Fig 1: Altered DNA methylation and allelic mis-expression of Dlk1 in offspring exposed to HFD in utero.a DNA bisulphite methylation analysis at Dlk1 sDMR, IG-DMR and Gtl2 sDMR in liver (upper) and brown adipose tissue (BAT) (lower) from representative male P56 F1mat-CD and F1mat-HFD animals. In liver and BAT, hypermethylation was detected at Dlk1 sDMR, increased methylation was observed at the Gtl2 sDMR (not statistically significant), but IG-DMR was unchanged. Closed circles indicate methylated CpGs, open circles un-methylated CpGs. Each row represents an individual clone. Percentages indicate total methylation level of the region from two wt and two KImat animals. (Kolmogorov-Smirnov test comparing clonal methylation levels, using Holm-Šídák’s correction for multiple comparisons: **padj < 0.0055, ****padj = 6 × 10-6, ns=not significant). Source data are provided as a Source Data file. b Gene expression (QRT-PCR) at the Dlk1-Dio3 cluster in the liver of male P56 F1mat-HFD (blue) and F1mat-CD (dark grey) animals. Expression levels for this single tissue comparison were normalised to ß-Actin expression. (Bars show the geometric mean of relative expression with geometric SD; N = 4 + 4 individual mice; unpaired two-sided t-tests on delta-Ct values with Holm-Šídák’s correction for multiple comparisons: **padj = 0.0067, ****padj < 0.0001, ns=not significant). Source data are provided as a Source Data file. c Dlk1 expression (QRT-PCR, upper panel) in different tissues from P56 male mice exposed to either control (F1mat-CD, black) or high-fat diet (F1mat-HFD, blue). Uterus samples from age-matched female mice were also analysed. Expression levels were normalised to ß-Actin, 18S and Hprt. (Bars show the geometric mean of relative expression with geometric SD; N = 4 + 4 individual mice; Two-way ANOVA on delta-Ct values (Tissue p < 0.0001, Diet p < 0.0001, Interaction p < 0.0001); results of Holm-Šídák’s multiple comparisons follow-up test for effect of diet in each tissue are shown: *padj = 0.013, **padj = 0.0042, ****padj < 0.0001, ns=not significant). Allelic Dlk1 analysis in F1mat-HFD mice (lower panel), using primers that distinguish the reporter from the wt allele, showed a reduced contribution for paternal allele expression (dark grey) when compared to maternal allele expression (light grey). (Bars indicate the mean contribution from each allele ±SD; N = 4 + 4 individual mice). Source data are provided as a Source Data file.
Fig 2: Inheritance of imprinted Dlk1 reporter expression in embryos and across generations.a BL signal (blue) detected in Dlk1-FLucLacZ pregnancies arising from KIpat (left) and KImat (right) transmission showed greater surface signal in KIpat pregnancies (E11.5). b Quantification of BL signal (Flux) detected in E11.5 Dlk1-FLucLacZ embryos following dissection, demonstrating higher levels of signal from KIpat than KImat embryos. BL signal in wt and KImat embryos is shown as a percentage of the average KIpat signal (number of embryos (N) indicated in table; One-way ANOVA on log-transformed data (p < 0.0001); results of Holm-Šídák’s multiple comparisons follow-up test are shown for comparisons to wt mice, and between KIpat/KImat mice as indicated: ****adjusted p (padj) < 0.0001). Source data are provided as a Source Data file. c BL imaging of embryos at different stages (E11.5, E14.5 and E17.5) showed progressive reduction in signal (blue) in both KIpat (left panel) and KImat (right panel) through gestation; signal was readily detected in E11.5 and E14.5 KIpat and KImat embryos, but at later stages (E17.5) was only seen after paternal transmission. Signal intensity scales are equalised between images. d Transmission of mono-allelic imprinted Dlk1 reporter expression in four generations (F0, F1, F2, F3); upon paternal inheritance of Dlk1-FLucLacZ the reporter was expressed (blue), while maternal inheritance resulted in reporter silencing (white). Imprinting was predictably re-set across generations, through both germlines (a minimum of two independent litters were analysed per generation and reciprocal cross).
Fig 3: Generational modulation of Dlk1-Dio3 imprinting in response to HFD exposure.a Schematic of Dlk1-Dio3 cluster miRs that were over-expressed in F1mat-HFD oocytes, as compared to F1mat-CD. Over-represented miRs are displayed as blue, while non-expressed miRs are displayed as grey. b Schematic summarizing the modifications to Dlk1 imprinting across generations. Imprinting is disturbed inter-generationally but restored trans-generationally. Blue (increased) and red (decreased) arrows depict expression or methylation levels relative to controls.
Fig 4: Germline DMRs in single MII oocytes from F1 females are unaffected by dietary exposure but show an altered transcriptional programme.a Heatmap representing mean DNA methylation levels for each gametic (g)DMR in F1mat-CD and F1mat-HFD oocytes (merged from 41 and 37 oocyte scBS-seq datasets, respectively). b SeqMonk screenshot showing mean DNA methylation in F1mat-CD and F1mat-HFD oocytes over nonoverlapping 100 CpG windows (colour-coded blocks) across a ~450 kb interval encompassing the Dlk1-Dio3 imprinted cluster with a zoomed-in region (below) showing the CpG methylation calls (methylated red; un-methylated blue) of the Dlk1-Gtl2 region with quantification over the gDMR and sDMRs. Error bars represent the standard deviation from the mean of 5 pseudo-bulk groupings of 7-8 oocytes each. c Principal component analysis of scRNA-seq datasets of individual oocytes from F1mat-CD and F1mat-HFD. d Heatmap revealing 5 unsupervised clusters of the 166 most variable genes between F1mat-CD and F1mat-HFD oocytes. Top bars identify the F1 donor and diet groups. Clusters 1 to 5 comprised 25, 62, 44, 25 and 9 genes respectively. e Major terms highlighted in the gene ontology analysis of up-regulated genes from clusters 1, 2 and 4 (x-axis, -log10 of FDR adjusted p values). Gene ontology analysis was performed with GOrilla and summarised with Revigo. f Comparison of Dlk1-Dio3 microRNA (miRs) expression in F1mat-CD (black) and F1mat-HFD (blue) oocytes, alongside three stably expressed miRs (27b-3p, 103-3p, 423-3p), analysed by small RNA sequencing. Each of the Dlk1-Dio3 miRs was found to be significantly more represented in F1mat-HFD oocytes. (Bars represent mean counts per million ±SD; small RNA-seq libraries generated from oocytes from four female mice per group; unpaired two-sided t-tests with Holm-Šídák’s correction for multiple comparisons: **padj = 0.0013, ***padj = 0.0005, ****padj < 0.0001, ns=not significant). Source data are provided as a Source Data file.
Fig 5: Obesity triggers deregulation of metabolic and inflammatory networks in subsets of cardiac, lung, kidney and brain ECs.a, UMAP clustering of cardiac ECs. b, Shifts in cardiac EC populations. Populations showing a log2 (WD/chow) > 0.3 change are highlighted in color. c, BioPlanet-annotated pathways upregulated in cardiac arterial ECs in obesity. The top 100 genes, ranked by fold change, were used for these analyses. d, Obesity-associated changes in the expression of AP1 transcription factor subunits. e, Obesity-associated gene expression changes in KLF-family transcription factors. f, UMAP clustering of lung ECs. g, Obesity-associated shifts in lung EC clusters. Populations showing a log2 (WD/chow) > 0.5 change are highlighted in color. h, FISH images showing overlap of typical pneumocyte markers (Lyz2, Sftpa1 and Sftpb) and EC marker (Pecam1). Double-positive cells are marked with arrows. Data were reproduced in three chow and three obese animals; scale bars, 5 µm. i, Changes in the expression of histocompatibility 2 (H2) genes in obesity. j, MSigDB-annotated pathways upregulated in aEC in obesity. The top 100 genes, ranked by fold change, were used for these analyses. k, UMAP clustering of kidney ECs; Ang, angiogenic. l, BioPlanet-annotated pathways upregulated in mEC2 cells in obesity. The top 100 genes, ranked by fold change, were used for these analyses; TCA, tricarboxylic acid. m, Top metabolic DEGs in mEC2 cells in obesity. n, Obesity-associated changes in the expression of AP1 transcription factor subunits. o, Quantification of DLK1 in gECs; n = 3 animals per group (black dots) and n = 10 images per animal (gray dots); scale bars, 20 µm. p, UMAP clustering of brain ECs. q, Obesity-associated changes in the expression of AP1 transcription factor subunits. r,s, Gene expression changes in select leukocyte adhesion (marked in red), tight junction (blue), adherens junction (green) and gap junction genes (black) in art (r) and fenestrated ECs (s) in obesity. t, Uptake of dextran dyes in the choroid plexus (CP); n = 5 animals per group (black dots); n = 4 sections per animal (gray dots); scale bars, 20 µm. Data in o and t are presented as mean ± s.e.m. and were analyzed using a two-sided Student’s t-test. The adjusted P value indicates adjustments for multiple comparisons using the Benjamini–Hochberg method (c, j and l).Source data
Supplier Page from Abcam for Anti-DLK-1 antibody [3A10]