- Research article
- Open Access
- Open Peer Review
Genome-wide DNA methylation analysis of transient neonatal diabetes type 1 patients with mutations in ZFP57
© Bak et al. 2016
- Received: 15 August 2015
- Accepted: 8 April 2016
- Published: 14 April 2016
Transient neonatal diabetes mellitus 1 (TNDM1) is a rare imprinting disorder characterized by intrautering growth retardation and diabetes mellitus usually presenting within the first six weeks of life and resolves by the age of 18 months. However, patients have an increased risk of developing diabetes mellitus type 2 later in life. Transient neonatal diabetes mellitus 1 is caused by overexpression of the maternally imprinted genes PLAGL1 and HYMAI on chromosome 6q24. One of the mechanisms leading to overexpression of the locus is hypomethylation of the maternal allele of PLAGL1 and HYMAI. A subset of patients with maternal hypomethylation at PLAGL1 have hypomethylation at additional imprinted loci throughout the genome, including GRB10, ZIM2 (PEG3), MEST (PEG1), KCNQ1OT1 and NESPAS (GNAS-AS1). About half of the TNDM1 patients carry mutations in ZFP57, a transcription factor involved in establishment and maintenance of methylation of imprinted loci. Our objective was to investigate whether additional regions are aberrantly methylated in ZFP57 mutation carriers.
Genome-wide DNA methylation analysis was performed on four individuals with homozygous or compound heterozygous ZFP57 mutations, three relatives with heterozygous ZFP57 mutations and five controls. Methylation status of selected regions showing aberrant methylation in the patients was verified using bisulfite-sequencing.
We found large variability among the patients concerning the number and identity of the differentially methylated regions, but more than 60 regions were aberrantly methylated in two or more patients and a novel region within PPP1R13L was found to be hypomethylated in all the patients. The hypomethylated regions in common between the patients are enriched for the ZFP57 DNA binding motif.
We have expanded the epimutational spectrum of TNDM1 associated with ZFP57 mutations and found one novel region within PPP1R13L which is hypomethylated in all TNDM1 patients included in this study. Functional studies of the locus might provide further insight into the etiology of the disease.
- Next-generation sequencing
- Imprinting disorder
- Transient neonatal diabetes
- DNA methylation
Imprinting is an epigenetic mechanism in mammals by which one allele of certain genes is expressed in a parent-of-origin specific manner . Imprinting is controlled by modifications of sequence elements termed “imprinting control regions” (ICRs). These modifications include DNA methylation as well as acetylation and methylation of histones . Transient neonatal diabetes mellitus 1 (TNDM1) is an imprinting disorder caused by overexpression of the maternally imprinted genes PLAGL1 and HYMAI on chromosome 6q24. There are three major mechanisms related to this disorder: paternal uniparental disomy of chromosome 6, paternal duplications of 6q24 and total loss of maternal methylation at the TNDM1 differentially methylated region (DMR), PLAGL1:alt-TSS-DMR, without any detectable DNA sequence changes . Hypomethylation of additional imprinted loci is observed in half of the TNDM1 patients displaying loss of methylation at the TNDM1 locus. In almost half of the TNDM1 patients with multilocus methylation defects (TND-MLMD), homozygous and compound heterozygous mutations were identified in ZFP57 . Methylation analysis of imprinted loci in these patients have shown that in addition to loss of methylation at PLAGL1:alt-TSS-DMR, PEG3:TSS-DMR and GRB10:alt-TSS-DMR are hypomethylated to different extents, while the MEST:alt-TSS-DMR, KCNQ1OT1:TSS-DMR and GNAS-AS1:TSS-DMR are hypomethylated in some patients [4, 5]. The normal function of ZFP57 is maintenance of imprinting during early embryonic development [6, 7]. Mouse and human ZFP57 binds the methylated hexanucleotide TGCCmeGC [7, 8] and missense mutations in ZFP57 can disrupt interaction between the protein and its target sequence .
Genome-wide methylation analyses have recently been carried out in patients with TNDM to identify additional aberrantly methylated regions [9–11]. These, analyses were performed using methylation microarrays and were thus restricted to analyzing regions covered by the probes on the arrays. In the present study, we employed a DNA sequencing based approach to detect aberrantly methylated regions in TNDM1 patients with ZFP57 mutations.
Probands, heterozygotes, and controls
The methylation status at six specific known imprinted loci was previously investigated by methylation specific PCR (MS-PCR) and verified by pyrosequencing  in four patients and three heterozygotes selected for this study. The ZFP57 mutations and methylation status of the patients were:
(Proband II-1, family 1): ZFP57 genotype: c.723C > A / c.723C > A (p.Cys241* / p.Cys241*). Total loss of methylation at PLAGL1:alt-TSS-DMR, GRB10:alt-TSS-DMR and PEG3:TSS-DMR. Partial loss of methylation at MEST:alt-TSS-DMR, KCNQ1OT1:TSS-DMR, and GNAS-AS1:TSS-DMR.
(Proband II-2, family 1): ZFP57 genotype: c.723C > A / c.723C > A (p.Cys241* / p.Cys241*). Total loss of methylation at PLAGL1:alt-TSS-DMR, GRB10:alt-TSS-DMR and PEG3:TSS-DMR. Partial loss of methylation at MEST:alt-TSS-DMR and KCNQ1OT1:TSS-DMR. Normal methylation at GNAS-AS1:TSS-DMR.
(Proband II-3, family 2): ZFP57 genotype: c.257_258delAG / c.257_258delAG (p.E86VfsX28 / p.E86VfsX28). Total loss of methylation at PLAGL1:alt-TSS-DMR and GRB10:alt-TSS-DMR. Partial loss of methylation at PEG3:TSS-DMR. Normal methylation at MEST:alt-TSS-DMR, KCNQ1OT1:TSS-DMR and GNAS-AS1:TSS-DMR.
(Proband II-3, family 7): ZFP57 genotype: c.683G > A / c.838_845delACCCAGGC (p.R228H / p.279fsX1). Total loss of methylation at PLAGL1:alt-TSS-DMR and GRB10:alt-TSS-DMR. Partial loss of methylation at PEG3:TSS-DMR, MEST:alt-TSS-DMR, and GNAS-AS1:TSS-DMR. Normal methylation at KCNQ1OT1:TSS-DMR.
The three heterozygotes had normal methylation at these six loci.
Five unrelated individuals were used as normal controls.
Genomic DNA (2 μg) was isolated from peripheral blood leukocytes (PBL) and randomly sheared by nebulization to fragments with an average size of 250 bp. Methylated DNA fragments were isolated using His-tagged methyl binding protein MBD2b using MethylCollector (ActiveMotif) and DNA adaptors were ligated to the ends of the isolated methylated DNA using the NEBNext DNA library preparation kit (New England BioLabs). Ligation products were separated on a 2 % agarose gel and fragments of 200–400 bp in size were isolated from the gel. The isolated fragments were amplified by 15 cycles of PCR using primers binding to the adapter sequences. The resulting library was quantified with picogreen and 36 bases of the fragments were sequenced on a Genome Analyzer IIx (Illumina) following the manufacturer’s protocol.
Sequences were aligned to the human genome (GRCh37/hg19) using BWA version 0.6.1 . Reads with a mapping quality < 37 and duplicate reads were removed. Methylated genomic regions were identified using MACS version 1.4.2 (p < 1e-8) . Methylated regions overlapping more than 50 % were merged. For each methylated region, the number of non-redundant reads was counted for each patient and controls. Regions with less than 20 reads per million reads in all samples were removed. For each patient and ZFP57-heterozygous individuals, methylation levels were compared to controls. Aberrantly methylated regions were detected using edgeR  (P < = 0.05, Benjamini-Hochberg adjusted). Overlap of aberrantly methylated regions with allele-specific methylated regions and mapping relative to Ensembl transcripts were performed using python scripts. The analysis was also performed using BALM  as peak caller yielding similar results.
Genomic DNA (1 μg) from PBL was bisulfite converted (Zymo Research). Differentially methylated regions were PCR amplified using 100 ng bisulfite converted DNA as template in a reaction volume of 15 μl (10 μl 10x reaction buffer, 1 μl forward primer (10 μM), 1 μl reverse primer (10 μM), 1 μl dNTPs (2.5 μM each), 0.45 μl MgCl2 (50 mM), 0.1 μl Platinum TAQ Polymerase (Invitrogen) and 1 μl DNA template, 8.95 μl H2O). Primers for PCR amplification were designed using the Methyl Primer Express Software v1.0 (Appplied Biosystems). Primer sequences were: GDF7_F: AGTTGGGTTATTTGTTGTTAGGA, GDF7_R: ACACRTAAACAACAACAACAAC, MAFF_F: TTGGGGTATTTAAAGGTGTTT, MAFF_R: TACAACTCCTCCTTCTAACACA, GAL3ST1_F: GATAGGGGAAAAAATTAAGGGT, GAL3ST1_R: ACCAACTTAAACCCTACCTCAA, KCNAB3_F: GGGGATATAGGAGTAAGGATTAGG, KCNAB3_R: CTAACAACCCTTAAATCCCAAA, DFNB31_F: TATGGAGTTATTGAAAAAGTTGTGTT, DFNB31_R: ACCCCCTACAAACAACCC, ICAM5_F: AGATGGTTTTAGGTTTGAGGAGT, ICAM5_R: AAACACCCCTACTCCCTACC, PPP1R13L_F: AGAAGGTTTGGGTGTTTTT, PPP1R13L_R: ATCCCTCAATACCCTAACCGTC, ADRA2A_F: TGGTGTGTTGGTTTTTTTTTT, ADRA2A_R: AACTAAACACCCCTCRATACC. PCR conditions were: 96 °C for 10 min., 5 cycles of [95°/15 s; 65°/30s; 72°/30s], 5 cycles of [95°/15 s; 60°/30s; 72°/30s], 30 cycles of [95°/15 s; 55°/30s; 72°/30s] and a final extension at 72 °C for 5 min. For each patient, PCR products were combined and libraries for sequencing on the Genome Analyzer were prepared. Briefly, the combined PCR products were blunt ended and concatemerized by DNA ligation. Ligated DNA was randomly sheared by sonication (Bioruptor, Diagenode), followed by blunt ending and ligation of indexed sequencing adapters. Indexed adapters were designed in a way such that the first 5 bases of each read identify the patient. Adapter oligo 1: 5′-ACACTCTTTCCCTACACGACGCTCTTCCGATCTXXXXXT, adapter oligo 2: 5′-phosphate-xxxxxAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAG, where XXXXX is the index and xxxxx is the complementary bases of the index. The following indexes were used: ACCAAT, AGAGAT, AGTCAT, CAGTCT, CCGGCT, CGATCT, CGTACT, GAGAGT and GCCGGT. Indexed libraries were pooled and sequenced on a Genome Analyzer IIx (Illumina). Reads were aligned to the amplicons using Bismark . For each CpG site, a methylated-unmethylated ratio was calculated. An overall methylated-unmethylated ratio was calculated for each amplicon as the average of all CpG methylation ratios within each amplicon.
We used methyl-CpG binding domain protein sequencing (MBD-seq)  to generate genome-wide methylation profiles of genomic DNA from peripheral blood leukocytes (PBL) from four TND-MLMD patients with homozygous or compound heterozygous ZFP57 mutations (ZFP57mut/mut), three relatives with heterozygous ZFP57 mutations (ZFP57norm/mut) and five unrelated controls. The four patients have previously been analyzed for changes in methylation levels at selected known imprinted loci [4, 5]. A total of 17,123 methylated regions with at least 20 reads per million reads (RPM) in at least one of the 12 individuals were detected by MBD-seq. More than 20 % (3712 / 17,123) of the methylated regions detected by this method are not covered by probes on the Inifinium HumanMethylation450 Beadchip (Illumina). As patients with imprinting defects can display substantial differences in the number and extent of affected loci [5, 9, 10] they were compared to the controls individually to allow detection of patient-specific methylation changes.
Validation of method
Aberrantly methylated loci
In the ZFP57 heterozygotes, all aberrantly methylated regions were private except for two regions within ESPNP and MUC4 which were hypermethylated in two of the three heterozygotes and a region encompassing ACTL10, which was hypomethylated in all heterozygotes. In the patients, ESPNP and ACTL10 were both hypomethylated in three individuals, whereas no changes in MUC4 methylation was detected.
Aberrantly methylated regions shared between two or more patients
To characterize the differentially methylated common regions, we focused on loci showing methylation changes in two or more patients. A total of 52 loci were hypomethylated and 9 were hypermethylated in at least two patients (Additional file 2: Table S8). Six shared aberrantly methylated regions are not covered by probes on the Inifinium HumanMethylation450 Beadchip (Illumina) (Additional file 2: Table S8). Six known imprinted loci were among the shared hypomethylated regions, including the maternally imprinted PLAGL1:alt-TSS-DMR, GRB10:alt-TSS-DMR, PEG3:TSS-DMR, GNAS-AS1:TSS-DMR, NAP1L5:TSS-DMR and the maternally expressed SLC22A18. The majority of affected regions overlap a CpG island (50 out of 52 hypomethylated and 5 out of 9 hypermethylated). Measured from the center of the regions, 24 hypomethylated and 6 hypermethylated regions map more than 1 kb from the 5′ end of an Ensembl transcript. Thus, more than half of the affected regions are not closely associated with known transcriptional start sites. They are, however, associated with gene bodies. Of those regions not closely associated with transcription start, almost 90 % localizes within Ensembl transcripts and many close to the 3′ end. The normal function of gene body methylation is currently not known, but it is not associated with transcriptional silencing .
To analyse whether the identified hypomethylated regions are differentially methylated regions (DMRs) of novel imprinted genes or imprinting control regions (ICRs) regulating parental-of-origin expression of nearby genes, we analysed them for enrichment of regions reported to show allele-specific methylation, enrichment for ZFP57 binding motifs and experimentally investigated a subset of them for allele-specific expression.
We compared the 52 hypomethylated regions with allele-specific methylated regions (AMRs) from MethBase (http://smithlabresearch.org/software/methbase/) . We extracted 92 data sets with AMRs from 22 studies and counted number of datasets showing AMR in the hypomethylated regions. As expected, the known human imprinted DMRs [28, 29] are highly enriched for AMRs. More than 77 % of human imprinted DMRs are detected as AMRs in more than five of the data sets and all germline DMRs (gDMRs) are detected as AMR in more than 15 data sets. Half (51 %) of the hypomethylated regions identified in this study are AMRs in more than 5 data sets whereas only 11 % of all detected methylated regions (1933 / 17,123) was reported as AMRs in more than 5 data sets. However, the five known maternally imprinted loci identified as hypomethylated in this study (PLAGL1:alt-TSS-DMR, GRB10:alt-TSS-DMR, PEG3:TSS-DMR, GNAS-AS1:TSS-DMR, NAP1L5:TSS-DMR) top the list with more than 36 datasets detecting them as AMRs. Thus, the hypomethylated regions are enriched for AMR. However, allele-specific methylation is not necessarily indicative of imprinting as it is well established that the genotype can influence upon the DNA methylation in cis [30–33].
Most of the regions show intermediate methylation in blood cells or other tissues  (Additional file 2: Table S8). This was also evident from the BS-seq validation. In the controls the average methylation levels ranged from 25 % to 88 %. The chromatin of the unmethylated allele of many imprinted DMRs are marked by H3K4me2/3 . We downloaded H3K4me2/3 data from blood cells from the ENCODE website (https://www.encodeproject.org/). Of the BS-seq validated regions ICAM5, DFNB31, KCNAB3 and MAFF showed H3K4me2/3 in most or all cell types whereas PPP1R13L and PES1 did not show the modifications in any of the cell types (Additional file 2: Table S8).
To further investigate if the hypomethylated regions are imprinted DMRs we genotyped nine trios in the genes adjacent to the eight BS-seq validated hypomethylated regions and sequenced cDNA from peripheral blood samples to investigate for allele-specific expression. We identified informative SNPs in DFNB31, GAL3ST1, ICAM5 and MAFF, which also were expressed in blood. All showed biallelic expression, suggesting that they are not imprinted. However, we cannot rule out the possibility that they exhibit tissue-specific imprinting.
Thus, the hypomethylated regions in the patients are enriched for allele specific methylated regions and for the ZFP57 binding motif, but not to an extent found at the affected regions that are known imprinted genes. Additionally, none of the regions have been identified as imprinted or candidate imprinted in genome-wide or chromosome-wide screens [35–40], suggesting that they are not associated with imprinted genes. This is in agreement with recent genome-wide studies of patients with multilocus methylation defects other than TND also reporting aberrant methylation at apparently non-imprinted loci [41, 42]. Experiments in mice have shown that ZFP57 in complex with KAP1 and SETDB also binds to methylated non-imprint control regions which looses methylation in Zfp57 knockout cells . It might be speculated that ZFP57 is also involved in maintenance of methylation at non-imprinted genes in humans.
In summary, by genome-wide methylation analysis we have expanded the epimutational spectrum of TNDM1 associated with mutations in ZFP57. We detected large differences in the number and extent of affected regions in individual patients, but 61 regions were aberrantly methylated in two or more patients. We found one novel region within PPP1R13L which was hypomethylated in all TNDM1 patients included in this study. Expansion of the patient cohort will reveal if hypomethylation of this locus is a common feature of TNDM1 and functional studies of the aberrantly methylated regions identified in this study might provide further insight into the etiology of the disease.
Patients were recruited as part of a Danish Imprinting and Methylation study and as part of the UK clinical local research network study: “Imprinting Disorders finding out why”. The Danish study was approved by The National Committee on Health Research Ethics (H-D-2008-079) and Danish Data Protection Agency (2008-41-2565). The UK study was approved by Southampton and South West Hampshire Research Ethics committee (07/H0502/85). Written consent was obtained from patients and guardians for participation in research.
Consent to publish
Written informed consent was obtained from families for presentation of clinical data and for publication of results. Written consent was given by patients and guardians for the publication of patient and family numbers in anonymised form.
Availability of data and materials
Data from this study that do not pertain to individual patients are freely available and can be obtained by contacting the corresponding author. We do not have the consent of patients to publish sequencing data in a format required by SRA (http://0-www.ncbi.nlm.nih.gov.brum.beds.ac.uk/sra), ENA (http://www.ebi.ac.uk/ena) or EGA (https://www.ebi.ac.uk/ega/). Sequencing data will be shared as aligned reads without sequence information. Files with alignments to hg18, hg19 and hg38 are available.
Patients and their families are thanked for their participation. Hanne Mølgaard is gratefully acknowledged for technical assistance. Wilhelm Johannsen Centre for Functional Genome Research was established by the Danish National Research Foundation. This work was supported by Diabetes UK, the Danish Agency for Science, Technology and Innovation and the University of Copenhagen. Furthermore, financial support was granted by the “Director Jacob Madsen and wife Olga Madsens Foundation” and “King Christian the 10th Foundation”.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Biliya S, Bulla LA. Genomic imprinting: the influence of differential methylation in the two sexes. Exp Biol Med (Maywood). 2010;235:139–47.View ArticleGoogle Scholar
- Delaval K, Feil R. Epigenetic regulation of mammalian genomic imprinting. Curr Opin Genet Dev. 2004;14:188–95.View ArticlePubMedGoogle Scholar
- Mackay DJG, Temple IK. Transient neonatal diabetes mellitus type 1. Am J Med Genet C Semin Med Genet. 2010;154C:335–42.View ArticlePubMedGoogle Scholar
- Mackay DJG, Callaway JLA, Marks SM, White HE, Acerini CL, Boonen SE, Dayanikli P, Firth H V, Goodship JA, Haemers AP, Hahnemann JMD, Kordonouri O, Masoud AF, Oestergaard E, Storr J, Ellard S, Hattersley AT, Robinson DO, Temple IK. Hypomethylation of multiple imprinted loci in individuals with transient neonatal diabetes is associated with mutations in ZFP57. Nat Genet. 2008;40:949–51.View ArticlePubMedGoogle Scholar
- Boonen SE, Mackay DJG, Hahnemann JMD, Docherty L, Grønskov K, Lehmann A, Larsen LG, Haemers AP, Kockaerts Y, Dooms L, Vu DC, Ngoc CTB, Nguyen PB, Kordonouri O, Sundberg F, Dayanikli P, Puthi V, Acerini C, Massoud AF, Tümer Z, Temple IK. Transient neonatal diabetes, ZFP57, and hypomethylation of multiple imprinted loci: a detailed follow-up. Diabetes Care. 2013;36:505–12.View ArticlePubMedPubMed CentralGoogle Scholar
- Li X, Ito M, Zhou F, Youngson N, Zuo X, Leder P, Ferguson-Smith AC. A maternal-zygotic effect gene, Zfp57, maintains both maternal and paternal imprints. Dev Cell. 2008;15:547–57.View ArticlePubMedPubMed CentralGoogle Scholar
- Quenneville S, Verde G, Corsinotti A, Kapopoulou A, Jakobsson J, Offner S, Baglivo I, Pedone P V., Grimaldi G, Riccio A, Trono D. In embryonic stem cells, ZFP57/KAP1 recognize a methylated hexanucleotide to affect chromatin and DNA methylation of imprinting control regions. Mol Cell. 2011;44:361–72.View ArticlePubMedPubMed CentralGoogle Scholar
- Baglivo I, Esposito S, De Cesare L, Sparago A, Anvar Z, Riso V, Cammisa M, Fattorusso R, Grimaldi G, Riccio A, Pedone PV. Genetic and epigenetic mutations affect the DNA binding capability of human ZFP57 in transient neonatal diabetes type 1. FEBS Lett. 2013;587:1474–81.View ArticlePubMedPubMed CentralGoogle Scholar
- Docherty LE, Rezwan FI, Poole RL, Jagoe H, Lake H, Lockett GA, Arshad H, Wilson DI, Holloway JW, Temple IK, Mackay DJG. Genome-wide DNA methylation analysis of patients with imprinting disorders identifies differentially methylated regions associated with novel candidate imprinted genes. J Med Genet. 2014;51:229–38.View ArticlePubMedPubMed CentralGoogle Scholar
- Court F, Martin-Trujillo A, Romanelli V, Garin I, Iglesias-Platas I, Salafsky I, Guitart M, Perez de Nanclares G, Lapunzina P, Monk D. Genome-wide allelic methylation analysis reveals disease-specific susceptibility to multiple methylation defects in imprinting syndromes. Hum Mutat. 2013;34:595–602.PubMedGoogle Scholar
- Martin-Subero JI, Bibikova M, Mackay D, Wickham-Garcia E, Sellami N, Richter J, Santer R, Caliebe A, Fan J-B, Temple IK, Siebert R. Microarray-based DNA methylation analysis of imprinted loci in a patient with transient neonatal diabetes mellitus. Am J Med Genet A. 2008;146A:3227–9.View ArticlePubMedGoogle Scholar
- Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–60.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nussbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9:R137.View ArticlePubMedPubMed CentralGoogle Scholar
- Robinson MD, McCarthy DJ, Smyth GK. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2009;26:139–40.View ArticlePubMedPubMed CentralGoogle Scholar
- Lan X, Adams C, Landers M, Dudas M, Krissinger D, Marnellos G, et al. High resolution detection and analysis of CpG dinucleotides methylation using MBD-seq technology. PLoS One. 2011;6.Google Scholar
- Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011;27:1571–2.View ArticlePubMedPubMed CentralGoogle Scholar
- Serre D, Lee BH, Ting AH. MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res. 2010;38:391–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Bergamaschi D, Samuels Y, O’Neil NJ, Trigiante G, Crook T, Hsieh J-K, O’Connor DJ, Zhong S, Campargue I, Tomlinson ML, Kuwabara PE, Lu X. iASPP oncoprotein is a key inhibitor of p53 conserved from worm to human. Nat Genet. 2003;33:162–7.View ArticlePubMedGoogle Scholar
- Zhang X, Wang M, Zhou C, Chen S, Wang J. The expression of iASPP in acute leukemias. Leuk Res. 2005;29:179–83.View ArticlePubMedGoogle Scholar
- Jiang L, Siu MKY, Wong OGW, Tam KF, Lu X, Lam EWF, Ngan HYS, Le XF, Wong ESY, Monteiro LJ, Chan HY, Cheung ANY. iASPP and chemoresistance in ovarian cancers: effects on paclitaxel-mediated mitotic catastrophe. Clin Cancer Res. 2011;17:6924–33.View ArticlePubMedGoogle Scholar
- Liu Z, Zhang X, Huang D, Liu Y, Zhang X, Liu L, Li G, Dai Y, Tan H, Xiao J, Tian Y. Elevated expression of iASPP in head and neck squamous cell carcinoma and its clinical significance. Med Oncol. 2012;29:3381–8.View ArticlePubMedGoogle Scholar
- Petryszak R, Burdett T, Fiorelli B, Fonseca N a., Gonzalez-Porta M, Hastings E, Huber W, Jupp S, Keays M, Kryvych N, McMurry J, Marioni JC, Malone J, Megy K, Rustici G, Tang AY, Taubert J, Williams E, Mannion O, Parkinson HE, Brazma A. Expression Atlas update - a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments. Nucleic Acids Res. 2014;42(December 2013):926–32.View ArticleGoogle Scholar
- Herron BJ, Rao C, Liu S, Laprade L, Richardson J a., Oliveri E, Semsarian C, Millar SE, Stubbs L, Beier DR. A mutation in NFkB interacting protein 1 results in cardiomyopathy and abnormal skin development in wa3 mice. Hum Mol Genet. 2005;14:667–77.View ArticlePubMedGoogle Scholar
- Elliott G, Hong C, Xing X, Zhou X, Li D, Coarfa C, Bell RJ a., Maire CL, Ligon KL, Sigaroudinia M, Gascard P, Tlsty TD, Harris RA, Schalkwyk LC, Bilenky M, Mill J, Farnham PJ, Kellis M, Marra M a., Milosavljevic A, Hirst M, Stormo GD, Wang T, Costello JF. Intermediate DNA methylation is a conserved signature of genome regulation. Nat Commun. 2015;6:6363.View ArticlePubMedPubMed CentralGoogle Scholar
- Illingworth RS, Gruenewald-Schneider U, Webb S, Kerr ARW, James KD, Turner DJ, Smith C, Harrison DJ, Andrews R, Bird AP. Orphan CpG islands identify numerous conserved promoters in the mammalian genome. PLoS Genet. 2010;6:e1001134.View ArticlePubMedPubMed CentralGoogle Scholar
- Jones P a. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat Rev Genet. 2012;13:484–92.View ArticlePubMedGoogle Scholar
- Song Q, Decato B, Hong EE, Zhou M, Fang F, Qu J, et al. A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics. PLoS One 2013; 8:e81148.Google Scholar
- Court F, Tayama C, Romanelli V, Martin-Trujillo A, Iglesias-Platas I, Okamura K, et al. Genome-wide parent-of-origin DNA methylation analysis reveals the intricacies of human imprinting and suggests a germline methylation-independent mechanism of establishment. Genome Res. 2014; 24:554–69.Google Scholar
- Okae H, Chiba H, Hiura H, Hamada H, Sato A. Genome-wide analysis of DNA methylation dynamics during early human development. PLoS Genet. 2014;10:1–12.View ArticleGoogle Scholar
- Gimelbrant A, Hutchinson JN, Thompson BR, Chess A. Widespread monoallelic expression on human autosomes. Science. 2007;318:1136–40.View ArticlePubMedGoogle Scholar
- Kerkel K, Spadola A, Yuan E, Kosek J, Jiang L, Hod E, Li K, Murty V V, Schupf N, Vilain E, Morris M, Haghighi F, Tycko B. Genomic surveys by methylation-sensitive SNP analysis identify sequence-dependent allele-specific DNA methylation. Nat Genet. 2008;40:904–8.View ArticlePubMedGoogle Scholar
- Schalkwyk LC, Meaburn EL, Smith R, Dempster EL, Jeffries AR, Davies MN, Plomin R, Mill J. Allelic skewing of DNA methylation is widespread across the genome. Am J Hum Genet. 2010;86:196–212.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhang Y, Rohde C, Reinhardt R, Voelcker-Rehage C, Jeltsch A. Non-imprinted allele-specific DNA methylation on human autosomes. Genome Biol. 2009;10:R138.View ArticlePubMedPubMed CentralGoogle Scholar
- Kacem S, Feil R. Chromatin mechanisms in genomic imprinting. Mamm Genome. 2009;20:544–56.View ArticlePubMedGoogle Scholar
- Choufani S, Shapiro JS, Susiarjo M, Butcher DT, Grafodatskaya D, Lou Y, Ferreira JC, Pinto D, Scherer SW, Shaffer LG, Coullin P, Caniggia I, Beyene J, Slim R, Bartolomei MS, Weksberg R. A novel approach identifies new differentially methylated regions (DMRs) associated with imprinted genes. Genome Res. 2011;21:465–76.View ArticlePubMedPubMed CentralGoogle Scholar
- Metsalu T, Viltrop T, Tiirats A, Rajashekar B, Reimann E, Kõks S, Rull K, Milani L, Acharya G, Basnet P, Vilo J, Mägi R, Metspalu A, Peters M, Haller-Kikkatalo K, Salumets A. Using RNA sequencing for identifying gene imprinting and random monoallelic expression in human placenta. Epigenetics. 2014;9:1397–409.View ArticlePubMedPubMed CentralGoogle Scholar
- Stelzer Y, Ronen D, Bock C, Boyle P, Meissner A, Benvenisty N. Identification of novel imprinted differentially methylated regions by global analysis of human-parthenogenetic-induced pluripotent stem cells. Stem Cell Rep. 2013;1:79–89.View ArticleGoogle Scholar
- Barbaux S, Gascoin-Lachambre G, Buffat C, Monnier P, Mondon F, Tonanny MB, Pinard A, Auer J, Bessières B, Barlier A, Jacques S, Simeoni U, Dandolo L, Letourneur F, Jammes H, Vaiman D. A genome-wide approach reveals novel imprinted genes expressed in the human placenta. Epigenetics. 2012;7(February 2015):1079–90.View ArticlePubMedPubMed CentralGoogle Scholar
- Yuen RK, Jiang R, Peñaherrera MS, McFadden DE, Robinson WP. Genome-wide mapping of imprinted differentially methylated regions by DNA methylation profiling of human placentas from triploidies. Epigenetics Chromatin. 2011;4:10.View ArticlePubMedPubMed CentralGoogle Scholar
- Baran Y, Subramaniam M, Biton A, Tukiainen T, Tsang EK, Rivas MA, et al. The landscape of genomic imprinting across diverse adult human tissues. Genome Res. 2015;25:927–36.Google Scholar
- Beygo J, Ammerpohl O, Gritzan D, Heitmann M, Rademacher K, Richter J, Caliebe A, Siebert R, Horsthemke B, Buiting K. Deep bisulfite sequencing of aberrantly methylated Loci in a patient with multiple methylation defects. PLoS One. 2013;8:e76953.View ArticlePubMedPubMed CentralGoogle Scholar
- Caliebe A, Richter J, Ammerpohl O, Kanber D, Beygo J, Bens S, Haake A, Jüttner E, Korn B, Mackay DJG, Martin-Subero JI, Nagel I, Sebire NJ, Seidmann L, Vater I, von Kaisenberg CS, Temple IK, Horsthemke B, Buiting K, Siebert R. A familial disorder of altered DNA-methylation. J Med Genet. 2014;51:407–12.View ArticlePubMedGoogle Scholar