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whole transcriptome rna sequencing data  (Biotechnology Information)

 
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    Biotechnology Information whole transcriptome rna sequencing data
    Whole Transcriptome Rna Sequencing Data, supplied by Biotechnology Information, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/transcriptome+sequencing+data/data+rna+seq+%E2%80%A2/pmc13194572-323-0-22
    Average 86 stars, based on 1 article reviews
    whole transcriptome rna sequencing data - by Bioz Stars, 2026-09
    86/100 stars

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    Related Articles

    Sequencing:

    Article Title: GPER agonist G1 suppresses neuronal apoptosis mediated by endoplasmic reticulum stress after exertional heat stroke injury.
    Article Snippet: .. Data Availability: The transcriptome sequencing data generated and analyzed during the current study are available in the National Center for Biotechnology Information (NCBI) under the BioProject number PRJNA1224851. ..

    Article Title: Gibberellin Disrupts Hormonal Homeostasis and Anther Integrity to Trigger Sex Reversal in Spinach
    Article Snippet: .. The raw transcriptome sequencing data of spinach ( Spinacia oleracea ) have been deposited in the National Center for Biotechnology Information (NCBI) under BioProject number PRJNA1310857. ..

    Article Title: Gamma-selinene synthase catalyzes the first step of dihydroagarofuran sesquiterpene alkaloid biosynthesis in Tripterygium.
    Article Snippet: 1State Key Laboratory of Plant Trait Design, CAS Center for Excellence in Molecular Plant Sciences/Shanghai Institute of Plant Physiology and Ecology, University of CAS, Chinese Academy of Sciences, Shanghai 200032, China 2Shanghai Key Laboratory of Plant Functional Genomics and Resources, Shanghai Chenshan Botanical Garden, Shanghai 201602, China 3State Key Laboratory of Phytochemistry and Natural Medicines, Chinese Academy of Sciences, Kunming 650201, China 4State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Department of Biochemistry, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200438, China

    Article Title: Dual RNA-Seq analysis unveils the multifaceted mechanisms of Trichoderma hamatum in the biological control of Fusarium graminearum , the causal agent of wheat fusarium head blight
    Article Snippet: .. The raw transcriptome sequencing data have been deposited in the national center for biotechnology information (NCBI) database under the BioProject ID PRJNA1356531. ..

    Article Title: Transcriptomics and Plant Hormone Analysis Reveal the Mechanism of Exogenous GA 3 Promoting Reflowering of Phalaenopsis ‘Hatuyuki’
    Article Snippet: .. The transcriptome sequencing data in this study have all been uploaded to the National Center for Biotechnology Information (NCBI), with access number PRJNA1320953 ( https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1320953 , accessed on 30 October 2025). ..

    Article Title: Isolation of Chicken Intestinal Glial Cells and Their Transcriptomic Response to LPS
    Article Snippet: .. The transcriptome sequencing data have been deposited in the National Center for Biotechnology Information (NCBI) under the BioProject accession number PRJNA1346664. ..

    Article Title: NSUN2/ALYREF stabilizes m5C-modified circCEP70 to enhance radioresistance in rectal cancer through NEDD8-dependent neddylation and ubiquitination regulation.
    Article Snippet: Background: 5-Methylcytosine (m5C) is an important RNA methylation modification implicated in tumor initiation and progression through its effects on RNA transcription, structural conformation, and stability.. However, the role of the interaction between circular RNAs (circRNAs) and m5C modification in oncogenesis remains limited.. This study aimed to elucidate the molecular mechanism by which m5C-modified circCEP70 facilitates radioresistance in rectal cancer (RC).

    Article Title: A minimal transcriptomic signature predicts intravascular tumor extension in renal cell carcinoma
    Article Snippet: .. In addition, whole-exome and transcriptome sequencing data from an independent RCC cohort published by Wang et al. were obtained from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). ..

    Generated:

    Article Title: GPER agonist G1 suppresses neuronal apoptosis mediated by endoplasmic reticulum stress after exertional heat stroke injury.
    Article Snippet: .. Data Availability: The transcriptome sequencing data generated and analyzed during the current study are available in the National Center for Biotechnology Information (NCBI) under the BioProject number PRJNA1224851. ..

    Gene Expression:

    Article Title: NSUN2/ALYREF stabilizes m5C-modified circCEP70 to enhance radioresistance in rectal cancer through NEDD8-dependent neddylation and ubiquitination regulation.
    Article Snippet: Background: 5-Methylcytosine (m5C) is an important RNA methylation modification implicated in tumor initiation and progression through its effects on RNA transcription, structural conformation, and stability.. However, the role of the interaction between circular RNAs (circRNAs) and m5C modification in oncogenesis remains limited.. This study aimed to elucidate the molecular mechanism by which m5C-modified circCEP70 facilitates radioresistance in rectal cancer (RC).



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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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    Image Search Results


    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