Ectopic expression of DNMT3L in human trophoblast stem cells restores features of the placental methylome [PBAT BS-Seq]

The placental DNA methylation landscape is unique, with widespread partially methylated domains (PMDs) and hundreds of placental-specific imprinted domains. Furthermore, the placental 'methylome' has been the focus of extensive study for links with pregnancy complications. Human trophoblast stem cells (hTSCs) offer exciting potential for functional epigenetic studies; however, whether the hTSC epigenome recapitulates primary cytotrophoblast, remains poorly described. In this study, we demonstrate that hTSCs exhibit an atypical methylome, with DNA methylation present over transcribed gene bodies but a complete loss of placental PMDs. Using single-cell RNA-seq from human embryogenesis, hTSCs display a notable absence of DNMT3L expression. Ectopic expression of DNMT3L in hTSCs restored placental PMDs. DNMT3L-expressing hTSCs showed comparable stemness but failed to syncytialise in organoid culture, associated with hypermethylation of STB transcription factor motifs. These findings reveal that DNMT3L is essential in establishing the human placental methylome and that DNMT3L downregulation is necessary for successful trophoblast differentiation. Overall design: To understand determinants of the DNA methylation landscape in hTSCs, we cultured blastocyst- (BTS11) and 1st trimester cytotrophoblast- (CT29) derived hTSCs in 2D conditions (Okae et al., 2018), 2D in organoid media, 3D as organoids (Sheridan et al., 2021), and as organoids cultured in hypoxic conditions. We hypothesized that the absence of DNMT3L from cultured hTSCs results in almost exclusive recruitment of DNMT3B to gene bodies leading to a loss of inter-genic partially methylated domains. To test this, we conducted overexpression (OE) experiments in BTS11 and CT29 hTSCs through lentiviral transduction of DNMT3L, in comparison to a control plasmid. Using post-bisulphite adaptor tagging (PBAT) bisulphite-sequencing, we assayed genome-wide DNA methylation patterns in each cell line and condition and compared to published datasets.