A Highly Sensitive and Robust Method for Genome-wide 5hmC Profiling of Rare Cell Populations

Abstract

We present a highly sensitive and selective chemical labeling and capture approach for genome-wide profiling of 5-hydroxylmethylcytosine (5hmC) using DNA isolated from ∼1,000 cells (nano-hmC-Seal). Using this technology, we assessed 5hmC occupancy and dynamics across different stages of hematopoietic differentiation. Nano-hmC-Seal profiling of purified Tet2-mutant acute myeloid leukemia (AML) murine stem cells allowed us to identify leukemia-specific, differentially hydroxymethylated regions that harbor known and candidate disease-specific target genes with differential 5hmC peaks compared to normal stem cells. The change of 5hmC patterns in AML strongly correlates with differential gene expression, demonstrating the importance of dynamic alterations of 5hmC in regulating transcription in AML. Together, covalent 5hmC labeling offers an effective approach to study and detect DNA methylation dynamics in in vivo disease models and in limited clinical samples.

Figure 1. Nano-hmC-Seal to generate genome-wide 5hmC maps from ultra-low DNA starting materials

(A) Schematic overview of the nano-hmC-Seal approach. (B) Genome browser views of 5hmC signals detected in a 30kb region from libraries generated with 5ng–10 μg of starting genomic DNA from mESCs. (Top) In blue, 5hmC profile obtained using regular hmC-Seal with 10μg genome DNA. Approximately 5–6 ng of genomic DNA could be isolated from 1,000 mESCs (1,000 cells). (C) Scatter plots showing correlation between nano-hmC-Seal replicates with Pearson correlation (r) displayed. Each dot represents a 5hmC-enriched peak. Read counts were transformed to log2 base. From left to right: correlation between replicate libraries prepared from 50 ng and 5 ng mESC genomic DNA, and genomic DNA isolated from 1,000 mESCs, respectively, and between libraries using 1,000 cells with regular hmC-Seal using 10 μg genomic DNA. See also Figure S1, Table S1.

Figure 2. Nano-hmC-Seal provides dynamic 5hmC profiles during early hematopoiesis

(A) Schematic of the hematopoietic differentiation stages. Cell types investigated in this study are outlined. Cell surface phenotypes were LSK (lin⁻ Sca⁺ cKit⁺), MPP (lin⁻ Sca⁺ cKit⁺ CD48⁺ CD150⁻), CMP (lin⁻ Sca⁻ cKit⁺ CD34⁺ CD16/32⁻), MEP (lin⁻ Sca⁻ cKit⁺ CD34⁻ CD16/32⁻), GMP (lin⁻ Sca⁻ cKit⁺ CD34⁺ CD16/32⁺). (B) Relationship of 5hmC profiles in four different types of hematopoiesis stem and progenitor cells. Hierarchical clustering applied to the matrix of sample-to-sample distance based on rlog-transformed read counts in 304,069 detected 5hmC-enriched peaks. (C) Distribution of 5hmC signals at lineage-specific enhancers (from left to right: common enhancers, erythroid enhancer, myeloid enhancers and T/NK cells enhancers). Lineage-specific enhancers were determined based on K-means analysis of H3K4me1 signals (See Figure S2). The genomic locations of enhancers were previously defined (Lara-Astiaso et al., 2014). (D) Representative examples of 5hmC profile in several loci (From left to right: Cebpe, Klf1, Hlf) See also Figure S2–S4.

Figure 3. Nano-hmC-Seal reveals 5hmC redistribution in a murine AML model

(A) Comparison of 5hmC profiles in bone marrow MPP and GMP cells from WT and Tet2^−/−;Flt3^ITD mice. Hierarchical clustering applied to the matrix of sample-to-sample distance based on rlog-transformed read counts in 272,087 detected 5hmC-enriched peaks. (B) Venn diagram showing the overlap of detected differentially hydroxymethylated regions (DhMRs) between MPP and GMP cells. (C) Distribution of 5hmC signals at DhMRs (left: 5hmC loss; right: 5hmC gain) in MPP cells. (D) Relative enrichment of the genomic overlap between DhMRs and lineage-specific enhancers. Only DhMRs with at least 2-fold 5hmC change, adjust p<0.1 and mean of normalized counts >20 were used for analysis. All 5hmC peaks were used as control set. (E) De novo motif analysis by HOMER at DhMRs (left: 5hmC loss; right: 5hmC gain) in MPP cells. See also Figure S4.

Figure 4. Alternations of 5hmC in gene body correlate with gene expression changes in AML model

(A) Cumulative distribution of 5hmC gain genes (blue) and 5hmC loss genes (red) correlate with expression changes in MPP cells from Tet2^−/−;Flt3^ITD(T2F3) mice vs. wild-type mice (WT). All genes were used as control. P values were calculated versus all genes (two-sided Wilcoxon Rank Sum test). (B) GO enrichment analysis of 366 differentially expressed genes (|fold change| >2 and adjust P <0.1) associated with significant 5hmC changes (adjust P <0.1) in MPP cells. (C) Functional gene networks derived from GO enrichment analysis. The border color of the nodes denotes the upregulation (red) or down regulation (green) of genes in MPP cells from Tet2^−/−;Flt3^ITD versus wild-type mice. Genes in the same terms were linked to each other. The genes within the same clusters are surrounded by a common background color. (D) Heatmap of RNA expression to compare gene expression of hematopoietic transcriptional regulators in different samples. Genes and samples were clustered by Euclidean distance using centered rlog-transformed expression counts.