美国哈佛大学Vijay G. Sankaran等研究人员合作开发出大规模平行单细胞线粒体DNA基因分型和染色质分析方法。这一研究成果于2020年8月12日在线发表在《自然—生物技术》上。
Title: Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling
Author: Caleb A. Lareau, Leif S. Ludwig, Christoph Muus, Satyen H. Gohil, Tongtong Zhao, Zachary Chiang, Karin Pelka, Jeffrey M. Verboon, Wendy Luo, Elena Christian, Daniel Rosebrock, Gad Getz, Genevieve M. Boland, Fei Chen, Jason D. Buenrostro, Nir Hacohen, Catherine J. Wu, Martin J. Aryee, Aviv Regev, Vijay G. Sankaran
Abstract: Natural mitochondrial DNA (mtDNA) mutations enable the inference of clonal relationships among cells. mtDNA can be profiled along with measures of cell state, but has not yet been combined with the massively parallel approaches needed to tackle the complexity of human tissue. Here, we introduce a high-throughput, droplet-based mitochondrial single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), a method that combines high-confidence mtDNA mutation calling in thousands of single cells with their concomitant high-quality accessible chromatin profile. This enables the inference of mtDNA heteroplasmy, clonal relationships, cell state and accessible chromatin variation in individual cells. We reveal single-cell variation in heteroplasmy of a pathologic mtDNA variant, which we associate with intra-individual chromatin variability and clonal evolution. We clonally trace thousands of cells from cancers, linking epigenomic variability to subclonal evolution, and infer cellular dynamics of differentiating hematopoietic cells in vitro and in vivo. Taken together, our approach enables the study of cellular population dynamics and clonal properties in vivo. Combining droplet-based ATAC-seq and mitochondrial DNA sequencing reveals clonal variation in human cells and tissues.