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. 2024 Jan 19;14(1):1694.
doi: 10.1038/s41598-024-52114-3.

Detection of DNA methylation signatures through the lens of genomic imprinting

Affiliations

Detection of DNA methylation signatures through the lens of genomic imprinting

Jean-Noël Hubert et al. Sci Rep. .

Abstract

Genomic imprinting represents an original model of epigenetic regulation resulting in a parent-of-origin expression. Despite the critical role of imprinted genes in mammalian growth, metabolism and neuronal function, there is no molecular tool specifically targeting them for a systematic evaluation. We show here that enzymatic methyl-seq consistently outperforms the bisulfite-based standard in capturing 165 candidate regions for genomic imprinting in the pig. This highlights the potential for a turnkey, fully customizable and reliable capture tool of genomic regions regulated by cytosine methylation in any population of interest. For the field of genomic imprinting, it opens up the possibility of detecting multilocus imprinting variations across the genome, with implications for basic research, agrigenomics and clinical practice.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Strategy and performances of technologies. (a) Schematic overview of the strategy, including the selection of 165 candidate regions for GI in the pig based on knowledge from humans and mice,, the use of a reciprocal cross (n = 8) to ensure the determination of parental inheritance and the tested technologies, Twist Bioscience (TB) vs. Agilent (AG). (b) Distribution and size of final designed panels by the two manufacturers, AG (green), TB (purple), and uncovered regions (grey). (c, d, e) Sequencing performances by technology, including insert size (c), duplication rate (d) and GC percentage (e). (f, g, h, i) Panel performances by technology, including efficiency, that is represented as the mean + /- standard deviation of the fraction of targets covered at a specific depth (f), homogeneity, that is represented as the mean + /- standard deviation of depth coverage for the 165 targeted regions (g), specificity, that is represented as percentage (h) and density (i) of off-target reads, which mapped outside of the 165 targeted regions. j, k, Correlation of the mean coverage with either the size (j) or the GC percentage (k) of the 165 targeted regions. For c to k, the AG classical protocol is in green and the two TB protocols (TB1 and TB2) are in light and dark purple. l, Feature annotation of region per technology.
Figure 2
Figure 2
Hemi-methylated CpGs, regions and PofO methylation. Results showed here come from the TB2 protocol. (a) Detection, methylation and classification of CpGs. The methylation at CpGs was considered hyper/hypo/hemi when methylation was < 70%, > 30% and between 30–70% and 40–60%, respectively. (b) Repartition of hyper/hypo/hemi-methylated CpGs in the 165 candidate regions for GI. (c) Location of the hemi-methylated candidate regions across the pig genome. (d) Schematic representation of the IGF2-H19/KCNQ1-CDKN1C imprinted region located on the swine chromosome 2 with genes expressed from the paternal and maternal allele in blue and red, respectively. (e, f) Magnification of two regions where two clusters of hemi-methylated CpGs, DMRs (pink), were detected. Locally weighted running lines smoother (LOESS) were represented. (g to n), Screenshots from IGV browser (https://software.broadinstitute.org/software/igv/) magnified in DMRs. (g, h) Annotation of the pig genome using Sus_scrofa.Sscrofa11.1.104.gtf showing that KCNQ1OT1 was missing. (i, j) Coverage. (k, l) Variants identification and informativity with parental origin in the offspring of reciprocal crosses. (n, m) Methylation evaluation in blood and sperm tissues and detection of PofO methylation. hemiR100: occurrence of ≥ 5 hemi-methylated CpGs within 100 bp; hemiR5: occurrence of ≥ 5 consecutive hemi-methylated CpGs.

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