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Ryke, E.

Publications and source records attributed to Ryke, E..

4 recordsLinked to original sources

Short-Read Sequencing Benchmarking with Donor-Specific Assemblies

BackgroundHigh-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. ResultsWe 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. ConclusionsDonor-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.

bioinformatics↗

Long-read MitoScope reveals tissue-resolved somatic mitochondrial variation and landscape of nuclear-embedded mitochondrial sequences

The mitochondrial genome (mtDNA), rich in repeats and prone to nuclear mitochondrial DNA segments (NUMTs), drives somatic mosaicism implicated in cancer, metabolic syndromes, and neurodegeneration, yet short-read sequencing yields incomplete catalogs, mapping artifacts, and false heteroplasmies. Here, we introduce MitoScope, a scalable long-read workflow to assemble mtDNA, perform high-fidelity variant calling, resolve heteroplasmy, and characterize NUMTs in benchmarking tissues from the Somatic Mosaicism Across Human Tissues (SMaHT) Network. MitoScope shows high sensitivity and precision, determines copy number, and uncovers low-frequency variants. We define an age- and tissue-dependent landscape of mtDNA mosaicism, including low-frequency pathogenic heteroplasmies, a bimodal heteroplasmy spectrum shaped by purifying selection, and age-accumulating deletions enriched for microhomology. Parallel profiling of NUMTs identifies high-confidence events with >2-fold more NUMTs than short-read surveys--with evidence of nonrandom trinucleotide contexts at breakpoints. These findings expose pervasive, tissue-resolved somatic mtDNA and NUMT instability with direct relevance for variant interpretation, aging, and human disease.

genomics↗

Donor-specific assemblies enhance somatic structural variant detection in complex genomic regions

Structural variants (SVs) contribute substantially to genomic variation and disease, but detecting somatic SVs (sSVs) remains difficult due to reference bias, mosaicism, and enrichment in repetitive regions. Linear reference genomes, like GRCh38 and CHM13, do not fully capture individual genomic structure, which can obscure true somatic variation. Donor-specific assemblies (DSAs) generated from the same genome where sSVs are being assayed provide a personalized alternative, yet their performance for sSV detection has not been systematically assessed. As part of the Somatic Mosaicism across Human Tissues (SMaHT) Network, we benchmark a DSA for sSV discovery in the COLO829 melanoma cell line with a matched normal sample from the same individual. We compare sSV detection across GRCh38, CHM13, and the COLO829BL_DSA using three different sSV callers (Delly, Severus, and Sniffles2) and sequence data from multiple long-read platforms. The COLO829BL_DSA identifies 1.8-fold more manually validated sSVs than linear references, in regions both shared with GRCh38 and CHM13 and unique to the COLO829BL_DSA. Variants detected only with the COLO829BL_DSA are often found in satellite and other repeat-rich regions that are difficult to resolve using standard references. In addition, several COLO829BL_DSA-specific sSVs are located in genes, some of which are associated with cancer. Overall, these results underscore the utility of DSAs in improving sSV detection.

genomics↗

A telomere-to-telomere map of somatic mutation burden and functional impact in cancer

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 cancers somatic variation and their functional impact, establishing a blueprint for T2T studies of mosaicism.

genomics↗