Array-based technologies transformed early genomics¹, but their probe-defined architecture is fundamentally limited for modern multi-omic analysis. Because microarrays only measure predefined loci, they cannot support de novo discovery, phase variants, or resolve complex structural events. Methylation arrays extended coverage into the epigenome, but still assay fewer than one million of the genome’s ~28 million CpG sites², capturing only a small, fixed portion of methylation biology. As a result, genomic and epigenomic variation must be analyzed through separate workflows, driving up cost, complexity, and sample burden.

Long-read sequencing, such as Wasatch BioLabs’ nanopore-based Direct Whole Methylome Sequencing (dWMS), overcomes these constraints by reading native DNA directly and unifying genetic and epigenetic information within a single, scalable assay.

Why Multi-Omic Sequencing Matters in Practice

dWMS is a whole-genome, nanopore-based sequencing service optimized for methylation analysis and designed to extend far beyond the limits of array-based genomics. By sequencing long, native DNA molecules, dWMS simultaneously resolves structural variants, haplotypes, and methylation states in the same continuous read, features arrays and short-read platforms cannot fully capture.

‍Unlike array technologies restricted to predetermined probes, dWMS delivers genome-wide coverage across both coding and noncoding regions. This enables forward variant discovery, reconstruction of complex rearrangements, and long-range variant phasing^3,4. Structural variants, repeat expansions, enhancer disruptions, allele-specific patterns, features invisible to arrays, become accessible with high resolution.

Critically, dWMS requires no bisulfite conversion or PCR. This preserves the native DNA molecule and its methylation context, enabling simultaneous measurement of CpG/CHG/CHH methylation, hydroxymethylation, and higher-order structural information⁵. Real-time nanopore signal profiles support allele-specific methylation and haplotype phasing^6,7, with customizable coverage to balance depth and throughput.

Across multiple benchmarking studies, whole-genome nanopore sequencing shows strong concordance with traditional array-based 5-mC measurements while revealing additional genomic and epigenomic features inaccessible to hybridization-based assays^8,9.

Key Benefits and Impact

1. A Single Multi-Omic Assay
‍dWMS consolidates genomic sequencing, methylation profiling, copy-number analysis, structural variant detection, and haplotyping, eliminating the need for multi-assay workflows. This reduces sample usage, turnaround time, and overall project cost^10,11.

2. Higher Sensitivity Across Regulatory and Structural Regions
‍Long reads provide visibility into enhancers, promoters, imprinted domains, repetitive regions, and non-coding “dark” DNA that arrays do not represent. This improves detection of regulatory disruptions that are increasingly central to cancer, rare disease, and developmental disorders^12,13.

3. Allele-Resolved and Single-Molecule Precision
‍By preserving the native linkage between variants and methylation marks, dWMS supports interpretation of clonal heterogeneity, tumor evolution, allele-specific expression, and context-specific epigenetic regulation¹⁴.

4. Lower Cost Via Consolidation of Multiple Assays
‍Replacing multiple orthogonal assays with one multi-omic workflow simplifies study design and reduces operational burden, which is ideal for clinical trials, biobanks, and large translational studies¹⁵.

Expanding Opportunities in Disease Biology and Diagnostics

Precision Oncology
Integrated detection of SNPs, indels, CNVs, SVs, and methylation signatures accelerates biomarker discovery, molecular subtyping, and monitoring of tumor evolution^4,16.

Rare Disease and Genetic Disorders
Long-read sequencing uncovers pathogenic events, including repeat expansions, structural rearrangements, and methylation-linked imprinting defects, that arrays and short-read panels routinely miss^17,18.

Epigenetics and Developmental Biology
Genome-wide, single-molecule methylation maps enable deeper insight into imprinting, developmental transitions, enhancer dynamics, and tissue-specific epigenetic landscapes^6,13.

Clinical Biomarker Discovery
Unified genomic-epigenomic profiles accelerates identification of multi-layer biomarkers with translational and therapeutic potential¹².

Pharmacogenomics and Drug Development
Integrated structural, regulatory, and methylation information improves variant interpretation, drug response prediction, and therapeutic design¹⁹.

Population and Cohort Studies
High-throughput long-read workflows support scalable molecular epidemiology, enabling detection of genotype-epigenotype interactions in diverse populations²⁰.

Where the Field Is Heading

Adoption of dWMS is accelerating across academia, industry, and clinical translational pipelines. Single-assay, multi-omic readouts now align with emerging needs in precision oncology, longitudinal monitoring, pharmacogenomics, and population-scale research¹¹. Improvements in throughput, cost, and analytics continue to expand the feasibility of long-read sequencing for diagnostics and clinical development.

Regulatory frameworks are beginning to incorporate integrative long-read assays as evidence grows for their clinical validity and utility.

Wasatch BioLabs: Powering the Next Wave of Multi-Omic Insight

Wasatch BioLabs integrates proprietary wet-lab optimization, Oxford Nanopore technology, and tailored bioinformatics to deliver end-to-end, direct whole-genome nanopore sequencing. Our dWMS platform captures genomic and epigenomic information, including methylation, variants, haplotypes, and structural features, from the same native DNA molecules without the need for separate assays or chemical conversions. This unified long-read approach supports biomarker discovery, translational research, and clinical trial enablement, offering scalable coverage and a future-ready foundation for multi-omic precision medicine.

Whether your goal is to resolve regulatory elements, characterize structural complexity, or develop next-generation diagnostics, dWMS brings clarity that arrays and short-read technologies consistently miss.Ready to unify your genomic and epigenomic workflows?

‍Contact Wasatch BioLabs at support@wasatchbiolabs.com to integrate dWMS into your next research or clinical program.

1. Lenoir T, Giannella E. The emergence and diffusion of DNA microarray technology. J Biomed Discov Collab. Aug 22 2006;1:11. doi:10.1186/1747-5333-1-11
2. Pidsley R, Zotenko E, Peters TJ, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome biology. 2016;17:1-17.
3. Gershman A, Sauria ME, Guitart X, et al. Epigenetic patterns in a complete human genome. Science. 2022;376(6588):eabj5089.
4. O’Neill K, Pleasance E, Fan J, et al. Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes. Cell Genomics. 2024;4(11)
5. Sigurpalsdottir BD, Stefansson OA, Holley G, et al. A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes. Genome Biology. 2024;25(1):69.
6. Akbari V, Garant J-M, O’Neill K, et al. Megabase-scale methylation phasing using nanopore long reads and NanoMethPhase. Genome biology. 2021;22(1):68.
7. Silva C, Machado M, Ferrão J, Sebastião Rodrigues A, Vieira L. Whole human genome 5’-mC methylation analysis using long read nanopore sequencing. Epigenetics. 2022;17(13):1961-1975.
8. Flynn R, Washer S, Jeffries AR, et al. Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays. Human Molecular Genetics. 2022;31(18):3181-3190. doi:10.1093/hmg/ddac112
9. Deinichenko KA, Vynogradskaya VG, Grebnev PA, et al. Benchmark of the Oxford Nanopore, EM-seq, and HumanMethylationEPIC BeadChip for the detection of the 5mC sites in cancer and normal samples. Frontiers in Epigenetics and Epigenomics. 2024;2:1362926.
10. Deacon S, Cahyani I, Holmes N, et al. ROBIN: A unified nanopore-based sequencing assay integrating real-time, intraoperative methylome classification and next-day comprehensive molecular brain tumour profiling for ultra-rapid tumour diagnostics. medRxiv. 2024:2024.09. 10.24313398.
11. Wasatch BioLabs and Oxford Nanopore team up to accelerate methylation sequencing towards clinical use. 2024;
12. Chera A, Stancu-Cretu M, Zabet NR, Bucur O. Shedding light on DNA methylation and its clinical implications: the impact of long-read-based nanopore technology. Epigenetics & Chromatin. 2024;17(1):39.
13. Stefansson OA, Sigurpalsdottir BD, Rognvaldsson S, et al. The correlation between CpG methylation and gene expression is driven by sequence variants. Nature genetics. 2024;56(8):1624-1631.
14. Rausch T, Snajder R, Leger A, et al. Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures. Cell Genomics. 2023;3(4)
15. Zhang T, Li H, Jiang M, et al. Nanopore sequencing: flourishing in its teenage years. Journal of Genetics and Genomics. 2024;51(12):1361-1374.
16. Katsman E, Orlanski S, Martignano F, et al. Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing. Genome Biology. 2022/07/15 2022;23(1):158. doi:10.1186/s13059-022-02710-1
17. Miller DE, Sulovari A, Wang T, et al. Targeted long-read sequencing identifies missing disease-causing variation. The American Journal of Human Genetics. 2021;108(8):1436-1449.
18. Sinha S, Rabea F, Ramaswamy S, et al. Long read sequencing enhances pathogenic and novel variation discovery in patients with rare diseases. Nature Communications. 2025;16(1):2500.
19. Verma R, Da Silva KE, Rockwood N, et al. A nanopore sequencing-based pharmacogenomic panel to personalize tuberculosis drug dosing. American Journal of Respiratory and Critical Care Medicine. 2024;209(12):1486-1496.
20. Neuenschwander S, Borcard L, Gempeler S, Miani MT, Casanova C, Ramette A. Evaluation of Oxford Nanopore Technologies workflows for genomic epidemiology of outbreak‐associated bacterial isolates in the clinical setting. medRxiv. 2025:2025.04. 25.25326448.