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genomic and transcriptomic sequencing data  (Biotechnology Information)

 
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    Biotechnology Information genomic and transcriptomic sequencing data
    Genomic And Transcriptomic Sequencing Data, supplied by Biotechnology Information, 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/transcriptomic+sequencing+data/genome+and+transcriptome+sequencing+data/pm36402137-775-2-16
    Average 90 stars, based on 1 article reviews
    genomic and transcriptomic sequencing data - by Bioz Stars, 2026-11
    90/100 stars

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    Related Articles

    Sequencing:

    Article Title: A facultative ectomycorrhizal association is triggered by organic nitrogen.
    Article Snippet: .. Genomic and transcriptomic sequencing data generated in this study are available at the National Center for Biotechnology Information under BioProjects PRJNA675211 and BioSample SAMN16692392. ..

    Article Title: Telomere-to-telomere Phragmites australis reference genome assembly with a B chromosome provides insights into its evolution and polysaccharide biosynthesis.
    Article Snippet: .. Whole genome and transcriptome raw sequencing data used in this study have been deposited at the National Center for Biotechnology Information (NCBI) under accession number PRJNA1055898. .. The genome assembly, annotations, protein sequences, CDS sequences, uncropped and unedited gel images, and the numerical source data underlying the graphs and charts are available for download from Figshare (https://doi.org/10.6084/m9. figshare.27016279).

    Article Title: Genomic and transcriptomic analyses of the elite rice variety Huizhan provide insight into disease resistance and heat tolerance.
    Article Snippet: .. Genome and transcriptome sequencing data of Huizhan are available at the National Center for Biotechnology Information under the accession number PRJNA1049505. ..

    Article Title: DNA hypomethylation mediates flower opening and senescence in sweet osmanthus through auxin and ethylene responsive pathways
    Article Snippet: Recent studies have shown that DNA methylation is critical for fruit ripening and leaf senescence, but its effect on flowering is unclear.. This study investigated the dynamic changes in DNA methylation and its regulatory role on flower opening and senescence of Osmanthus fragrans ‘Liuyejingui’ by whole-genome bisulfite sequencing and transcriptome sequencing at six developmental stages (unopened floral bud to late flower senescence, S1 to S6).. In total 3222 differentially methylated regions (DMRs) were identified in senescent flowers, of which 89% were hypomethylated (hypo-DMRs), and the number increased form S1 to S6, suggesting that DNA demethylation is associated with the progression of flowering.

    Article Title: Formation mechanism of glandular trichomes involved in the synthesis and storage of terpenoids in lavender
    Article Snippet: .. The raw whole-genome and transcriptome sequencing data used in this study are available from the National Center for Biotechnology Information (NCBI) database (Project No. PRJNA642976). ..

    Article Title: Population structure and adaptability analysis of Schizothorax o’connori based on whole-genome resequencing
    Article Snippet: .. Whole-genome data for S. o’connori have been published, and the genome and transcriptome sequencing data were submitted to the National Biotechnology Information Center (NCBI) biological project number PRJNA557578 [ ]. ..

    Generated:

    Article Title: A facultative ectomycorrhizal association is triggered by organic nitrogen.
    Article Snippet: .. Genomic and transcriptomic sequencing data generated in this study are available at the National Center for Biotechnology Information under BioProjects PRJNA675211 and BioSample SAMN16692392. ..



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    Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and <t>transcriptomic</t> profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.
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    Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and transcriptomic profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.

    Journal: Frontiers in Immunology

    Article Title: Identification of MTURN as a trained immunity-related biomarker for heart failure via integrative transcriptomic machine learning analysis and experimental validation

    doi: 10.3389/fimmu.2026.1739660

    Figure Lengend Snippet: Identification of core genes associated with macrophage immune training and heart failure. (A) Schematic overview of human-derived macrophage trained immunity model and transcriptomic profiling workflow ( GSE235897 ). (B) The volcano plot and (C) DEGs heatmap of hMDMs from trained (n=3) and untrained (n=3) samples in the macrophage-trained immunity dataset GSE235897 (|log2FC| ≥ 0.585, p < 0.05). (D) Sample clustering dendrogram of GSE135055 dataset based on gene expression profiles. (E) Scale-free topology fit index and (F) mean connectivity analysis across a range of soft-thresholding powers. (G) Cluster dendrogram of genes showing co-expression modules identified by WGCNA in database GSE135055 . (H) Module-trait heatmap values represent correlation coefficients between healthy controls and HF samples (* p < 0.05, ** p < 0.01). (I) Venn diagram showing the overlap among heart failure DEGs, trained-immunity DEGs, and WGCNA module genes.

    Article Snippet: For single-cell transcriptomic data, we accessed the SCP1303 project from the Broad Institute ( https://singlecell.broadinstitute.org/single_cell ), which includes raw scRNA-seq data from failing human hearts with dilated and hypertrophic cardiomyopathy.

    Techniques: Derivative Assay, Gene Expression, Expressing

    Five heart failure transcriptomic datasets were integrated with a macrophage-trained immunity model to identify immune-related biomarkers. Through DEGs analysis, WGCNA, CIBERSORT, and six machine learning algorithms, hub genes were prioritized with MTURN emerging as the top candidate. Its potential was further validated by scRNA-seq analysis, which confirmed MTURN enrichment in cardiac macrophages. Finally, MTURN expression was validated using previously published heart failure transcriptomic data and in vitro experiments.

    Journal: Frontiers in Immunology

    Article Title: Identification of MTURN as a trained immunity-related biomarker for heart failure via integrative transcriptomic machine learning analysis and experimental validation

    doi: 10.3389/fimmu.2026.1739660

    Figure Lengend Snippet: Five heart failure transcriptomic datasets were integrated with a macrophage-trained immunity model to identify immune-related biomarkers. Through DEGs analysis, WGCNA, CIBERSORT, and six machine learning algorithms, hub genes were prioritized with MTURN emerging as the top candidate. Its potential was further validated by scRNA-seq analysis, which confirmed MTURN enrichment in cardiac macrophages. Finally, MTURN expression was validated using previously published heart failure transcriptomic data and in vitro experiments.

    Article Snippet: For single-cell transcriptomic data, we accessed the SCP1303 project from the Broad Institute ( https://singlecell.broadinstitute.org/single_cell ), which includes raw scRNA-seq data from failing human hearts with dilated and hypertrophic cardiomyopathy.

    Techniques: Expressing, In Vitro