How Fiber-Seq enables assay consolidation through extending the multi-omic potential of long-read sequencing

Poster Abstract:

Emily A. Madden1, James T. Anderson1, Connor P. Frasier1, Sabrina R. Hunt1, Anup Vaidya1, Zu-Wen Sun1, Keith E Maier1, Andrea L. Johnstone1, Martis W. Cowles1, Bryan J. Venters1, Andrew Stergachis2, and Michael, Christopher Keogh1, 1EpiCypher, Inc., Durham, NC2Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA

Abstract

Understanding gene regulation requires integrated profiles of chromatin accessibility, DNA methylation, protein–DNA interactions, and genetic variation. These features are typically captured using separate short-read assays such as ATAC-seq, bisulfite sequencing, ChIP-seq, and whole genome sequencing with variant calling workflows. This multi-assay approach increases sample requirements, cost, and analytical complexity while breaking the physical linkage between features that co-occur on the same DNA molecule. As a result, key relationships between genetic variation and epigenomic function remain obscured, particularly in complex or repetitive regions of the genome. Fiber-seq addresses this challenge by consolidating these measurements into a single long-read, multiomic assay. The method directly encodes chromatin accessibility information onto native DNA while preserving endogenous DNA methylation and enabling sensitive inference of protein footprints. The resulting long-read sequencing data contain, in a single experiment, genetic variants, DNA methylation states, chromatin accessibility profiles, and protein–DNA interaction signatures, all phased along individual DNA molecules.

Because these data are collected at the single molecule level, Fiber-seq supports analysis at three distinct levels: genome-wide by aligning data to a single reference genome and analyzing in aggregate, haplotype[1]resolved by phasing reads by haplotype before aggregate analysis, and single-molecule by analyzing data collected in the individual reads. This multi-scale view provides flexibility in data analysis and enables new analytical opportunities like integrated variant-to-function analysis, uncovering haplotype-specific gene regulation, and profiling genome regulation across segmental duplications and repetitive regions inaccessible to short reads.

Fiber-seq has already provided insights in challenging clinical genetics cases by directly linking gene dysregulation to their causal genetic variants, demonstrating its potential for diagnostic interpretation and biomarker discovery (PMIDs 38714869, 39880924). By replacing multiple separate assays with one unified workflow, 

Conclusions: Fiber-seq reduces operational burden while greatly expanding the analytical power of long-read sequencing. This makes it a compelling new platform for genomics consortia, sequencing service providers, and computational groups seeking to scale multiomic analysis and unlock new layers of regulatory biology.