{
  "id": 16446901,
  "title": "Alignment-free discovery of conserved RNA structures in the human genome",
  "url": "https://urgent.news/2026/10/24/alignment-free-discovery-of-conserved-rna-structures-in-the-human",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-24T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.24.761493v1?rss=1"
  },
  "original_language": "en",
  "account": "Functional RNA molecules have historically been identified as conserved RNA structures, with their roles in gene regulation discovered subsequently. Due to imperfect genome alignments, discovering these structures in humans and vertebrates has been challenging. Introducing RLMHelix, a method that identifies candidate conserved RNA structures within single sequences before any alignment, employing a scoring system for helices supported by language-model dependencies and thermodynamics. RLMHelix swiftly scans the transcribed human genome, outperforming traditional thermodynamic scanning by ranking known RNAs higher.\n\nAmong the 15,821 candidates, two-thirds are novel to four prior genome-wide screens, and these candidates align with in-cell probing. Moreover, more than half of these structures maintain their signal in homologous sequences. In eCLIP data and exploratory pull-down assays, higher RLMHelix scores correlate with increased binding by double-stranded RNA-binding proteins. By associating these candidates with their binding proteins, RLMHelix generates testable functional hypotheses, opening a pathway from unidentified human RNA structures to RNA biology and potential therapeutic targets.",
  "summary": "Many functional RNAs were first found as conserved RNA structures, and their roles in gene regulation were identified later. In humans and other vertebrates, imperfect genome alignments have hindered the discovery of such structures. Here we present RLMHelix, which selects candidate conserved RNA structures from single sequences before any alignment by scoring helices supported by language-model…",
  "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."
}