Single-cell genome, DNA methylome, and transcriptome sequencing methods have been separately developed. However, to accurately analyze the mechanism by which transcriptome, genome and DNA methylome regulate each other, these omic methods need to be performed in the same single cell. Here we demonstrate a single-cell triple omics sequencing technique, scTrio-seq, that can be used to simultaneously analyze the genomic copy-number variations (CNVs), DNA methylome, and transcriptome of an individual mammalian cell. We show that large-scale CNVs cause proportional changes in RNA expression of genes within the gained or lost genomic regions, whereas these CNVs generally do not affect DNA methylation in these regions. Furthermore, we applied scTrio-seq to 25 single cancer cells derived from a human hepatocellular carcinoma tissue sample. We identified two subpopulations within these cells based on CNVs, DNA methylome, or transcriptome of individual cells. Our work offers a new avenue of dissecting the complex contribution of genomic and epigenomic heterogeneities to the transcriptomic heterogeneity within a population of cells.

The heart is the central organ of the circulatory system, and its proper development is vital for maintaining human life. Here, we used single-cell RNA sequencing to profile the gene expression landscapes of ∼4,000 cardiac cells from human embryos and identified four major types of cells: cardiomyocytes (CMs), cardiac fibroblasts, endothelial cells (ECs), and valvar interstitial cells (VICs). Atrial and ventricular CMs acquired distinct features early in heart development. Furthermore, both CMs and fibroblasts show stepwise changes in gene expression. As development proceeds, VICs may be involved in the remodeling phase, and ECs display location-specific characteristics. Finally, we compared gene expression profiles between humans and mice and identified a series of unique features of human heart development. Our study lays the groundwork for elucidating the mechanisms of in vivo human cardiac development and provides potential clues to understand cardiac regeneration.

DNA methylation is crucial for a wide variety of biological processes, yet no technique suitable for the methylome analysis of DNA methylation at single-cell resolution is available. Here, we describe a methylome analysis technique that enables single-cell and single-base resolution DNA methylation analysis based on reduced representation bisulfite sequencing (scRRBS). The technique is highly sensitive and can detect the methylation status of up to 1.5 million CpG sites within the genome of an individual mouse embryonic stem cell (mESC). Moreover, we show that the technique can detect the methylation status of individual CpG sites in a haploid sperm cell in a digitized manner as either unmethylated or fully methylated. Furthermore, we show that the demethylation dynamics of maternal and paternal genomes after fertilization can be traced within the individual pronuclei of mouse zygotes. The demethylation process of the genic regions is faster than that of the intergenic regions in both male and female pronuclei. Our method paves the way for the exploration of the dynamic methylome landscapes of individual cells at single-base resolution during physiological processes such as embryonic development, or during pathological processes such as tumorigenesis.