Author response: Genome-wide detection of imprinted differentially methylated regions using nanopore sequencing
Year: 2022
Type: peer-review
Abstract: Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Materials and methods Appendix 1 Appendix 2 Appendix 3 Data availability References Decision letter Author response Article and author information Metrics Abstract Imprinting is a critical part of normal embryonic development in mammals, controlled by defined parent-of-origin (PofO) differentially methylated regions (DMRs) known as imprinting control regions. Direct nanopore sequencing of DNA provides a means to detect allelic methylation and to overcome the drawbacks of methylation array and short-read technologies. Here, we used publicly available nanopore sequencing data for 12 standard B-lymphocyte cell lines to acquire the genome-wide mapping of imprinted intervals in humans. Using the sequencing data, we were able to phase 95% of the human methylome and detect 94% of the previously well-characterized, imprinted DMRs. In addition, we found 42 novel imprinted DMRs (16 germline and 26 somatic), which were confirmed using whole-genome bisulfite sequencing (WGBS) data. Analysis of WGBS data in mouse (Mus musculus), rhesus monkey (Macaca mulatta), and chimpanzee (Pan troglodytes) suggested that 17 of these imprinted DMRs are conserved. Some of the novel imprinted intervals are within or close to imprinted genes without a known DMR. We also detected subtle parental methylation bias, spanning several kilobases at seven known imprinted clusters. At these blocks, hypermethylation occurs at the gene body of expressed allele(s) with mutually exclusive H3K36me3 and H3K27me3 allelic histone marks. These results expand upon our current knowledge of imprinting and the potential of nanopore sequencing to identify imprinting regions using only parent-offspring trios, as opposed to the large multi-generational pedigrees that have previously been required. Editor's evaluation This work uses nanowire sequencing to detect genome-Wide imprinted differentially methylated regions. It will be of broad interest to DNA methylation researchers. https://doi.org/10.7554/eLife.77898.sa0 Decision letter eLife's review process Introduction The addition of a methyl group to the fifth carbon of cytidine is the most prevalent and stable epigenetic modification of human DNA (Laurent et al., 2010). DNA methylation is involved in gene regulation and influences a vast array of biological mechanisms, including embryonic development and cell fate, genome imprinting, X-chromosome inactivation, and transposon silencing (Moore et al., 2013; Smith and Meissner, 2013). In mammals, there are two copies or alleles of a gene, one inherited from each parent. Most gene transcripts are expressed from both alleles. However, a subset of genes are only expressed from a single allele; this allele can be selected either randomly, as seen in X-chromosome inactivation in females, or based upon the parent-of-origin (PofO), referred to as imprinting (Chess, 2013; Khamlichi and Feil, 2018). In imprinting, mono-allelic expression of a gene or cluster of genes is controlled by a cis-acting imprinting control region (ICR) (Bartolomei and Ferguson-Smith, 2011). The main mechanism by which this occurs is PofO-defined differential methylation at ICRs, also known as imprinted differentially methylated regions (DMRs) (Bartolomei and Ferguson-Smith, 2011; Maupetit-Méhouas et al., 2016). Imprinted DMRs are classified as germline (primary) or somatic (secondary), hereinafter referred to as gDMR and sDMR. gDMRs are established during the first wave of methylation reprogramming in germ cell development and escape the second methylation reprogramming after fertilization (Zink et al., 2018). sDMRs are established de novo after fertilization during somatic development, usually under the control of a nearby gDMR (Zink et al., 2018). Imprinted clusters of genes may span up to ~4 Mb, by acting through a CCCTC-binding factor (CTCF)-binding site or by allelic expression of a long non-coding RNA (Bartolomei and Ferguson-Smith, 2011; da Rocha and Gendrel, 2019). By contrast, individually imprinted genes are typically regulated by PofO-derived differential methylation at the gene promoter (Bartolomei and Ferguson-Smith, 2011). Imprinting is implicated in various genetic disorders, either from aberrations in imprinted methylation or from deleterious variants affecting the ICR and imprinted genes. Aberrant imprinted methylation is also detected in several human cancers (Goovaerts et al., 2018; Jelinic and Shaw, 2007; Tomizawa and Sasaki, 2012). Thus, accurate mapping and characterization of imprinting in humans is key to the treatment and actionability of genetic disorders, and to personalized oncogenomonics. To detect imprinted methylation, accurate assignment of methylation data to paternal and maternal alleles is required. Achieving this with traditional bisulfite sequencing or arrays is challenging. Several studies have used samples with large karyotypic abnormalities, such as uniparental disomies, teratomas, and hydatidiform moles, to infer regions of imprinting (Court et al., 2014; Hernandez Mora et al., 2018; Joshi et al., 2016). This approach relies not only on rare structural variants, but also on the assumption that both normal methylation and the imprinted state remain intact in spite of substantial genomic aberrations. A study by Zink et al., 2018, leveraged a genotyped, multi-generation pedigree spanning nearly half the population of Iceland (n=150,000), in combination with whole-genome oxidative bisulfite sequencing, to phase methylation and infer PofO (Zink et al., 2018). However, despite being able to phase nearly every SNP in that cohort, they were only able to phase 84% of the human autosomal methylome in over 200 samples due to the short length of reads. Furthermore, the study was based on a single, genetically isolated population, which may not be representative of the wider human population. A comprehensive mapping of imprinted methylation using a technology more suited to phasing reads, based on individuals more representative of the human population, could greatly advance our understanding of imprinting, with direct benefits for human health. Previously, we have shown that nanopore sequencing can detect allelic methylation in a single sample and accurately determine PofO using only trio data. We also previously developed the software NanoMethPhase for this purpose (Akbari et al., 2021). Here, we applied NanoMethPhase to public nanopore data from a diverse set of 12 lymphoblastoid cell lines (LCLs) from the 1000 Genomes Project (1KGP) and Genome in a Bottle (GIAB) to investigate genome-wide allele-specific methylation (ASM) and detect novel imprinted DMRs (Figure 1A; Auton et al., 2015; De Coster et al., 2019; Jain et al., 2018; Shafin et al., 2020; Zook et al., 2016; Zook et al., 2019). Using trio data from GIAB and 1KGP for these cell lines, we phased nanopore long reads to their PofO and inferred allelic methylation (Akbari et al., 2021; Auton et al., 2015; Zook et al., 2019). We were able to detect haplotype and methylation status for 26.5 million autosomal CpGs comprising 95% of the human autosomal methylome (GRCh38 main chromosomes). We further used public whole-genome bisulfite sequencing (WGBS) data to confirm the presence of the detected DMRs in other tissues and to classify the novel DMRs as germline or somatic. We captured 94% of the well-characterized DMRs and detected 42 novel DMRs (16 gDMRs and 26 sDMRs). Of these novel DMRs, 40.5% show evidence of conservation. We also detected seven blocks of PofO methylation bias at seven imprinted clusters with mutual exclusive allelic H3K36me3 and H3K27me3 histone marks. Collectively, our results extend the set of known imprinted intervals in humans and demonstrate a major contribution in our ability to characterize imprinting by ASM, brought about by the capabilities of long-read nanopore sequencing. Figure 1 with 1 supplement see all Download asset Open asset Detection of allelic methylation using nanopore sequencing. (a) Flowchart of the study representing all the analysis steps. (b) Pearson correlation matrix of the nanopore CpG methylation frequencies for the 12 cell lines and NA12878 whole-genome bisulfite sequencing (WGBS) from ENCODE (ENCFF835NTC). (c) Upset plot of the number of differentially methylated regions (DMRs) detected in our study and previous studies, including overlaps. Results Assessing the effectiveness of nanopore methylation calling and detection of known imprinted DMRs Using the set of 12 LCLs for which we called methylation data, we conducted correlation analysis among nanopore-called methylation data and another WGBS dataset for NA12878 cell line (ENCFF835NTC) to confirm the reliability of methylation calling (Figure 1B). We observed high correlation across cell lines (r=0.75–0.93), as expected as they were the same cell type. NA12878 nanopore-called methylation also showed the highest correlation (r=0.89) with NA12878 WGBS, as expected (Figure 1B). To assess the use of nanopore long reads in detecting known DMRs, we identified previously reported DMRs, including 383 imprinted intervals (Court et al., 2014; Hernandez Mora et al., 2018; Joshi et al., 2016; Zink et al., 2018). Of these 383, we classified 68 as ‘well-characterized’ as they were reported by at least two genome-wide mapping studies or were previously known to be imprinted (Supplementary file 1). Subsequently, we haplotyped the methylome in each cell line, and performed differential methylation analysis (DMA) between alleles across cell lines; 95% (26.5M) of the human autosomal CpGs could be assigned to a haplotype. We detected 200 allelic DMRs (p-value <0.001, |methylation difference|>0.20, and detected in at least four cell lines in each haplotype) (Supplementary file 2). Out of the 200 detected DMRs, 101 overlapped with 103 previously reported DMRs with consistent PofO (Supplementary file 3), while the remaining 99 were novel (Figure 1C). Of the well-characterized DMRs, 64/68 (94%) were detected in our study (Figure 1C; Supplementary file 3). Similarly, we assessed methylation haplotyping and detection of imprinted DMRs within a single sample. On average, 90% (M ± SD = 25 M ± 1.61 M) of the human methylome could be assigned to a parental haplotype in each cell line (Figure 1—figure supplement 1). Among the well-characterized DMRs, ~73% (M ± SD = 49.5 ± 4.5) could be detected in a single cell line. An additional 33 DMRs (SD = 9.6) reported by only one previous study were detected in each cell line (Figure 1—figure supplement 1). Confirmation of novel imprinted DMRs We detected 99 imprinted DMRs that did not overlap with previously reported imprinted DMRs (Court et al., 2014; Hernandez Mora et al., 2018; Joshi et al., 2016; Zink et al., 2018). In order to confirm these DMRs in human tissues and detect potential novel imprinted regions, we investigated WGBS datasets for partial methylation at nanopore-detected DMRs (Materials and methods). We used 60 WGBS datasets from 29 tissue types and 119 blood samples from 87 individuals (Bernstein et al., 2010; ENCODE Project Consortium, 2012; Stunnenberg et al., 2016). We first examined the 68 well-characterized DMRs, 91% of them demonstrated partial methylation (more than 60% of the CpGs at the DMR having between 0.35 and 0.65 methylation) in at least one tissue and individual blood samples (Figure 2A and B). As controls, we used 100 randomly selected 1, 2, 3 kb bins, and CpG islands (CGIs) in 100 resampling iterations. Of these, 0.65%, 0.74%, 2.28%, and 4.83% of the randomly selected 3, 2, 1 kb, and CGIs, respectively, demonstrated partial methylation (Figure 2—figure supplement 1). Applying this approach to the 99 previously unreported DMRs, the WGBS data supported 42 of the novel DMRs (Figure 2, Table 1). In agreement with previous studies reporting a higher number of maternally methylated intervals (Court et al., 2014; Hernandez Mora et al., 2018; Joshi et al., 2016), 74% of the novel DMRs were maternally methylated. Overall, we detected 143 imprinted DMRs of which 101 were found to overlap with previously reported DMRs while 42 were novel DMRs detected by nanopore and confirmed using WGBS data (Figure 2C, Supplementary file 4). Figure 2 with 1 supplement see all Download asset Open asset Confirmation of nanopore-detected differentially methylated regions (DMRs) using whole-genome bisulfite sequencing (WGBS) data. (a) and (b) Violin plots representing the average methylation of each DMR in WGBS tissue and blood samples. (c) Idiogram of the 101 DMRs overlapping to reported intervals and 42 novel DMRs which were confirmed by WGBS. Paternally methylated DMRs are labelled on the left side of each chromosome while maternally methylated DMRs are on the right. Red labels represent germline DMRs while blue labels represent somatic DMRs. Novel DMRs are boxed and named based on their nearest gene (Ensembl Gene 103 GRCh38.p13). Figure 2—source data 1 The average methylation of each DMR in human WGBS tissue samples. https://cdn.elifesciences.org/articles/77898/elife-77898-fig2-data1-v1.txt Download elife-77898-fig2-data1-v1.txt Figure 2—source data 2 The average methylation of each DMR in human WGBS blood samples. https://cdn.elifesciences.org/articles/77898/elife-77898-fig2-data2-v1.txt Download elife-77898-fig2-data2-v1.txt Table 1 Forty-two detected imprinted differentially methylated regions (DMRs) from nanopore data and confirmed using whole-genome bisulfite sequencing (WGBS) data. DMRs are named after the nearest gene (EnsemblGene 103 GRCh38.p13). IDDMR nameOriginTypeDistance to nearest imprinted gene% Individuals with partial methylation% Tissues with partial methylation22AC024940.1MaternalGermline015.93.835DDA1MaternalGermline07.315.438ACTL10;NECAB3MaternalGermline03.78.742SYCE1MaternalGermline3.2 kb49.112FAM83HMaternalGermline149 kb48.81220OPCMLMaternalGermline744.1 kb45.12519YBX2P1MaternalGermline>2 Mb3.77.726NALCN-AS1MaternalGermline>2 Mb30.51028PTGDRMaternalGermline>2 Mb8.43.432AATKMaternalGermline>2 Mb23.29.134MIR7-3HGMaternalGermline>2 Mb8.13.62AC007391.3MaternalGermline>2 Mb37.260.75C4orf50MaternalGermline>2 Mb14.522.27CPLANE1MaternalGermline>2 Mb2.37.114SPTLC1MaternalGermline>2 Mb5.848.11BMP8AMaternalSomatic04.526.124LPAR6;RB1MaternalSomatic02.310.336ZNF714MaternalSomatic043.929.617BTBD7P1MaternalSomatic>2 Mb73.555.618ANKRD2MaternalSomatic>2 Mb34.13.823GJA3MaternalSomatic>2 Mb25.621.427RANBP20PMaternalSomatic>2 Mb283233NFE2L3P1MaternalSomatic>2 Mb29.344.439AL096828.3MaternalSomatic>2 Mb507.741SLC5A1MaternalSomatic>2 Mb56.125.98TMEM232MaternalSomatic>2 Mb25.637.99NME5MaternalSomatic>2 Mb22.110.711AC092634.8MaternalSomatic>2 Mb6.13.813CDRT15P6MaternalSomatic>2 Mb12.75.615TMOD1MaternalSomatic>2 Mb35.414.816LHX6MaternalSomatic>2 Mb44.62530MIR6085PaternalGermline>2 Mb27.125.93PAX8;PAX8-AS1PaternalSomatic024.432.14ZDBF2PaternalSomatic053.658.629SNHG14PaternalSomatic3 kb4.737.937AC092296.3PaternalSomatic90 kb1.27.740RIMBP3PaternalSomatic296 kb17.411.110RNU6-293PPaternalSomatic1.03 Mb65.13721PARP11PaternalSomatic>2 Mb10.822.225UBAC2PaternalSomatic>2 Mb1.26.931CFAP161PaternalSomatic>2 Mb22.46.96MIR4456PaternalSomatic>2 Mb11.322.2 Novel imprinted DMRs display inter-individual variation Although imprinted methylation is generally regarded as consistent between individuals and resistant to environmental factors, there are examples of polymorphic imprinting where imprinted methylation is not consistently observed across individuals. In order to assess the inter-individual variation of the novel imprinted DMRs, we examined partial methylation in the 119 blood samples from 87 individuals. Some imprinted DMRs such as VTRNA2-1, IGF2, RB1, PARD6G, CHRNE, and IGF2R are known to be polymorphic (Joshi et al., 2016; Zink et al., 2018). The detected DMRs that mapped to these imprinted regions displayed partial methylation in 2–65% of the individuals in our analysis (M ± SD = 40% ± 22%; Supplementary file 5). ZNF331 DMR is known to be consistently imprinted across individuals (Zink et al., 2018). In our analysis, the DMR that mapped to ZNF331 reported interval displayed partial methylation in 99% of the individuals (Supplementary file 5). We then examined inter-individual variation across the 42 novel DMRs. Imprinted methylation at all the novel DMRs demonstrated variation ranging from 1.2% to 73.5% of the individuals (M ± SD = 23.6% ± 19.2%; Table 1). Among the novel DMRs, maternal sDMR near BTBD7P1 is the most consistent with partial methylation in 73.5% of the individuals (Table 1). On the other hand, the novel paternal sDMRs within AC092296.3 and UBAC2 are the most variable with partial methylation in 1.2% of the individuals (Table 1). Among the individuals, four displayed hypermethylation at several of the well-characterized and novel DMRs (Figure 2B), in line with a previous study that identified rare individuals with consistent hyper- or hypomethylation at dozens of imprinted loci, indicative of a generalized imprinting disruption (Joshi et al., 2016). As demonstrated in Figure 1C, a considerable number of imprinted DMRs detected in different studies are not overlapping between studies. Different studies used different samples and individuals, therefore, we examined inter-individual variation at DMRs detected in two or more studies (including the current work) and those that detected in one study (Supplementary file 5). The DMRs that detected in at least two studies demonstrated more consistency across individuals (M ± SD = 41.2% ± 33%) while DMRs detected in a single study showed more variability (M ± SD = 10.6% ± 15.4%) (Supplementary file 5). These results suggest that polymorphic imprinting can explain this non-overlapping DMRs across studies. Determination of germline versus somatic status of novel imprinted DMRs We investigated the methylation status of the detected novel DMRs in sperm and oocyte to determine if they are germline or somatic imprinted intervals. Maternally methylated gDMRs must display high methylation in oocyte and very low or no methylation in sperm with partial methylated after fertilization. Paternally methylated gDMRs must show high methylation in sperm and very low or no methylation in oocyte with partial methylated after fertilization. For the novel DMRs, 16 were detected as germline (more than 70% methylation in oocyte and less than 20% in sperm and vice versa) from which 15 were maternally methylated and one was paternally methylated (Figure 3A and B). Moreover, novel candidate gDMRs showed partial methylation in the blastocyst and fetal samples, indicating the gDMRs escaped de-methylation after fertilization. Meanwhile, sDMRs displayed partial methylation in fetal tissues, indicating their establishment during somatic development (Figure 3A and B). Overall, 16 of the novel DMRs were found to be germline while 26 were sDMRs. Figure 3 Download asset Open asset Detection of novel germline and somatic differentially methylated regions (DMRs). (a) Heatmap displaying average methylation of the 42 nanopore-detected DMRs confirmed by whole-genome bisulfite sequencing (WGBS). DMRs are named based on their nearest gene (Ensembl Gene 103 GRCh38.p13). (b) Dot plots representing the methylation of novel germline and somatic DMRs in each sample with respect to other samples. (c) IGV screenshots from six novel germline DMRs overlapping with ZNF445 and/or ZFP57 chromatin immunoprecipitation sequencing (ChIP-seq) peaks. The range for all methylation tracks is 0–1. During germ cell development, gDMRs are bound by proteins critical for their methylation maintenance during post-fertilization reprogramming. ZFP57 and ZNF445 have been identified as imprinting maintenance proteins (Takahashi et al., 2019). Using ZFP57 and ZNF445 ChIP-seq peak calling information from human embryonic stem cells and the HEK 293T cell line (Imbeault et al., 2017; Takahashi et al., 2019), 44% of the novel gDMRs and 49% of the reported gDMRs were bound by ZFP57 and/or ZNF445 (Figure 3C; Supplementary file 4). Of these gDMRs, 89% had a ZFP57 peak and 45% had a ZNF445 peak. This highlights the importance of ZFP57 as an important factor for the maintenance of imprinted methylation at gDMRs. 5′-TGC(5mC)GC-3′ is the canonical binding motif for ZFP57 (Quenneville et al., 2011). Eighty-eight percent of the gDMRs with a ZFP57 peak had at least one 5′-TGCCGC-3′ motif, while 40% of the gDMRs without ZFP57 peak had at least one 5′-TGCCGC-3′ motif in the human genome (GRCh38; Supplementary file 4). Moreover, at gDMRs the number of 5′-TGCCGC-3′ motifs demonstrated a significant positive correlation with the number of individuals demonstrating partial methylation (Pearson = 0.54, p-value = 3.6e−07; Appendix 1—figure 1). This suggests that a greater number of motifs provide more functional binding opportunities for ZFP57 and also less likelihood that all ZFP57 motifs could be perturbed through polymorphism or DNA sequence variation resulting in the imprinted methylation being less polymorphic. Allelic H3K4me3 histone mark at detected DMRs The H3K4me3 histone mark is protective against DNA methylation. At imprinted DMRs, the unmethylated allele is usually enriched for this histone modification (Court et al., 2014; John and Lefebvre, 2011). We used H3K4me3 chromatin immunoprecipitation sequencing (ChIP-seq) data for six LCLs and their heterozygous single-nucleotide variant (SNV) calls from 1KGP. Fifty of the DMRs mapped to reported intervals and 19 of the novel DMRs could be examined. Of these, 47 previously reported and 16 novel DMRs showed a significant allelic count in ChIP-seq data (Fisher’s combined p-value binomial <0.05 with at least 80% of the reads on one allele) (Figure 4a; Supplementary file 6). We also examined if the allelic H3K4me3 and methylation are in opposite alleles in NA12878 and NA19240. Forty of the previously reported DMRs and 10 of the novel DMRs with significant allelic H3K4me3 could be examined in NA12878 and/or NA19240. Thirty-seven previously reported and seven novel DMRs showed opposite allelic states between H3K4me3 and methylation (Figure 4b; Supplementary file 6). Figure 4 Download asset Open asset Allelic H3K4me3 histone mark at detected imprinted differentially methylated regions (DMRs). (a) The plots representing and alleles H3K4me3 for the heterozygous single-nucleotide variants mapped to the detected DMRs for the six examined samples. an with combined p-value binomial <0.05 and at least 80% of the reads on one allele and represent those that did not either of these (b) The plots representing paternal and maternal H3K4me3 for the heterozygous at DMRs in NA12878 and NA19240. an The the methylation of the DMR and if the DMR is novel or Figure data 1 H3K4me3 allelic for the heterozygous single-nucleotide variants mapped to the detected DMRs. Download Figure data 2 H3K4me3 allelic for the paternal and maternal heterozygous single-nucleotide variants mapped to the detected DMRs. Download Overall, gDMRs were enriched more with the H3K4me3 percent of the gDMRs and of the sDMRs with at least one heterozygous demonstrated an allelic H3K4me3 mark (Supplementary file 4). This is consistent with previous studies demonstrating the protective of H3K4me3 against DNA methylation, at germline in the second of during and somatic development and 2020; and of detected imprinted DMRs across To investigate the of detected DMRs and determine if of the novel DMRs are in mammals, we used WGBS data from mouse (Mus musculus), rhesus (Macaca mulatta), and chimpanzee (Pan troglodytes) et al., 2013; et al., 2021; et al., 2012). In of the regions in these displayed partial methylation, we found that of the detected intervals which overlapped with previously reported DMRs and 17 of the novel imprinted DMRs displayed partial methylation in at least one tissue sample in one or more (Figure Supplementary file 4). In the of the 33 detected DMRs were of these were previously reported to be imprinted in et al., 2019; et al., 2012). Most of the methylated DMRs in the mouse were also methylated in rhesus and/or chimpanzee across These DMRs mapped to imprinted clusters including and where their allelic PofO expression been reported in mouse and other 2021; et al., Figure Download asset Open asset of detected differentially methylated regions (DMRs). (a) Upset plot representing the number of previously reported and novel DMRs with evidence of methylation) in each of the (b) Heatmap representing human DMRs on the and average methylation of their intervals in mouse and in different tissues and also in and embryonic samples. regions represent that either did not have an or CpG in the whole-genome bisulfite sequencing (WGBS) data. and WGBS data for mouse and rhesus were used to investigate if DMRs classified as germline or somatic in humans were germline or somatic in other and vice (Figure et al., 2020; et al., 2017; et al., 2017; et al., 2019). Overall, imprinted DMRs their as germline or somatic in the two other examined (Figure However, in a the of imprinted DMR was not consistent between humans and other (Figure This is supported by an study that imprinting is in while the of ICR at the germline is not et al., Novel DMRs within known imprinted gene To the of novel DMRs to known imprinted we a of imprinted genes identified in previous studies (Supplementary file et al., 2015; et al., 2015; 2021; et al., 2019; et al., Zink et al., 2018). of the novel DMRs germline and identified in our study could be mapped nearby to known imprinted genes (Table Supplementary file 4). Novel sDMRs close to known imprinted genes were paternal of of them mapped within known imprinted genes including and while four mapped close to imprinted genes including and IGF2R (Figure Figure For and there are no reported imprinted DMRs within the gene or very close to them that explain their imprinted of the novel sDMRs mapped to the of these genes with a between of methylation and expression (Figure these DMRs could paternal and maternal alleles in and Figure with see all Download asset Open asset IGV screenshots of two novel somatic differentially methylated regions (DMRs). (a) Novel maternally methylated somatic DMR overlapping with the promoter of paternally expressed (b) Novel paternally methylated somatic DMR overlapping with the promoter of maternally expressed regions represent the DMRs. (PofO) allele-specific expression is using publicly available data from Zink et al., Materials and methods). represent paternal expression and represent maternal The range for all methylation tracks is 0–1. novel gDMRs close to imprinted genes were maternal of of them mapped within known imprinted genes including and while of them mapped close to imprinted genes including and (Figure Figure of the germline DMRs mapped within or very close to known imprinted genes without reported ICR including and A novel maternal gDMR mapped to the promoter of the paternally expressed (Zink et al., 2018; Figure In a previous a CpG site from the DMR we detected was demonstrated to be a with PofO et al., 2018). Thus, the novel gDMR be the ICR of this gene and the maternal novel maternal gDMR mapped to the promoter of which paternal expression bias in the allele-specific expression (Zink et al., 2018; Figure et al., also
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