Dataset Information

Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton.

ABSTRACT: Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Our results reveal a dynamic and diverse transcriptional map in cotton: tissue-specific gene expression, alternative usage of TSSs and polyadenylation sites, hotspot of alternative splicing, and transcriptional read-through. These regulated events affect many genes in various aspects such as gain or loss of functional RNA motifs and protein domains, fine-tuning of DNA binding activity, and co-regulation for genes in the same complex or pathway. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community.

SUBMITTER: Wang K

PROVIDER: S-EPMC6797763 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton.

Wang Kun K Wang Dehe D Zheng Xiaomin X Qin Ai A Zhou Jie J Guo Boyu B Chen Yanjun Y Wen Xingpeng X Ye Wen W Zhou Yu Y Zhu Yuxian Y

Nature communications 20191017 1

Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Our ...[more]

PMID: 31624240

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Project description:Rationale: V-domain immunoglobulin suppressor of T cell activation (VISTA) is a novel inhibitory immune checkpoint molecule. Vsir-/- mice have exacerbated psoriasis-like skin inflammation. The immune cell subsets involved in inflammation in Vsir-/- psoriatic mice are largely unknown. We have used scRNA-seq as an unbiased profiling strategy to study the heterogeneity of immune cells at a single cell level in the skin of Vsir-/- psoriatic mice. Methods: In the present study, the right ear and shaved back skin of wild type and Vsir-/- mice were treated with IMQ for 5 consecutive days to induce psoriasis-like dermatitis. Then, the single-cell RNA sequencing analysis of mouse back skin lesions was performed using 10 × Genomics technique. Results: We identified 12 major cell subtypes among 23,258 cells. The major populations of the skin cells included macrophages, dendritic cells and fibroblasts. Macrophages constituted the main immune cell population in the WT (61.29%) and Vsir-/- groups (77.7%). It should be noted that DCs and fibroblasts were expanded in the Vsir-/- psoriatic mice. Furthermore, the gene expression signatures were assessed. We observed that Hspb1 and Cebpb were significantly upregulated in the Vsir-/- psoriatic mice. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these subsets and uncovered putative functions of each cell type. Date analysis resulted in the discovery of a number of novel psoriasis-associated genes in Vsir-/- mice. Conclusion: We present a comprehensive single-cell landscape of the skin immune cells in Vsir-/- psoriatic mice. These unprecedented data uncovered the transcriptional landscape and phenotypic heterogeneity of skin macrophages in psoriasis and identified their gene expression signature suggesting specialized functions in Vsir-/- mice. Our findings will open novel opportunities to investigate the role of VISTA in driving psoriasis.

Dataset Information

Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton.

Publications

Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton.

Similar Datasets

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