利用基因变异性的无标记单细胞RNA多重分析

Label-free single-cell RNA multiplexing leveraging genetic variability.

作者信息

Hoeft Konrad, Bleckwehl Tore, Schumacher David, Kim Hyojin, Meyer Robert, Long Qingqing, Zhang Ling, Möller Christian, Clahsen-van Groningen Marian C, Babler Anne, Saritas Turgay, Kurth Ingo, Milting Hendrik, Hayat Sikander, Kramann Rafael

机构信息

Department of Medicine 2 (Nephrology, Rheumatology, Clinical Immunology and Hypertension), Medical Faculty, RWTH Aachen University, Aachen, Germany.

Department of Internal Medicine, Nephrology and Transplantation, Erasmus Medical Center, Rotterdam, The Netherlands.

出版信息

Nat Commun. 2024 Dec 5;15(1):10612. doi: 10.1038/s41467-024-54270-6.

DOI:10.1038/s41467-024-54270-6

PMID:39638798

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11621319/

Abstract

Single cell RNA sequencing has provided unprecedented insights into the molecular cues and cellular heterogeneity underlying human disease. However, the high costs and complexity of single cell methods remain a major obstacle for generating large-scale human cohorts. Here, we compare current state-of-the-art single cell multiplexing technologies, and provide a widely applicable demultiplexing method, SoupLadle, that enables simple, yet robust high-throughput multiplexing leveraging genetic variability of patients.

摘要

单细胞RNA测序为深入了解人类疾病背后的分子线索和细胞异质性提供了前所未有的视角。然而，单细胞方法的高成本和复杂性仍然是生成大规模人类队列的主要障碍。在这里，我们比较了当前最先进的单细胞多重技术，并提供了一种广泛适用的解复用方法SoupLadle，该方法能够利用患者的基因变异性实现简单而稳健的高通量多重分析。