小柯机器人

浙江大学医学院Guoji Guo，Xiaoping Han和Jingjing Wang共同合作近期取得重要工作进展，他们通过对对跨物种单细胞谱图的深度学习确定了细胞类型背后的保守调控程序。相关研究成果2022年10月13日在线发表于《自然—遗传学》杂志上。

研究人员生成了斑马鱼、果蝇和蚯蚓的全身单细胞转录组图谱。随后整合了8个代表性的后生动物物种的细胞图谱来研究基因在进化过程中的调节。利用这些统一构建的跨物种图谱，研究人员开发了一种基于深度学习的策略，Nvwa，来预测基因表达并识别单细胞水平的调控序列。

该研究团队系统地比较了细胞类型特异性转录因子，以揭示在脊椎动物和无脊椎动物中的保守遗传调控。他们的工作提供了宝贵的资源，并为研究不同生物系统的调控提供了有价值的参考和新策略。

据介绍，尽管在生成和分析参考基因组方面做出了广泛的努力，但对于大多数物种来说，仍缺乏预测基因调控和细胞命运决定的遗传模型。

附：英文原文

Title: Deep learning of cross-species single-cell landscapes identifies conserved regulatory programs underlying cell types

Author: Li, Jiaqi, Wang, Jingjing, Zhang, Peijing, Wang, Renying, Mei, Yuqing, Sun, Zhongyi, Fei, Lijiang, Jiang, Mengmeng, Ma, Lifeng, E, Weigao, Chen, Haide, Wang, Xinru, Fu, Yuting, Wu, Hanyu, Liu, Daiyuan, Wang, Xueyi, Li, Jingyu, Guo, Qile, Liao, Yuan, Yu, Chengxuan, Jia, Danmei, Wu, Jian, He, Shibo, Liu, Huanju, Ma, Jun, Lei, Kai, Chen, Jiming, Han, Xiaoping, Guo, Guoji

Issue&Volume: 2022-10-13

Abstract: Despite extensive efforts to generate and analyze reference genomes, genetic models to predict gene regulation and cell fate decisions are lacking for most species. Here, we generated whole-body single-cell transcriptomic landscapes of zebrafish, Drosophila and earthworm. We then integrated cell landscapes from eight representative metazoan species to study gene regulation across evolution. Using these uniformly constructed cross-species landscapes, we developed a deep-learning-based strategy, Nvwa, to predict gene expression and identify regulatory sequences at the single-cell level. We systematically compared cell-type-specific transcription factors to reveal conserved genetic regulation in vertebrates and invertebrates. Our work provides a valuable resource and offers a new strategy for studying regulatory grammar in diverse biological systems.

DOI: 10.1038/s41588-022-01197-7

Source: https://www.nature.com/articles/s41588-022-01197-7

Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex