Jia Yuran, Dong Hongchao, Li Linhao, Wang Fang, Juan Liran, Wang Yadong, Guo Hongzhe, Zhao Tianyi
Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China.
School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China.
Nucleic Acids Res. 2025 Jan 6;53(D1):D1270-D1277. doi: 10.1093/nar/gkae837.
Understanding how genetic variants influence molecular phenotypes in different cellular contexts is crucial for elucidating the molecular and cellular mechanisms behind complex traits, which in turn has spurred significant advances in research into molecular quantitative trait locus (xQTL) at the cellular level. With the rapid proliferation of data, there is a critical need for a comprehensive and accessible platform to integrate this information. To meet this need, we developed xQTLatlas (http://www.hitxqtl.org.cn/), a database that provides a multi-omics genetic regulatory landscape at cellular resolution. xQTLatlas compiles xQTL summary statistics from 151 cell types and 339 cell states across 55 human tissues. It organizes these data into 20 xQTL types, based on four distinct discovery strategies, and spans 13 molecular phenotypes. Each entry in xQTLatlas is meticulously annotated with comprehensive metadata, including the origin of the tissue, cell type, cell state and the QTL discovery strategies utilized. Additionally, xQTLatlas features multiscale data exploration tools and a suite of interactive visualizations, facilitating in-depth analysis of cell-level xQTL. xQTLatlas provides a valuable resource for deepening our understanding of the impact of functional variants on molecular phenotypes in different cellular environments, thereby facilitating extensive research efforts.
了解基因变异如何在不同细胞环境中影响分子表型,对于阐明复杂性状背后的分子和细胞机制至关重要,这反过来又推动了细胞水平上分子数量性状基因座(xQTL)研究的重大进展。随着数据的迅速增长,迫切需要一个全面且易于使用的平台来整合这些信息。为满足这一需求,我们开发了xQTLatlas(http://www.hitxqtl.org.cn/),这是一个在细胞分辨率下提供多组学遗传调控图谱的数据库。xQTLatlas汇编了来自55种人体组织中151种细胞类型和339种细胞状态的xQTL汇总统计数据。它根据四种不同的发现策略将这些数据组织成20种xQTL类型,并涵盖13种分子表型。xQTLatlas中的每个条目都用全面的元数据进行了精心注释,包括组织来源、细胞类型、细胞状态以及所采用的QTL发现策略。此外,xQTLatlas具有多尺度数据探索工具和一套交互式可视化功能,便于对细胞水平的xQTL进行深入分析。xQTLatlas为加深我们对功能变异在不同细胞环境中对分子表型影响的理解提供了宝贵资源,从而促进广泛的研究工作。