( A ), NPRC ( B ), and the ratio of GC-A -to- NPRC ( C ) in lean versus obese individuals from cohort 2 (n = 56). Correlation between adipose GC-A expression and HOMA-IR ( D ) and de novo lipogenesis measured in isolated adipocytes ( E ). ***p
    Figure Legend Snippet: Human adipose tissue gene expression from microarrays of GC-A ( A ), NPRC ( B ), and the ratio of GC-A -to- NPRC ( C ) in lean versus obese individuals from cohort 2 (n = 56). Correlation between adipose GC-A expression and HOMA-IR ( D ) and de novo lipogenesis measured in isolated adipocytes ( E ). ***p

    Techniques Used: Expressing, Isolation

    16) Product Images from "Exon array analyses across the NCI-60 reveals potential regulation of TOP1 by transcription pausing at guanosine quartets in the first intron"

    Article Title: Exon array analyses across the NCI-60 reveals potential regulation of TOP1 by transcription pausing at guanosine quartets in the first intron

    Journal: Cancer research

    doi: 10.1158/0008-5472.CAN-09-3528

    Estimated TOP1 DNA copy numbers and transcript () levels across the NCI-60, and correlation between the two. A , Mean-centered aCGH intensities and estimated DNA copy number are plotted on the left-hand panel x-axis, and transcript expression
    Figure Legend Snippet: Estimated TOP1 DNA copy numbers and transcript () levels across the NCI-60, and correlation between the two. A , Mean-centered aCGH intensities and estimated DNA copy number are plotted on the left-hand panel x-axis, and transcript expression

    Techniques Used: Expressing

    Variation of mean-centered log 2 TOP1 probe set intensities from Affymetrix GH Exon 1.0 ST microarrays. A , Clustered image map (heat map) for mRNA expression for each of the 21 exons of TOP1 across the NCI-60 cell lines. The cell lines are clustered on
    Figure Legend Snippet: Variation of mean-centered log 2 TOP1 probe set intensities from Affymetrix GH Exon 1.0 ST microarrays. A , Clustered image map (heat map) for mRNA expression for each of the 21 exons of TOP1 across the NCI-60 cell lines. The cell lines are clustered on

    Techniques Used: Expressing

    TOP1 transcript level intensities, z-score distribution in the NCI-60, and exon location of probesets. A , Table of intensity levels for six probesets from the HG-U95, HG-U133, and HG-U133 Plus2 microarrays, with their combined z-score means (presented
    Figure Legend Snippet: TOP1 transcript level intensities, z-score distribution in the NCI-60, and exon location of probesets. A , Table of intensity levels for six probesets from the HG-U95, HG-U133, and HG-U133 Plus2 microarrays, with their combined z-score means (presented

    Techniques Used:

    17) Product Images from "Characterization of a Distinct Population of Circulating Human Non-Adherent Endothelial Forming Cells and Their Recruitment via Intercellular Adhesion Molecule-3"

    Article Title: Characterization of a Distinct Population of Circulating Human Non-Adherent Endothelial Forming Cells and Their Recruitment via Intercellular Adhesion Molecule-3

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0046996

    Gene expression analysis of naEFCs versus HUVEC. In (A), a heat map illustrating the hierarchical clustering of Log2 relative gene expression in 3 separate HUVEC and naEFC samples. In (B), scatter data showing the average gene expression data in naEFCs and HUVEC. The dots represent the gene expression of UCB CD133+ 4 day cultured naEFCs versus HUVEC. The diagonal lines indicate the cut off value of 1.5 fold activation and genes coloured on the basis of expression level (yellow, evenly expressed genes; blue, naEFC upregulated genes; red, naEFC downregulated genes). In (C), ICAM-3 mRNA levels in naEFCs and HUVEC as determined by qPCR with relative gene expression normalised to CycA. Data are expressed as relative fold change (mean ± sem) normalised to HUVEC, n = 3,* p
    Figure Legend Snippet: Gene expression analysis of naEFCs versus HUVEC. In (A), a heat map illustrating the hierarchical clustering of Log2 relative gene expression in 3 separate HUVEC and naEFC samples. In (B), scatter data showing the average gene expression data in naEFCs and HUVEC. The dots represent the gene expression of UCB CD133+ 4 day cultured naEFCs versus HUVEC. The diagonal lines indicate the cut off value of 1.5 fold activation and genes coloured on the basis of expression level (yellow, evenly expressed genes; blue, naEFC upregulated genes; red, naEFC downregulated genes). In (C), ICAM-3 mRNA levels in naEFCs and HUVEC as determined by qPCR with relative gene expression normalised to CycA. Data are expressed as relative fold change (mean ± sem) normalised to HUVEC, n = 3,* p

    Techniques Used: Expressing, Cell Culture, Activation Assay, Real-time Polymerase Chain Reaction

    Vascular properties of naEFCs. In (A), representative dot plots from one experiment show the incorporation of DiI-Ac-LDL and binding of UEA-1-FITC by naEFCs and HUVEC. The percentage of cells double positive for DiI-Ac-LDL uptake and binding of UEA-1-FITC was quantified. * p
    Figure Legend Snippet: Vascular properties of naEFCs. In (A), representative dot plots from one experiment show the incorporation of DiI-Ac-LDL and binding of UEA-1-FITC by naEFCs and HUVEC. The percentage of cells double positive for DiI-Ac-LDL uptake and binding of UEA-1-FITC was quantified. * p

    Techniques Used: Binding Assay

    Surface expression profiling of freshly isolated CD133 + cells, naEFCs and HUVEC. In (A), freshly isolated CD133 + cells were phenotyped for hematopoietic progenitor cell and endothelial cell markers by flow cytometry. In the histograms, the light dotted lines represent unstained cells and the dark lines represent stained cells of one representative experiment from n≥3. In (B), CD133 + enriched cells at 4 days of culture (naEFCs) and HUVEC were more extensively assessed for surface antigen phenotype. The histograms show one representative experiment from n≥3 with the light and dark lines as above. In (C), the pan-leukocyte marker CD45 and the myeloid markers CD11b and CD14 were examined with the light dotted lines representing unstained cells and the dark lines representing stained cells of one representative experiment from n≥3.
    Figure Legend Snippet: Surface expression profiling of freshly isolated CD133 + cells, naEFCs and HUVEC. In (A), freshly isolated CD133 + cells were phenotyped for hematopoietic progenitor cell and endothelial cell markers by flow cytometry. In the histograms, the light dotted lines represent unstained cells and the dark lines represent stained cells of one representative experiment from n≥3. In (B), CD133 + enriched cells at 4 days of culture (naEFCs) and HUVEC were more extensively assessed for surface antigen phenotype. The histograms show one representative experiment from n≥3 with the light and dark lines as above. In (C), the pan-leukocyte marker CD45 and the myeloid markers CD11b and CD14 were examined with the light dotted lines representing unstained cells and the dark lines representing stained cells of one representative experiment from n≥3.

    Techniques Used: Expressing, Isolation, Flow Cytometry, Cytometry, Staining, Marker

    ICAM-3 mediates rolling and adhesion of naEFCs. In (A), still images of Video S1 illustrate the interaction of naEFCs with untreated (left panel), TNFα treated (5 ng/ml for 5 hours, middle and right panels) where naEFCs were pre-treated with an isotype control antibody (middle panel) or an antibody to ICAM-3 (right panel) prior to perfusion over HUVEC at 2 dynes/cm 2 . In (B and C), data of rolling and adherent naEFCs is represented as the mean ± sem per field of view (fov) for n = 3;* p
    Figure Legend Snippet: ICAM-3 mediates rolling and adhesion of naEFCs. In (A), still images of Video S1 illustrate the interaction of naEFCs with untreated (left panel), TNFα treated (5 ng/ml for 5 hours, middle and right panels) where naEFCs were pre-treated with an isotype control antibody (middle panel) or an antibody to ICAM-3 (right panel) prior to perfusion over HUVEC at 2 dynes/cm 2 . In (B and C), data of rolling and adherent naEFCs is represented as the mean ± sem per field of view (fov) for n = 3;* p

    Techniques Used:

    18) Product Images from "Genome-wide analysis of novel splice variants induced by topoisomerase I poisoning shows preferential occurrence in genes encoding splicing factors"

    Article Title: Genome-wide analysis of novel splice variants induced by topoisomerase I poisoning shows preferential occurrence in genes encoding splicing factors

    Journal: Cancer research

    doi: 10.1158/0008-5472.CAN-10-2491

    Validation of the ExonHit results in HCT116 cells treated with CPT (10 μM, 20 h). A , Example of the EIF2S2 gene. Upper panel: schematic gene representation and position of the ExonHit probes (B, C, D, E, F, T) and of the primers used for the RT-PCR
    Figure Legend Snippet: Validation of the ExonHit results in HCT116 cells treated with CPT (10 μM, 20 h). A , Example of the EIF2S2 gene. Upper panel: schematic gene representation and position of the ExonHit probes (B, C, D, E, F, T) and of the primers used for the RT-PCR

    Techniques Used: Cycling Probe Technology, Reverse Transcription Polymerase Chain Reaction

    Description of the ExonHit Array. A , Number of genes and spliced events in ExonHit array. B , Schematic representation of the position of the ExonHit probes for splicing events concerning exon E. C , Probe hybridization profile for novel exon and related
    Figure Legend Snippet: Description of the ExonHit Array. A , Number of genes and spliced events in ExonHit array. B , Schematic representation of the position of the ExonHit probes for splicing events concerning exon E. C , Probe hybridization profile for novel exon and related

    Techniques Used: Hybridization

    19) Product Images from "Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues"

    Article Title: Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues

    Journal: The Journal of Molecular Diagnostics : JMD

    doi: 10.1016/j.jmoldx.2015.02.002

    Genes from the signatures that are represented on each platform were projected onto two principal components and plotted. Colors represent the compared classes and distinct plotting characters represent the technical replicates from the same specimen. A: NuGen + Affymetrix profiles of tumor versus normal signature on prostate samples. Tumor samples are shown in orange and normal samples are shown in blue. B: NanoString profiles of tumor versus normal signature on prostate samples. Tumor samples are shown in orange and normal samples are shown in blue. C: NuGen + Affymetrix profiles of Gleason signature on prostate tumor samples. Gleason 6 samples are shown in blue, Gleason 7 samples are shown in green, and Gleason 8 samples are shown in orange. D: NanoString profiles of Gleason signature on prostate tumor samples. Gleason 6 samples are shown in blue, Gleason 8 samples are shown in orange. E: NuGen + Affymetrix profiles of histology signature on ovarian samples. Clear cell carcinoma samples are shown in blue and serous carcinoma samples are shown in orange. F: NanoString profiles of histology signature on ovarian samples. Clear cell carcinoma samples are shown in blue and serous carcinoma samples are shown in orange. PCA, principal components analysis.
    Figure Legend Snippet: Genes from the signatures that are represented on each platform were projected onto two principal components and plotted. Colors represent the compared classes and distinct plotting characters represent the technical replicates from the same specimen. A: NuGen + Affymetrix profiles of tumor versus normal signature on prostate samples. Tumor samples are shown in orange and normal samples are shown in blue. B: NanoString profiles of tumor versus normal signature on prostate samples. Tumor samples are shown in orange and normal samples are shown in blue. C: NuGen + Affymetrix profiles of Gleason signature on prostate tumor samples. Gleason 6 samples are shown in blue, Gleason 7 samples are shown in green, and Gleason 8 samples are shown in orange. D: NanoString profiles of Gleason signature on prostate tumor samples. Gleason 6 samples are shown in blue, Gleason 8 samples are shown in orange. E: NuGen + Affymetrix profiles of histology signature on ovarian samples. Clear cell carcinoma samples are shown in blue and serous carcinoma samples are shown in orange. F: NanoString profiles of histology signature on ovarian samples. Clear cell carcinoma samples are shown in blue and serous carcinoma samples are shown in orange. PCA, principal components analysis.

    Techniques Used:

    A and B: Bubble chart showing the relationship between the correlations of the gene expression values on the NuGen + Affymetrix and NanoString platforms and the average expression levels of those genes. Each circle represents a gene and the size is proportional to the absolute value of the correlations. Red represents positive correlations and blue represents negative correlations. C and D: Density plots of the observed correlations between the gene expression values on the NuGen + Affymetrix and NanoString platforms (solid lines) and the correlations under the null hypothesis of no association between the expression values measured on the NuGen + Affymetrix and NanoString platforms obtained by permuting sample labels (dashed lines).
    Figure Legend Snippet: A and B: Bubble chart showing the relationship between the correlations of the gene expression values on the NuGen + Affymetrix and NanoString platforms and the average expression levels of those genes. Each circle represents a gene and the size is proportional to the absolute value of the correlations. Red represents positive correlations and blue represents negative correlations. C and D: Density plots of the observed correlations between the gene expression values on the NuGen + Affymetrix and NanoString platforms (solid lines) and the correlations under the null hypothesis of no association between the expression values measured on the NuGen + Affymetrix and NanoString platforms obtained by permuting sample labels (dashed lines).

    Techniques Used: Expressing

    20) Product Images from "The impact of microRNA expression on cellular proliferation"

    Article Title: The impact of microRNA expression on cellular proliferation

    Journal: Human genetics

    doi: 10.1007/s00439-014-1434-4

    Pattern of correlation between miRNA and iGrowth in CEU and YRI. a miR-768-5p is significantly correlated with iGrowth in both CEU ( p = 0.0024) and YRI ( p
    Figure Legend Snippet: Pattern of correlation between miRNA and iGrowth in CEU and YRI. a miR-768-5p is significantly correlated with iGrowth in both CEU ( p = 0.0024) and YRI ( p

    Techniques Used:

    Negative expression correlation of miR-22 and 39 genes. The expression levels of all genes are correlated with iGrowth in YRI samples. miR-22 ranked 5th in association with iGrowth in pooled analysis of CEU and YRI ( p = 1.7 × 10 −6 ). The
    Figure Legend Snippet: Negative expression correlation of miR-22 and 39 genes. The expression levels of all genes are correlated with iGrowth in YRI samples. miR-22 ranked 5th in association with iGrowth in pooled analysis of CEU and YRI ( p = 1.7 × 10 −6 ). The

    Techniques Used: Expressing

    21) Product Images from "Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells"

    Article Title: Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0017982

    Validation of microarray results by quantitative RT-PCR. Total RNA was extracted from two cell lines each of control, Cr_small, and Cr_large group, as well as parental BEAS-2B cells. Expression levels of KRT34, DSC3, PSG2 and RSP4Y were analyzed by quantitative RT-PCR. Relative gene expression level, normalized to 18s rRNA expression, was presented as fold change to the level expressed in Beas-2B cells. Data are mean ± SD (n = 3). The expression value of each gene determined from the microarray data was listed below the corresponding PCR results. The color bar related color code to the expression value determined after quantile normalization and baseline transformation to the median levels of all samples.
    Figure Legend Snippet: Validation of microarray results by quantitative RT-PCR. Total RNA was extracted from two cell lines each of control, Cr_small, and Cr_large group, as well as parental BEAS-2B cells. Expression levels of KRT34, DSC3, PSG2 and RSP4Y were analyzed by quantitative RT-PCR. Relative gene expression level, normalized to 18s rRNA expression, was presented as fold change to the level expressed in Beas-2B cells. Data are mean ± SD (n = 3). The expression value of each gene determined from the microarray data was listed below the corresponding PCR results. The color bar related color code to the expression value determined after quantile normalization and baseline transformation to the median levels of all samples.

    Techniques Used: Microarray, Quantitative RT-PCR, Expressing, Polymerase Chain Reaction, Transformation Assay

    22) Product Images from "Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits"

    Article Title: Dynamic Role of trans Regulation of Gene Expression in Relation to Complex Traits

    Journal: American Journal of Human Genetics

    doi: 10.1016/j.ajhg.2017.02.003

    Work Flow and Results Summary 42,271 SNPs associated with 1,960 traits were obtained from GRASP (at p ≤ 5 × 10 −8 ). Whole blood samples were collected from 5,257 FHS participants. Genome-wide genotyping and mRNA expression levels were assayed. We correlated 39,165 GWAS SNPs (after filtering) with expression levels of 17,873 genes to identify expression quantitative trait loci (eQTLs). For SNPs having both local ( cis ) and remote ( trans ) regulation effects, we then tested whether the effect of trans -eQTLs was mediated through cis -eGenes. Finally, integrating genotype, gene expression, and phenotype data, we conducted causal inference testing to identify causal variants for eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, fasting blood glucose).
    Figure Legend Snippet: Work Flow and Results Summary 42,271 SNPs associated with 1,960 traits were obtained from GRASP (at p ≤ 5 × 10 −8 ). Whole blood samples were collected from 5,257 FHS participants. Genome-wide genotyping and mRNA expression levels were assayed. We correlated 39,165 GWAS SNPs (after filtering) with expression levels of 17,873 genes to identify expression quantitative trait loci (eQTLs). For SNPs having both local ( cis ) and remote ( trans ) regulation effects, we then tested whether the effect of trans -eQTLs was mediated through cis -eGenes. Finally, integrating genotype, gene expression, and phenotype data, we conducted causal inference testing to identify causal variants for eight cardiometabolic traits (BMI, systolic and diastolic blood pressure, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, fasting blood glucose).

    Techniques Used: Flow Cytometry, Genome Wide, Expressing, GWAS

    23) Product Images from "Systems-Level Comparison of Host-Responses Elicited by Avian H5N1 and Seasonal H1N1 Influenza Viruses in Primary Human Macrophages"

    Article Title: Systems-Level Comparison of Host-Responses Elicited by Avian H5N1 and Seasonal H1N1 Influenza Viruses in Primary Human Macrophages

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0008072

    Components of the RIG-I, TNF and type I IFN pathways are up-regulated in response to H5N1 to greater extent than H1N1. Viral ligands are shown as diamonds, genes/proteins as circles, and complexes or pathways as rectangles. Green arrows indicate activation, red T-bars represent inhibition, black lines indicate binding, and blue lines indicate stimulation of gene expression. For clarity, blue lines feeding back to upstream pathway components were removed; many of these upstream components, however, are regulated by type I IFN and/or NFκB. The colour of a node reflected the H5N1:H1N1 expression ratio: blue nodes were not significantly differentially expressed in response to either virus, pink/red nodes were up-regulated more in response to H5N1 than H1N1 (red = > 1.5-fold more in response to H5N1, pink = 1.0-1.49-fold higher in response to H5N1), and the green node was down-regulated to a greater extent in response to H5N1. Larger nodes had a fold-change value of > 10 in H5N1 infection.
    Figure Legend Snippet: Components of the RIG-I, TNF and type I IFN pathways are up-regulated in response to H5N1 to greater extent than H1N1. Viral ligands are shown as diamonds, genes/proteins as circles, and complexes or pathways as rectangles. Green arrows indicate activation, red T-bars represent inhibition, black lines indicate binding, and blue lines indicate stimulation of gene expression. For clarity, blue lines feeding back to upstream pathway components were removed; many of these upstream components, however, are regulated by type I IFN and/or NFκB. The colour of a node reflected the H5N1:H1N1 expression ratio: blue nodes were not significantly differentially expressed in response to either virus, pink/red nodes were up-regulated more in response to H5N1 than H1N1 (red = > 1.5-fold more in response to H5N1, pink = 1.0-1.49-fold higher in response to H5N1), and the green node was down-regulated to a greater extent in response to H5N1. Larger nodes had a fold-change value of > 10 in H5N1 infection.

    Techniques Used: Activation Assay, Inhibition, Binding Assay, Expressing, Infection

    Expression of selected genes annotated are related to cytokine and chemokine activity. Increased gene expression levels were seen in response to H5N1 compared to H1N1 infection.
    Figure Legend Snippet: Expression of selected genes annotated are related to cytokine and chemokine activity. Increased gene expression levels were seen in response to H5N1 compared to H1N1 infection.

    Techniques Used: Expressing, Activity Assay, Infection

    24) Product Images from "Nucleosome positioning changes during human embryonic stem cell differentiation"

    Article Title: Nucleosome positioning changes during human embryonic stem cell differentiation

    Journal: Epigenetics

    doi: 10.1080/15592294.2016.1176649

    Gene expression analysis supports the cell identity and homogeneity of the WA09-human embryonic stem cell (hESC) →  ISL1 + nascent mesoderm (INM) → smooth muscle cell (SMC) differentiation. (A) The principle component analysis (PCA) was performed with the entire transcript set (22,089 in total) included in the Affymetrix Human Gene 1.0 ST array. (B) Heat map indicates genes with significant changes (red: upregulated; green: downregulated) among the 3 cell types and their enriched functional groups (see also Table S1).
    Figure Legend Snippet: Gene expression analysis supports the cell identity and homogeneity of the WA09-human embryonic stem cell (hESC) → ISL1 + nascent mesoderm (INM) → smooth muscle cell (SMC) differentiation. (A) The principle component analysis (PCA) was performed with the entire transcript set (22,089 in total) included in the Affymetrix Human Gene 1.0 ST array. (B) Heat map indicates genes with significant changes (red: upregulated; green: downregulated) among the 3 cell types and their enriched functional groups (see also Table S1).

    Techniques Used: Expressing, Functional Assay

    25) Product Images from "Deciphering transcriptome profiles of peripheral blood mononuclear cells in response to PRRSV vaccination in pigs"

    Article Title: Deciphering transcriptome profiles of peripheral blood mononuclear cells in response to PRRSV vaccination in pigs

    Journal: BMC Genomics

    doi: 10.1186/s12864-016-2849-1

    Hierarchical heat map showing differential gene expression over time. Normalized log 2 transformed values as determined by Affymetrix GeneChip® porcine gene 1.0 ST array in PBMCs of German Landrace pigs at 6, 24 and 72 h post PRRSV vaccination. The cutoff value of log 2 fold change as either ˃1.5 or ˂ −1.5 and FDR
    Figure Legend Snippet: Hierarchical heat map showing differential gene expression over time. Normalized log 2 transformed values as determined by Affymetrix GeneChip® porcine gene 1.0 ST array in PBMCs of German Landrace pigs at 6, 24 and 72 h post PRRSV vaccination. The cutoff value of log 2 fold change as either ˃1.5 or ˂ −1.5 and FDR

    Techniques Used: Expressing, Transformation Assay

    26) Product Images from "Mitotic vulnerability in triple-negative breast cancer associated with LIN9 is targetable with BET inhibitors"

    Article Title: Mitotic vulnerability in triple-negative breast cancer associated with LIN9 is targetable with BET inhibitors

    Journal: Cancer research

    doi: 10.1158/0008-5472.CAN-17-1571

    BET activity is necessary for sustained expression of cell cycle-associated genes ( A–C ) MDA-MB-231 and HCC70 cells were treated for 72 hours with vehicle or 500 nM JQ1 and transcriptomes were analyzed using Affymetrix Human Gene 2.0 ST expression microarrays. ( A ) Venn diagram showing the number of genes whose expression significantly changed in each cell line as well as the number of genes commonly altered in both. ( B ) Top 5 non-overlapping Reactome terms for MDA-MB-231 (left) and HCC70 (right) cells. ( C ) GSEA of cell cycle-classifying genes whose expression was altered by JQ1 in MDA-MB-231 and HCC70 cells. ( D-F ) RT-qPCR analysis of three cell cycle/mitosis genes ( CCNB1 , KIF20A , and PLK1 ) in four TNBC cell lines treated with vehicle or 500 nM JQ1 for 24 hours. ( G ) RT-qPCR analysis of cell cycle and mitosis genes ( CCNB1 , KIF20A , PLK1 , and KIF2C ) in MDA-MB-231 (n=5) and MDA-MB-468 (n=10) tumors from orthotopically xenografted mice treated with vehicle or JQ1. ( H ) Volcano plots depicting mRNA log2 fold changes versus the corresponding log 10 p -values for genes whose expression significantly changes in response to JQ1 in MDA-MB-231 (right) and HCC70 (left) cells after 72 hours. Red dots indicate genes that are critical for mitosis. For all bar graphs, data are presented as means ± SD (*=p
    Figure Legend Snippet: BET activity is necessary for sustained expression of cell cycle-associated genes ( A–C ) MDA-MB-231 and HCC70 cells were treated for 72 hours with vehicle or 500 nM JQ1 and transcriptomes were analyzed using Affymetrix Human Gene 2.0 ST expression microarrays. ( A ) Venn diagram showing the number of genes whose expression significantly changed in each cell line as well as the number of genes commonly altered in both. ( B ) Top 5 non-overlapping Reactome terms for MDA-MB-231 (left) and HCC70 (right) cells. ( C ) GSEA of cell cycle-classifying genes whose expression was altered by JQ1 in MDA-MB-231 and HCC70 cells. ( D-F ) RT-qPCR analysis of three cell cycle/mitosis genes ( CCNB1 , KIF20A , and PLK1 ) in four TNBC cell lines treated with vehicle or 500 nM JQ1 for 24 hours. ( G ) RT-qPCR analysis of cell cycle and mitosis genes ( CCNB1 , KIF20A , PLK1 , and KIF2C ) in MDA-MB-231 (n=5) and MDA-MB-468 (n=10) tumors from orthotopically xenografted mice treated with vehicle or JQ1. ( H ) Volcano plots depicting mRNA log2 fold changes versus the corresponding log 10 p -values for genes whose expression significantly changes in response to JQ1 in MDA-MB-231 (right) and HCC70 (left) cells after 72 hours. Red dots indicate genes that are critical for mitosis. For all bar graphs, data are presented as means ± SD (*=p

    Techniques Used: Activity Assay, Expressing, Multiple Displacement Amplification, Quantitative RT-PCR, Mouse Assay

    27) Product Images from "Specific microRNA–mRNA Regulatory Network of Colon Cancer Invasion Mediated by Tissue Kallikrein–Related Peptidase 6"

    Article Title: Specific microRNA–mRNA Regulatory Network of Colon Cancer Invasion Mediated by Tissue Kallikrein–Related Peptidase 6

    Journal: Neoplasia (New York, N.Y.)

    doi: 10.1016/j.neo.2017.02.003

    Validation of selected miRNA-mRNA interactions. (A) 3′UTR reporter assays confirming the interaction of miR-181d and miR-182-3p with the 3′UTR of their candidate target genes: EHF (EHF-3′UTR), PAM (PAM-3′UTR) and FOS (FOS-3′UTR). Luciferase assays were done 24 h after co-transfections of the 3′UTR luciferase constructs with miR-181d or miR-182-3p or scrambled miRNA at the concentration of 50 nM. RLU: Relative luciferase units, which were calculated as a ratio of 3′UTR activity of gene transcript transfected with selected miRNAs and average 3′UTR activity of control plasmids as described in Materials and Methods section. Each experiment was performed in triplicates and repeated twice * P
    Figure Legend Snippet: Validation of selected miRNA-mRNA interactions. (A) 3′UTR reporter assays confirming the interaction of miR-181d and miR-182-3p with the 3′UTR of their candidate target genes: EHF (EHF-3′UTR), PAM (PAM-3′UTR) and FOS (FOS-3′UTR). Luciferase assays were done 24 h after co-transfections of the 3′UTR luciferase constructs with miR-181d or miR-182-3p or scrambled miRNA at the concentration of 50 nM. RLU: Relative luciferase units, which were calculated as a ratio of 3′UTR activity of gene transcript transfected with selected miRNAs and average 3′UTR activity of control plasmids as described in Materials and Methods section. Each experiment was performed in triplicates and repeated twice * P

    Techniques Used: Luciferase, Transfection, Construct, Concentration Assay, Activity Assay

    Effect of selected miRNA mimics on KLK6 expression and/or secretion and invasion in HCT116 colon cancer cells. (A) Western blot analysis of KLK6 intracellular protein level in HCT116 cells treated with miR-181d, miR-182 and miR-203 mimics. HCT116 cells were transfected with each of selected miRNA mimics at concentration of 75 nM and cells were processed for Western blot analysis 48 h after transfection. Some cell culture plates were also treated with TGF-β2 ligand (5 ng/ml in a serum-free media) and/or miR-203 mimic. β-actin was used as a loading control. Protein bands quantitation was done using Image J software and presented as Relative Intensity Units (RIU, protein/β-actin ratio normalized to scrambled miRNA sample). Figure is a representative of two independent experiments. (B) Concentration of KLK6 in the conditioned media of HCT116 cells upon treatment with selected miRNA mimics by ELISA * P ≤ .02, ** P = .002 by t -test. (C) Matrigel invasion assay of HCT116 cells treated with individual miRNA mimics. Cells were seeded onto Matrigel coated Boyden chambers 24 h after transfections and allow to invade for 48 hours. Analysis was done as described in Material and Methods section * P ≤ .002 by t -test.
    Figure Legend Snippet: Effect of selected miRNA mimics on KLK6 expression and/or secretion and invasion in HCT116 colon cancer cells. (A) Western blot analysis of KLK6 intracellular protein level in HCT116 cells treated with miR-181d, miR-182 and miR-203 mimics. HCT116 cells were transfected with each of selected miRNA mimics at concentration of 75 nM and cells were processed for Western blot analysis 48 h after transfection. Some cell culture plates were also treated with TGF-β2 ligand (5 ng/ml in a serum-free media) and/or miR-203 mimic. β-actin was used as a loading control. Protein bands quantitation was done using Image J software and presented as Relative Intensity Units (RIU, protein/β-actin ratio normalized to scrambled miRNA sample). Figure is a representative of two independent experiments. (B) Concentration of KLK6 in the conditioned media of HCT116 cells upon treatment with selected miRNA mimics by ELISA * P ≤ .02, ** P = .002 by t -test. (C) Matrigel invasion assay of HCT116 cells treated with individual miRNA mimics. Cells were seeded onto Matrigel coated Boyden chambers 24 h after transfections and allow to invade for 48 hours. Analysis was done as described in Material and Methods section * P ≤ .002 by t -test.

    Techniques Used: Expressing, Western Blot, Transfection, Concentration Assay, Cell Culture, Quantitation Assay, Software, Enzyme-linked Immunosorbent Assay, Invasion Assay

    (A) Validated miRNA-mRNA network in HCT116 cells with knockdown of KLK6 gene. (B) Network of predicted miRNA-RNA target pairs and pathways for the gene targets. Cytoscape [52] was used to generate the network. Pink Nodes are Kegg pathways; Green colored nodes indicate decrease in expression; Red colored nodes indicate increase in expression. Dark gray edges show genes connected to pathways. Light gray edges show relationship between miRNAs and their target genes. Purple edges show inverse correlation between miRNAs and their target genes. Nodes with a yellow border are the three miRNAs and the six mRNAs for which inverse correlations have been confirmed experimentally.
    Figure Legend Snippet: (A) Validated miRNA-mRNA network in HCT116 cells with knockdown of KLK6 gene. (B) Network of predicted miRNA-RNA target pairs and pathways for the gene targets. Cytoscape [52] was used to generate the network. Pink Nodes are Kegg pathways; Green colored nodes indicate decrease in expression; Red colored nodes indicate increase in expression. Dark gray edges show genes connected to pathways. Light gray edges show relationship between miRNAs and their target genes. Purple edges show inverse correlation between miRNAs and their target genes. Nodes with a yellow border are the three miRNAs and the six mRNAs for which inverse correlations have been confirmed experimentally.

    Techniques Used: Expressing

    28) Product Images from "Specific microRNA–mRNA Regulatory Network of Colon Cancer Invasion Mediated by Tissue Kallikrein–Related Peptidase 6"

    Article Title: Specific microRNA–mRNA Regulatory Network of Colon Cancer Invasion Mediated by Tissue Kallikrein–Related Peptidase 6

    Journal: Neoplasia (New York, N.Y.)

    doi: 10.1016/j.neo.2017.02.003

    Validation of KLK6 knockdown in HCT116 isogenic stable cell lines. (A) qRT-PCR for KLK6 RNA levels in Control clones 1 and 3 and shKLK6 clones 1, 2, and 3 harvested 48 h after subculture. (B) Levels of secreted KLK6 in conditioned media at 7 days after subculture in Control clones 1 and 3 and shKLK6 clones 1, 2, and 3. * P ≤ .05, Control clones vs. shKLK6 clone 1; ** P
    Figure Legend Snippet: Validation of KLK6 knockdown in HCT116 isogenic stable cell lines. (A) qRT-PCR for KLK6 RNA levels in Control clones 1 and 3 and shKLK6 clones 1, 2, and 3 harvested 48 h after subculture. (B) Levels of secreted KLK6 in conditioned media at 7 days after subculture in Control clones 1 and 3 and shKLK6 clones 1, 2, and 3. * P ≤ .05, Control clones vs. shKLK6 clone 1; ** P

    Techniques Used: Stable Transfection, Quantitative RT-PCR, Clone Assay

    Effect of selected miRNA mimics on KLK6 expression and/or secretion and invasion in HCT116 colon cancer cells. (A) Western blot analysis of KLK6 intracellular protein level in HCT116 cells treated with miR-181d, miR-182 and miR-203 mimics. HCT116 cells were transfected with each of selected miRNA mimics at concentration of 75 nM and cells were processed for Western blot analysis 48 h after transfection. Some cell culture plates were also treated with TGF-β2 ligand (5 ng/ml in a serum-free media) and/or miR-203 mimic. β-actin was used as a loading control. Protein bands quantitation was done using Image J software and presented as Relative Intensity Units (RIU, protein/β-actin ratio normalized to scrambled miRNA sample). Figure is a representative of two independent experiments. (B) Concentration of KLK6 in the conditioned media of HCT116 cells upon treatment with selected miRNA mimics by ELISA * P ≤ .02, ** P = .002 by t -test. (C) Matrigel invasion assay of HCT116 cells treated with individual miRNA mimics. Cells were seeded onto Matrigel coated Boyden chambers 24 h after transfections and allow to invade for 48 hours. Analysis was done as described in Material and Methods section * P ≤ .002 by t -test.
    Figure Legend Snippet: Effect of selected miRNA mimics on KLK6 expression and/or secretion and invasion in HCT116 colon cancer cells. (A) Western blot analysis of KLK6 intracellular protein level in HCT116 cells treated with miR-181d, miR-182 and miR-203 mimics. HCT116 cells were transfected with each of selected miRNA mimics at concentration of 75 nM and cells were processed for Western blot analysis 48 h after transfection. Some cell culture plates were also treated with TGF-β2 ligand (5 ng/ml in a serum-free media) and/or miR-203 mimic. β-actin was used as a loading control. Protein bands quantitation was done using Image J software and presented as Relative Intensity Units (RIU, protein/β-actin ratio normalized to scrambled miRNA sample). Figure is a representative of two independent experiments. (B) Concentration of KLK6 in the conditioned media of HCT116 cells upon treatment with selected miRNA mimics by ELISA * P ≤ .02, ** P = .002 by t -test. (C) Matrigel invasion assay of HCT116 cells treated with individual miRNA mimics. Cells were seeded onto Matrigel coated Boyden chambers 24 h after transfections and allow to invade for 48 hours. Analysis was done as described in Material and Methods section * P ≤ .002 by t -test.

    Techniques Used: Expressing, Western Blot, Transfection, Concentration Assay, Cell Culture, Quantitation Assay, Software, Enzyme-linked Immunosorbent Assay, Invasion Assay

    (A) Validated miRNA-mRNA network in HCT116 cells with knockdown of KLK6 gene. (B) Network of predicted miRNA-RNA target pairs and pathways for the gene targets. Cytoscape [52] was used to generate the network. Pink Nodes are Kegg pathways; Green colored nodes indicate decrease in expression; Red colored nodes indicate increase in expression. Dark gray edges show genes connected to pathways. Light gray edges show relationship between miRNAs and their target genes. Purple edges show inverse correlation between miRNAs and their target genes. Nodes with a yellow border are the three miRNAs and the six mRNAs for which inverse correlations have been confirmed experimentally.
    Figure Legend Snippet: (A) Validated miRNA-mRNA network in HCT116 cells with knockdown of KLK6 gene. (B) Network of predicted miRNA-RNA target pairs and pathways for the gene targets. Cytoscape [52] was used to generate the network. Pink Nodes are Kegg pathways; Green colored nodes indicate decrease in expression; Red colored nodes indicate increase in expression. Dark gray edges show genes connected to pathways. Light gray edges show relationship between miRNAs and their target genes. Purple edges show inverse correlation between miRNAs and their target genes. Nodes with a yellow border are the three miRNAs and the six mRNAs for which inverse correlations have been confirmed experimentally.

    Techniques Used: Expressing

    29) Product Images from "Risk of childhood asthma is associated with CpG-site polymorphisms, regional DNA methylation and mRNA levels at the GSDMB/ORMDL3 locus"

    Article Title: Risk of childhood asthma is associated with CpG-site polymorphisms, regional DNA methylation and mRNA levels at the GSDMB/ORMDL3 locus

    Journal: Human Molecular Genetics

    doi: 10.1093/hmg/ddu479

    ( A , upper panel) Dot-plot showing the distribution of the 61 CpG sites analyzed in the Swedish Search study ( n = 46) and the P -value after 10 000 permutations of comparing the three groups (healthy controls versus controlled asthma versus severe asthma, Kruskal–Wallis test). Dotted line: significance level at P = 0.05; red line: significance level at P = 0.01; red circles: differentially methylated probes according to asthma; black circle: CpG site excluded as the probe sequence is affected by a SNP; lower panel: DNA methylation levels ( β -values) for the two CpG sites located in ORMDL3 (cg02305874 and cg16638648). HC: healthy controls ( n = 15); CA: controlled asthma ( n = 16); SA: severe asthma ( n = 15). Error bars represent mean and standard deviation. All CpG sites were analyzed in peripheral blood leukocytes using the Infinium 450K assay. ( B ) mRNA expression of ORMDL3 according to disease status in children of the Swedish Search study. HC: healthy controls ( n = 15); CA: controlled asthma ( n = 16); SA: severe asthma ( n = 15). Error bars represent mean and standard deviation. Gene expression was analyzed in peripheral blood leukocytes using the GeneChip Human ST1.0 array from Affymetrix. ( C ) Spearman correlation coefficient for the relation between DNA methylation levels within the asthma-associated CpG sites. Correlation significant at * P = 0.05, ** P = 0.01 level and *** P
    Figure Legend Snippet: ( A , upper panel) Dot-plot showing the distribution of the 61 CpG sites analyzed in the Swedish Search study ( n = 46) and the P -value after 10 000 permutations of comparing the three groups (healthy controls versus controlled asthma versus severe asthma, Kruskal–Wallis test). Dotted line: significance level at P = 0.05; red line: significance level at P = 0.01; red circles: differentially methylated probes according to asthma; black circle: CpG site excluded as the probe sequence is affected by a SNP; lower panel: DNA methylation levels ( β -values) for the two CpG sites located in ORMDL3 (cg02305874 and cg16638648). HC: healthy controls ( n = 15); CA: controlled asthma ( n = 16); SA: severe asthma ( n = 15). Error bars represent mean and standard deviation. All CpG sites were analyzed in peripheral blood leukocytes using the Infinium 450K assay. ( B ) mRNA expression of ORMDL3 according to disease status in children of the Swedish Search study. HC: healthy controls ( n = 15); CA: controlled asthma ( n = 16); SA: severe asthma ( n = 15). Error bars represent mean and standard deviation. Gene expression was analyzed in peripheral blood leukocytes using the GeneChip Human ST1.0 array from Affymetrix. ( C ) Spearman correlation coefficient for the relation between DNA methylation levels within the asthma-associated CpG sites. Correlation significant at * P = 0.05, ** P = 0.01 level and *** P

    Techniques Used: Methylation, Sequencing, DNA Methylation Assay, Standard Deviation, Expressing

    30) Product Images from "ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks"

    Article Title: ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks

    Journal: Nature neuroscience

    doi: 10.1038/nn.4345

    spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values
    Figure Legend Snippet: spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values

    Techniques Used: Preserving

    31) Product Images from "ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks"

    Article Title: ALS disrupts spinal motor neuron maturation and aging pathways within gene co-expression networks

    Journal: Nature neuroscience

    doi: 10.1038/nn.4345

    spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values
    Figure Legend Snippet: spMN maturation and age modules are dysregulated in sporadic ALS. ( a ) Gene set enrichment analysis of 15,614 ranked gene loadings from PC1 for pathways and GO terms. “Positive” and “Negative” categories indicate gene sets enriched among genes whose loadings contribute most to the respective positive or negative direction of the sALS component (PC1 in a PCA performed on n = 22 samples). Enriched gene sets for each category are listed along with family-wise error rate (FWER) corrected P -values. Enrichment plots are shown for bolded gene sets. ( b ) For each of the 52 sALS modules, a hypergeometric test was performed to detect enrichment for genes from each of the 55 iMN modules. Upper panel: iMN modules are displayed along with the sample traits with which they are significantly associated, as identified and also shown in Fig. 2b . Enrichment for ClinVar pathogenic variants in motor neuron disease or ALS is also shown. The Z -summary value for each iMN module measures the extent of module preservation in the sALS data set. For the likelihood of module preservation, Z -summary > 10 indicates strong evidence; 10 > Z -summary > 2 indicates moderate to weak evidence, and 2 > Z -summary indicates no evidence. Bar graphs above indicate the number of genes assigned to each iMN module that were also represented by probe sets on the Affymetrix Human Exon 1.0 ST Array. Left panel: sALS modules are displayed along with the sample traits with which they are significantly correlated or anti-correlated, as identified in Supplementary Fig. 4d . The Z -summary value for each sALS module measures the extent of module preservation in the iMN data set. Bar graphs to the left indicate the number of genes assigned to each sALS module that were also represented by probe sets on the Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. A matrix of P -values from hypergeometric tests performed for each iMN and sALS module overlap were corrected by the Benjamini-Hochberg method, and subsequent P -values

    Techniques Used: Preserving

    32) Product Images from "Epigallocatechin-3-gallate (EGCG) protects against chromate-induced toxicity in vitro"

    Article Title: Epigallocatechin-3-gallate (EGCG) protects against chromate-induced toxicity in vitro

    Journal: Toxicology and Applied Pharmacology

    doi: 10.1016/j.taap.2011.10.018

    EGCG reduces Cr(VI)-induced cytotoxicity. A, BEAS-2B cells were exposed to 10 μM Cr(VI) and increasing concentrations of EGCG (5–100 μM) for 24 h. MTT assay showed EGCG dose-dependently increased cell viability in Cr(VI)-treated
    Figure Legend Snippet: EGCG reduces Cr(VI)-induced cytotoxicity. A, BEAS-2B cells were exposed to 10 μM Cr(VI) and increasing concentrations of EGCG (5–100 μM) for 24 h. MTT assay showed EGCG dose-dependently increased cell viability in Cr(VI)-treated

    Techniques Used: MTT Assay

    EGCG inhibits Cr(VI)-induced apoptosis. BEAS-2B cells were treated with 10 μM Cr(VI) and increasing concentrations of EGCG (5–25 μM) for 24 h. A, The cells were collected and stained with propidium iodide. DNA content was analyzed
    Figure Legend Snippet: EGCG inhibits Cr(VI)-induced apoptosis. BEAS-2B cells were treated with 10 μM Cr(VI) and increasing concentrations of EGCG (5–25 μM) for 24 h. A, The cells were collected and stained with propidium iodide. DNA content was analyzed

    Techniques Used: Staining

    EGCG inhibits Cr(VI)-induced intracellular ROS generation. A, BEAS-2B cells were simultaneously treated with Cr(VI) and EGCG for 2 h and fluorescence micrographs were taken. (a) negative control, (b) positive control (100 μM H 2 O 2 ), (c) 5 μM
    Figure Legend Snippet: EGCG inhibits Cr(VI)-induced intracellular ROS generation. A, BEAS-2B cells were simultaneously treated with Cr(VI) and EGCG for 2 h and fluorescence micrographs were taken. (a) negative control, (b) positive control (100 μM H 2 O 2 ), (c) 5 μM

    Techniques Used: Fluorescence, Negative Control, Positive Control

    Confirmation of expression levels of selected genes by quantitative RT-PCR. BEAS-2B cells were treated with 10 μM Cr(VI) in the presence of absence of 25 μM EGCG for 24 h. Total RNA was extracted and expression levels of (a) EGR1, (b)
    Figure Legend Snippet: Confirmation of expression levels of selected genes by quantitative RT-PCR. BEAS-2B cells were treated with 10 μM Cr(VI) in the presence of absence of 25 μM EGCG for 24 h. Total RNA was extracted and expression levels of (a) EGR1, (b)

    Techniques Used: Expressing, Quantitative RT-PCR

    33) Product Images from "Early Transcriptomic Response to LDL and oxLDL in Human Vascular Smooth Muscle Cells"

    Article Title: Early Transcriptomic Response to LDL and oxLDL in Human Vascular Smooth Muscle Cells

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0163924

    Hierarchical cluster analysis of the differentially expressed genes with more than 2-fold changed expression in one out of six groups (nLDL 1h, nLDL 5h, nLDL 24h, oxLDL 1h, oxLDL 5h and oxLDL 24h) compared to parental hVSMC cells. The dendrogram on the left indicates correlation between gene expression profiles. The columns in the middle show the normalized expression of each gene in pseudocolor scale (key in the upper).
    Figure Legend Snippet: Hierarchical cluster analysis of the differentially expressed genes with more than 2-fold changed expression in one out of six groups (nLDL 1h, nLDL 5h, nLDL 24h, oxLDL 1h, oxLDL 5h and oxLDL 24h) compared to parental hVSMC cells. The dendrogram on the left indicates correlation between gene expression profiles. The columns in the middle show the normalized expression of each gene in pseudocolor scale (key in the upper).

    Techniques Used: Expressing

    34) Product Images from "Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells"

    Article Title: Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0017982

    Validation of microarray results by quantitative RT-PCR. Total RNA was extracted from two cell lines each of control, Cr_small, and Cr_large group, as well as parental BEAS-2B cells. Expression levels of KRT34, DSC3, PSG2 and RSP4Y were analyzed by quantitative RT-PCR. Relative gene expression level, normalized to 18s rRNA expression, was presented as fold change to the level expressed in Beas-2B cells. Data are mean ± SD (n = 3). The expression value of each gene determined from the microarray data was listed below the corresponding PCR results. The color bar related color code to the expression value determined after quantile normalization and baseline transformation to the median levels of all samples.
    Figure Legend Snippet: Validation of microarray results by quantitative RT-PCR. Total RNA was extracted from two cell lines each of control, Cr_small, and Cr_large group, as well as parental BEAS-2B cells. Expression levels of KRT34, DSC3, PSG2 and RSP4Y were analyzed by quantitative RT-PCR. Relative gene expression level, normalized to 18s rRNA expression, was presented as fold change to the level expressed in Beas-2B cells. Data are mean ± SD (n = 3). The expression value of each gene determined from the microarray data was listed below the corresponding PCR results. The color bar related color code to the expression value determined after quantile normalization and baseline transformation to the median levels of all samples.

    Techniques Used: Microarray, Quantitative RT-PCR, Expressing, Polymerase Chain Reaction, Transformation Assay

    35) Product Images from "Gastrointestinal Transcriptomic Response of Metabolic Vitamin B12 Pathways in Roux-en-Y Gastric Bypass"

    Article Title: Gastrointestinal Transcriptomic Response of Metabolic Vitamin B12 Pathways in Roux-en-Y Gastric Bypass

    Journal: Clinical and Translational Gastroenterology

    doi: 10.1038/ctg.2016.67

    Validation of expression levels of vitamin B12 pathway-encoding genes by real-time quantitative PCR (RT–qPCR). Red columns indicate that opposite results were obtained by microarray and RT–qPCR techniques. CUBN, cubilin; GIF, gastric intrinsic factor; M, microarray; RT–qPCR, real-time quantitative PCR; TCN1, transcobalamin I-encoding gene; TCN2, transcobalamin II-encoding gene.
    Figure Legend Snippet: Validation of expression levels of vitamin B12 pathway-encoding genes by real-time quantitative PCR (RT–qPCR). Red columns indicate that opposite results were obtained by microarray and RT–qPCR techniques. CUBN, cubilin; GIF, gastric intrinsic factor; M, microarray; RT–qPCR, real-time quantitative PCR; TCN1, transcobalamin I-encoding gene; TCN2, transcobalamin II-encoding gene.

    Techniques Used: Expressing, Real-time Polymerase Chain Reaction, Quantitative RT-PCR, Microarray

    Changes in gastrointestinal (GI) expression of vitamin B12 (B12) pathway–encoding genes following Roux-en-Y gastric bypass (RYGB). ( a ) Before RYGB. B12, bound to animal proteins, enters the stomach, where it is released by actions of pepsin and hydrochloric acid (HCl). B12 binds to transcobalamin I (TCN1), found in saliva or gastric fluid, and is transported to duodenum. Here TCN1 is degraded by pancreatic enzymes, and B12 is captured by intrinsic factor (IF). The B12–IF complex moves through the intestine and is absorbed by enterocytes via the cubam subunit cubilin (CUBN). Degradation of IF in enterocytes releases B12, which binds transcobalamin II (TCN2) and is transported by blood flow throughout the body. ( b ) After RYGB. Dietary B12 enters the stomach bound to animal proteins. Removal of the gastric fundus leads to impaired production of gastric and pepsin acids, which hinders B12 release from food. Decreased IF and TCN1 expression levels limit intestinal transport of B12. In response to decreased B12 levels, the intestine triggers production of CUBN and TCN2 in an (apparently unsuccessful) effort to maintain systemic B12 delivery. Red font denotes downregulated pathways, whereas blue font denotes upregulation.
    Figure Legend Snippet: Changes in gastrointestinal (GI) expression of vitamin B12 (B12) pathway–encoding genes following Roux-en-Y gastric bypass (RYGB). ( a ) Before RYGB. B12, bound to animal proteins, enters the stomach, where it is released by actions of pepsin and hydrochloric acid (HCl). B12 binds to transcobalamin I (TCN1), found in saliva or gastric fluid, and is transported to duodenum. Here TCN1 is degraded by pancreatic enzymes, and B12 is captured by intrinsic factor (IF). The B12–IF complex moves through the intestine and is absorbed by enterocytes via the cubam subunit cubilin (CUBN). Degradation of IF in enterocytes releases B12, which binds transcobalamin II (TCN2) and is transported by blood flow throughout the body. ( b ) After RYGB. Dietary B12 enters the stomach bound to animal proteins. Removal of the gastric fundus leads to impaired production of gastric and pepsin acids, which hinders B12 release from food. Decreased IF and TCN1 expression levels limit intestinal transport of B12. In response to decreased B12 levels, the intestine triggers production of CUBN and TCN2 in an (apparently unsuccessful) effort to maintain systemic B12 delivery. Red font denotes downregulated pathways, whereas blue font denotes upregulation.

    Techniques Used: Expressing, Flow Cytometry

    36) Product Images from "Novel Genes and Pathways Modulated by Syndecan-1: Implications for the Proliferation and Cell-Cycle Regulation of Malignant Mesothelioma Cells"

    Article Title: Novel Genes and Pathways Modulated by Syndecan-1: Implications for the Proliferation and Cell-Cycle Regulation of Malignant Mesothelioma Cells

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0048091

    Validation of syndecan-1 silencing (A) and microarray data (B–D). ( A ) Succesful silencing of syndecan-1 was confirmed by RT-PCR and flow cytometry. The level of syndecan-1 mRNA (left column) and protein (right column) after silencing compared to cells treated with negative/scrambled control, 24 hours after silencing. The silencing is highly significant (p
    Figure Legend Snippet: Validation of syndecan-1 silencing (A) and microarray data (B–D). ( A ) Succesful silencing of syndecan-1 was confirmed by RT-PCR and flow cytometry. The level of syndecan-1 mRNA (left column) and protein (right column) after silencing compared to cells treated with negative/scrambled control, 24 hours after silencing. The silencing is highly significant (p

    Techniques Used: Microarray, Reverse Transcription Polymerase Chain Reaction, Flow Cytometry, Cytometry

    37) Product Images from "Exon array analyses across the NCI-60 reveals potential regulation of TOP1 by transcription pausing at guanosine quartets in the first intron"

    Article Title: Exon array analyses across the NCI-60 reveals potential regulation of TOP1 by transcription pausing at guanosine quartets in the first intron

    Journal: Cancer research

    doi: 10.1158/0008-5472.CAN-09-3528

    Three oligonucleotides tested for G-quadruplex formation. A , Sequences of the three human TOP1 exon 1 oligonucleotides tested (located in ). B , UV melting profiles at 295 nm in 0.1 M KCl. C , Thermal difference spectra (TDS) in 0.1 M KCl. D , Circular
    Figure Legend Snippet: Three oligonucleotides tested for G-quadruplex formation. A , Sequences of the three human TOP1 exon 1 oligonucleotides tested (located in ). B , UV melting profiles at 295 nm in 0.1 M KCl. C , Thermal difference spectra (TDS) in 0.1 M KCl. D , Circular

    Techniques Used:

    Exon analysis of TOP1 reveals differential expression between the first and the other exons
    Figure Legend Snippet: Exon analysis of TOP1 reveals differential expression between the first and the other exons

    Techniques Used: Expressing

    Estimated TOP1 DNA copy numbers and transcript () levels across the NCI-60, and correlation between the two. A , Mean-centered aCGH intensities and estimated DNA copy number are plotted on the left-hand panel x-axis, and transcript expression
    Figure Legend Snippet: Estimated TOP1 DNA copy numbers and transcript () levels across the NCI-60, and correlation between the two. A , Mean-centered aCGH intensities and estimated DNA copy number are plotted on the left-hand panel x-axis, and transcript expression

    Techniques Used: Expressing

    Variation of mean-centered log 2 TOP1 probe set intensities from Affymetrix GH Exon 1.0 ST microarrays. A , Clustered image map (heat map) for mRNA expression for each of the 21 exons of TOP1 across the NCI-60 cell lines. The cell lines are clustered on
    Figure Legend Snippet: Variation of mean-centered log 2 TOP1 probe set intensities from Affymetrix GH Exon 1.0 ST microarrays. A , Clustered image map (heat map) for mRNA expression for each of the 21 exons of TOP1 across the NCI-60 cell lines. The cell lines are clustered on

    Techniques Used: Expressing

    Schematic representation of potential quadruplex-forming G-rich sequences within TOP1 intron 1. A
    Figure Legend Snippet: Schematic representation of potential quadruplex-forming G-rich sequences within TOP1 intron 1. A

    Techniques Used:

    TOP1 transcript level intensities, z-score distribution in the NCI-60, and exon location of probesets. A , Table of intensity levels for six probesets from the HG-U95, HG-U133, and HG-U133 Plus2 microarrays, with their combined z-score means (presented
    Figure Legend Snippet: TOP1 transcript level intensities, z-score distribution in the NCI-60, and exon location of probesets. A , Table of intensity levels for six probesets from the HG-U95, HG-U133, and HG-U133 Plus2 microarrays, with their combined z-score means (presented

    Techniques Used:

    38) Product Images from "Tolfenamic acid-induced alterations in genes and pathways in pancreatic cancer cells"

    Article Title: Tolfenamic acid-induced alterations in genes and pathways in pancreatic cancer cells

    Journal: Oncotarget

    doi: 10.18632/oncotarget.14651

    Validation of microarray results Quantitative PCR analysis was performed using TaqMan primer-probes for seven genes differentially expressed genes (selected from Table 2 ) in pancreatic cancer cell lines L3.6pl ( A ), MIA PaCa-2 ( B ), and Panc1 ( C ). Except for DDI3, which was upregulated, all other genes were downregulated by TA treatment. The figure shows the fold-change in gene expression in TA treated sample compared to DMSO treated control.
    Figure Legend Snippet: Validation of microarray results Quantitative PCR analysis was performed using TaqMan primer-probes for seven genes differentially expressed genes (selected from Table 2 ) in pancreatic cancer cell lines L3.6pl ( A ), MIA PaCa-2 ( B ), and Panc1 ( C ). Except for DDI3, which was upregulated, all other genes were downregulated by TA treatment. The figure shows the fold-change in gene expression in TA treated sample compared to DMSO treated control.

    Techniques Used: Microarray, Real-time Polymerase Chain Reaction, Expressing

    39) Product Images from "Metformin induces cell cycle arrest at the G1 phase through E2F8 suppression in lung cancer cells"

    Article Title: Metformin induces cell cycle arrest at the G1 phase through E2F8 suppression in lung cancer cells

    Journal: Oncotarget

    doi: 10.18632/oncotarget.21552

    Effect of metformin on E2F8 expression and effect of E2F8 knockdown on proliferation of lung cancer cells ( A ) H1299 cells were treated with 5 mM metformin and E2F8 mRNA levels were measured by qRT-PCR. RPLP0 was used as an internal control. Relative E2F8 mRNA levels were calculated by comparing it to the expression level of the control. Error bars indicate standard deviation ( n = 3, * P
    Figure Legend Snippet: Effect of metformin on E2F8 expression and effect of E2F8 knockdown on proliferation of lung cancer cells ( A ) H1299 cells were treated with 5 mM metformin and E2F8 mRNA levels were measured by qRT-PCR. RPLP0 was used as an internal control. Relative E2F8 mRNA levels were calculated by comparing it to the expression level of the control. Error bars indicate standard deviation ( n = 3, * P

    Techniques Used: Expressing, Quantitative RT-PCR, Standard Deviation

    Effect of metformin on proliferation of lung cancer cells ( A ) H1299 cells were treated with metformin (5 mM or 10 mM). Upper panels: representative images of cultured H1299 cells. Green indicates dead cells stained with cyanine dye. Middle panel: percentage of confluence. The images were obtained every two hours and the percent confluence was calculated. Lower panel: percentage of regions displaying cytotoxicity. The cyanine dye was added 16 h after metformin treatment. ( B ) Cell proliferation was detected by MTS assay. Error bars indicate standard deviation ( n = 8, * P
    Figure Legend Snippet: Effect of metformin on proliferation of lung cancer cells ( A ) H1299 cells were treated with metformin (5 mM or 10 mM). Upper panels: representative images of cultured H1299 cells. Green indicates dead cells stained with cyanine dye. Middle panel: percentage of confluence. The images were obtained every two hours and the percent confluence was calculated. Lower panel: percentage of regions displaying cytotoxicity. The cyanine dye was added 16 h after metformin treatment. ( B ) Cell proliferation was detected by MTS assay. Error bars indicate standard deviation ( n = 8, * P

    Techniques Used: Cell Culture, Staining, MTS Assay, Standard Deviation

    Effect of E2F8 overexpression on proliferation of lung cancer cells ( A ) H1299 cells were transfected with the pCMV6-Entry vector expressing GFP-tagged human E2F8 and images were obtained by immunofluorescence microscopy. DNA was stained with DAPI. ( B ) After 24 h of hydroxyurea treatment, E2F8 protein levels (upper panel) and cell cycle (lower panel) were analyzed using western blotting and FACS with PI staining, respectively, at 6, 12, 18, 24, and 30 h. ( C ) E2F8 expression was verified using western blot analysis in H1299 cells transfected with an E2F8 expression vector. ( D – F ) A plasmid encoding E2F8 was transfected into H1299 cells and incubated with or without 5 mM metformin. Cell proliferation (D) and cell cycle (E) were analyzed using MTS assay and FACS on the third day after transfection ( n = 8, * P
    Figure Legend Snippet: Effect of E2F8 overexpression on proliferation of lung cancer cells ( A ) H1299 cells were transfected with the pCMV6-Entry vector expressing GFP-tagged human E2F8 and images were obtained by immunofluorescence microscopy. DNA was stained with DAPI. ( B ) After 24 h of hydroxyurea treatment, E2F8 protein levels (upper panel) and cell cycle (lower panel) were analyzed using western blotting and FACS with PI staining, respectively, at 6, 12, 18, 24, and 30 h. ( C ) E2F8 expression was verified using western blot analysis in H1299 cells transfected with an E2F8 expression vector. ( D – F ) A plasmid encoding E2F8 was transfected into H1299 cells and incubated with or without 5 mM metformin. Cell proliferation (D) and cell cycle (E) were analyzed using MTS assay and FACS on the third day after transfection ( n = 8, * P

    Techniques Used: Over Expression, Transfection, Plasmid Preparation, Expressing, Immunofluorescence, Microscopy, Staining, Western Blot, FACS, Incubation, MTS Assay

    Effect of transcription factors and AMPK on E2F8 expression ( A ) H1299 cells were treated with metformin (5 mM, 10 mM). After inhibition of de novo mRNA synthesis with actinomycin D, E2F8 mRNA levels were measured by qRT-PCR at indicated time points. Error bars indicate one standard deviation ( n = 3, * P
    Figure Legend Snippet: Effect of transcription factors and AMPK on E2F8 expression ( A ) H1299 cells were treated with metformin (5 mM, 10 mM). After inhibition of de novo mRNA synthesis with actinomycin D, E2F8 mRNA levels were measured by qRT-PCR at indicated time points. Error bars indicate one standard deviation ( n = 3, * P

    Techniques Used: Expressing, Inhibition, Quantitative RT-PCR, Standard Deviation

    40) Product Images from "TM6SF2 is a regulator of liver fat metabolism influencing triglyceride secretion and hepatic lipid droplet content"

    Article Title: TM6SF2 is a regulator of liver fat metabolism influencing triglyceride secretion and hepatic lipid droplet content

    Journal: Proceedings of the National Academy of Sciences of the United States of America

    doi: 10.1073/pnas.1323785111

    Identification of TM6SF2 as putative functional gene/protein in the chromosome 19p12 locus associated with plasma TG concentration. ( A ) Comparison of the hepatic mRNA levels for all 19 genes in the 19p12 locus. mRNA levels are expressed in arbitrary units
    Figure Legend Snippet: Identification of TM6SF2 as putative functional gene/protein in the chromosome 19p12 locus associated with plasma TG concentration. ( A ) Comparison of the hepatic mRNA levels for all 19 genes in the 19p12 locus. mRNA levels are expressed in arbitrary units

    Techniques Used: Functional Assay, Concentration Assay

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