A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing

Combinatorial quantification of 5mC and 5hmC at individual CpG dyads and the transcriptome in single cells reveals modulators of DNA methylation maintenance fidelity

Inheritance of 5-methylcytosine from one cell generation to the next by DNA methyltransferase 1 (DNMT1) plays a key role in regulating cellular identity. While recent work has shown that the activity of DNMT1 is imprecise, it remains unclear how the fidelity of DNMT1 is tuned in different genomic and cell state contexts. Here we describe Dyad-seq, a method to quantify the genome-wide methylation status of cytosines at the resolution of individual CpG dinucleotides to find that the fidelity of DNMT1-mediated maintenance methylation is related to the local density of DNA methylation and the landscape of histone modifications. To gain deeper insights into methylation/demethylation turnover dynamics, we first extended Dyad-seq to quantify all combinations of 5-methylcytosine and 5-hydroxymethylcytosine at individual CpG dyads. Next, to understand how cell state transitions impact maintenance methylation, we scaled the method down to jointly profile genome-wide methylation levels, maintenance methylation fidelity and the transcriptome from single cells (scDyad&T-seq). Using scDyad&T-seq, we demonstrate that, while distinct cell states can substantially impact the activity of the maintenance methylation machinery, locally there exists an intrinsic relationship between DNA methylation density, histone modifications and DNMT1-mediated maintenance methylation fidelity that is independent of cell state.

Simultaneous single-cell analysis of 5mC and 5hmC with SIMPLE-seq

Dynamic 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) modifications to DNA regulate gene expression in a cell-type-specific manner and are associated with various biological processes, but the two modalities have not yet been measured simultaneously from the same genome at the single-cell level. Here we present SIMPLE-seq, a scalable, base resolution method for joint analysis of 5mC and 5hmC from thousands of single cells. Based on orthogonal labeling and recording of 'C-to-T' mutational signals from 5mC and 5hmC sites, SIMPLE-seq detects these two modifications from the same molecules in single cells and enables unbiased DNA methylation dynamics analysis of heterogeneous biological samples. We applied this method to mouse embryonic stem cells, human peripheral blood mononuclear cells and mouse brain to give joint epigenome maps at single-cell and single-molecule resolution. Integrated analysis of these two cytosine modifications reveals distinct epigenetic patterns associated with divergent regulatory programs in different cell types as well as cell states.

Integrated single-cell sequencing of 5-hydroxymethylcytosine and genomic DNA using scH&G-seq

The asymmetric distribution of 5-hydroxymethylcytosine (5hmC) between two DNA strands of a chromosome enables endogenous reconstruction of cellular lineages at an individual-cell-division resolution. Further, when integrated with data on genomic variants to infer clonal lineages, this combinatorial information accurately reconstructs larger lineage trees. Here, we provide a detailed protocol for single-cell 5-hydroxymethylcytosine and genomic DNA sequencing (scH&G-seq) to simultaneously quantify 5hmC and genomic DNA from the same cell to reconstruct lineage trees at a single-cell-division resolution.

For complete details on the use and execution of this protocol, please refer to Wangsanuwat et al., 2021.

•

scH&G-seq enables quantification of 5hmC and genomic DNA (gDNA) from the same cell

•

Strand-specific 5hmC enables reconstructing trees at a single-cell-division resolution

•

Genomic variants allow identification of clonal subtrees within a lineage tree

•

Integrated 5hmC and gDNA detection improves prediction accuracy of larger lineage trees