Dataset Information

Seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

ABSTRACT: The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer the relative proportions of 10 major immune cells in mouse tissues from RNA-Seq data. The performance of seq-ImmuCC was evaluated among multiple computational algorithms, transcriptional platforms, and simulated and experimental datasets. The test results showed its stable performance and superb consistency with experimental observations under different conditions. With seq-ImmuCC, we generated the comprehensive landscape of immune cell compositions in 27 normal mouse tissues and extracted the distinct signatures of immune cell proportion among various tissue types. Furthermore, we quantitatively characterized and compared 18 different types of mouse tumor tissues of distinct cell origins with their immune cell compositions, which provided a comprehensive and informative measurement for the immune microenvironment inside tumor tissues. The online server of seq-ImmuCC are freely available at http://wap-lab.org:3200/immune/.

SUBMITTER: Chen Z

PROVIDER: S-EPMC5996037 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

Chen Ziyi Z Quan Lijun L Huang Anfei A Zhao Qiang Q Yuan Yao Y Yuan Xuye X Shen Qin Q Shang Jingzhe J Ben Yinyin Y Qin F Xiao-Feng FX Wu Aiping A

Frontiers in immunology 20180605

The RNA sequencing approach has been broadly used to provide gene-, pathway-, and network-centric analyses for various cell and tissue samples. However, thus far, rich cellular information carried in tissue samples has not been thoroughly characterized from RNA-Seq data. Therefore, it would expand our horizons to better understand the biological processes of the body by incorporating a cell-centric view of tissue transcriptome. Here, a computational model named seq-ImmuCC was developed to infer ...[more]

PMID: 29922297

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Project description:Sugarcane smut caused by Sporisorium scitamineum is a critical fungal disease in the sugarcane industry. However, molecular mechanistic studies of pathological response of sugarcane to S. scitamineum are scarce and preliminary. Here, transcriptome analysis of sugarcane disease induced by S. scitamineum at 24, 48 and 120 h was conducted, using an S. scitamineum-resistant and -susceptible genotype (Yacheng05-179 and "ROC"22). The reliability of Illumina data was confirmed by real-time quantitative PCR. In total, transcriptome sequencing of eight samples revealed gene annotations of 65,852 unigenes. Correlation analysis of differentially expressed genes indicated that after S. scitamineum infection, most differentially expressed genes and related metabolic pathways in both sugarcane genotypes were common, covering most biological activities. However, expression of resistance-associated genes in Yacheng05-179 (24-48 h) occurred earlier than those in "ROC"22 (48-120 h), and more transcript expressions were observed in the former, suggesting resistance specificity and early timing of these genes in non-affinity sugarcane and S. scitamineum interactions. Obtained unigenes were related to cellular components, molecular functions and biological processes. From these data, functional annotations associated with resistance were obtained, including signal transduction mechanisms, energy production and conversion, inorganic ion transport and metabolism, and defense mechanisms. Pathway enrichment analysis revealed that differentially expressed genes are involved in plant hormone signal transduction, flavonoid biosynthesis, plant-pathogen interaction, cell wall fortification pathway and other resistance-associated metabolic pathways. Disease inoculation experiments and the validation of in vitro antibacterial activity of the chitinase gene ScChi show that this sugarcane chitinase gene identified through RNA-Seq analysis is relevant to plant-pathogen interactions. In conclusion, expression data here represent the most comprehensive dataset available for sugarcane smut induced by S. scitamineum and will serve as a resource for finally unraveling the molecular mechanisms of sugarcane responses to S. scitamineum.

Dataset Information

Seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

Publications

seq-ImmuCC: Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

Similar Datasets

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