RESUMEN
Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.
Asunto(s)
Metilación de ADN , Epigénesis Genética , Secuenciación de Nucleótidos de Alto Rendimiento , Programas Informáticos , Epigenómica , Análisis de Secuencia de ADN , SulfitosRESUMEN
The most well-studied epigenetic marker in humans is the 5-methyl modification of cytosine in DNA, which has great potential as a disease biomarker in liquid biopsies of cell-free DNA. Currently, quantification of DNA methylation relies heavily on bisulfite conversion followed by PCR amplification and NGS or microarray analysis. PCR is subject to potential bias in differential amplification of bisulfite-converted methylated versus unmethylated sequences. Here, we combine bisulfite conversion with single-molecule kinetic fingerprinting to develop an amplification-free assay for DNA methylation at the branched-chain amino acid transaminase 1 (BCAT1) promoter. Our assay selectively responds to methylated sequences with a limit of detection below 1 fM and a specificity of 99.9999%. Evaluating complex genomic DNA matrices, we reliably distinguish 2-5% DNA methylation at the BCAT1 promoter in whole blood DNA from completely unmethylated whole-genome amplified DNA. Taken together, these results demonstrate the feasibility and sensitivity of our amplification-free, single-molecule quantification approach to improve the early detection of methylated cancer DNA biomarkers.
RESUMEN
Infinium Methylation BeadChips are widely used to profile DNA cytosine modifications in large cohort studies for reasons of cost-effectiveness, accurate quantification, and user-friendly data analysis in characterizing these canonical epigenetic marks. In this work, we conducted a comprehensive evaluation of the updated Infinium MethylationEPIC v2 BeadChip (EPICv2). Our evaluation revealed that EPICv2 offers significant improvements over its predecessors, including expanded enhancer coverage, applicability to diverse ancestry groups, support for low-input DNA down to one nanogram, coverage of existing epigenetic clocks, cell type deconvolution panels, and human trait associations, while maintaining accuracy and reproducibility. Using EPICv2, we were able to identify epigenome and sequence signatures in cell line models of DNMT and SETD2 loss and/or hypomorphism. Furthermore, we provided probe-wise evaluation and annotation to facilitate the use of new features on this array for studying the interplay between somatic mutations and epigenetic landscape in cancer genomics. In conclusion, EPICv2 provides researchers with a valuable tool for studying epigenetic modifications and their role in development and disease.