SUMMARY Human genome sequencing typically relies on mapping reads to a reference genome to call variants, but this approach introduces technical biases, excluding duplicated and structurally polymorphic regions of the genome. To overcome this, we present a telomere-to-telomere genome benchmark with near-perfect accuracy across 99.4% of the diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), which were absent from prior benchmarks. We annotated genes and repeats on both haplotypes, including 19,956 protein-coding genes on the maternal haplotype and 19,190 on the paternal haplotype, and developed new methods to measure the accuracy of reads, phased variant call sets, and assemblies against a diploid reference. Genome-wide analyses show that de novo assembly resolves 2%–7% more sequence and outperforms variant calling accuracy by an order of magnitude, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.
Nancy F. Hansen, Nathan Dwarshuis, Hyun Joo Ji et al.· Cell· 6 citations
Gene regulation emerges from coordinated interactions among DNA sequence, chromatin accessibility, DNA methylation, nucleosome positioning, and transcription factor occupancy. These features are typically measured using separate short-read assays, fragmenting regulatory information across experiments and obscuring how regulatory states co-occur along individual DNA molecules. This limits mechanistic interpretation of cis-regulatory architecture, particularly within repetitive or structurally complex genomic regions that are poorly resolved by short-read approaches. Fiber-seq is a long-read, single-assay multiomic method that preserves regulatory context across individual DNA molecules by integrating chromatin accessibility footprinting with native long-read sequencing. Accessible adenines are enzymatically methylated using the N6-adenine methyltransferase Hia5 and sequenced alongside endogenous 5mC using PacBio or Oxford Nanopore Technologies platforms. Each long read therefore links chromatin accessibility, DNA methylation, nucleosome positioning, and transcription factor occupancy across extended regulatory domains with haplotype resolution. Fiber-seq recapitulates accessibility patterns observed with conventional assays while revealing chromatin architectures that are collapsed in short-read data. Single-molecule profiles resolve heterogeneous protein occupancy across individual DNA molecules, enabling direct detection of nucleosome positioning, transcription factor binding, and polymerase II recruitment at active regulatory elements. By distinguishing protected from accessible motifs within motif-dense regions, Fiber-seq supports composite motif analysis and prioritization of candidate regulatory elements and transcription factors for functional validation. These capabilities could support mechanistic studies of therapeutic response by enabling direct observation of regulatory state transitions following pharmacologic perturbation. For example, Fiber-seq could resolve loss of occupancy following transcription factor degradation together with local rearrangement of neighboring protein occupancy within the same cis-regulatory domain and on the same DNA molecule. This integrated single-molecule view of regulatory remodeling may support identification of adaptive resistance mechanisms, compensatory regulatory programs, pharmacodynamic biomarkers, and candidate synthetic lethal interactions relevant to epigenetic drug development. NOTE: Generative AI was used to assist in drafting the abstract text; all authors reviewed and approved the final content.
Keith E. Maier, James T. Anderson, Connor P. Frasier, Allison R. Hickman, Sabrina R. Hunt, Zu-Wen Sun, Martis W. Cowles, Andrew Stergachis, Bryan J. Venters, Michael-Christopher Keogh. Single-molecule protein footprinting with Fiber-seq resolves coordinated chromatin states across regulatory domain [abstract]. In: Proceedings of AACR Drug Discovery and Development (AACR D3) Conference; 2026 Jul 21-24; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(14_Suppl):Abstract nr B011.
Keith E. Maier, James T. Anderson, Connor P. Frasier et al.· Clinical Cancer Research· 0 citations
The pangenome provides unparalleled specificity to understand genetic variation in SD genes allowing us to distinguish functional genes from pseudogenes and highlighting potential gene innovations that arose most recently in human evolution.
Luyao Ren, DongAhn Yoo, Katarina Vlajic et al.· bioRxiv· 0 citations
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