ifc system Search Results


94
fluidigm lp 48 48
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fluidigm c1 single cell auto prep ifc
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fluidigm bmk m 96 96 platform
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fluidigm autoprep ifc microfluidic chip
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fluidigm 96 96 ifc dynamic array
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fluidigm c1 single cell preamp ifcs

C1 Single Cell Preamp Ifcs, supplied by fluidigm, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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fluidigm bmk-m-48.48gt

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fluidigm 48 48 dynamic array chips

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fluidigm 192 24 dynamic array integrated fluidic circuits

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fluidigm c1 single cell mrna seq ifc
(A) Bulk RNA-seq heat map of differentially expressed mRNAs and lincRNAs in mESCs grown in 2i + LIF medium, mESCs grown in serum + LIF medium, or derived NPCs. Black bars on the left indicate lincRNAs, and lincRNAs explored in this study are labelled on the right. The 2,000 genes with highest variance were selected. (B) An example of a lincRNA with strong differential expression (bulk RNA-seq) during mESC to NPC differentiation. (C) LincRNA and <t>mRNA</t> expression distributions from bulk RNA-seq analysis of mESCs (serum + LIF). (D) Two-dimensional t-SNE (t-Distributed Stochastic Neighbor Embedding) projection of single cells during mESC to NPC differentiation, coloured by sample (“cell annotations”) or the expression of marker genes. (E) Heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation (rows), across single cells (columns). Protein-coding genes encoding stem cell, neuronal, or cell cycle factors are highlighted (green, blue, and violet bars), as are lincRNAs (black bars). LincRNAs selected for further study are indicated by red bars. (F) Magnified view of the highlighted region (red rectangle) from (E), revealing subpopulations of serum + LIF mESCs with characteristic expression of pluripotency markers (rows indicated with orange labels) and lincRNAs (rows indicated with black bars). Previously reported subpopulations are indicated (columns highlighted by green bars underneath). See also and Table S1A.
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fluidigm c1 single cell auto prep ifcs
(A) Bulk RNA-seq heat map of differentially expressed mRNAs and lincRNAs in mESCs grown in 2i + LIF medium, mESCs grown in serum + LIF medium, or derived NPCs. Black bars on the left indicate lincRNAs, and lincRNAs explored in this study are labelled on the right. The 2,000 genes with highest variance were selected. (B) An example of a lincRNA with strong differential expression (bulk RNA-seq) during mESC to NPC differentiation. (C) LincRNA and <t>mRNA</t> expression distributions from bulk RNA-seq analysis of mESCs (serum + LIF). (D) Two-dimensional t-SNE (t-Distributed Stochastic Neighbor Embedding) projection of single cells during mESC to NPC differentiation, coloured by sample (“cell annotations”) or the expression of marker genes. (E) Heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation (rows), across single cells (columns). Protein-coding genes encoding stem cell, neuronal, or cell cycle factors are highlighted (green, blue, and violet bars), as are lincRNAs (black bars). LincRNAs selected for further study are indicated by red bars. (F) Magnified view of the highlighted region (red rectangle) from (E), revealing subpopulations of serum + LIF mESCs with characteristic expression of pluripotency markers (rows indicated with orange labels) and lincRNAs (rows indicated with black bars). Previously reported subpopulations are indicated (columns highlighted by green bars underneath). See also and Table S1A.
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Image Search Results


Journal: STAR Protocols

Article Title: Assessment of escape from X chromosome inactivation and gene expression in single human immune cells

doi: 10.1016/j.xpro.2021.100641

Figure Lengend Snippet:

Article Snippet: Determine the size of your cell type of interest The Fluidigm C1 Single-Cell Preamp IFCs are optimized for different cells sizes.

Techniques: Recombinant, Suspension, Saline, Binding Assay, Control, Multiplex Assay, Cell Isolation, Real-time Polymerase Chain Reaction, Software, Gene Expression, Transferring, Fluorescence, Microscopy

(A) Bulk RNA-seq heat map of differentially expressed mRNAs and lincRNAs in mESCs grown in 2i + LIF medium, mESCs grown in serum + LIF medium, or derived NPCs. Black bars on the left indicate lincRNAs, and lincRNAs explored in this study are labelled on the right. The 2,000 genes with highest variance were selected. (B) An example of a lincRNA with strong differential expression (bulk RNA-seq) during mESC to NPC differentiation. (C) LincRNA and mRNA expression distributions from bulk RNA-seq analysis of mESCs (serum + LIF). (D) Two-dimensional t-SNE (t-Distributed Stochastic Neighbor Embedding) projection of single cells during mESC to NPC differentiation, coloured by sample (“cell annotations”) or the expression of marker genes. (E) Heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation (rows), across single cells (columns). Protein-coding genes encoding stem cell, neuronal, or cell cycle factors are highlighted (green, blue, and violet bars), as are lincRNAs (black bars). LincRNAs selected for further study are indicated by red bars. (F) Magnified view of the highlighted region (red rectangle) from (E), revealing subpopulations of serum + LIF mESCs with characteristic expression of pluripotency markers (rows indicated with orange labels) and lincRNAs (rows indicated with black bars). Previously reported subpopulations are indicated (columns highlighted by green bars underneath). See also and Table S1A.

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Bulk RNA-seq heat map of differentially expressed mRNAs and lincRNAs in mESCs grown in 2i + LIF medium, mESCs grown in serum + LIF medium, or derived NPCs. Black bars on the left indicate lincRNAs, and lincRNAs explored in this study are labelled on the right. The 2,000 genes with highest variance were selected. (B) An example of a lincRNA with strong differential expression (bulk RNA-seq) during mESC to NPC differentiation. (C) LincRNA and mRNA expression distributions from bulk RNA-seq analysis of mESCs (serum + LIF). (D) Two-dimensional t-SNE (t-Distributed Stochastic Neighbor Embedding) projection of single cells during mESC to NPC differentiation, coloured by sample (“cell annotations”) or the expression of marker genes. (E) Heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation (rows), across single cells (columns). Protein-coding genes encoding stem cell, neuronal, or cell cycle factors are highlighted (green, blue, and violet bars), as are lincRNAs (black bars). LincRNAs selected for further study are indicated by red bars. (F) Magnified view of the highlighted region (red rectangle) from (E), revealing subpopulations of serum + LIF mESCs with characteristic expression of pluripotency markers (rows indicated with orange labels) and lincRNAs (rows indicated with black bars). Previously reported subpopulations are indicated (columns highlighted by green bars underneath). See also and Table S1A.

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: RNA Sequencing, Derivative Assay, Quantitative Proteomics, Expressing, Marker

(A) Quality control filtering of single cells, based on the measures indicated in the key. Total reads per cell are shown on the x -axis, and reads mapping to RNA spike-ins (as a control for library generation) on the y -axis. (B) Condensed version of with lincRNAs labelled (single-cell RNA-seq heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation). NB: lincRNA names are truncated for readability and correspond to the “Descriptive Gene Name” column in Table S1A. (C) Principle component analysis of single cells based on gene expression during mESC to NPC differentiation, using mRNA and lincRNA single-cell RNA-seq data, and with bulk RNA-seq samples overlaid for comparison. (D) Scatter plot comparing the expression of Zic3 and Nmnat2 to that of Pvt1, in serum + LIF mESCs, measured by single-cell RNA-seq.

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Quality control filtering of single cells, based on the measures indicated in the key. Total reads per cell are shown on the x -axis, and reads mapping to RNA spike-ins (as a control for library generation) on the y -axis. (B) Condensed version of with lincRNAs labelled (single-cell RNA-seq heat map showing the most variably expressed mRNAs and lincRNAs during mESC to NPC differentiation). NB: lincRNA names are truncated for readability and correspond to the “Descriptive Gene Name” column in Table S1A. (C) Principle component analysis of single cells based on gene expression during mESC to NPC differentiation, using mRNA and lincRNA single-cell RNA-seq data, and with bulk RNA-seq samples overlaid for comparison. (D) Scatter plot comparing the expression of Zic3 and Nmnat2 to that of Pvt1, in serum + LIF mESCs, measured by single-cell RNA-seq.

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Control, RNA Sequencing, Gene Expression, Comparison, Expressing

(A) Expression of highly variable lincRNAs (rows; listed in Table S1B) in single cells (columns), clustered by lincRNA expression. Cell types (mESCs in 2i + LIF or serum + LIF, and day 6 and 8 NPCs) and cell cycle stages (assigned by clustering on cell cycle marker gene expression) are indicated at the top. (B) Cell-to-cell variation in expression for mRNAs (grey) and lincRNAs (red), across mESCs (top), or NPCs (bottom), quantified using the DM method . The median DMs for lincRNAs and mRNAs are listed, and the distributions tested for similarity using the Wilcoxon rank sum test. (C) Scatter plot comparing the 90th expression percentile across single cells versus the median expression, for each lincRNA (red) and mRNA (grey). (D, E) Single cell expression pattern of a highly variable mESC lincRNA (D, Pvt1 ) and a uniformly expressed mESC lincRNA (E, linc1333 ), overlaid on the t-SNE projection. (F) An example of correlated lincRNA-mRNA single cell expression across mESC to NPC differentiation, with cells ordered by pseudotime determined using Monocle . (G) Top panels: cell cycle stage assignments for day 8 NPCs based on single cell expression of marker genes . Bottom panels: examples of three lincRNAs expressed during specific cell cycle stages ( XLOC_071380 = G1/S enriched, and Miat and Rmst = G2/M enriched). For each lincRNA, the heat bars show expression levels across the 67 G1/S cells (top bar) and 48 G2/M cells (bottom bar). In (B, C), key lincRNAs selected for detailed exploration are highlighted in green. See also and Tables S1A, B, and S3.

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Expression of highly variable lincRNAs (rows; listed in Table S1B) in single cells (columns), clustered by lincRNA expression. Cell types (mESCs in 2i + LIF or serum + LIF, and day 6 and 8 NPCs) and cell cycle stages (assigned by clustering on cell cycle marker gene expression) are indicated at the top. (B) Cell-to-cell variation in expression for mRNAs (grey) and lincRNAs (red), across mESCs (top), or NPCs (bottom), quantified using the DM method . The median DMs for lincRNAs and mRNAs are listed, and the distributions tested for similarity using the Wilcoxon rank sum test. (C) Scatter plot comparing the 90th expression percentile across single cells versus the median expression, for each lincRNA (red) and mRNA (grey). (D, E) Single cell expression pattern of a highly variable mESC lincRNA (D, Pvt1 ) and a uniformly expressed mESC lincRNA (E, linc1333 ), overlaid on the t-SNE projection. (F) An example of correlated lincRNA-mRNA single cell expression across mESC to NPC differentiation, with cells ordered by pseudotime determined using Monocle . (G) Top panels: cell cycle stage assignments for day 8 NPCs based on single cell expression of marker genes . Bottom panels: examples of three lincRNAs expressed during specific cell cycle stages ( XLOC_071380 = G1/S enriched, and Miat and Rmst = G2/M enriched). For each lincRNA, the heat bars show expression levels across the 67 G1/S cells (top bar) and 48 G2/M cells (bottom bar). In (B, C), key lincRNAs selected for detailed exploration are highlighted in green. See also and Tables S1A, B, and S3.

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Expressing, Marker, Gene Expression

(A) Plasmid-based fluorescent reporter assay to test RNA knock down by the Hammerhead ribozyme. The HHRz, or an inactive point mutant, was placed between GFP and RFP ORFs, and the relative fluorescence intensity measured (bar chart, right) to quantify cleavage efficiency. Statistical significance was tested using a two-tailed t test, comparing with the wild-type cell line. Mean ± SD is shown (n = 192 technical replicates). (B) Assessment of knockdown of endogenous G9a mRNA levels upon genomic integration of an HHRz cassette into the 3′ UTR of G9a . RNA levels were quantified by RT–qPCR and normalised to TBP. Statistical significance was tested using a two-tailed t test, comparing with all wild-type cell lines. Mean ± SD is shown (n = 3 technical replicates). (C) PCA to assess the gene expression pattern in four G9a HHRz cell lines (green) relative to 136 cell lines with a wild-type G9a locus (grey). (D) Differential expression analysis of G9a HHRz knockdown cell lines, with significantly differentially expressed genes highlighted in red (DESeq2 adjusted P < 0.05), and significantly up-regulated genes also up-regulated in a previous study of G9a knockdown cells highlighted in green . See also .

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Plasmid-based fluorescent reporter assay to test RNA knock down by the Hammerhead ribozyme. The HHRz, or an inactive point mutant, was placed between GFP and RFP ORFs, and the relative fluorescence intensity measured (bar chart, right) to quantify cleavage efficiency. Statistical significance was tested using a two-tailed t test, comparing with the wild-type cell line. Mean ± SD is shown (n = 192 technical replicates). (B) Assessment of knockdown of endogenous G9a mRNA levels upon genomic integration of an HHRz cassette into the 3′ UTR of G9a . RNA levels were quantified by RT–qPCR and normalised to TBP. Statistical significance was tested using a two-tailed t test, comparing with all wild-type cell lines. Mean ± SD is shown (n = 3 technical replicates). (C) PCA to assess the gene expression pattern in four G9a HHRz cell lines (green) relative to 136 cell lines with a wild-type G9a locus (grey). (D) Differential expression analysis of G9a HHRz knockdown cell lines, with significantly differentially expressed genes highlighted in red (DESeq2 adjusted P < 0.05), and significantly up-regulated genes also up-regulated in a previous study of G9a knockdown cells highlighted in green . See also .

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Plasmid Preparation, Reporter Assay, Knockdown, Mutagenesis, Fluorescence, Two Tailed Test, Quantitative RT-PCR, Gene Expression, Quantitative Proteomics

(A) Luciferase reporter assay to test knockdown by the Hepatitis Delta virus ribozyme (HDVRz) and two guanine-responsive aptazyme versions with various flanking sequences (HDVAz −1/+84 and −2/+152). Active (wt) and inactive point mutant (mut) versions were tested, with or without (NaOH control) the addition of guanine. Renilla luciferase levels were normalised to an internal firefly luciferase control. Mean ± SD is shown (n = 3 technical replicates). (B) Assessment of knockdown of endogenous G9a mRNA levels upon genomic integration of an HDV aptazyme cassette into the 3′ UTR of G9a. RNA levels were quantified by RT–qPCR, and normalised to TBP. Cells were treated with guanine for 2 h, and the RNA level expressed relative to the pretreatment level. Statistical significance was tested using a two-tailed t test, comparing with all wild-type cell lines. Mean ± SD is shown (n = 3 technical replicates). (C) qPCR measurements of lincRNA knockdowns in HHRz cell lines. Each point indicates one cell line, and expression is normalised against TBP and then compared with the median expression of control cell lines (no ribozyme integration). Horizontal bars show the median values across the tested cell lines.

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Luciferase reporter assay to test knockdown by the Hepatitis Delta virus ribozyme (HDVRz) and two guanine-responsive aptazyme versions with various flanking sequences (HDVAz −1/+84 and −2/+152). Active (wt) and inactive point mutant (mut) versions were tested, with or without (NaOH control) the addition of guanine. Renilla luciferase levels were normalised to an internal firefly luciferase control. Mean ± SD is shown (n = 3 technical replicates). (B) Assessment of knockdown of endogenous G9a mRNA levels upon genomic integration of an HDV aptazyme cassette into the 3′ UTR of G9a. RNA levels were quantified by RT–qPCR, and normalised to TBP. Cells were treated with guanine for 2 h, and the RNA level expressed relative to the pretreatment level. Statistical significance was tested using a two-tailed t test, comparing with all wild-type cell lines. Mean ± SD is shown (n = 3 technical replicates). (C) qPCR measurements of lincRNA knockdowns in HHRz cell lines. Each point indicates one cell line, and expression is normalised against TBP and then compared with the median expression of control cell lines (no ribozyme integration). Horizontal bars show the median values across the tested cell lines.

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Luciferase, Reporter Assay, Knockdown, Virus, Mutagenesis, Control, Quantitative RT-PCR, Two Tailed Test, Expressing

(A) Diversity of knockdown efficiencies for 15 selected lincRNAs, targeted by genomic integration of the HHRz and assessed using RNA-seq analysis across the collection of 140 cell lines. The expression of the lincRNAs targeted in the knockdown cell lines is shown, normalised to the median of all other cell lines. Each point corresponds to a biological replicate/cell line and the bar is the median across replicates. G9a mRNA expression across the G9a HHRz cell lines is shown for reference. (B) Representative knockdown of linc1509 using the HHRz. RNA-seq reads across the linc1509 pre-lincRNA (including introns) are shown, comparing the average read depth in non-targeted cell lines (black) with that in cell lines with the HHRz in linc1509 exon 2 (top) or exon 3 (bottom) (red). (C) Rescue of linc1405 expression in HHRz depleted linc1405 cell lines using an oligonucleotide that blocks ribozyme cleavage. Linc1405 expression measured by qPCR across a wild-type cell line (white) and a linc1405 HHRz cell line (red), treated with increasing concentrations of the oligonucleotide. As a negative control, the linc1405 HHRz cell line was treated with a non-complimentary oligonucleotide (“−ve control”). Dots represent individual measurements (two biological replicates, each with three technical replicates), and statistical significance was assessed using a two-tailed t test. (D) Expression of genes neighbouring eight lincRNA loci, in cell lines where those lincRNA loci were targeted by HHRz integration (coloured triangles) or genomic deletion (coloured crosses). Gene expression was measured by RNA-seq and normalised to median expression in non-targeted cell lines (grey points). Median expression differences between targeted and non-targeted groups of cell lines were tested for significance using a Monte Carlo simulation, applying the Bonferroni correction for multiple hypothesis testing. (E) Expression of linc1405 (red) and the neighbouring gene Eomes (black) across the differentiation time course, measured by bulk RNA-seq (n = 2 biological replicates). For each gene, measurements are centred on the mean and scaled by standard deviation. (F) Assessment of correlated expression across mESCs and NPCs of cis -linked gene pairs involving one lincRNA gene, quantified by Euclidean distance using single-cell RNA-seq data. The % of gene pairs (in 200 kb bins) with Euclidean distances below the 1% significance threshold (determined in by examining distant gene pairs) is shown. In the absence of proximity-dependent effects, we expect only 1% of gene pairs to be correlated below this threshold. (G) Representative single-cell RNA-seq tracks (three mESCs and three NPCs) for the genomic neighbourhood around linc_2485 (red bar). Genes co-expressed with linc_2485 (according to ) are indicated as black bars. See also and and Table S4A and B.

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Diversity of knockdown efficiencies for 15 selected lincRNAs, targeted by genomic integration of the HHRz and assessed using RNA-seq analysis across the collection of 140 cell lines. The expression of the lincRNAs targeted in the knockdown cell lines is shown, normalised to the median of all other cell lines. Each point corresponds to a biological replicate/cell line and the bar is the median across replicates. G9a mRNA expression across the G9a HHRz cell lines is shown for reference. (B) Representative knockdown of linc1509 using the HHRz. RNA-seq reads across the linc1509 pre-lincRNA (including introns) are shown, comparing the average read depth in non-targeted cell lines (black) with that in cell lines with the HHRz in linc1509 exon 2 (top) or exon 3 (bottom) (red). (C) Rescue of linc1405 expression in HHRz depleted linc1405 cell lines using an oligonucleotide that blocks ribozyme cleavage. Linc1405 expression measured by qPCR across a wild-type cell line (white) and a linc1405 HHRz cell line (red), treated with increasing concentrations of the oligonucleotide. As a negative control, the linc1405 HHRz cell line was treated with a non-complimentary oligonucleotide (“−ve control”). Dots represent individual measurements (two biological replicates, each with three technical replicates), and statistical significance was assessed using a two-tailed t test. (D) Expression of genes neighbouring eight lincRNA loci, in cell lines where those lincRNA loci were targeted by HHRz integration (coloured triangles) or genomic deletion (coloured crosses). Gene expression was measured by RNA-seq and normalised to median expression in non-targeted cell lines (grey points). Median expression differences between targeted and non-targeted groups of cell lines were tested for significance using a Monte Carlo simulation, applying the Bonferroni correction for multiple hypothesis testing. (E) Expression of linc1405 (red) and the neighbouring gene Eomes (black) across the differentiation time course, measured by bulk RNA-seq (n = 2 biological replicates). For each gene, measurements are centred on the mean and scaled by standard deviation. (F) Assessment of correlated expression across mESCs and NPCs of cis -linked gene pairs involving one lincRNA gene, quantified by Euclidean distance using single-cell RNA-seq data. The % of gene pairs (in 200 kb bins) with Euclidean distances below the 1% significance threshold (determined in by examining distant gene pairs) is shown. In the absence of proximity-dependent effects, we expect only 1% of gene pairs to be correlated below this threshold. (G) Representative single-cell RNA-seq tracks (three mESCs and three NPCs) for the genomic neighbourhood around linc_2485 (red bar). Genes co-expressed with linc_2485 (according to ) are indicated as black bars. See also and and Table S4A and B.

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Knockdown, RNA Sequencing, Expressing, Negative Control, Control, Two Tailed Test, Gene Expression, Standard Deviation

(A) Half-lives of mRNAs and lincRNAs, calculated from RNA-seq decay curves following actinomycin D–mediated transcription shut-off. Messenger RNAs are shown in black, lincRNAs in red, and lincRNAs highlighted in this study in green. A running median trend line for mRNAs is shown in blue. (B) Box plot summary of lincRNA and mRNA half-lives (bar = median; notches = 1.58 × IQR/sqrt(n)), with the distributions tested for similarity using the Wilcoxon rank sum test. The three plots show low expressed (<40 normalised counts), high expressed (>40 normalised counts), or all transcripts (left to right). (C) Length of non-genome-encoded oligonucleotide tails detected on RNA fragments captured by Mtr4 CRAC. Oligo(A) tails correspond to degradation intermediates and oligo(C/G/T) tails are shown as a negative control. (D) Metaplots showing the distribution of Pol II Native Elongating Transcript sequencing (NET-seq) (top) and Mtr4 CRAC (middle) RNA fragments around the start and end of mRNA exons and introns (first three and the last exon shown). Mtr4 CRAC RNA fragments with non-genome-encoded 3′ oligo(A) tails, corresponding to initial Mtr4 recruitment sites, are shown separately (bottom). (E) An example of Mtr4 CRAC reads mapping near the 3′ end of an intron (β-actin intron 1). Individual sequencing reads corresponding to fragments with 3′ oligo(A) tails are shown as red bars, with an alignment of these sequences below (highlighting in red the non-genome-encoded oligo(A) tails). (F) Total distribution of RNA fragments bound to Pol II (NET-seq) or Mtr4 (CRAC) around mRNA TSSs, in the sense (top) and antisense (bottom) directions. “Sense PROMPTs” are defined as short, prematurely terminated transcripts originating from TSSes in the sense direction and “antisense PROMPTs” are similar transcripts that arise in the upstream antisense orientation (see diagram). Mtr4 A-tailed read (as for D) distributions are shown in green. See also .

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Half-lives of mRNAs and lincRNAs, calculated from RNA-seq decay curves following actinomycin D–mediated transcription shut-off. Messenger RNAs are shown in black, lincRNAs in red, and lincRNAs highlighted in this study in green. A running median trend line for mRNAs is shown in blue. (B) Box plot summary of lincRNA and mRNA half-lives (bar = median; notches = 1.58 × IQR/sqrt(n)), with the distributions tested for similarity using the Wilcoxon rank sum test. The three plots show low expressed (<40 normalised counts), high expressed (>40 normalised counts), or all transcripts (left to right). (C) Length of non-genome-encoded oligonucleotide tails detected on RNA fragments captured by Mtr4 CRAC. Oligo(A) tails correspond to degradation intermediates and oligo(C/G/T) tails are shown as a negative control. (D) Metaplots showing the distribution of Pol II Native Elongating Transcript sequencing (NET-seq) (top) and Mtr4 CRAC (middle) RNA fragments around the start and end of mRNA exons and introns (first three and the last exon shown). Mtr4 CRAC RNA fragments with non-genome-encoded 3′ oligo(A) tails, corresponding to initial Mtr4 recruitment sites, are shown separately (bottom). (E) An example of Mtr4 CRAC reads mapping near the 3′ end of an intron (β-actin intron 1). Individual sequencing reads corresponding to fragments with 3′ oligo(A) tails are shown as red bars, with an alignment of these sequences below (highlighting in red the non-genome-encoded oligo(A) tails). (F) Total distribution of RNA fragments bound to Pol II (NET-seq) or Mtr4 (CRAC) around mRNA TSSs, in the sense (top) and antisense (bottom) directions. “Sense PROMPTs” are defined as short, prematurely terminated transcripts originating from TSSes in the sense direction and “antisense PROMPTs” are similar transcripts that arise in the upstream antisense orientation (see diagram). Mtr4 A-tailed read (as for D) distributions are shown in green. See also .

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: RNA Sequencing, Negative Control, Sequencing

(A) Comparison of Mtr4 CRAC and Pol II NET-seq read counts for mRNA (black) and lincRNA (red) exons, with lincRNAs studied in detail highlighted in green, lincRNAs mentioned in the text labelled, and a trend line for mRNAs shown in blue. For (A–C), only transcripts for which high-confidence TSSes could be assigned are included (see the Materials and Methods section and column “CRAC.biotype” in Table S1A). (B) The ratio of Mtr4 CRAC to Pol II NET-seq read counts for mRNA and lincRNA exons, introns, and sense and antisense PROMPTs, using the most stringent set of criteria to select lincRNA genes (genes >2 kb long and >5 kb away from neighbouring coding genes). A Wilcoxon rank sum test was used to compare lincRNAs and mRNAs. The bar indicates the median values, and notches = 1.58 × IQR/sqrt(n). (C) Mtr4 CRAC and Pol II NET-seq read counts in mRNA (black) and lincRNA (red) sense PROMPT regions. The CRAC RNA fragments arising here reflect short, early transcription termination products. LincRNAs studied in more detail are highlighted (green) and a trend line for mRNAs is shown in blue. (D) Genome browser snapshot showing Mtr4 CRAC and Pol II NET-seq reads across a representative mRNA (Cxxc1; top) and three lincRNAs (XLOC_026132, XLOC_047481, and XLOC_008616). Regions for which reads were counted in are (A–C) indicated, as are oligo(A)-tailed reads that we detect for XLOC_026132, corresponding to early transcription termination sites. (E) Genomic nucleotide distributions around PROMPT 3′ ends (= premature transcription termination sites) and intron 3′ ends, defined by analysing Mtr4-bound oligo(A)-tailed fragments that map to lincRNA and mRNA genes. Within introns, two classes of 3′ ends can be distinguished, with nucleotide signatures corresponding to 3′ splice sites (bottom right) or, when intron 3′ ends are filtered out, early termination sites (top right). See also .

Journal: Life Science Alliance

Article Title: Distinctive features of lincRNA gene expression suggest widespread RNA-independent functions

doi: 10.26508/lsa.201800124

Figure Lengend Snippet: (A) Comparison of Mtr4 CRAC and Pol II NET-seq read counts for mRNA (black) and lincRNA (red) exons, with lincRNAs studied in detail highlighted in green, lincRNAs mentioned in the text labelled, and a trend line for mRNAs shown in blue. For (A–C), only transcripts for which high-confidence TSSes could be assigned are included (see the Materials and Methods section and column “CRAC.biotype” in Table S1A). (B) The ratio of Mtr4 CRAC to Pol II NET-seq read counts for mRNA and lincRNA exons, introns, and sense and antisense PROMPTs, using the most stringent set of criteria to select lincRNA genes (genes >2 kb long and >5 kb away from neighbouring coding genes). A Wilcoxon rank sum test was used to compare lincRNAs and mRNAs. The bar indicates the median values, and notches = 1.58 × IQR/sqrt(n). (C) Mtr4 CRAC and Pol II NET-seq read counts in mRNA (black) and lincRNA (red) sense PROMPT regions. The CRAC RNA fragments arising here reflect short, early transcription termination products. LincRNAs studied in more detail are highlighted (green) and a trend line for mRNAs is shown in blue. (D) Genome browser snapshot showing Mtr4 CRAC and Pol II NET-seq reads across a representative mRNA (Cxxc1; top) and three lincRNAs (XLOC_026132, XLOC_047481, and XLOC_008616). Regions for which reads were counted in are (A–C) indicated, as are oligo(A)-tailed reads that we detect for XLOC_026132, corresponding to early transcription termination sites. (E) Genomic nucleotide distributions around PROMPT 3′ ends (= premature transcription termination sites) and intron 3′ ends, defined by analysing Mtr4-bound oligo(A)-tailed fragments that map to lincRNA and mRNA genes. Within introns, two classes of 3′ ends can be distinguished, with nucleotide signatures corresponding to 3′ splice sites (bottom right) or, when intron 3′ ends are filtered out, early termination sites (top right). See also .

Article Snippet: Reverse transcription and cDNA preamplification was then performed in the 10- to 17-μm Fluidigm C1 Single Cell mRNA Seq IFC using the SMARTer Ultra Low RNA kit for the Fluidigm C1 System and Advantage 2 PCR kit. cDNA was harvested and diluted to 0.1–0.3 ng/μl.

Techniques: Comparison