西安交通大学叶凯团队宣布他们研究借助ANNEVO实现高精度的从头基因注释。该项成果发表在2026年3月12日出版的《自然—方法学》上。

了基于专家的基因组语言模型ANNEVO，该模型直接模拟了来自不同基因组的远端序列依赖和联合进化关系，从而实现了精确的从头开始基因注释。通过对566种系统发育不同物种的广泛基准测试，研究人员证明了ANNEVO大大优于现有的从头算方法，并实现了与最先进的注释管道相当的性能。

此外，ANNEVO的独立性从外部证据允许它提供更完整的注释比参考注释范围广泛的物种，同时纠正错误。这些进步将改善基因组序列的解释，并提供一个能够整合进化见解的框架。

据了解，准确的基因注释对于破译基因组序列到其功能角色的映射至关重要。然而，目前的方法难以模拟复杂的基因传递模式，如垂直遗传和水平基因转移。

附：英文原文

Title: Highly accurate ab initio gene annotation with ANNEVO

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

Issue&Volume: 2026-03-12

Abstract: 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.

DOI: 10.1038/s41592-026-03036-7

Source: https://www.nature.com/articles/s41592-026-03036-7