Deciphering cell states and genealogies of human hematopoiesis with single-cell multi-omics [Young2]

The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived hematopoietic stem cells (HSCs). Perturbations to this process underlie a diverse set of diseases, but the clonal contributions to human hematopoiesis and how this changes with age remain incompletely understood. While recent insights have emerged from barcoding studies in model systems, simultaneous detection of cell states and phylogenies from natural barcodes in humans has been challenging, which has limited the ability to explore functional differences between HSC clones. Here, we introduce an improved single-cell lineage tracing system based on deep detection of naturally-occurring mitochondrial DNA (mtDNA) mutations with simultaneous readout of transcriptional states and chromatin accessibility. We use this system to define the clonal architecture of HSCs, and map the physiological state and output of these clones. We uncover functional heterogeneity in HSC clones, which is stable over months and manifests as differences in total HSC output as well as biases toward the production of different mature blood and immune lineages. We also find that the diversity of HSC clones decreases dramatically with age leading to an oligoclonal structure with multiple distinct clonal expansions. Our study thus provides the first clonally-resolved and cell-state aware atlas of human hematopoiesis at single-cell resolution revealing an unappreciated functional diversity of human HSC clones both in young and aged individuals and more broadly paves the way for refined studies of clonal dynamics across a range of tissues in human health and disease. Overall design: We developed single-cell Regulatory multi-omics with Deep Mitochondrial mutation profiling (ReDeeM), which is a modified massive parallel single cell protocol to simultaneously profile multi-omics with deep mtDNA sequencing based on the 10X Genomics platform. With ReDeeM, three separate libraries are generated, including enriched mtDNA library for deep sequencing and mutation profiling, RNA library for gene expression, as well as ATAC library for chromatin accessibility profiling, all of which are linked via matchable single cell barcodes. Following the principle of our previous work, we firstly modified the droplet-based 10X genomics multi-omics protocol (Catalog #100283) by processing the whole cell instead of nuclei with fixation and mild permeabilization to maximally retain mitochondrial DNA. Next, we designed mtDNA specific probe sets to enrich the mitochondrial fragments using DNA hybridization. The RNA and ATAC library preps follow the standard 10X protocol with some modifications. More method details are described in the method section and an open ReDeeM Protocol is available. ReDeeM is further computationally supported by consensus variant calling pipeline redeemV , and an inhouse R package redeemR for the downstream mutation quality control, as well as single cell phylogenetic and integrative analysis.

人体造血系统通过有限数量的长寿造血干细胞（hematopoietic stem cells, HSCs）的分化与大规模扩增得以维持。该过程的紊乱是多种疾病的共同基础，但人类造血过程中的克隆贡献及其随年龄的变化仍未被完全阐明。尽管近年来通过模型系统中的条形码研究取得了诸多进展，但在人类中同时检测天然条形码的细胞状态与系统发育一直颇具挑战，这限制了我们对造血干细胞克隆间功能差异的探索能力。在此，我们提出一种改进的单细胞谱系追踪系统，该系统可深度检测天然存在的线粒体DNA（mitochondrial DNA, mtDNA）突变，并同时读取转录状态与染色质可及性。我们利用该系统解析了造血干细胞的克隆架构，并绘制了这些克隆的生理状态与输出模式。我们发现造血干细胞克隆存在功能异质性，该异质性可稳定维持数月，表现为总造血干细胞输出量的差异，以及向不同成熟血液与免疫谱系分化的偏向性。我们还发现，造血干细胞克隆的多样性随年龄增长显著降低，最终形成由多个不同克隆扩增构成的寡克隆结构。因此，本研究首次在单细胞分辨率下提供了人类造血过程的克隆解析且兼具细胞状态感知的图谱，揭示了年轻与老年个体中人类造血干细胞克隆此前未被认识的功能多样性，并为在人类健康与疾病的多种组织中开展更精细的克隆动态研究奠定了基础。整体实验设计：我们开发了结合深度线粒体突变谱分析的单细胞调控多组学技术（Regulatory multi-omics with Deep Mitochondrial mutation profiling, ReDeeM），该技术基于10X Genomics平台，是一种改良的大规模并行单细胞实验方案，可同时结合深度mtDNA测序进行多组学分析。通过ReDeeM，可生成三个独立文库：用于深度测序与突变谱分析的富集型mtDNA文库、用于基因表达分析的RNA文库，以及用于染色质可及性分析的ATAC文库，所有文库均可通过匹配的单细胞条形码进行关联。基于我们此前工作的原理，我们首先对基于液滴的10X Genomics多组学实验方案（Catalog #100283）进行了改良：采用固定与轻度透化处理完整细胞而非细胞核，以最大程度保留线粒体DNA。随后，我们设计了mtDNA特异性探针组，通过DNA杂交富集线粒体片段。RNA与ATAC文库制备则遵循标准10X实验方案并进行了部分修改。更多实验方法细节详见方法部分，公开的ReDeeM实验方案已可获取。ReDeeM还得到了配套计算工具的支持：一致性变异检测流程redeemV，以及用于下游突变质量控制、单细胞系统发育与整合分析的自研R包redeemR。