Single-nucleus transcriptomic survey of cell diversity and functional maturation in the postnatal mammalian hearts

A fundamental challenge in understanding cardiac biology and disease is that the remarkable heterogeneity in cell-type composition and functional states have not been well characterized at single-cell resolution in maturing and diseased mammalian hearts. Massively parallel single-nucleus RNA sequencing (snRNA-Seq) has emerged as a powerful tool to address these questions by interrogating the transcriptome of tens of thousands of nuclei isolated from fresh or frozen tissues. snRNA-Seq overcomes the technical challenge of isolating intact single cell from complex tissues including the maturing mammalian hearts, reduces biased recovery of easily dissociated cell types and minimizes aberrant gene expression during the whole-cell dissociation. Here we applied sNucDrop-Seq, a droplet microfluidics-based massively parallel snRNA-Seq method, to investigate the transcriptional landscape of postnatal maturing mouse hearts in both healthy or disease state. By profiling the transcriptome of nearly 20,000 nuclei, we identified major and rare cardiac cell types and revealed significant heterogeneity of cardiomyocytes, fibroblasts and endothelial cells in the postnatal developing heart. When applied to a mouse model of pediatric mitochondrial cardiomyopathy, we uncovered profound cell type-specific modifications of the cardiac transcriptional landscape at single-nucleus resolution, including changes of subtype composition, maturation states and functional remodeling of each cell type. Furthermore, we employed sNucDrop-Seq to decipher the cardiac cell type-specific gene regulatory network (GRN) of GDF15, a heart-derived hormone and clinically important diagnostic biomarker of heart disease. Together, our results present a rich resource for studying cardiac biology and provide new insights into heart disease using an approach broadly applicable to many fields of biomedicine. Single-nucleus RNA sequencing analysis of postnatal maturing mouse hearts in both healthy or disease state解析心脏生物学与疾病的核心挑战之一，在于成熟病变哺乳动物心脏中细胞类型组成与功能状态存在显著异质性，但目前尚未在单细胞分辨率层面得到充分表征。大规模并行单细胞核RNA测序（single-nucleus RNA sequencing, snRNA-Seq）现已成为解决此类问题的有力工具，可对从新鲜或冷冻组织中分离出的数万个细胞核的转录组进行表征分析。snRNA-Seq可克服从包括成熟哺乳动物心脏在内的复杂组织中分离完整单细胞的技术难题，减少对易解离细胞类型的偏倚性富集，并最大限度降低全细胞解离过程中出现的异常基因表达。本研究采用基于液滴微流控的大规模并行snRNA-Seq方法sNucDrop-Seq，对健康与疾病状态下出生后成熟小鼠心脏的转录组图谱进行探究。通过对近2万个细胞核的转录组进行表征，本研究鉴定出主要及罕见心脏细胞类型，并揭示了出生后发育中心脏内心肌细胞、成纤维细胞与内皮细胞的显著异质性。当将该方法应用于儿科线粒体心肌病小鼠模型时，本研究在单细胞核分辨率下揭示了心脏转录组图谱的显著细胞类型特异性改变，包括各细胞类型的亚型组成、成熟状态及功能重塑的变化。此外，本研究利用sNucDrop-Seq解析了GDF15的心脏细胞类型特异性基因调控网络（gene regulatory network, GRN）——GDF15是一种心脏来源的激素，亦是临床上重要的心脏病诊断生物标志物。综上，本研究的结果为心脏生物学研究提供了丰富的资源，并通过一种可广泛应用于生物医学诸多领域的方法，为心脏病研究提供了新的见解。健康与疾病状态下出生后成熟小鼠心脏的单细胞核RNA测序分析