{
  "abstract": "Advances in genome sequencing have enabled phylogenomic studies involving tens or even hundreds of thousands of species. However, scalability remains a major computational challenge for statistically consistent species tree inference at this scale. ASTRAL, the most widely used coalescent-based species tree estimator, remains limited by computational and memory bottlenecks that make ultra-large analyses impractical. Here we present ASTRAL-X, a complete algorithmic redesign of the ASTRAL framework that overcomes these computational limitations. By fundamentally redesigning the underlying data representations, algorithms, and computational framework, ASTRAL-X dramatically reduces running time while lowering memory requirements to nearly the size of the input--the asymptotically optimal bound--thereby enabling statistically consistent species tree inference directly from unrooted gene trees at an unprecedented scale. ASTRAL-X preserves ASTRAL's statistical guarantees and achieves accuracy comparable to state-of-the-art methods across simulated and empirical datasets while reconstructing species trees containing 200,000 and 300,000 taxa in only 5 hours and 12 hours, respectively, using modest computational resources. Notably, ASTRAL-X reconstructed the evolutionary history of 9{,}524 angiosperm species in only 16 minutes. These results enable statistically consistent coalescent-based species tree inference at the scale demanded by emerging Tree of Life initiatives. ASTRAL-X is publicly available at \\url{https://github.com/aaniksahaa/ASTRAL-X}.",
  "abstract_shown": true,
  "affiliations": [
    "Bangladesh University of Engineering and Technology"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "A. Saha"
    },
    {
      "affs": [
        0
      ],
      "name": "M. S. Bayzid"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6tferachpk3df.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.07.31.742122",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.07.31.742122v2.full",
  "id": "6tferachpk3df",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.07.31.742122v2",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1312|Genomics and Phylogenetic Studies"
    ]
  ],
  "openalex": "W7196947094",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.07.31.742122v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-07-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6tferachpk3df.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:26Z",
      "native_id": "10.64898/2026.07.31.742122",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.07.31.742122v2"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "ASTRAL-X: Scaling Coalescent-Based Species Tree Inference to 300,000 Taxa",
  "title_text": "ASTRAL-X: Scaling Coalescent-Based Species Tree Inference to 300,000 Taxa",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:26Z",
  "url": "https://research.draconitic.com/paper/6tferachpk3df",
  "venue": "bioRxiv",
  "versions": []
}