Biology subjects

Rowell, W. J.

Publications and source records attributed to Rowell, W. J..

17 recordsLinked to original sources

bioRxiv2026

A computational model for quantifying instability of tandem repeats across the genome

Tandem repeats (TRs) exhibit high levels of somatic mosaicism, which is increasingly recognized as an important modifier of repeat expansion disorders. Long-read sequencing can capture full-length repeat alleles, yet robust frameworks for quantifying instability across TRs genome-wide are still needed. Here, we introduce a general-purpose model for quantifying TR instability in a given long-read sequencing dataset, without explicitly distinguishing biological mosaicism from technical noise, and which is broadly applicable to both simple and structurally complex loci. This model accurately characterizes allelic instability at each TR locus by representing the distribution of read-to-consensus deviations for each allele. Using HiFi sequencing data from 256 HPRC cell line samples, we fitted models for 617,007 TR loci, including known pathogenic repeats. We observe that instability levels are generally low, but vary substantially across individual TRs, and are driven more strongly by repeat composition than overall repeat length. Furthermore, we applied our method to targeted PureTarget long-read data from samples with known repeat expansions and identified significant mosaicism in the majority of expanded alleles. Our model offers a practical way to quantify instability of tandem repeats across the genome and to detect unusually unstable repeat alleles.

bioinformatics↗

bioRxiv2026

Hunting for microsatellite instability in long-read data with Owl

Microsatellite instability (MSI) is a key biomarker of mismatch repair deficiency and response to immunotherapy, yet most existing genomic detection methods are optimized for short-read sequencing and rely on small panels of homopolymer markers, limiting the ability to characterize genome-wide and motif-specific patterns of instability. Here we present Owl, a bioinformatic tool for quantifying MSI from long-read (PacBio) genomic data. Owl leverages a genome-wide marker set of more than 140,000 microsatellite repeats ranging from 1-6 bp in length to measure MSI across a phased genome. Using a wrap-around alignment algorithm, Owl constructs repeat-length distributions at each marker site and flags somatic instability using the coefficient of variation. We applied Owl to screen for markers with stable coverage, phasing, and baseline variation across 131 diverse genomes from the Human Pangenome Reference Consortium, where Owl scores ranged from 1.4% to 5.4% of markers exceeding the instability threshold. When applied to 19 cancer cell lines and one diffuse astrocytoma tumor-normal pair, Owl identified five MSI-high genomes with 15-18% unstable markers and showed close concordance with an Illumina DRAGEN MSI assay for the astrocytoma sample. Motif-level analyses revealed shared enrichment of short homopolymer and dinucleotide (A- and AT-rich) repeats across MSI-high cancers, and additionally uncovered a distinct pattern of elevated GGAA microsatellite instability in Ewing sarcoma cell lines, consistent with the known role of the EWS::FLI1 fusion protein at GGAA-rich regulatory elements. Owl is implemented in Rust and integrated into the PacBio HiFi Somatic workflow, providing a scalable framework for MSI analysis from long-read sequencing focused on repeat instability specifically in tumor samples.

bioinformatics↗

bioRxiv2026

Portello: Making global assembly more effective for rare-disease whole genome sequencing

MotivationLong-read de novo assembly methods provide great potential to improve whole genome sequencing analysis for rare-disease, however these methods are typically under-utilized. Among the complications of an assembly-based approach is the difficulty of reviewing read evidence for assembly-based inferences, including access to read-based information on basecall qualities, methylation, and mosaic variants not captured in the assembly consensus. An additional complication is resolving conflicts in variant representation between assembly-based inferences and those based on conventional reference-based read-mapping pipelines. Here we propose a new assembly-based mapping approach, portello, which addresses both of these issues by transferring read mappings from the samples de novo assembly contigs onto a standard reference sequence. ResultsPortellos assembly-based mapping approach results in read-to-reference alignments that can be used by standard mapping-based variant callers without modification, resulting in improved accuracy due to higher-quality mapping. This approach also enables assembly and reference mapping-based inferences to be unified onto a consistent view of the sample, and enables direct review of read-level support for the assembly consensus in the context of a standard reference genome. To demonstrate portellos impact on variant calling, we show that DeepVariant calls from portello alignments remove 47% of small variant basecall errors found in calls made from conventional read mapping. We additionally demonstrate how portello alignments can improve visualization and interpretation of complex loci, including an example where a copy number gain in a segmental duplication region can be easily inferred from assembly-based mapping while interpretation of the same region from conventional read mapping remains impractical. Portello is also capable of directly phasing and haplotagging read alignments as part of the alignment transfer process, including for partially-phased assembly contig inputs where phasing blocks need to be delineated within each contig. AvailabilityThe portello source and pre-compiled binary is released on GitHub: https://github.com/PacificBiosciences/portello.

genomics↗

bioRxiv2025

Complex structural variant visualization with SVTopo

Structural variants are genomic variants that impact at least 50 nucleotides and can play major roles in diversity and human health. Many structural variants are complex multi-breakpoint rearrangements that are difficult to comprehend with existing visualization tools. We present SVTopo, a tool to visualize complex structural variants with supporting evidence from high-accuracy long reads, in easily understood figures. We include examples of eleven categories of complex structural variants from seven human genomes. SVTopo shows breakpoint evidence in ways that aid reasoning about the impact of large, multi-breakpoint events such as inversions, translocations, and combinations of simpler structural variants.

bioinformatics↗

bioRxiv2024

The Platinum Pedigree: A long-read benchmark for genetic variants

Recent advances in genome sequencing have improved variant calling in complex regions of the human genome. However, it is difficult to quantify variant calling performance since existing standards often focus on specificity, neglecting completeness in difficult to analyze regions. To create a more comprehensive truth set, we used Mendelian inheritance in a large pedigree (CEPH-1463) to filter variants across Illumina, PacBio high-fidelity (HiFi), and Oxford Nanopore Technologies platforms. This generated a variant map with over 4.7 million single-nucleotide variants, 767,795 indels, 537,486 tandem repeats, and 24,315 structural variants, covering 2.77 Gb of the GRCh38 genome. This work adds [~]200 Mb of high-confidence regions, including 8% more small variants, and introduces the first tandem repeat and structural variant truth sets for NA12878. As an example of the value of this improved benchmark, we retrained DeepVariant using this data to reduce genotyping errors by [~]34%.

genomics↗

bioRxiv2024

Sawfish: Improving long-read structural variant discovery and genotyping with local haplotype modeling

MotivationStructural variants (SVs) play an important role in evolutionary and functional genomics but are challenging to characterize. High-accuracy, long-read sequencing can substantially improve SV characterization when coupled with effective calling methods. While state-of the-art long-read SV callers are highly accurate, further improvements are achievable by systematically modeling local haplotypes during SV discovery and genotyping. ResultsWe describe sawfish, an SV caller for mapped high-quality long reads incorporating systematic SV haplotype modeling to improve accuracy and resolution. Assessment against the draft Genome in a Bottle (GIAB) SV benchmark from the T2T-HG002-Q100 diploid assembly shows that sawfish has the highest accuracy among state-of-the-art long-read SV callers across every tested SV size group. Additionally, sawfish maintains the highest accuracy at every tested depth level from 10 to 32-fold coverage, such that other callers required at least 30-fold coverage to match sawfish accuracy at 15-fold coverage. Sawfish also shows the highest accuracy in the GIAB challenging medically relevant genes benchmark, demonstrating improvements in both comprehensive and medically relevant contexts. When joint-genotyping 10 samples from CEPH-1463, sawfish has over 9000 more pedigree-concordant calls than other state-of-the-art SV callers, with the highest proportion of concordant SVs (78%) as well. Sawfishs quality model can be used to select for an even higher proportion of concordant SVs (86%), while still calling over 5000 more pedigree-concordant SVs than other callers. These results demonstrate that sawfish improves on the state-of-the-art for long-read SV calling accuracy across both individual and joint-sample analyses. AvailabilitySawfish is released as a pre-compiled Linux binary and user guide on GitHub: https://github.com/PacificBiosciences/sawfish.

bioinformatics↗

bioRxiv2024

A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree

Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map ([~]3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.

genomics↗

bioRxiv2023

Small-field visual projection neurons detect translational optic flow and support walking control

Animals rely on visual motion for navigating the world, and research in flies has clarified how neural circuits extract information from moving visual scenes. However, the major pathways connecting these patterns of optic flow to behavior remain poorly understood. Using a high-throughput quantitative assay of visually guided behaviors and genetic neuronal silencing, we discovered a region in Drosophilas protocerebrum critical for visual motion following. We used neuronal silencing, calcium imaging, and optogenetics to identify a single cell type, LPC1, that innervates this region, detects translational optic flow, and plays a key role in regulating forward walking. Moreover, the population of LPC1s can estimate the travelling direction, such as when gaze direction diverges from body heading. By linking specific cell types and their visual computations to specific behaviors, our findings establish a foundation for understanding how the nervous system uses vision to guide navigation.

neuroscience↗

bioRxiv2023

Resolving the unsolved: Comprehensive assessment of tandem repeats at scale

Tandem repeat (TR) variation is associated with gene expression changes and over 50 rare monogenic diseases. Recent advances in sequencing have enabled accurate, long reads that can characterize the full-length sequence and methylation profile of TRs. However, despite these advances in sequencing technology, computational methods to fully profile tandem repeats across the genome do not exist. To address this gap, we introduce tools for tandem repeat genotyping (TRGT), visualization and an accompanying TR database. TRGT accurately resolves the length and sequence composition of TR regions in the human genome. Assessing 937,122 TRs, TRGT showed a Mendelian concordance of 99.56%, allowing a single repeat unit difference. In six samples with known repeat expansions, TRGT detected all repeat expansions while also identifying methylation signals, mosaicism, and providing finer resolution of repeat length. Additionally, we release a database with allele sequences and methylation levels for 937,122 TRs across 100 genomes.

genomics↗

bioRxiv2023

HiPhase: Jointly phasing small and structural variants from HiFi sequencing

BackgroundIn diploid organisms, phasing is the problem of assigning the heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation such as structural variants. However, current phasing tools typically only phase small variants, leaving larger structural variants unphased. MethodsWe developed HiPhase, a tool that jointly phases SNVs, indels, and structural variants. The main benefits of HiPhase are 1) dual mode allele assignment for detecting structural variants, 2) a novel application of the A*-algorithm to phasing, and 3) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. ResultsIn our assessment, HiPhase produced an average phase block NG50 of 493 kb with 933 switchflip errors and fully phased 95.2% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, and structural variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. Availabilityhttps://github.com/PacificBiosciences/HiPhase

bioinformatics↗

bioRxiv2022

Sentieon DNAscope LongRead - A highly Accurate, Fast, and Efficient Pipeline for Germline Variant Calling from PacBio HiFi reads

PacBio(R) HiFi sequencing is the first technology to offer economical and highly accurate long-read sequencing, with average read lengths greater than 10kb and average base accuracy of 99.8%1. Here, we present DNAscope LongRead, an accurate and efficient pipeline for germline variant calling from PacBio(R) HiFi reads. DNAscope LongRead is a modification and extension of Sentieons DNAscope tool, a precisionFDA award-winning variant caller. DNAscope LongRead is computationally efficient, calling variants from 30x HiFi samples in under 4 hours on a 16-core machine (120 virtual core-hours) and highly accurate, with precision and recall on the most recent GIAB benchmark dataset exceeding 99.83% for HiFi samples sequenced at 30x coverage, and robust to changes in benchmark dataset and upstream library preparation and sequencing.

bioinformatics↗

bioRxiv2021

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Pacific BioScience (PacBio) circular consensus sequencing (CCS) generates long (10-25 kb), accurate "HiFi" reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation uses a hidden Markov model (pbccs). Here, we introduce DeepConsensus, which uses a unique alignment-based loss to train a gap-aware transformer-encoder (GATE) for sequence correction. Compared to pbccs, DeepConsensus reduces read errors in the same dataset by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27%, and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity (NG50 4.9Mb to 17.2Mb), increase gene completeness (94% to 97%), reduce false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45), and also reduce variant calling errors by 24%.

bioinformatics↗

bioRxiv2021

A population of descending neurons that regulate the flight motor of Drosophila

Like many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours(1, 2). Because aerodynamic torque is roughly proportional to the fifth power of wing length(3), even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to the both damaged and intact wings(4). Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neurons (DNg02) that project directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike most descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

neuroscience↗

bioRxiv2021

Towards a Comprehensive Variation Benchmark for Challenging Medically-Relevant Autosomal Genes

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

genomics↗

bioRxiv2020

Benchmarking challenging small variants with linked and long reads

Genome in a Bottle (GIAB) benchmarks have been widely used to help validate clinical sequencing pipelines and develop new variant calling and sequencing methods. Here, we use accurate linked reads and long reads to expand the prior benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are not readily accessible to short reads. Our new benchmark adds more than 300,000 SNVs, 50,000 indels, and 16 % new exonic variants, many in challenging, clinically relevant genes not previously covered (e.g., PMS2). For HG002, we include 92% of the autosomal GRCh38 assembly, while excluding problematic regions for benchmarking small variants (e.g., copy number variants and reference errors) that should not have been in the previous version, which included 85% of GRCh38. By including difficult-to-map regions, this benchmark identifies eight times more false negatives in a short read variant call set relative to our previous benchmark.We have demonstrated the utility of this benchmark to reliably identify false positives and false negatives across technologies in more challenging regions, which enables continued technology and bioinformatics development.

genomics↗

bioRxiv2019

The landscape of SNCA transcripts across synucleinopathies: New insights from long reads sequencing analysis

Dysregulation of alpha-synuclein expression has been implicated in the pathogenesis of synucleinopathies, in particular Parkinsons Disease (PD) and Dementia with Lewy bodies (DLB). Previous studies have shown that the alternatively spliced isoforms of the SNCA gene are differentially expressed in different parts of the brain for PD and DLB patients. Similarly, SNCA isoforms with skipped exons can have a functional impact on the protein domains. The large intronic region of the SNCA gene was also shown to harbor structural variants that affect transcriptional levels. Here we apply the first study of using long read sequencing with targeted capture of both the gDNA and cDNA of the SNCA gene in brain tissues of PD, DLB, and control samples using the PacBio Sequel system. The targeted full-length cDNA (Iso-Seq) data confirmed complex usage of known alternative start sites and variable 3 UTR lengths, as well as novel 5 starts and 3 ends not previously described. The targeted gDNA data allowed phasing of up to 81% of the ~114kb SNCA region, with the longest phased block excedding 54 kb. We demonstrate that long gDNA and cDNA reads have the potential to reveal long-range information not previously accessible using traditional sequencing methods. This approach has a potential impact in studying disease risk genes such as SNCA, providing new insights into the genetic etiologies, including perturbations to the landscape the gene transcripts, of human complex diseases such as synucleinopathies.

genetics↗

bioRxiv2019

Highly-accurate long-read sequencing improves variant detection and assembly of a human genome

The major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

genomics↗