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gene exp cdh1 mm01247357 m1  (Thermo Fisher)


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    Thermo Fisher gene exp cdh1 mm01247357 m1
    Gene Exp Cdh1 Mm01247357 M1, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/gene exp cdh1 mm01247357 m1/product/Thermo Fisher
    Average 99 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    gene exp cdh1 mm01247357 m1 - by Bioz Stars, 2024-12
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    Thermo Fisher gene exp cdh1 mm01247357 m1
    Gene Exp Cdh1 Mm01247357 M1, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/gene exp cdh1 mm01247357 m1/product/Thermo Fisher
    Average 99 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    gene exp cdh1 mm01247357 m1 - by Bioz Stars, 2024-12
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    Thermo Fisher gene exp gapdh mm99999915 g1
    Overview of the CellOracle pipeline to infer cell type- and state-specific GRN configurations. (A) First, CellOracle uses scATAC-seq data to identify accessible promoter/enhancer DNA sequences. The DNA sequence of regulatory elements is scanned for TF binding motifs, generating a list of potential regulatory connections between a TF and its target genes to generate a ‘Base GRN’ (B) . (C) Using single-cell expression data, active connections are identified from all potential connections in the base GRN. (D) Cell type- and state-specific GRN configurations are constructed by pruning insignificant or weak connections. (E) Schematic of Hnf4α and Foxa1-mediated fibroblast to iEP reprogramming. Our previous CellTag lineage tracing revealed two conversion trajectories; reprogramming and dead-end . (F) Left panel: Force-directed graph of fibroblast to iEP reprogramming: from Louvain clustering, 15 clusters of cells were annotated manually, using marker gene expression, and grouped into five cell types; Fibroblasts, Early_Transition, Transition, Dead-end, and Reprogrammed iEPs. Right panels: Projection of <t>Apoa1</t> (iEP marker) and Col1a2 (fibroblast marker) expression onto the force-directed graph. (G) CellOracle analysis: The strength of network edges between Hnf4α-Foxa1 and its target genes, visualized as a heatmap (left panel), and plotted as a boxplot (right panel). (H) Degree and Eigenvector centrality scores for the Hnf4α-Foxa1 transgene. (I) Hnf4α-Foxa1 network cartography terms for each cluster. (J, K) Scatter plots showing a comparison of degree centrality scores between specific clusters. (J) Comparison of degree centrality scores between the Fib_1 cluster GRN configuration and the GRN configurations of other clusters in relatively early stages of reprogramming. (K) Comparison of degree centrality scores between iEP_1 and Dead-end_0 cluster GRN configurations.
    Gene Exp Gapdh Mm99999915 G1, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/gene exp gapdh mm99999915 g1/product/Thermo Fisher
    Average 99 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    gene exp gapdh mm99999915 g1 - by Bioz Stars, 2024-12
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    Overview of the CellOracle pipeline to infer cell type- and state-specific GRN configurations. (A) First, CellOracle uses scATAC-seq data to identify accessible promoter/enhancer DNA sequences. The DNA sequence of regulatory elements is scanned for TF binding motifs, generating a list of potential regulatory connections between a TF and its target genes to generate a ‘Base GRN’ (B) . (C) Using single-cell expression data, active connections are identified from all potential connections in the base GRN. (D) Cell type- and state-specific GRN configurations are constructed by pruning insignificant or weak connections. (E) Schematic of Hnf4α and Foxa1-mediated fibroblast to iEP reprogramming. Our previous CellTag lineage tracing revealed two conversion trajectories; reprogramming and dead-end . (F) Left panel: Force-directed graph of fibroblast to iEP reprogramming: from Louvain clustering, 15 clusters of cells were annotated manually, using marker gene expression, and grouped into five cell types; Fibroblasts, Early_Transition, Transition, Dead-end, and Reprogrammed iEPs. Right panels: Projection of Apoa1 (iEP marker) and Col1a2 (fibroblast marker) expression onto the force-directed graph. (G) CellOracle analysis: The strength of network edges between Hnf4α-Foxa1 and its target genes, visualized as a heatmap (left panel), and plotted as a boxplot (right panel). (H) Degree and Eigenvector centrality scores for the Hnf4α-Foxa1 transgene. (I) Hnf4α-Foxa1 network cartography terms for each cluster. (J, K) Scatter plots showing a comparison of degree centrality scores between specific clusters. (J) Comparison of degree centrality scores between the Fib_1 cluster GRN configuration and the GRN configurations of other clusters in relatively early stages of reprogramming. (K) Comparison of degree centrality scores between iEP_1 and Dead-end_0 cluster GRN configurations.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: Overview of the CellOracle pipeline to infer cell type- and state-specific GRN configurations. (A) First, CellOracle uses scATAC-seq data to identify accessible promoter/enhancer DNA sequences. The DNA sequence of regulatory elements is scanned for TF binding motifs, generating a list of potential regulatory connections between a TF and its target genes to generate a ‘Base GRN’ (B) . (C) Using single-cell expression data, active connections are identified from all potential connections in the base GRN. (D) Cell type- and state-specific GRN configurations are constructed by pruning insignificant or weak connections. (E) Schematic of Hnf4α and Foxa1-mediated fibroblast to iEP reprogramming. Our previous CellTag lineage tracing revealed two conversion trajectories; reprogramming and dead-end . (F) Left panel: Force-directed graph of fibroblast to iEP reprogramming: from Louvain clustering, 15 clusters of cells were annotated manually, using marker gene expression, and grouped into five cell types; Fibroblasts, Early_Transition, Transition, Dead-end, and Reprogrammed iEPs. Right panels: Projection of Apoa1 (iEP marker) and Col1a2 (fibroblast marker) expression onto the force-directed graph. (G) CellOracle analysis: The strength of network edges between Hnf4α-Foxa1 and its target genes, visualized as a heatmap (left panel), and plotted as a boxplot (right panel). (H) Degree and Eigenvector centrality scores for the Hnf4α-Foxa1 transgene. (I) Hnf4α-Foxa1 network cartography terms for each cluster. (J, K) Scatter plots showing a comparison of degree centrality scores between specific clusters. (J) Comparison of degree centrality scores between the Fib_1 cluster GRN configuration and the GRN configurations of other clusters in relatively early stages of reprogramming. (K) Comparison of degree centrality scores between iEP_1 and Dead-end_0 cluster GRN configurations.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Sequencing, Binding Assay, Expressing, Construct, Marker

    (A) After base GRN construction (left panel) using single-cell expression data, an active connection between the TF and the target gene is identified for defined cell identities and states by building a machine learning (ML) model that predicts the relationship between the TF and the target gene. ML model fitting results present the certainty of connection as a distribution, enabling the identification of GRN configurations by removing inactive connections from the base GRN structure. (B) Force-directed graph of iEP reprogramming scRNA-seq data (n = 27,663 cells). Projection of: Reprogramming time point information onto the force-directed graph. There are 8 time points; day 0, 3, 6, 9, 12, 15, 21, and 28; Hnf4α-t2a-Foxa1 ( Hnf4α-Foxa1) transgene expression levels; marker gene expression for key iEP states. Reprogrammed iEP cell cluster marker genes: Cdh1, Apoa1, and Kng1 . Fibroblast marker gene: Col1a2 . Transition marker gene: Mettl7a1 . Dead-end marker genes: Peg3, Igf2, and Fzd1. (C) Violin plots of marker gene expression in each cluster. (D) PAGA connectivity analysis across the reprogramming time course. (E) Illustration of the cartography analysis method. The cartography method classifies genes into seven groups according to two network scores: within-module degree and participation coefficient . In complex networks, high degree nodes (hubs) play the most significant roles in maintaining network structure. (F) Pie charts depicting the clonal composition of Dead-end cluster 0 and Dead-end cluster 1. Clone and trajectory information is derived from our previous CellTagging study .

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) After base GRN construction (left panel) using single-cell expression data, an active connection between the TF and the target gene is identified for defined cell identities and states by building a machine learning (ML) model that predicts the relationship between the TF and the target gene. ML model fitting results present the certainty of connection as a distribution, enabling the identification of GRN configurations by removing inactive connections from the base GRN structure. (B) Force-directed graph of iEP reprogramming scRNA-seq data (n = 27,663 cells). Projection of: Reprogramming time point information onto the force-directed graph. There are 8 time points; day 0, 3, 6, 9, 12, 15, 21, and 28; Hnf4α-t2a-Foxa1 ( Hnf4α-Foxa1) transgene expression levels; marker gene expression for key iEP states. Reprogrammed iEP cell cluster marker genes: Cdh1, Apoa1, and Kng1 . Fibroblast marker gene: Col1a2 . Transition marker gene: Mettl7a1 . Dead-end marker genes: Peg3, Igf2, and Fzd1. (C) Violin plots of marker gene expression in each cluster. (D) PAGA connectivity analysis across the reprogramming time course. (E) Illustration of the cartography analysis method. The cartography method classifies genes into seven groups according to two network scores: within-module degree and participation coefficient . In complex networks, high degree nodes (hubs) play the most significant roles in maintaining network structure. (F) Pie charts depicting the clonal composition of Dead-end cluster 0 and Dead-end cluster 1. Clone and trajectory information is derived from our previous CellTagging study .

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Expressing, Marker, Derivative Assay

    (A) Projection of Leiden cluster and gene expression information onto the state-fate UMAP embedding (from ) to identify reprogrammed and dead-end fates. (B) Violin plots of reprogrammed ( Apoa1, Cdh1 ), fibroblast ( Col1a1, Col1a2 ), and dead-end ( Peg3 ) marker expression along the iEP-enriched and iEP-depleted trajectories. (C) To assess the quality of the inferred networks, we calculated the degree distribution for each GRN configuration after pruning weak network edges, based on the p-value and strength. We counted the network degree (k), representing the number of network edges for each gene. P(k) is the frequency of network degree k, visualized in scatter plots. We also visualized the relationship between k and P(k) after log-transformation shows that these are scale-free networks, demonstrating successful network inference from these relatively small cell populations.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) Projection of Leiden cluster and gene expression information onto the state-fate UMAP embedding (from ) to identify reprogrammed and dead-end fates. (B) Violin plots of reprogrammed ( Apoa1, Cdh1 ), fibroblast ( Col1a1, Col1a2 ), and dead-end ( Peg3 ) marker expression along the iEP-enriched and iEP-depleted trajectories. (C) To assess the quality of the inferred networks, we calculated the degree distribution for each GRN configuration after pruning weak network edges, based on the p-value and strength. We counted the network degree (k), representing the number of network edges for each gene. P(k) is the frequency of network degree k, visualized in scatter plots. We also visualized the relationship between k and P(k) after log-transformation shows that these are scale-free networks, demonstrating successful network inference from these relatively small cell populations.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Expressing, Marker, Transformation Assay

    (A) Degree centrality, betweenness centrality, and eigenvector centrality of Fos for each cluster. (B) Network cartography terms of Fos for each cluster. (C) Fos expression projected onto the force-directed graph of the 2018 reprogramming time course. (D) Violin plot of Fos expression across reprogramming stages. (E) Fos gene overexpression simulation with reprogramming GRN configurations. The left panel is the projection of simulated cell transitions onto the force-directed graph. The Sankey diagram summarizes the simulation of cell transitions between cell clusters. For overexpression simulation, Fos expression was set to a value of 1.476, representing its maximum value in the imputed gene expression matrix (F) Fos gene knockout simulation. (G) Colony formation assay with addition of Fos to the Hnf4α-Foxa1 reprogramming cocktail. Left panel: E-cadherin immunohistochemistry. Right panel: box plot of colony numbers (n = 6 technical replicates, 2 independent biological replicates; *** = P < 0.001, t- test, one-sided). (H) qPCR assay for Fos and iEP marker expression ( Apoa1 and Chd1 ) following addition of Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 3 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided). (I) Fos gene knockout simulation in expanded, long-term cultured iEPs. (J) CRISPR/Cas9 knockout of Fos using CRISPR/Cas9 in expanded iEP cells. We designed 3 guide RNAs to target Fos, and transduced Cas9-expressing iEP cells with this guide RNA lentivirus pool. Left panels: Kernel density estimation method was applied with the t-SNE embedding to compare cell density between control guide RNAs and guide RNAs targeting Fos . Right panels: Quantification of changes in cell ratio following Fos knockout.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) Degree centrality, betweenness centrality, and eigenvector centrality of Fos for each cluster. (B) Network cartography terms of Fos for each cluster. (C) Fos expression projected onto the force-directed graph of the 2018 reprogramming time course. (D) Violin plot of Fos expression across reprogramming stages. (E) Fos gene overexpression simulation with reprogramming GRN configurations. The left panel is the projection of simulated cell transitions onto the force-directed graph. The Sankey diagram summarizes the simulation of cell transitions between cell clusters. For overexpression simulation, Fos expression was set to a value of 1.476, representing its maximum value in the imputed gene expression matrix (F) Fos gene knockout simulation. (G) Colony formation assay with addition of Fos to the Hnf4α-Foxa1 reprogramming cocktail. Left panel: E-cadherin immunohistochemistry. Right panel: box plot of colony numbers (n = 6 technical replicates, 2 independent biological replicates; *** = P < 0.001, t- test, one-sided). (H) qPCR assay for Fos and iEP marker expression ( Apoa1 and Chd1 ) following addition of Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 3 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided). (I) Fos gene knockout simulation in expanded, long-term cultured iEPs. (J) CRISPR/Cas9 knockout of Fos using CRISPR/Cas9 in expanded iEP cells. We designed 3 guide RNAs to target Fos, and transduced Cas9-expressing iEP cells with this guide RNA lentivirus pool. Left panels: Kernel density estimation method was applied with the t-SNE embedding to compare cell density between control guide RNAs and guide RNAs targeting Fos . Right panels: Quantification of changes in cell ratio following Fos knockout.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Expressing, Over Expression, Gene Knockout, Colony Assay, Immunohistochemistry, Marker, Cell Culture, CRISPR, Knock-Out

    (A) Comparison of eigenvector centrality scores between the Fib_1 cluster GRN configuration and the GRN configurations of other clusters in relatively early stages of reprogramming. (B) Comparison of eigenvector centrality scores between iEP_1 and Dead-end_0 cluster GRN configurations. (C-E) Expression and network cartography of Jun family members, Jun, Junb, and Jund . (F) qPCR of Fos expression in fibroblasts and iEPs, with and without cell dissociation prior to the assay, ** = P < 0.01, t- test, one-sided. (G) Analysis of Fos mRNA splicing state in the scRNA-seq data of iEP reprogramming to investigate the Fos mRNA maturation state: Violin plot for spliced Fos mRNA counts. (H) t -SNE plots of 9,914 expanded iEPs, cultured long-term, revealing fibroblast-like, intermediate, and three iEP subpopulations. Expression levels of Apoa1 (marking typical iEPs) , Col4a1 (fibroblast-like cells) , Cdh1, Serpina1b (hepatic-like iEPs), and Areg (intestine-like iEPs) projected onto the t -SNE plot.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) Comparison of eigenvector centrality scores between the Fib_1 cluster GRN configuration and the GRN configurations of other clusters in relatively early stages of reprogramming. (B) Comparison of eigenvector centrality scores between iEP_1 and Dead-end_0 cluster GRN configurations. (C-E) Expression and network cartography of Jun family members, Jun, Junb, and Jund . (F) qPCR of Fos expression in fibroblasts and iEPs, with and without cell dissociation prior to the assay, ** = P < 0.01, t- test, one-sided. (G) Analysis of Fos mRNA splicing state in the scRNA-seq data of iEP reprogramming to investigate the Fos mRNA maturation state: Violin plot for spliced Fos mRNA counts. (H) t -SNE plots of 9,914 expanded iEPs, cultured long-term, revealing fibroblast-like, intermediate, and three iEP subpopulations. Expression levels of Apoa1 (marking typical iEPs) , Col4a1 (fibroblast-like cells) , Cdh1, Serpina1b (hepatic-like iEPs), and Areg (intestine-like iEPs) projected onto the t -SNE plot.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Expressing, Cell Culture

    (A) Heatmap of expression of the top 50 inferred Fos targets across all stages of reprogramming. Established targets of YAP1 are highlighted in red. (B) Colony formation assay with the addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail. Left panels: E-cadherin immunohistochemistry. Right panel: box plot of colony numbers (n = 6 independent biological replicates; *** = P < 0.001, t- test, one-sided). (C) Brightfield and epifluorescence images of cells reprogrammed with Hnf4α-Foxa1 or Hnf4α-Foxa1-Fos-Yap1 cocktails. Scale bar = 500 μM. (D) scRNA-seq analysis of cells reprogrammed with Hnf4α-Foxa1 (n= 7,414 cells), Hnf4α-Foxa1-Fos (n= 8,771 cells), Hnf4α-Foxa1-Yap1 (n= 8,549 cells), and Hnf4α-Foxa1-Fos-Yap1 (n= 10,507 cells) cocktails and collected at day 20. Projection of fibroblast and iEP identity scores onto the UMAP embedding. (E) Kernel density estimation of cell density for each reprogramming cocktail from (D) . (F) Violin plot of iEP identity scores for each reprogramming cocktail. **** = p<0.0001, Wilcoxon test. (G) Unsupervised cell type classification for each reprogramming cocktail, using normal and injured mouse liver as a reference. BEC: Biliary epithelial cells. * = p = 0, randomized test.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) Heatmap of expression of the top 50 inferred Fos targets across all stages of reprogramming. Established targets of YAP1 are highlighted in red. (B) Colony formation assay with the addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail. Left panels: E-cadherin immunohistochemistry. Right panel: box plot of colony numbers (n = 6 independent biological replicates; *** = P < 0.001, t- test, one-sided). (C) Brightfield and epifluorescence images of cells reprogrammed with Hnf4α-Foxa1 or Hnf4α-Foxa1-Fos-Yap1 cocktails. Scale bar = 500 μM. (D) scRNA-seq analysis of cells reprogrammed with Hnf4α-Foxa1 (n= 7,414 cells), Hnf4α-Foxa1-Fos (n= 8,771 cells), Hnf4α-Foxa1-Yap1 (n= 8,549 cells), and Hnf4α-Foxa1-Fos-Yap1 (n= 10,507 cells) cocktails and collected at day 20. Projection of fibroblast and iEP identity scores onto the UMAP embedding. (E) Kernel density estimation of cell density for each reprogramming cocktail from (D) . (F) Violin plot of iEP identity scores for each reprogramming cocktail. **** = p<0.0001, Wilcoxon test. (G) Unsupervised cell type classification for each reprogramming cocktail, using normal and injured mouse liver as a reference. BEC: Biliary epithelial cells. * = p = 0, randomized test.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Expressing, Colony Assay, Immunohistochemistry

    (A) Top 50 decreased genes in Fos knockout simulation in the early reprogramming transition (left) and GO analysis based on these genes (right). (B) Violin plot of YAP1 target gene scores across reprogramming, which are significantly enriched as reprogramming progresses (*** = P < 0.001, permutation test, one-sided). (C) Projection of YAP1 target gene scores onto the force-directed graph of reprogramming. (D) qPCR assay for Yap1 expression following addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 4 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided), confirming Yap1 overexpression. (E) qPCR assay for iEP marker expression ( Apoa1 and Chd1 ) following addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 4 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided). (F) Projection of Leiden cluster, dead-end identity scores, and gene expression information onto the state-fate UMAP embedding (from ). (G) Expression of key marker genes for each reprogramming cocktail.

    Journal: bioRxiv

    Article Title: Gene Regulatory Network Reconfiguration in Direct Lineage Reprogramming

    doi: 10.1101/2022.07.01.497374

    Figure Lengend Snippet: (A) Top 50 decreased genes in Fos knockout simulation in the early reprogramming transition (left) and GO analysis based on these genes (right). (B) Violin plot of YAP1 target gene scores across reprogramming, which are significantly enriched as reprogramming progresses (*** = P < 0.001, permutation test, one-sided). (C) Projection of YAP1 target gene scores onto the force-directed graph of reprogramming. (D) qPCR assay for Yap1 expression following addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 4 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided), confirming Yap1 overexpression. (E) qPCR assay for iEP marker expression ( Apoa1 and Chd1 ) following addition of Yap1 and Fos to the Hnf4α-Foxa1 reprogramming cocktail (n = 4 independent biological replicates; *** = P < 0.001, ** = P < 0.01, t- test, one-sided). (F) Projection of Leiden cluster, dead-end identity scores, and gene expression information onto the state-fate UMAP embedding (from ). (G) Expression of key marker genes for each reprogramming cocktail.

    Article Snippet: Following cDNA synthesis (Maxima cDNA synthesis kit, Life Tech), qPCR was performed to quantify Fos/Yap1 overexpression (TaqMan Probes: Gapdh Mm99999915_g1; Cdh1 Mm01247357_m1; Apoa1 Mm00437569_m1; Fos Mm00487425_m1; Yap1 Mm01143263_m1; TaqMan qPCR Mastermix, Applied Biosystems).

    Techniques: Knock-Out, Expressing, Over Expression, Marker