Epigenetic variation plays a critical role in gene regulation, adaptation, and pathology, including developmental disorders (DD). Episignatures – disorder-specific methylation patterns – aid diagnosis when genetic findings are inconclusive. However, these methods can be costly and time-consuming.
Long-read whole-genome sequencing (lrWGS), using Oxford Nanopore Technologies (ONT), now enables simultaneous detection of genetic and epigenetic variations, including methylation disturbances, imprinting defects, and skewed X-chromosome inactivation (XCI).
A study involving 20 patients with presumed or proven episignature-related DD and 40 healthy individuals utilized long-read ONT sequencing to evaluate episignatures and genomic variants. Episignatures were analyzed using UMAP, t-SNE, and hierarchical clustering, and a support vector machine (SVM) classifier was developed to predict disorder-specific episignatures.
The Geneyx platform (v6.0) facilitated variant prioritization through phenotype-driven analysis and ACMG classification, enabling efficient detection of structural and single nucleotide variants.
Read more about Epigenetics: Impact, Resources, and Technology in DNA Methylation Analysis
Written by Eli Sward PhD., Geneyx expert Field Application Specialist.
ONT episignature analysis in patients with Wiedemann-Steiner, Sotos, Kabuki, and Cornelia de Lange syndromes accurately classified cases against microarray references.
An SVM classifier recognized correct episignatures in 85% of cases, with discrepancies explained by factors like XCI.
Genetic variants, including single nucleotide variants and structural variants, were concurrently detected, with potentially causative variants ranked among the top 4 candidates using the Geneyx platform.
In summary, this study highlights the diagnostic potential of lrWGS for detecting episignatures and genetic variants, emphasizing its ability to analyze phased genome and methylation data concurrently. Skewed XCI and mosaicism are shown to complicate episignature detection in X-linked disorders, necessitating tissue-specific or maternal analyses to confirm pathogenicity. Although lrWGS currently incurs higher costs and requires significant computational resources, its improving accuracy, declining expenses, and ability to combine genetic and epigenetic testing suggest it may become a first-tier diagnostic tool for DD.
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