Mapping and characterizing N6-methyladenine in eukaryotic genomes using single-molecule real-time sequencing

Abstract

N6-Methyladenine (m⁶dA) has been discovered as a novel form of DNA methylation prevalent in eukaryotes; however, methods for high-resolution mapping of m⁶dA events are still lacking. Single-molecule real-time (SMRT) sequencing has enabled the detection of m⁶dA events at single-nucleotide resolution in prokaryotic genomes, but its application to detecting m⁶dA in eukaryotic genomes has not been rigorously examined. Herein, we identified unique characteristics of eukaryotic m⁶dA methylomes that fundamentally differ from those of prokaryotes. Based on these differences, we describe the first approach for mapping m⁶dA events using SMRT sequencing specifically designed for the study of eukaryotic genomes and provide appropriate strategies for designing experiments and carrying out sequencing in future studies. We apply the novel approach to study two eukaryotic genomes. For green algae, we construct the first complete genome-wide map of m⁶dA at single-nucleotide and single-molecule resolution. For human lymphoblastoid cells (hLCLs), it was necessary to integrate SMRT sequencing data with independent sequencing data. The joint analyses suggest putative m⁶dA events are enriched in the promoters of young full-length LINE-1 elements (L1s), but call for validation by additional methods. These analyses demonstrate a general method for rigorous mapping and characterization of m⁶dA events in eukaryotic genomes.

Figure 1.

Differences between bacterial and eukaryotic m⁶dA methylomes and a novel approach for mapping m⁶dA events in eukaryotic organisms. (A) Comparison between bacterial and eukaryotic m⁶dA methylomes over three aspects. (B) A novel approach for mapping and characterizing m⁶dA events in eukaryotic genomes. The novel approach, including a set of methods as summarized on the left, is comprehensively evaluated using subsampled bacterial m⁶dA methylome data and applied to Chlamydomonas reinhardtii (green algae) and human lymphoblastoid cells (LCLs).

Figure 2.

Comprehensive evaluation of m⁶dA detection based on SMRT-seq data. (A,B) Sensitivity-FDR curves at different levels of per strand SMRT-seq coverage (A) and fraction of methylated A sites in the genome (B). Curves are estimated based on either P-value or IPD ratio; both are shown. FDR estimation is based on the coverage-matched native (Escherichia coli with m⁶dA at GATC sites; Methods) and WGA samples. (C) FDRs estimated for different combinations of per strand SMRT-seq coverage and fraction of m⁶dA sites, f(m⁶dA/A), in the genome. FDR estimation is based on the coverage-matched native and WGA samples (Methods) at an IPD ratio of four. (D) Motif specific methylation detection leads to more reliable m⁶dA calls with lower FDRs. (E) Distribution of P-values (−log₁₀) and IPD ratios of m⁶dA events (red) and nonmethylated A's (black) from 11 well-characterized bacterial m⁶dA methylomes. (F) Enrichment score for motifs with different fractions of motif sites methylated across the genome f_m(m⁶dA/A), estimated based on P-value (−log₁₀; left) and IPD ratio (right). SMRT-seq data from 11 bacterial species/strains with well-characterized m⁶dA methylomes are used for this simulation analysis. (G) Schematic illustrating single-molecule-level analysis for the estimation of partial methylation. A single molecule (two DNA strands and two adapters) and the subreads that are produced from the top strand of this molecule in SMRT-seq (top). For a given genomic position, when non-single-molecule analysis is performed, IPD ratios for the methylated and nonmethylated subreads follow two exponential distributions (red and black curves in the second panel). In contrast, when single-molecule analysis was performed, IPD ratios across all molecules follow two normal distributions with smaller variance over increasing coverage per molecule strand (third and fourth panels). (H) Estimation of partial methylation f_l(m⁶dA/A) by aggregate analysis (left) and single-molecule-level analysis (right). x-axis indicates background truth f_l based on simulation; y-axis, estimated f_l; and dots, 4359 A's with known fraction of m⁶dA methylation based on subsampling from a well-characterized E. coli m⁶dA methylome. (I,J) Distribution of IPD ratios for partially methylated m⁶dA sites and nonmethylated A's based on aggregate analysis (I) and single-molecule level analysis (J). The inset provides an enlarged view. The motif enrichment score for the same, known methylation motif GATC significantly differs between the two types of analyses (1.3 in aggregated analysis vs. 25 in single-molecule analysis).

Figure 3.

Characterization of a complete m⁶dA methylome of C. reinhardtii reveals novel biological insights. (A) FDR estimation by comparing the IPD ratio distribution of C. reinhardtii native (red) with WGA (black) samples. The inset provides an enlarged view. (B) A rigorous motif enrichment analysis reveals that VATB (V = A, C, or G and B = C, G, or T) is the m⁶dA motif of in C. reinhardtii. Each 4 × 4 heatmap corresponds to all 16 4-mer motifs, for which the second and third bases are fixed at the center/title (e.g., AA). The rows and columns in the heatmaps represent the first and last bases of 4-mer motifs. Each cell in the following 4 × 4 heatmaps shows the motif enrichment score based on the native DNA sample. (C) Putative m⁶dA sites called by SMRT-seq are highly consistent with those detected by independent techniques: m⁶dA-DIP-seq (DIP), m⁶dA-CLIP-exo-seq (CLIP), and m⁶dA-RE-seq (RE). (D) VATB, but not non-VATB (i.e., TATN/NATA), motifs have a periodic pattern of IPD ratio distribution around TSSs. Average IPD ratio (normalized by motif frequency) for each of the nine VATB motifs (top) and each of the seven non-VATB motifs (bottom) are plotted around TSSs. (E) Relationship across four different distributions (top to bottom panels): average IPD ratio of VATB sites, nucleosome positioning, and frequency of VATB and non-VATB motif sites. Peaks and valleys of the periodic patterns are indicated by red and blue dots, aligned across the four panels. (F) Illustrative examples showing m⁶dA sites near the TSSs of three genes. This figure is adapted from Fu et al. (2015), where we project m⁶dA sites detected by SMRT-seq (red dots; FDR < 0.05; randomly generated heights to ease visualization) on top of GATC and CATG sites detected by m⁶dA-RE-seq (blue bars; middle) and nucleosome occupancy (bottom). (G) m⁶dA events at VATB sites are associated with active gene expression. Average IPD ratios are compared between two groups of genes with high (FPKM > 1) and low (FPKM < 1) expression levels. (H) The correlation between the gene expression level in C. reinhardtii and methylated VATB on gene promoters. The x-axis represents the number of methylated VATB sites (IPD ratio > 4.5; FDR = 0.05) within [0, +2000 bp] of TSSs. The y-axis represents the mean log₂ FPKM of genes. Error bars, SEs. (I–K) Single-molecule, strand-specific analysis of SMRT-seq data to examine full-, non-, or hemi-methylation status at m⁶dA sites. Three sets of m⁶dA sites are analyzed: m⁶dA in GATC sites (I) and CATG sites (J) based on m⁶dA-RE-seq (Fu et al. 2015) and (K) VATB sites with high aggregate IPD ratio (IPD ratio > 4.5; Methods) based on SMRT-seq. The x- and y-axes denote the single-molecule, strand-specific IPD ratio of each pair of reverse-complementary VATB sites at the two strands of each single molecule.

Figure 4.

m⁶dA deposition on full-length L1s in hLCLs. (A) Mean IPD ratio of A sites (adjusted by the frequency of A's) across 1274 young (evolutionary age<10 Myr), full-length (>6000 bp) L1s for three hLCL lines, respectively. Consistent across the trio, the IPD ratio is relatively higher in the promoter and proximal region than the flanking regions. (B) The mean IPD ratio of A sites at full-length L1s is inversely correlated with the L1s’ evolutionary ages in hLCLs. The heatmap shows the mean IPD ratio of A's on each L1, [0, +500] from the 5′ UTR start site, for each of the trio. As indicated in the sidebar, L1s (rows) are ordered by their evolutionary ages. Consistently across the trio, the IPD ratio of A sites is higher in younger full-length L1s than in older L1s. (C) Average m⁶dA-DIP-seq read count (adjusted for the read count in the input DNA sample and the A/T content) on hLCL young (1274), middle-aged (4164), and old L1 elements (1670), respectively. Consistent with SMRT-seq data, m⁶dA is enriched at the promoter and proximal region of young full-length L1s. (D) Average m⁶dA-DIP-seq read count adjusted for the A/T content and the read count in two control samples on hLCL young L1 elements, respectively: input DNA as control (black curve in top panel) and m⁶dA-DIP-seq on WGA as control (blue curve in bottom panel). (E) Motif AG is enriched for putative m⁶dA events. The barplot represents the motif enrichment score of all dinucleotide motifs in each of the trio. The putative methylated position is underscored. It suggests that motif AG is enriched for high IPD ratios in clear contrast to all the other dinucleotides. (F) Motif enrichment analysis of human young full-length L1s. Each 4 × 4 heatmap corresponds to all 16 4-mer motifs, for which the second and third bases are fixed at the center/title. The rows and columns in the heatmaps represent the first and last bases of 4-mer motifs. Each cell in the following 4 × 4 heatmaps shows the motif enrichment score based on the native DNA sample. (G) Peaks of putative m⁶dA events across human young full-length L1s occur at loci with certain sequence features. (Top) Level of sequence conservation across young full-length L1 elements based on multiple alignment by Mauve (Darling et al. 2004); (two middle panels) frequency of AG dinucleotides (relative to A's) and A's on young full-length L1s; and (bottom) frequency of putative m⁶dA events at each locus across all young full-length L1s (averaged among the trio). The peaks of sequence conservation, AG/A frequency, and m⁶dA frequency across young full-length L1s are colocalized as indicated by the red, blue, and green dots.