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Additional file 1: Figure S1. Analysis of blastocyst-derived ZFP57 null ES cells. a Western Blot analysis confirming absence of detectable ZFP57 protein. b, Bisulfite pyrosequencing of ICRs in WT, ZFP57 KO and ZFP57 MZ-KO ES cells. Figure S2. IGB viewer snapshot showing representative ZFP57 peak at IAPLTR2a2_Mm retroelements, which harbors the most number of ZFP57 peaks. Paired-end sequencing, together with sequence divergence of the retroelements allowing us to map ChIP-seq reads to individual transposable elements in the genome. The color scale indicates the mapping quality score (MAPQ) for each read pair. MAPQ = $$ - 10log_{10} P $$ - 10 l o g 10 P where P is the probability that true alignment belongs elsewhere. b, Transposable elements indicated by alignments of “multi-mapping reads. ZFP57 targets of these elements show KAP1 binding and H3K9me3 enrichment in both WT and KO cells, and no reactivation has been observed (data not shown). Figure S3. Genome browser screenshots for Snrpn, H19 and KvDMR1 imprinted loci. Figure S4. Genome browser screenshots for Grb10, Fkbp6 and Peg10 imprinted loci. Figure S5. Heat maps showing signal enrichment of H3K9me3 at ZFP57 binding sites in ZFP57 KO and MZ-KO ES cells. Figure S6. Transposable elements bound by ZFP57 are not reactivated in ZFP57 KO ES cells. a, Expression status of ZFP57 bound transposable elements in WT and ZFP57 mutants. b, Scatterplot showing no transcriptional changes of TEs (FPKM ≥ 0.1 in WT or KO) in ZFP57 KO cells versus WT. Figure S7. Analysis of expression of transposable elements jointly bound by ZFP57, ZFP932 and/or Gm15446 in different mutant ES cells. Top left – ZFP57 KO, Top right – ZFP932/Gm15446 DKO, Bottom left – KAP1 KO. The IAP retroelement in vicinity of Bglap3 locus is not shown in the ZFP932/Gm15446 DKO as its expression far exceeds other jointly bound TEs [6]. Figure S8. Genome browser screenshot showing loss of ZFP57 binding at MER20 DNA transposon resulting in loss of KAP1 and H3K9me3 and upregulation of an unannotated transcript. Figure S9. Genome browser screenshot showing loss of KAP1 and H3K9me3 in solo LTRs located within and adjacent to Mapk4 gene, and an increase in Mapk4 levels in ZFP57 KO ES cells. Figure S10. Heat maps of DNA methylation-dependent H3K9me3 enriched regions in WT and DNMT TKO cells (blue colored heat map) [25]. Enrichment of ZFP57, KAP1 and H3K9me3 in ZFP57 KO ES cells (red) at the same regions. Figure S11. ZFP57 maintains H3K9me3 methylation during preimplantation development. H3K9me3 methylation level dynamics during preimplantation development at non-DMR regions methylated in both germ lineages (left) and oocyte-specific germline DMRs (right). Light colored boxes show non-ZFP57 bound (n = 100 randomly selected regions) versus those targeted by ZFP57 (darker colored). Known maternally methylated ICRs are shown as hatched boxes for comparison. ICM, inner cell mass. ns, not significant, *P

The BLUEPRINT consortium, DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics., This work was performed in the context of the BLUEPRINT project (European Union’s Seventh Framework Programme grant agreement 282510), which funded the study logistics and the integrative data analysis. The assay costs were paid by the contributing laboratories using institutional funds and the following grants: BBSRC BB/G020930/1, BBSRC BB/G020930/1, BMBF 01KU1001A, BMBF 01KU1002A, BMBF 01KU1216F, EU-FP7 282510, FWF I 1575-B19, NHMRC 1063559, NHMRC 1088144 and the DKFZ Graduate School.

SummaryMore than one-half billion people are obese, and despite progress in genetic research, much of the heritability of obesity remains enigmatic. Here, we identify a Trim28-dependent network capable of triggering obesity in a non-Mendelian, “on/off” manner. Trim28+/D9 mutant mice exhibit a bi-modal body-weight distribution, with isogenic animals randomly emerging as either normal or obese and few intermediates. We find that the obese-“on” state is characterized by reduced expression of an imprinted gene network including Nnat, Peg3, Cdkn1c, and Plagl1 and that independent targeting of these alleles recapitulates the stochastic bi-stable disease phenotype. Adipose tissue transcriptome analyses in children indicate that humans too cluster into distinct sub-populations, stratifying according to Trim28 expression, transcriptome organization, and obesity-associated imprinted gene dysregulation. These data provide evidence of discrete polyphenism in mouse and man and thus carry important implications for complex trait genetics, evolution, and medicine.Video Abstract

BACKGROUND: Selective maintenance of genomic epigenetic imprints during pre-implantation development is required for parental origin-specific expression of imprinted genes. The Kruppel-like zinc finger protein ZFP57 acts as a factor necessary for maintaining the DNA methylation memory at multiple imprinting control regions in early mouse embryos and embryonic stem (ES) cells. Maternal-zygotic deletion of ZFP57 in mice presents a highly penetrant phenotype with no animals surviving to birth. Additionally, several cases of human transient neonatal diabetes are associated with somatic mutations in the ZFP57 coding sequence. RESULTS: Here, we comprehensively map sequence-specific ZFP57 binding sites in an allele-specific manner using hybrid ES cell lines from reciprocal crosses between C57BL/6J and Cast/EiJ mice, assigning allele specificity to approximately two-thirds of all binding sites. While half of these are biallelic and include endogenous retrovirus (ERV) targets, the rest show monoallelic binding based either on parental origin or on genetic background of the allele. Parental-origin allele-specific binding is methylation-dependent and maps only to imprinting control differentially methylated regions (DMRs) established in the germline. We identify a novel imprinted gene, Fkbp6, which has a critical function in mouse male germ cell development. Genetic background-specific sequence differences also influence ZFP57 binding, as genetic variation that disrupts the consensus binding motif and its methylation is often associated with monoallelic expression of neighboring genes. CONCLUSIONS: The work described here uncovers further roles for ZFP57-mediated regulation of genomic imprinting and identifies a novel mechanism for genetically determined monoallelic gene expression.