{
  "id": 12225541,
  "title": "Reconstructing donor genotypes from scRNA-seq for downstream eQTL and HLA-TCR analysis",
  "url": "https://urgent.news/2026/10/05/reconstructing-donor-genotypes-from-scrna-seq-for-downstream-eqtl-and",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-05T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755703v1?rss=1"
  },
  "original_language": "en",
  "account": "In the field of single-cell genomics, researchers have developed a novel bioinformatic approach called scTAPAS, or single-cell Transcriptome Allelic Prediction and Association Studies. This innovative framework addresses the challenge of lacking matched genotype data in single-cell eQTL studies, which hinders their wider application. By directly reconstructing donor genotypes from single-cell RNA-sequencing reads and subsequent genetic analysis, scTAPAS opens up new avenues for downstream genetic analysis.\n\nWhen applied to five datasets from the COVID-19 Multi-omic Blood Atlas (COMBAT), scTAPAS demonstrates its effectiveness in generating genotype dosages that are sufficiently accurate for association testing. Remarkably, despite only testing 18.0% of the variants available through conventional array-based genotyping and imputation, scTAPAS manages to recover 68.6% of cell type-eGene pairs identified using traditional methods. The concordance in effect sizes between the two approaches is strong, underscoring the reliability of scTAPAS.\n\nFurthermore, the scTAPAS-derived variants prove to be invaluable for imputing classical HLA alleles, enabling HLA-aware QTL analyses. This groundbreaking capability allows researchers to explore associations between HLA variation and TCR repertoire at unprecedented single-cell resolution. By utilizing matched single-cell TCR-sequencing data, scTAPAS uncovers CD4+ T cell-specific associations between HLA class II alleles and T-cell receptor (TCR) Va gene segment usage, demonstrating the potential of integrating HLA types with TCR sequencing at a single-cell level.\n\nThe implications of these findings are far-reaching. The genetic information recovered from single-cell RNA sequencing data can now support both regulatory and immunogenetic association analyses, significantly expanding the discovery potential of single-cell cohorts where conventional genotyping or HLA typing is not feasible. This pioneering work paves the way for more comprehensive and precise investigations into the interplay between genetics, gene expression, and cellular responses, ultimately advancing our understanding of complex biological phenomena.",
  "summary": "Single-cell eQTL studies can reveal heterogeneous genetic effects on gene expression that vary with cell type, but their wider application has been constrained by the frequent absence of matched genotype data. Here, we present single-cell Transcriptome Allelic Prediction and Association Studies (scTAPAS), a bioinformatic framework for reconstructing donor genotypes directly from single-cell…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}