ArticleFrontiers in immunology2021
A Single-Cell Transcriptome Profiling of Anterior Kidney Leukocytes From Nile Tilapia (
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed, 44 citations in OpenAlex.
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- Single-Cell Transcriptome Profiling Reveals Conserved IFNγ-IL8 Signaling-Induced Antibacterial Neutrophil States during Bacterial Infection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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- Comparative Transcriptome Analysis of the Response toBiology · 2023Article
- Single cell genomics as a transformative approach for aquaculture research and innovation.Reviews in aquaculture · 2023Review
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- Teleost fish IgMFrontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Teleost fish anterior kidney (AK) is an important hematopoietic organ with multifarious immune cells, which have immune functions comparable to mammalian bone marrow. Myeloid and lymphoid cells locate in the AK, but the lack of useful specific gene markers and antibody-based reagents for the cell subsets makes the identification of the different cell types difficult. Single-cell transcriptome sequencing enables single-cell capture and individual library construction, making the study on the immune cell heterogeneity of teleost fish AK possible. In this study, we examined the transcriptional patterns of 11,388 AK leukocytes using 10× Genomics single-cell RNA sequencing (scRNA-seq). A total of 22 clusters corresponding to five distinct immune cell subsets were identified, which included B cells, T cells, granulocytes, macrophages, and dendritic cells (DCs). However, the subsets of myeloid cells (granulocytes, macrophages, and DCs) were not identified in more detail according to the known specific markers, even though significant differences existed among the clusters. Thereafter, we highlighted the B-cell subsets and identified them as pro/pre B cells, immature/mature B cells, activated B/plasmablasts, or plasma cells based on the different expressions of the transcription factors (TFs) and cytokines. Clustering of the differentially modulated genes by pseudo-temporal trajectory analysis of the B-cell subsets showed the distinct kinetics of the responses of TFs to cell conversion. Moreover, we classified the T cells and discovered that CD3
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Registered trials
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