SummaryIncreasing evidence of functional and transcriptional heterogeneity in phenotypically similar cells examined individually has prompted interest in obtaining parallel methylome data. We describe the development and application of such a protocol to index-sorted murine and human hematopoietic cells that are highly enriched in their content of functionally defined stem cells. Utilizing an optimized single-cell bisulfite sequencing protocol, we obtained quantitative DNA methylation measurements of up to 5.7 million CpGs in single hematopoietic cells. In parallel, we developed an analytical strategy (PDclust) to define single-cell DNA methylation states through pairwise comparisons of single-CpG methylation measurements. PDclust revealed that a single-cell epigenetic state can be described by a small (<1%) stochastically sampled fraction of CpGs and that these states are reflective of cell identity and state. Using relationships revealed by PDclust, we derive near complete methylomes for epigenetically distinct subpopulations of hematopoietic cells enriched for functional stem cell content.

The genomes of myeloid malignancies are characterized by epigenomic abnormalities. Heterozygous, inactivating ten-eleven translocation 2 (TET2) mutations and neomorphic isocitrate dehydrogenase (IDH) mutations are recurrent and mutually exclusive in acute myeloid leukaemia genomes. Ascorbic acid (vitamin C) has been shown to stimulate the catalytic activity of TET2 in vitro and thus we sought to explore its effect in a leukaemic model expressing IDH1R132H. Vitamin C treatment induced an IDH1R132H-dependent reduction in cell proliferation and an increase in expression of genes involved in leukocyte differentiation. Vitamin C induced differentially methylated regions that displayed a significant overlap with enhancers implicated in myeloid differentiation and were enriched in sequence elements for the haematopoietic transcription factors CEBPβ, HIF1α, RUNX1 and PU.1. Chromatin immunoprecipitation sequencing of PU.1 and RUNX1 revealed a significant loss of PU.1 and increase of RUNX1-bound DNA elements accompanied by their demethylation following vitamin C treatment. In addition, vitamin C induced an increase in H3K27ac flanking sites bound by RUNX1. On the basis of these data we propose a model of vitamin C-induced epigenetic remodelling of transcription factor-binding sites driving differentiation in a leukaemic model.

Aging is associated with significant changes in the hematopoietic system, including increased inflammation, impaired hematopoietic stem cell (HSC) function, and increased incidence of myeloid malignancy. Inflammation of aging (“inflammaging”) has been proposed as a driver of age-related changes in HSC function and myeloid malignancy, but mechanisms linking these phenomena remain poorly defined. We identified loss of miR-146a as driving aging-associated inflammation in AML patients. miR-146a expression declined in old wild-type mice, and loss of miR-146a promoted premature HSC aging and inflammation in young miR-146a–null mice, preceding development of aging-associated myeloid malignancy. Using single-cell assays of HSC quiescence, stemness, differentiation potential, and epigenetic state to probe HSC function and population structure, we found that loss of miR-146a depleted a subpopulation of primitive, quiescent HSCs. DNA methylation and transcriptome profiling implicated NF-κB, IL6, and TNF as potential drivers of HSC dysfunction, activating an inflammatory signaling relay promoting IL6 and TNF secretion from mature miR-146a−/− myeloid and lymphoid cells. Reducing inflammation by targeting Il6 or Tnf was sufficient to restore single-cell measures of miR-146a−/− HSC function and subpopulation structure and reduced the incidence of hematological malignancy in miR-146a−/− mice. miR-146a−/− HSCs exhibited enhanced sensitivity to IL6 stimulation, indicating that loss of miR-146a affects HSC function via both cell-extrinsic inflammatory signals and increased cell-intrinsic sensitivity to inflammation. Thus, loss of miR-146a regulates cell-extrinsic and -intrinsic mechanisms linking HSC inflammaging to the development of myeloid malignancy.

Elucidation of the identity and diversity of mechanisms that sustain long-term human blood cell production remains an important challenge. Previous studies indicate that, in adult mice, this property is vested in cells identified uniquely by their ability to clonally regenerate detectable, albeit highly variable levels and types, of mature blood cells in serially transplanted recipients. From a multi-parameter analysis of the molecular features of very primitive human cord blood cells that display long-term cell outputs in vitro and in immunodeficient mice, we identified a prospectively separable CD33CD34CD38CD45RACD90CD49f phenotype with serially transplantable, but diverse, cell output profiles. Single-cell measurements of the mitogenic response, and the transcriptional, DNA methylation and 40-protein content of this and closely related phenotypes revealed subtle but consistent differences both within and between each subset. These results suggest that multiple regulatory mechanisms combine to maintain different cell output activities of human blood cell precursors with high regenerative potential.

We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic and published single-cell CpG datasets, we show that Epiclomal outperforms non-probabilistic methods and can handle the inherent missing data characteristic that dominates single-cell CpG genome sequences. Using newly generated single-cell 5mCpG sequencing data, we show that Epiclomal discovers sub-clonal methylation patterns in aneuploid tumour genomes, thus defining epiclones that can match or transcend copy number-determined clonal lineages and opening up an important form of clonal analysis in cancer. Epiclomal

The yeast Sup35 protein is a subunit of the translation termination factor, and its conversion to the [PSI +] prion state leads to more translational read-through. Although extensive studies have been done on [PSI +], changes at the proteomic level have not been performed exhaustively. We therefore used a SILAC-based quantitative mass spectrometry approach and identified 4187 proteins from both [psi −] and [PSI +] strains. Surprisingly, there was very little difference between the two proteomes under standard growth conditions. We found however that several [PSI +] strains harbored an additional chromosome, such as chromosome I. Albeit, we found no evidence to support that [PSI +] induces chromosomal instability (CIN). Instead we hypothesized that the selective pressure applied during the establishment of [PSI +]-containing strains could lead to a supernumerary chromosome due to the presence of the ade1-14 selective marker for translational read-through. We therefore verified that there was no prevalence of disomy among newly generated [PSI +] strains in absence of strong selection pressure. We also noticed that low amounts of adenine in media could lead to higher levels of mitochondrial DNA in [PSI +] in ade1-14 cells. Our study has important significance for the establishment and manipulation of yeast strains with the Sup35 prion.

We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and impute missing values. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer. Epiclomal is written in R and Python and is available at https://github.com/shahcompbio/Epiclomal.

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