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<p>Accurate gene annotation is essential for deciphering the mapping from genomic sequences to their functional roles. However, current methods struggle to model complex gene transmission patterns, such as vertical inheritance and horizontal gene transfer. Here we introduce ANNEVO, a mixture of experts-based genomic language model that directly models distal sequence dependencies and joint evolutionary relationships from diverse genomes, enabling precise ab initio gene annotation. Through extensive benchmarking on 566 phylogenetically diverse species, we demonstrate that ANNEVO substantially outperforms existing ab initio methods and achieves performance comparable to state-of-the-art annotation pipelines. Furthermore, ANNEVO’s independence from external evidence allows it to deliver more complete annotations than reference annotations for a broad range of species while correcting errors within them. These advancements will improve genome sequence interpretation and provide a framework capable of integrating evolutionary insights.</p>

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Highly accurate ab initio gene annotation with ANNEVO

  • 期刊论文

  • 发表日期：

    2026年3月12日

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  • Pengyu Zhang,
  • Tun Xu,
  • Songbo Wang,
  • Xiaofei Yang,
  • Peisen Sun,
  • Peng Jia,
  • Jiadong Lin,
  • Bo Wang,
  • Yizhe Zhang,
  • Deyu Meng,
  • Stephen J. Bush,
  • Zemin Ning,
  • Kai Ye

摘要

Accurate gene annotation is essential for deciphering the mapping from genomic sequences to their functional roles. However, current methods struggle to model complex gene transmission patterns, such as vertical inheritance and horizontal gene transfer. Here we introduce ANNEVO, a mixture of experts-based genomic language model that directly models distal sequence dependencies and joint evolutionary relationships from diverse genomes, enabling precise ab initio gene annotation. Through extensive benchmarking on 566 phylogenetically diverse species, we demonstrate that ANNEVO substantially outperforms existing ab initio methods and achieves performance comparable to state-of-the-art annotation pipelines. Furthermore, ANNEVO’s independence from external evidence allows it to deliver more complete annotations than reference annotations for a broad range of species while correcting errors within them. These advancements will improve genome sequence interpretation and provide a framework capable of integrating evolutionary insights.