小柯机器人

科学家利用新算法在单细胞分辨率下实现变异体到功能的映射
2022-06-11 15:03

美国波士顿儿童医院Vijay G. Sankaran研究团队利用新算法在单细胞分辨率下实现变异体到功能的映射。相关论文于2022年6月6日在线发表在《自然—生物技术》杂志上。

研究人员表示,全基因组关联研究与单细胞基因组图谱相结合,可以深入了解致病遗传变异的机制。然而,识别疾病相关或性状相关的细胞类型、状态和轨迹往往受到稀疏性和噪声的阻碍,特别是在分析单细胞表观基因组数据时。

为了克服这些挑战,研究人员提出了SCAVENGE,一种使用网络传播的计算算法,在单细胞分辨率下将因果变体映射到其相关的细胞环境中。研究人员展示了SCAVENGE如何帮助确定人类遗传变异的关键生物机制,将该方法应用于人类造血不同阶段的血液特征,应用于增加严重2019冠状病毒疾病(COVID-19)风险的单核细胞亚群,以及易导致急性白血病的中间淋巴细胞发育状态。

这个方法不仅提供了一个在单细胞分辨率下实现变体到功能洞察的框架,而且还提出了一个更普遍的战略,能够最大限度地利用单细胞基因组数据进行推断。

附:英文原文

Title: Variant to function mapping at single-cell resolution through network propagation

Author: Yu, Fulong, Cato, Liam D., Weng, Chen, Liggett, L. Alexander, Jeon, Soyoung, Xu, Keren, Chiang, Charleston W. K., Wiemels, Joseph L., Weissman, Jonathan S., de Smith, Adam J., Sankaran, Vijay G.

Issue&Volume: 2022-06-06

Abstract: Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data. 

DOI: 10.1038/s41587-022-01341-y

Source: https://www.nature.com/articles/s41587-022-01341-y

Nature Biotechnology:《自然—生物技术》,创刊于1996年。隶属于施普林格·自然出版集团,最新IF:68.164
官方网址:https://www.nature.com/nbt/
投稿链接:https://mts-nbt.nature.com/cgi-bin/main.plex


本期文章:《自然—生物技术》:Online/在线发表

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