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deep rna seq  (Azenta)

 
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    Azenta deep rna seq
    A A pooled library of groups I–III was grown under five different conditions. PI-seq <t>and</t> <t>RNA-seq</t> libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.
    Deep Rna Seq, supplied by Azenta, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization"

    Article Title: CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

    Journal: Nature Communications

    doi: 10.1038/s41467-026-69903-1

    A A pooled library of groups I–III was grown under five different conditions. PI-seq and RNA-seq libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.
    Figure Legend Snippet: A A pooled library of groups I–III was grown under five different conditions. PI-seq and RNA-seq libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.

    Techniques Used: RNA Sequencing, Activity Assay, In Silico, Clone Assay, Comparison, Gene Expression, Expressing



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    A A pooled library of groups I–III was grown under five different conditions. PI-seq <t>and</t> <t>RNA-seq</t> libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.
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    Image Search Results


    A A pooled library of groups I–III was grown under five different conditions. PI-seq and RNA-seq libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.

    Journal: Nature Communications

    Article Title: CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

    doi: 10.1038/s41467-026-69903-1

    Figure Lengend Snippet: A A pooled library of groups I–III was grown under five different conditions. PI-seq and RNA-seq libraries were created for each condition ( n = 2 biological replicates). B – E Analysis of PI-seq data for the cells grown in 20 mM glucose. DNA barcode counts showed a narrow distribution and high coverage of the designed library ( B ) with high reproducibility ( C ). RNA barcode counts normalized to DNA barcode counts showed a large variation in promoter activity. Groups II and III promoters (intergenic distance ≥31 bp) were more active than group I promoters (intergenic distance ≤ 30 bp). log₂ promoter activity is shown in arbitrary units (A.U.) ( D ). The biological replicates for groups II and III showed high reproducibility of promoter activity, while group I promoter activity was weaker ( E ). Pearson’s r correlation values for each group are shown. F In silico prediction of operon structure identified 1149 operons and 2094 single genes. Of these 3243 genes, 2880 promoters were cloned into the library. G Comparison of promoter activity under two conditions. PI-seq data under 20 mM glucose (x-axis; blue points) and 20 mM citrate (y-axis; red points) highlights upregulated promoters. Differentially activated promoters were selected based on fold changes (FCs) (log 2 FC > 2.5) after filtering out low-activity promoters (log 2 promoter activity <2). H Comparison of gene expression under 20 mM glucose and 20 mM citrate conditions using RNA-seq data. Genes driven by the promoters identified by PI-seq in ( G ) are highlighted. I Comparison of log 2 fold changes between PI-seq (x-axis) and RNA-seq (y-axis) shows strong quantitative agreement, particularly for promoters with large fold changes (log 2 FC > 2.5). The fold changes were calculated by analyzing expression under 20 mM citrate condition divided by that under 20 mM glucose condition for each method. Pearson’s r correlation values are provided (all genes: dashed gray line, genes with log 2 FC > 2.5: solid black line). J Illustrations of the most upregulated promoters and their associated downstream genes. 140 bp promoter regions are highlighted in pink. Source data are provided as a Source Data file.

    Article Snippet: Deep RNA-seq on root samples (Supplementary Fig. ) were also processed by Azenta Life Sciences, incorporating dual rRNA depletion for both plant and bacterial RNA.

    Techniques: RNA Sequencing, Activity Assay, In Silico, Clone Assay, Comparison, Gene Expression, Expressing