James T. Bennett

Background High-throughput short-read sequencing has become a core technology for genomics, but the rapid expansion of available platforms has made it increasingly important to benchmark them under standardized conditions. A major challenge is that conventional reference-based comparisons confound true sequencing errors with inherited variation and reference bias, making it difficult to isolate platform-intrinsic performance. Results We benchmarked nine short-read chemistries across seven DNA sequencers using two highly characterized benchmark samples, HG002 and COLO829BL, together with donor-specific assemblies to measure sequencing errors against sample-matched genomic references. This strategy separated authentic platform errors from biological divergence and revealed substantial differences in substitution, indel, read-position, and sequence-context error profiles. Element AVITI UltraQ and Roche SBX-D showed the lowest substitution error rates, whereas Ultima and Roche chemistries exhibited the strongest indel-associated biases. We also found pronounced platform-specific effects in low-complexity regions and trinucleotide contexts, including homopolymer-associated errors and context-dependent substitution skews that are directly relevant to rare-variant detection. In addition, we show that donor-specific references are essential for unbiased base-quality recalibration because they minimize reference bias and more faithfully support cross-platform comparison and low-frequency variant-calling thresholds. Conclusions Donor-specific assembly-based benchmarking provides a robust framework for measuring true short-read sequencing errors and comparing platforms on a common, sample-matched basis. Our results establish a comprehensive reference for the community and show that authentic error profiles can guide platform selection, quality filtering, and improved detection of rare somatic variation.

The mitochondrial genome (mtDNA), rich in repeats and prone to nuclear mitochondrial DNA segments (NUMTs), is implicated in cancer, metabolic syndromes, and neurodegeneration, yet short-read sequencing yields incomplete catalogs, mapping artifacts, and false heteroplasmies. We introduce MitoScope, a scalable end-to-end long-read mitochondrial analysis workflow that integrates mtDNA-read selection, heteroplasmic variant detection, assembly, copy number estimation, read-level haplotyping, and NUMT profiling. Applied to benchmarking data from the Somatic Mosaicism Across Human Tissues (SMaHT) Network, we reveal high sensitivity and precision compared to existing methods and successfully uncover known mitochondrial biology relevant for variant interpretation, aging, and human disease.

Gene regulation is orchestrated by the co-binding of proteins along chromosome-length chromatin fibers within single cells, yet the heterogeneity of this occupancy between haplotypes and cells remains poorly resolved in diploid organisms. Here we present Deaminase-Assisted single-molecule chromatin Fiber sequencing (DAF-seq), which enables single-molecule footprinting at near-nucleotide resolution while synchronously profiling single-molecule chromatin states and DNA sequence. DAF-seq illuminates cooperative protein occupancy at individual regulatory elements and resolves the functional impact of somatic variants and rare chromatin epialleles. Single-cell DAF-seq (scDAF-seq) generates chromosome-length protein co-occupancy maps across 99% of each individual cell's mappable genome. scDAF-seq uncovers extensive chromatin plasticity both within and between single diploid cells, with chromatin actuation diverging by 61% between haplotypes within a cell, and 63% between cells. Moreover, we find that regulatory elements are preferentially co-actuated along the same fiber in a distance-dependent manner that mirrors cohesin-mediated loops. Overall, DAF-seq enables the characterization of protein occupancy across entire chromosomes with single-nucleotide, single-molecule, single-haplotype and single-cell precision.

Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep whole-genome sequencing using short and long reads (five centers, 180–500× each). We assembled a reference of 44,008 mosaic SNVs and 2,059 Indels, cross-validation between platforms to expose limits of short-read analysis. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied eleven algorithms to mixture data, call sets were largely discordant across tools and replicates, partly reflecting stochastic presence of low-VAF mutations in biological replicants. For >2% VAF SNVs, sensitivity and precision approached ∼80% at ≥300×, with little gain from additional sequencing. This work provides a comprehensive framework for reliable detection of low-VAF mutations in non-cancer tissues and a valuable resource for the community.

Oncogenesis involves widespread genetic and epigenetic alterations, yet the full spectrum of somatic variation genome-wide remains unresolved. We generated a near-telomere-to-telomere (T2T) diploid assembly of a donor paired with deep short- and long-read sequencing of their melanoma. This revealed that 16% of somatic variants occur in sequences absent from GRCh38, with satellite repeats acting as hotspots for UV-induced damage due to sequence-intrinsic mutability and inefficient repair. Centromere kinetochore domains emerged as focal sites of structural, genetic, and epigenetic variation, leading to remodeling of centromere kinetochore binding domains during tumor evolution. Single-molecule telomere reconstructions uncovered cycles of attrition, deletion, and telomerase-mediated extension that shape cancer telomeres. Finally, diploid chromatin maps exposed that copy number alterations and epimutations, rather than point mutations, predominate in rewiring cancer regulatory programs. These findings define the full landscape of a cancer’s somatic variation and their functional impact, establishing a blueprint for T2T studies of mosaicism.

From fertilization onwards, the cells of the human body acquire variations in their DNA sequence, known as somatic mutations. These postzygotic mutations arise from intrinsic errors in DNA replication and repair, as well as from exposure to mutagens. Somatic mutations have been implicated in some diseases, but a fundamental understanding of the frequency, type and patterns of mutations across healthy human tissues has been limited. This is primarily due to the small proportion of cells harbouring specific somatic variants within an individual, making them more challenging to detect than inherited variants. Here we describe the Somatic Mosaicism across Human Tissues Network, which aims to create a reference catalogue of somatic mutations and their clonal patterns across 19 different tissue sites from 150 non-diseased donors and develop new technologies and computational tools to detect somatic mutations and assess their phenotypic consequences, including clonal expansions. This strategy enables a comprehensive examination of the mutational landscape across the human body, and provides a comparison baseline for somatic mutation in diseases. This will lead to a deep understanding of somatic mutations and clonal expansions across the lifespan, as well as their roles in health, in ageing and, by comparison, in diseases.

Gene regulation is mediated by the co-occupancy of numerous proteins along individual chromatin fibers. However, our tools for deeply profiling how proteins co-occupy individual fibers, especially at the single-cell level, remain limited. We present Deaminase-Assisted single-molecule chromatin Fiber sequencing (DAF-seq), which leverages a non-specific double-stranded DNA deaminase toxin A (SsDddA) to efficiently stencil protein occupancy along DNA molecules via selective deamination of accessible cytidines, which are preserved via C-to-T transitions upon DNA amplification. We demonstrate that DAF-seq enables ~200,000-fold enrichment of target loci for single-molecule footprinting at near single-nucleotide resolution, enabling the precise delineation of the regulatory logic guiding neighboring proteins to cooperatively occupy chromatin fibers. Furthermore, DAF-seq enables the synchronous identification of single-molecule chromatin and genetic architectures - resolving the functional impact of rare somatic variants, as well as transitional chromatin states guiding haplotype-selective promoter actuation. Finally, we demonstrate that single-cell DAF-seq enables the accurate reconstruction of the diploid genome and epigenome from a single cell, revealing that a cell's accessible regulatory landscape can diverge by as much as 63% while still retaining the cell's identity. Overall, DAF-seq enables the comprehensive characterization of protein occupancy and chromatin accessibility across entire chromosomes with single-nucleotide, single-molecule, single-haplotype, and single-cell precision.

Diploid human cells contain two non-identical genomes, and differences in their regulation underlie human development and disease. We present Fiber-seq Inferred Regulatory Elements (FIRE) and show that FIRE provides a more comprehensive and quantitative snapshot of the accessible chromatin landscape across the 6 Gbp diploid human genome, overcoming previously unrecognized biases in existing regulatory element catalogs. FIRE enables comprehensive detection of haplotype-selective chromatin accessibility (HSCA), exposing novel imprinted elements lacking underlying parent-of-origin CpG methylation differences, and gene regulatory modules that permit genes to escape X chromosome inactivation. We uncover that the human leukocyte antigen (HLA) locus harbors the most HSCA in immune cells, where we resolve specific transcription factor (TF) binding events disrupted by disease-associated variants. Finally, we demonstrate that the regulatory landscape of a cell is littered with autosomal somatic chromatin epimutations that are propagated by clonal expansions to create mitotically stable and non-genetically deterministic chromatin alterations.