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Related Experiment Video

Updated: Jul 15, 2026

The bm12 Inducible Model of Systemic Lupus Erythematosus (SLE) in C57BL/6 Mice
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SLECA: A Single-Cell Atlas of Systemic Lupus Erythematosus Enabling Rare-Cell Discovery Using Graph Transformer.

Maoteng Duan1,2, Yao Shi1,2, Hao Tian1,2

  • 1School of Mathematics, Shandong University, Jinan, Shandong 250100, China.

Computational and Structural Biotechnology Journal
|July 14, 2026
PubMed
Summary

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Systemic lupus erythematosus (SLE) research now has a comprehensive single-cell atlas (SLECA) to identify rare immune cells. This atlas reveals double-negative T cells (DNTs) expand in SLE and correlate with disease severity.

Area of Science:

  • Immunology
  • Genomics
  • Computational Biology

Background:

  • Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by significant interpatient heterogeneity.
  • This heterogeneity complicates the precise characterization of immune dysregulation.
  • Existing single-cell transcriptomic data is insufficient for identifying and analyzing rare immune cell populations crucial to SLE pathogenesis.

Purpose of the Study:

  • To create the first large-scale single-cell RNA sequencing atlas for SLE (SLECA).
  • To develop a novel graph-transformer framework for discovering and analyzing disease-relevant rare cell populations.
  • To systematically identify and characterize immune cell heterogeneity in SLE.

Main Methods:

  • Integration of 366 SLE samples with standardized clinical and biological metadata.

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Published on: November 1, 2015

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  • Application of a novel graph-transformer framework for scalable data integration and analysis.
  • Systematic identification and characterization of cell types, including rare populations.

    • Main Results:

    • The SLECA atlas resolved 54 distinct cell types, including potentially disease-relevant rare populations.
    • A specific subset, double-negative T cells (DNTs), was identified as a disease-expanded population in SLE.
    • DNT cell abundance positively correlated with clinical SLE severity.
    • In silico perturbation analyses suggested regulatory roles for JUN and EGR1 in DNT cell transcriptional programs.

    Conclusions:

    • SLECA provides a valuable resource for understanding SLE pathogenesis through comprehensive single-cell transcriptomics.
    • Double-negative T cells (DNTs) represent a key cell population expanded in SLE, linked to clinical severity.
    • Further investigation into DNT cells and their regulatory pathways (e.g., JUN, EGR1) may offer therapeutic insights for SLE.