{
  "abstract": "Large-scale genomic language models (gLMs) hold promise for modeling gene regulation, yet their ability to capture personal gene expression variations remains unresolved. We developed xDecoder, a unified decoding framework that utilizes gLMs and sequence-to-function (S2F) embeddings to learn how personal genetic variation shapes gene expression from paired genome-transcriptome data. Compared to the pretrained genomic models, xDecoder with personalized DNA–RNA training makes cross-individual prediction tractable for seen genes in a few-shot setting. However, zero-shot prediction at unseen loci remains unreliable and gene-dependent, revealing a cross-locus transfer bottleneck of current sequence models. Experiments incorporating individual-level chromatin accessibility suggested that regulatory-state information important for unseen-locus prediction is not fully captured by current DNA-only models. Overall, these results highlight the potential utility of the few-shot setting, the limitations of DNA-only models, and point toward multi-omic, variant-aware frameworks as a promising direction for building personalized regulatory models.",
  "abstract_shown": true,
  "affiliations": [
    "School of Biomedical Sciences, University of Hong Kong, Hong Kong, China",
    "School of Computing and Data Science, University of Hong Kong, Hong Kong, China",
    "School of Artificial Intelligence, Shenzhen University, Shenzhen, China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Shumin Li",
      "orcid": "0000-0002-3691-1098"
    },
    {
      "affs": [
        1
      ],
      "name": "Ruibang Luo",
      "orcid": "0000-0001-9711-6533"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Yuanhua Huang",
      "orcid": "0000-0003-3124-9186"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dr93e66s6x4av.bib",
  "cited_by": 1,
  "doi": "10.1038/s44320-026-00238-1",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13728230/",
  "id": "dr93e66s6x4av",
  "issns": [
    "1744-4292"
  ],
  "landing_url": "https://doi.org/10.1038/s44320-026-00238-1",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
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      "lcc",
      "QH301-705.5"
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      "lcc",
      "R5-920"
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      "openalex",
      "1312|Genomics and Chromatin Dynamics"
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  "openalex": "W7171540344",
  "pdf_url": "https://link.springer.com/content/pdf/10.1038/s44320-026-00238-1.pdf",
  "pmcid": "PMC13728230",
  "pmid": "42521815",
  "published": "2026-07-01",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/dr93e66s6x4av.ris",
  "sources": [
    {
      "first_seen": "2026-11-06T12:23:57Z",
      "native_id": "PMC13728230",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s44320-026-00238-1"
    },
    {
      "first_seen": "2026-11-08T14:21:03Z",
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      "url": "https://doi.org/10.1038/s44320-026-00238-1"
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  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Genomics and Chromatin Dynamics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "xDecoder unlocks the potential of genomic foundation models for few-shot personal gene expression prediction",
  "title_text": "xDecoder unlocks the potential of genomic foundation models for few-shot personal gene expression prediction",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T14:21:03Z",
  "url": "https://research.draconitic.com/paper/dr93e66s6x4av",
  "venue": "Molecular Systems Biology",
  "versions": []
}