{
  "abstract": "Transfer RNA (tRNA) is highly modified and difficult to profile using reverse-transcription-based sequencing. Here, we established a direct RNA sequencing (tRNA-DRS) workflow to simultaneously characterize tRNA abundance and modification signals in mouse liver. The workflow included small-RNA enrichment, deacylation, splint-adapter ligation, barcoding, reverse transcription, and nanopore sequencing on PromethION with modification-aware basecalling. From 1,678,666 raw reads, 1,421,279 (84.67%) reads were retained after 20-200 nt length filtering, and 17,094 uniquely mapped reads (MAPQ [≥] 10) were obtained. These reads covered 244 tRNA genes and represented all 23 tRNA isotypes. tRNA abundance was strongly skewed, with Asp, Gly, Ser, and Lys accounting for 56.6% of uniquely mapped reads. Read-body coverage indicated that most uniquely mapped reads spanned substantial portions of tRNA molecules (mean 71.1%, median 75.9%; 83.3% reads covering [≥]50% of the reference). Modification analysis identified 41,013 candidate sites, of which 711 passed stringent filtering (modification fraction [≥]50%, coverage [≥]5), spanning eight modification types and dominated by pseudouridine and m5C. Filtered sites showed position-specific clustering and isotype-dependent patterns. Together, these results support tRNA-DRS as a practical single-assay framework for simultaneous tRNA expression and epitranscriptomic profiling in mammalian tissue.",
  "abstract_shown": true,
  "affiliations": [
    "Benagen Institute"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 14,
  "authors": [
    {
      "name": "S. Dai"
    },
    {
      "name": "Z. Tian"
    },
    {
      "affs": [
        0
      ],
      "name": "Y. Zhang"
    },
    {
      "name": "X. Li"
    },
    {
      "name": "X. Yi"
    },
    {
      "name": "T. Qiu"
    },
    {
      "name": "L. Yang"
    },
    {
      "name": "J. Ke"
    },
    {
      "name": "M. Chen"
    },
    {
      "name": "J. Huang"
    },
    {
      "name": "X. Hu"
    },
    {
      "name": "Y. Li"
    },
    {
      "name": "H. Chen"
    },
    {
      "affs": [
        0
      ],
      "name": "T. Zhang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e6km4g6esn7az.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.04.754913",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.04.754913v1.full",
  "id": "e6km4g6esn7az",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.04.754913v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "molecular biology"
    ],
    [
      "openalex",
      "1312|RNA modifications and cancer"
    ]
  ],
  "openalex": "W7220699308",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.04.754913v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/e6km4g6esn7az.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:14Z",
      "native_id": "10.64898/2026.10.04.754913",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.04.754913v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:molecular biology",
      "subfield": "molecular-biology"
    }
  ],
  "title": "A direct RNA sequencing workflow for simultaneous profiling of tRNA abundance and modifications in mouse liver",
  "title_text": "A direct RNA sequencing workflow for simultaneous profiling of tRNA abundance and modifications in mouse liver",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:14Z",
  "url": "https://research.draconitic.com/paper/e6km4g6esn7az",
  "venue": "bioRxiv",
  "versions": []
}