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smart-seq2 transcriptome library preparation and sequencing  (Broad Institute Inc)

 
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    Broad Institute Inc smart-seq2 transcriptome library preparation and sequencing
    Smart Seq2 Transcriptome Library Preparation And Sequencing, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/smart+seq2+library+sequencing/smart+seq2+rna+seq/pm37150360-37-5-9
    Average 90 stars, based on 1 article reviews
    smart-seq2 transcriptome library preparation and sequencing - by Bioz Stars, 2026-11
    90/100 stars

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    other:

    Article Title: Akkermansia mono-colonization modulates microglia and astrocytes in a strain specific manner
    Article Snippet: Microglia and astrocytes were processed on the same plate at the Broad Institute using their mRNA SMART-Seq2 Cell Population v1 sequencing pipeline.

    Article Title: scRCA: A Siamese network-based pipeline for annotating cell types using noisy single-cell RNA-seq reference data.
    Article Snippet: Accurate cell type annotation is fundamentally critical for single-cell sequencing (scRNA-seq) data analysis to provide insightful knowledge of tissue-specific cell heterogeneity and cell state transition tracking.. Cell type annotation is usually conducted by comparative analysis with known data (i.e., reference) – which contains a presumably accurate representation of cell types.. However, this assumption is often problematic, as factors such as human errors in wet-lab experiments and methodological limitations can introduce annotation errors in the reference dataset.

    Article Title: Nicotinamide metabolism reprogramming drives reversible senescence of glioblastoma cells.
    Article Snippet: Four publicly available single-cell transcriptomes of GB cells were downloaded from the Broad Institute Single Cell Portal or GEO: Neftel_ SMARTseq2, Neftel_10X, Yu and Wang_10X (Table S1).

    Article Title: A new IDH-independent hypermethylation phenotype is associated with astrocyte-like cell state in glioblastoma
    Article Snippet: In glioblastoma, scRNA-seq data (Smartseq2) from IDH-wild-type tumors were obtained from the Broad Institute Single-Cell Portal [ ].

    Article Title: A new IDH-independent hypermethylation phenotype is associated with astrocyte-like cell state in glioblastoma.
    Article Snippet: In glioblastoma, scRNA-seq data (Smartseq2) from IDH-wild-type tumors were obtained from the Broad Institute Single-Cell Portal [66].

    Article Title: Transcriptome profiling of tendon fibroblasts at the onset of embryonic muscle contraction reveals novel force-responsive genes
    Article Snippet: Software, algorithm , Smart-seq2 single sample pipeline , Broad Institute , RRID: SCR_021228 , .

    Sequencing:

    Article Title: Akkermansia mono-colonization modulates microglia and astrocytes in a strain specific manner.
    Article Snippet: .. Microglia and astrocytes were processed on the same plate at the Broad Institute using their mRNA SMARTSeq2 Cell Population v1 sequencing pipeline. ..



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    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) <t>and</t> <t>Smart‐seq2</t> (FDR<0.05, FC>1.5).
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    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) <t>and</t> <t>Smart‐seq2</t> (FDR<0.05, FC>1.5).
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    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) <t>and</t> <t>Smart‐seq2</t> (FDR<0.05, FC>1.5).
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    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) <t>and</t> <t>Smart‐seq2</t> (FDR<0.05, FC>1.5).
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    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) <t>and</t> <t>Smart‐seq2</t> (FDR<0.05, FC>1.5).
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    Image Search Results


    Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) and Smart‐seq2 (FDR<0.05, FC>1.5).

    Journal: Advanced Science

    Article Title: EIF5A Couples Translational Control With Transcriptional Reprogramming Through Chromocenter Reorganization During Spermiogenesis

    doi: 10.1002/advs.202517423

    Figure Lengend Snippet: Increased chromatin accessibility in knockout round spermatids. A).Volcano plot of DEGs between control and Eif5a SKO samples.FDR<0.05. B.The average tag density plot(top pannel) and heatmaps (bottom pannel)around TSS (±3 kb) for the enrichment of ATAC‐seq reads in control and Eif5a SKO round spermatids. C).Plot shows Gain and Loss sites in all control and Eif5a SKO sample replicates. D).Venn diagram showing the overlap of differential peaks identified by CUT&Tag and ATAC‐seq between WT and CKO groups. E).Four‐quadrant scatter plot comparing the log 2 fold changes of significantly differential peaks (FDR < 0.05) from H3K4me3 CUT&Tag (x‐axis) and ATAC‐seq (y‐axis). The Pearson correlation coefficient for the compared data is 0.468. Pearson's *r* = 0.468. F) Venn diagram show shared genes between ATAC‐seq (FDR<0.05) and Smart‐seq2 (FDR<0.05, FC>1.5).

    Article Snippet: The Smart‐seq2 library sequencing was performed by Novogene on Illumina platforms, generating 150 bp paired‐end reads.

    Techniques: Knock-Out, Control

    Proteomic alterations associated with transcriptional changes induced by Eif5a deletion. A).Venn diagram of shared genes between Smart‐seq2 (P value<0.05, FC>1.5) and Proteomics (P<0.05, FC>1.5) analyses. B).GO enrichment analysis based on the 119 commonly upregulated genes. C).QRT‐PCR analysis of candidate genes that were consistently dysregulated in both the transcriptome and proteome of Eif5a SKO testes. Data are presented as mean ± SD from three independent biological replicates (n = 3). Statistical significance was determined using a two‐tailed, unpaired Student's t‐test (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). D). Western blots show SPATA1, SPACA3 and SPACA9 proteins in Eif5a SKO and control mice. β‐Actin served as the loading control. E). IGV visualization of genomic regions harboring acrosome‐related ( Spaca3, Ly6K,Spaca9,Spata1,Lamp2 ) and microtubule‐associated ( Ccdc169, Dynlt3 ) genes. Top: ATAC‐seq tracks showing chromatin accessibility in control (blue) versus SKO (red) round spermatids. Bottom: Corresponding Smart‐seq2 coverage.

    Journal: Advanced Science

    Article Title: EIF5A Couples Translational Control With Transcriptional Reprogramming Through Chromocenter Reorganization During Spermiogenesis

    doi: 10.1002/advs.202517423

    Figure Lengend Snippet: Proteomic alterations associated with transcriptional changes induced by Eif5a deletion. A).Venn diagram of shared genes between Smart‐seq2 (P value<0.05, FC>1.5) and Proteomics (P<0.05, FC>1.5) analyses. B).GO enrichment analysis based on the 119 commonly upregulated genes. C).QRT‐PCR analysis of candidate genes that were consistently dysregulated in both the transcriptome and proteome of Eif5a SKO testes. Data are presented as mean ± SD from three independent biological replicates (n = 3). Statistical significance was determined using a two‐tailed, unpaired Student's t‐test (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). D). Western blots show SPATA1, SPACA3 and SPACA9 proteins in Eif5a SKO and control mice. β‐Actin served as the loading control. E). IGV visualization of genomic regions harboring acrosome‐related ( Spaca3, Ly6K,Spaca9,Spata1,Lamp2 ) and microtubule‐associated ( Ccdc169, Dynlt3 ) genes. Top: ATAC‐seq tracks showing chromatin accessibility in control (blue) versus SKO (red) round spermatids. Bottom: Corresponding Smart‐seq2 coverage.

    Article Snippet: The Smart‐seq2 library sequencing was performed by Novogene on Illumina platforms, generating 150 bp paired‐end reads.

    Techniques: Quantitative RT-PCR, Two Tailed Test, Western Blot, Control