Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Dec;18(1):2199374.
doi: 10.1080/15592294.2023.2199374.

Nanopore sequencing reveals methylation changes associated with obesity in circulating cell-free DNA from Göttingen Minipigs

Affiliations

Nanopore sequencing reveals methylation changes associated with obesity in circulating cell-free DNA from Göttingen Minipigs

Markus Hodal Drag et al. Epigenetics. 2023 Dec.

Abstract

Profiling of circulating cell-free DNA (cfDNA) by tissue-specific base modifications, such as 5-methylcytosines (5mC), may enable the monitoring of ongoing pathophysiological processes. Nanopore sequencing allows genome-wide 5mC detection in cfDNA without bisulphite conversion. The aims of this study were: i) to find differentially methylated regions (DMRs) of cfDNA associated with obesity in Göttingen minipigs using Nanopore sequencing, ii) to validate a subset of the DMRs using methylation-specific PCR (MSP-PCR), and iii) to compare the cfDNA DMRs with those from whole blood genomic DNA (gDNA). Serum cfDNA and gDNA were obtained from 10 lean and 7 obese Göttingen Minipigs both with experimentally induced myocardial infarction and sequenced using Oxford Nanopore MinION. A total of 1,236 cfDNA DMRs (FDR<0.01) were associated with obesity. In silico analysis showed enrichment of the adipocytokine signalling, glucagon signalling, and cellular glucose homoeostasis pathways. A strong cfDNA DMR was discovered in PPARGC1B, a gene linked to obesity and type 2 diabetes. The DMR was validated using MSP-PCR and correlated significantly with body weight (P < 0.05). No DMRs intersected between cfDNA and gDNA, suggesting that cfDNA originates from body-wide shedding of DNA. In conclusion, nanopore sequencing detected differential methylation in minute quantities (0.1-1 ng/µl) of cfDNA. Future work should focus on translation into human and comparing 5mC from somatic tissues to pinpoint the exact location of pathology.

Keywords: Cell-free DNA; Nanopore sequencing; diagnostics; epigenetics; methylation; obesity.

Plain language summary

Oxford nanopore sequencing can reveal changes in methylation patterns associated with obesity in minute quantities of cell-free DNA from serum.Bisulphite conversion and methylation-specific PCR can be used to validate differentially methylated regions in cell-free DNA.A differentially methylated region in an intronic region of the PPARGC1B gene was found associated with obesity.Differentially methylated regions in cell-free DNA could be useful as early risk markers of certain diseases and pathologies.

PubMed Disclaimer

Conflict of interest statement

No potential conflict of interest was reported by the authors.

Figures

Figure 1.
Figure 1.
Illustration of the study design. MSP-PCR: Methylation-specific polymerase chain reaction. Created with BioRender.Com.
Figure 2.
Figure 2.
Violin plot of log-likelihood ratios (LLR) of methylation of the 1,236 cell-free DNA (cfDNA) differentially methylated regions (DMRs) significantly associated with obesity. A Wilcoxon non-parametric test was used to compare the distributions of LLR between the two groups.
Figure 3.
Figure 3.
Genomic plots showing Oxford Nanopore sequencing data for the four differentially methylated regions (DMRs, blue highlights) obtained from cell-free DNA (cfDNA) and selected for validation by methylation-specific PCR. Each DMR was named by their closest genes of A: TUB and RIC3, B: PPARGC1B, C: GAS6 and D: EVL. Bottom X-axis indicates the number of CpG positions in the region. Lower window indicates the aggregated log-likelihood ratio (LLR) of the methylation of the CpG position, where 1 is highest probability of methylation. Middle Rawstat window indicates the raw computed test statistic for each cfDNA read obtained from Nanopolish, where positive indicates methylation and negative indicates unmethylation. The upper window shows each individual sequenced cfDNA read with identified CpG position illustrated as circles. A closed circle indicates methylation, whereas open circle indicates unmethylation. Top X-axis indicates genome coordinates in base pairs, with chromosome number in top left corner. Red: obese pigs. Green: lean pigs. Blue highlights: DMRs.
Figure 4.
Figure 4.
Validation of four differentially methylated regions (DMRs) associated with obesity by bisulphite conversion of cell-free DNA (cfDNA) and subsequent methylation-specific PCR (MSP-PCR) throughout the two experimental groups. Methylation ratios were obtained from the MSP-PCR procedure. Positive Y-axis value indicates methylation, negative Y-axis value indicates unmethylation. P values were obtained from a non-parametric Wilcoxon test.
Figure 5.
Figure 5.
Spearman correlations between methylation-specific PCR (MSP-PCR) ratios (Y-axis) and body weight of all 17 pigs for four differentially methylated regions (DMRs) associated with obesity. Positive Y-axis value indicates methylation, negative Y-axis value indicates unmethylation.
Figure 6.
Figure 6.
Significantly enriched (FDR<0.05) GO and KEGG pathways associated with obesity found from the transcription start sites (TSS) located near or within the differentially methylated regions (DMRs) of cell-free DNA (cfDNA). X-axis indicates -log10(FDR) obtained from ClueGO. Y-axis indicates GO term and/or KEGG pathways (green circle: biological process; blue triangle: cellular component; orange square: KEGG pathways; plus sign: molecular function).

Similar articles

Cited by

References

    1. Cristiano S, Leal A, Phallen J, et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature. 2019;570:385–15. - PMC - PubMed
    1. Turchinovich A, Baranova A, Drapkina O, et al. Cell-free circulating nucleic acids as early biomarkers for NAFLD and NAFLD-associated disorders. Front Physiol. 2018;9:1256. - PMC - PubMed
    1. Peng X, Li H-D, Wu F-X, et al. Identifying the tissues-of-origin of circulating cell-free DNAs is a promising way in noninvasive diagnostics. Brief Bioinform. 2020;22(3):bbaa060. - PubMed
    1. Jylhävä J, Lehtimäki T, Jula A, et al. Circulating cell-free DNA is associated with cardiometabolic risk factors: the health 2000 survey. Atherosclerosis. 2014;233:268–271. - PubMed
    1. Grabuschnig S, Bronkhorst AJ, Holdenrieder S, et al. Putative origins of cell-free DNA in humans: a review of active and passive nucleic acid release mechanisms. Int J Mol Sci. 2020;21:8062. - PMC - PubMed

Publication types