Biology subjects

Quinlan, A. R.

Publications and source records attributed to Quinlan, A. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Inherited DNA damage generates multi-allelic mutations in C. elegans

Exogenous and endogenous mutagens generate a wide variety of DNA lesions, including bulky adducts, chemical modifications, and single- or double-stranded breaks. A phenomenon called "lesion segregation," in which lesions evade repair and persist for multiple cell divisions, has recently been documented in tumors and healthy somatic tissues from mice and humans, respectively. Persistent lesions can generate multi-allelic variants (MAVs) by serving as templates for multiple rounds of error-prone replication. By reanalyzing data from a large C. elegans mutagenesis experiment, we observed robust evidence for MAVs at a small fraction (~0.2%) of mutated sites in the offspring of strains treated with alkylating agents. Because these sequencing data were derived from the progeny of a single F1 animal -- itself the offspring of a mutagenized P0 -- all mutations should be biallelic. The presence of multi-allelic variation implies that some DNA lesions are transmitted to the F1 zygote, evade repair, and are repeatedly bypassed by error-prone polymerases during embryogenesis. We suspect that many more lesions are inherited than is suggested by MAV prevalence, and that a large fraction of biallelic mutations are also caused by inherited lesions. Our results demonstrate that DNA lesions serve as durable, transgenerational templates for mutagenesis in C. elegans . We speculate that lesion segregation in the early embryo may be a source of mosaicism and genetic diversity in humans, as well.

genetics↗

bioRxiv2026

A family portrait of the genomic factors shaping tandem repeat mutagenesis

Tandem repeats (TRs) are among the most mutable loci in the human genome, but the genomic determinants of TR mutagenesis remain mysterious. We used PacBio HiFi long-read sequencing to profile nearly eight million TR loci in 28 members of a large, four-generation CEPH/Utah family designated K1463. We identified 1,270 de novo TR expansions and contractions across 20 children in the pedigree. De novo mutations (DNMs) were more likely to occur at loci that were longer, composed of uninterrupted motif sequences, and heterozygous in the parental germline. Children born to older fathers also exhibited more de novo mutations at short tandem repeats (STRs). A total of 43 TR loci were hyper-mutable in K1463, expanding or contracting up to twelve times across the pedigree. Among hyper-mutable loci that comprised multiple motifs (i.e., "complex" loci), specific motifs expanded and contracted more often than others; for example, all ten DNMs at a complex, hyper-mutable locus near the non-coding RNA LINC03021 involved the same 19bp motif. The mutability of particular motifs may be attributable to allele length, as 95% of DNMs at complex loci were expansions and contractions of the most abundant motif on a parental haplotype. However, future work will be required to disentangle the effects of nucleotide content and allele length on motif-specific mutability, especially at hyper-mutable TRs. Overall, this study combines long-read sequencing technologies with new software tools to comprehensively investigate the factors that influence TR mutagenesis.

genomics↗

bioRxiv2026

The performance of genetic-constraint metrics varies significantly across the human noncoding genome

A longstanding goal in human genetics is to prioritize noncoding loci that, when disrupted, lead to developmental disorders and other Mendelian traits. In pursuit of this goal, multiple metrics have been developed to distinguish neutrally evolving sequences from those subjected to purifying selection. These metrics are commonly evaluated genome-wide, e.g., by computing a precision-recall curve on windows tiling the entire noncoding genome. Here, we identify parts of the noncoding genome where these metrics significantly underperform relative to their genome-wide performance due to "bias" in the underlying models of neutral genetic variation and/or a low "signal-to-noise ratio" in the genetic data. The most extreme effects are found for Gnocchi (Chen et al. 2024), the performance of which declines as GC content increases. We suggest annotating constraint scores of noncoding genomic intervals with robust measures of the bias of the corresponding model, allowing users to gauge confidence in those scores.

genomics↗

bioRxiv2025

Human acrocentric chromosome short arm de novo mutation and recombination

The extraordinary repetitive content of human acrocentric short arms has prevented detailed investigations into recombination and de novo mutation. Integrating multiple sequencing technologies, we created 156 phased short arms and assessed 107 intergenerational transmissions from 23 samples in a four-generation pedigree. We observed a significant depletion (P<0.0001) of p-arm allelic recombination but one ectopic chr13-chr21 recombination breakpoint mediated by a 630 kbp segmental duplication mapping 1.6 Mbp distal to the SST1 array. In contrast, 18 maternal-biased q-arm allelic recombinations are significantly enriched within 5 Mbp of the centromere. Compared to autosomal euchromatin, the overall p-arm de novo single-nucleotide variant rate (1.33x10- per base pair per generation) is 10-fold higher, with a significant reduction of C>T but increased C>G and A>C mutations. We hypothesize that acrocentric sequence composition biases and the dearth of allelic recombination contribute to an elevated mutation rate and unique mutational signatures suggestive of mismatch repair defects and oxidative stress-induced DNA lesions.

genomics↗

bioRxiv2025

AVITI sequencing of a four-generation CEPH/Utah pedigree confirms low mutation rates at homopolymer loci despite their low sequence complexity

BackgroundShort tandem repeats (STRs) and homopolymers are among the most mutable loci in the human genome. Despite their presumed mutability owing to replication slippage, homopolymer loci exhibit lower mutation rates and minimal paternal age effects compared to other STRs. This paradox questions if technical limitations, rather than biological mechanisms, explain these observations. ResultsWe used the Element Biosciences AVITI platform to sequence the genomes of a 48-member, four-generation CEPH/Utah pedigree. As the AVITI platform reduces error rates at repetitive sequences compared to Illumina, this design enabled accurate mutation discovery at 90% of assayed homopolymers and a 1.7-fold increase in discoverable mutations compared to Illumina. We identified a median of 35 de novo homopolymer mutations per trio and a mutation rate of 5.28 x 10-5 DNMs per locus per generation, confirming a lower rate than dinucleotides (1.94 x 10-4). Most DNMs were single base-pair expansions or contractions. Despite comprising <1% of homopolymer loci, G/C homopolymers showed 18-fold higher mutation rates than A/T homopolymers; in contrast, the high dinucleotide mutation rate is not driven by a particular motif class. Parent-of-origin analysis revealed 78% of homopolymer mutations are paternal in origin, but no significant paternal age effect was observed. ConclusionsThis study confirms that homopolymers exhibit lower mutation rates and lack strong paternal age effects compared to other STRs, likely owing to the combination of a lower propensity to form slippage-causing secondary structures and more efficient mismatch repair. Our set of high-quality mutations suggest these phenomena are biological rather than technical in nature. Finally, we demonstrate that AVITI sequencing unlocks previously intractable regions of the genome and will be a powerful tool for continued investigation of repeat mutation.

genomics↗

bioRxiv2025

The selective dynamics of interruptions at short tandem repeats

Short tandem repeats (STRs) are hotspots of genomic instability that mutate at rates orders of magnitude greater than non-repetitive loci due to frequent replication slippage. Expansions at some STR loci cause Mendelian diseases, while variation at other noncoding loci may affect complex traits, possibly by altering transcription factor occupancy of nearby binding sites. Accordingly, some STRs are inferred to be under purifying selection, regardless of their instability. One or more "interruptions", or bases that disrupt the locuss canonical repeat, significantly decrease an STRs mutability. For example, the onset of Huntingtons Disease, a neurodegenerative disorder associated with somatic expansions of a trinucleotide coding STR, is delayed in individuals whose inherited alleles contain interruptions. Thus, interruptions that decrease mutation rate at some coding loci may broadly protect against deleterious phenotypes associated with locus instability. However, interruptions may themselves be deleterious at constrained loci, particularly at noncoding loci in gene regulatory elements, possibly disrupting the formation of secondary structures key to their function. We therefore hypothesized that the frequency of interruptions could depend on a locuss functional importance-at constrained loci, the fitness effects of expansions but also interruptions could be more deleterious than at neutral loci. To test this hypothesis, we examined the distribution of interruptions at [~]650,000 autosomal STRs. In the [~]2,500 3- or 6bp-motif coding STRs, we find that synonymous interruption density increases with purifying selection on the gene, while the opposite is true for missense-causing interruptions. In contrast, noncoding STRs in gene regulatory elements harbor fewer interruptions than those unassociated with function and putatively evolving neutrally. Our findings indicate that the abundance of interruptions may be partially explained at coding STRs by the benefit of lower instability. In contrast, maintaining a minimum core stretch of uninterrupted repeat may be key to the function of noncoding STRs that fall within regulatory elements, outweighing the benefits of stability.

evolutionary biology↗

bioRxiv2024

Vcfexpress: flexible, rapid user-expressions to filter and format VCFs

MotivationVariant Call Format (VCF) files are the standard output format for various software tools that identify genetic variation from DNA sequencing experiments. Downstream analyses require the ability to query, filter, and modify them simply and efficiently. Several tools are available to perform these operations from the command line, including BCFTools, vembrane, slivar, and others. ResultsHere, we introduce vcfexpress, a new, high-performance toolset for the analysis of VCF files, written in the Rust programming language. It is nearly as fast as BCFTools, but adds functionality to execute user expressions in the lua programming language for precise filtering and reporting of variants from a VCF or BCF file. We demonstrate performance and flexibility by comparing vcfexpress to other tools using the vembrane benchmark. Availabilityvcfexpress is available under the MIT license at https://github.com/brentp/vcfexpress Contactbpederse@gmail.com, aquinlan@genetics.utah.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2024

Identification of CNTN2 as a genetic modifier of PIGA-CDG through pedigree analysis of a family with incomplete penetrance and functional testing in Drosophila

Loss of function mutations in the X-linked PIGA gene lead to PIGA-CDG, an ultra-rare congenital disorder of glycosylation (CDG), typically presenting with seizures, hypotonia, and neurodevelopmental delay. We identified two brothers (probands) with PIGA-CDG, presenting with epilepsy and mild developmental delay. Both probands carry PIGAS132C, an ultra-rare variant predicted to be damaging. Strikingly, the maternal grandfather and a great-uncle also carry PIGAS132C, but neither presents with symptoms associated with PIGA-CDG. We hypothesized genetic modifiers may contribute to this reduced penetrance. Using whole genome sequencing and pedigree analysis, we identified possible susceptibility variants found in the probands and not in carriers and possible protective variants found in the carriers and not in the probands. Candidate variants included heterozygous, damaging variants in three genes also involved directly in GPI-anchor biosynthesis and a few genes involved in other glycosylation pathways or encoding GPI-anchored proteins. We functionally tested the predicted modifiers using a Drosophila eye-based model of PIGA-CDG. We found that loss of CNTN2, a predicted protective modifier, rescues loss of PIGA in Drosophila eye-based model, like what we predict in the family. Further testing found that loss of CNTN2 also rescues patient-relevant phenotypes, including seizures and climbing defects in Drosophila neurological models of PIGA-CDG. By using pedigree information, genome sequencing, and in vivo testing, we identified CNTN2 as a strong candidate modifier that could explain the incomplete penetrance in this family. Identifying and studying rare disease modifier genes in human pedigrees may lead to pathways and targets that may be developed into therapies.

genetics↗

bioRxiv2024

TRGT-denovo: accurate detection of de novo tandem repeat mutations

MotivationIdentifying de novo tandem repeat (TR) mutations on a genome-wide scale is essential for understanding genetic variability and its implications in rare diseases. While PacBio HiFi sequencing data enhances the accessibility of the genomes TR regions for genotyping, simple de novo calling strategies often generate an excess of likely false positives, which can obscure true positive findings, particularly as the number of surveyed genomic regions increases. ResultsWe developed TRGT-denovo, a computational method designed to accurately identify all types of de novo TR mutations--including expansions, contractions, and compositional changes-- within family trios. TRGT-denovo directly interrogates read evidence, allowing for the detection of subtle variations often overlooked in variant call format (VCF) files. TRGT-denovo improves the precision and specificity of de novo mutation (DNM) identification, reducing the number of de novo candidates by an order of magnitude compared to genotype-based approaches. In our experiments involving eight rare disease trios previously studied TRGT-denovo correctly reclassified all false positive DNM candidates as true negatives. Using an expanded repeat catalog, it identified new candidates, of which 95% (19/20) were experimentally validated, demonstrating its effectiveness in minimizing likely false positives while maintaining high sensitivity for true discoveries. Availability and implementationBuilt in Rust, TRGT-denovo is available as source code and a pre-compiled Linux binary along with a user guide at: https://github.com/PacificBiosciences/trgt-denovo.

bioinformatics↗

bioRxiv2024

Improved characterization of single-cell RNA-seq libraries with paired-end avidity sequencing

Prevailing poly(dT)-primed 3 single-cell RNA-seq protocols generate barcoded cDNA fragments containing the reverse transcriptase priming site, which is expected to be the poly(A) tail or a genomic adenine homopolymer. Direct sequencing across this priming site was historically difficult because of DNA sequencing errors induced by the homopolymeric primer at the barcode end. Here, we evaluate the capability of "avidity base chemistry" DNA sequencing from Element Biosciences to sequence through this homopolymer accurately, and the impact of the additional cDNA sequence on read alignment and precise quantification of polyadenylation site usage. We find that the Element Aviti instrument sequences through the thymine homopolymer into the subsequent cDNA sequence without detectable loss of accuracy. The resulting paired-end alignments enable direct and independent assignment of reads to polyadenylation sites, which bypasses complexities and limitations of conventional approaches but does not consistently improve read mapping rates compared to single-end alignment. We also characterize low-level artifacts and arrive at an adjusted adapter trimming and alignment workflow that significantly improves the alignment of sequence data from Element and Illumina, particularly in the context of extended read lengths. Our analyses confirm that Element avidity sequencing is an effective alternative to Illumina sequencing for standard single-cell RNA-seq, particularly for polyadenylation site analyses but do not rule out the potential for similar performance from other emerging platforms.

genomics↗

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

Epistasis between mutator alleles contributes to germline mutation rate variability in laboratory mice

Maintaining germline genome integrity is essential and enormously complex. Although many proteins are involved in DNA replication, proofreading, and repair [1], mutator alleles have largely eluded detection in mammals. DNA replication and repair proteins often recognize sequence motifs or excise lesions at specific nucleotides. Thus, we might expect that the spectrum of de novo mutations -- the frequencies of C>T, A>G, etc. -- will differ between genomes that harbor either a mutator or wild-type allele. Previously, we used quantitative trait locus mapping to discover candidate mutator alleles in the DNA repair gene Mutyh that increased the C>A germline mutation rate in a family of inbred mice known as the BXDs [2,3]. In this study we developed a new method to detect alleles associated with mutation spectrum variation and applied it to mutation data from the BXDs. We discovered an additional C>A mutator locus on chromosome 6 that overlaps Ogg1, a DNA glycosylase involved in the same base-excision repair network as Mutyh [4]. Its effect depended on the presence of a mutator allele near Mutyh, and BXDs with mutator alleles at both loci had greater numbers of C>A mutations than those with mutator alleles at either locus alone. Our new methods for analyzing mutation spectra reveal evidence of epistasis between germline mutator alleles and may be applicable to mutation data from humans and other model organisms.

genetics↗

bioRxiv2022

Annotation of structural variants with reported allele frequencies and related metrics from multiple datasets using SVAFotate

BackgroundIdentification of impactful genetic variants from DNA sequencing data relies on increasingly detailed filtering strategies to isolate the small subset of variants that are more likely to underlie a disease phenotype. Datasets reflecting population allele frequencies of different types of variants have been demonstrated as powerful filtering tools, especially in the context of rare disease analysis. While such population-scale allele frequency datasets now exist for structural variants (SVs), it remains a challenge to match SV calls between multiple datasets and thereby correctly estimate the population allele frequency of a putative SV. ResultsWe introduce SVAFotate, a software tool for SV matching that enables the annotation of SVs with variant allele frequency and related information. These annotations are derived from known SV datasets which are incorporated by SVAFotate. As a result, VCF files annotated by SVAFotate offer a variety of annotations to aid in the stratification of SVs as common or rare in the broader human population. ConclusionsHere we demonstrate the use of SVAFotate in the classification of SVs with regards to their population frequency and illustrate how annotations provided by SVAFotate can be used to filter and prioritize SVs. Lastly, we detail how best to utilize these SV annotations in the analysis of genetic variation in studies of rare disease.

bioinformatics↗

bioRxiv2022

Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies

BackgroundDespite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites. ResultsSeveral existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in "cryptic" splicing regions beyond canonical donor or acceptor splice sites. ConclusionIntegrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.

genomics↗

bioRxiv2021

STRling: a k-mer counting approach that detects short tandem repeat expansions at known and novel loci

Expansions of short tandem repeats (STRs) cause dozens of rare Mendelian diseases. However, STR expansions, especially those arising from repeats not present in the reference genome, are challenging to detect from short-read sequencing data. Such "novel" STRs include new repeat units occurring at known STR loci, or entirely new STR loci where the sequence is absent from the reference genome. A primary cause of difficulty detecting STR expansions is that reads arising from STR expansions are frequently mismapped or unmapped. To address this challenge, we have developed STRling, a new STR detection algorithm that counts k-mers (short DNA sequences of length k) in DNA sequencing reads, to efficiently recover reads that inform the presence and size of STR expansions. As a result, STRling can call expansions at both known and novel STR loci. STRling has a sensitivity of 83% for 14 known STR disease loci, including the novel STRs that cause CANVAS and DBQD2. It is the first method to resolve the position of novel STR expansions to base pair accuracy. Such accuracy is essential to interpreting the consequence of each expansion. STRling has an estimated 0.078 false discovery rate for known pathogenic loci in unaffected individuals and a 0.20 false discovery rate for genome-wide loci in unaffected individuals when using variants called from long-read data as truth. STRling is fast, scalable on cloud computing, open-source, and freely available at https://github.com/quinlan-lab/STRling.

bioinformatics↗

bioRxiv2021

Mining Thousands of Genomes to Classify Somatic and Pathogenic Structural Variants

Structural variants (SVs) are associated with cancer progression and Mendelian disorders, but challenges with estimating SV frequency remain a barrier to somatic and de novo classification. In particular, variability in filtering and variant calling heuristics limit our ability to use SV catalogs from large cohorts. We present a method to index and search the raw alignments from thousands of samples that overcomes these limitations and supports robust SV analysis.

bioinformatics↗

bioRxiv2021

Extensive recombination-driven coronavirus diversification expands the pool of potential pandemic pathogens

The ongoing SARS-CoV-2 pandemic is the third zoonotic coronavirus identified in the last twenty years. Enzootic and epizootic coronaviruses of diverse lineages also pose a significant threat to livestock, as most recently observed for virulent strains of porcine epidemic diarrhea virus (PEDV) and swine acute diarrhea-associated coronavirus (SADS-CoV). Unique to RNA viruses, coronaviruses encode a proofreading exonuclease (ExoN) that lowers point mutation rates to increase the viability of large RNA virus genomes, which comes with the cost of limiting virus adaptation via point mutation. This limitation can be overcome by high rates of recombination that facilitate rapid increases in genetic diversification. To compare dynamics of recombination between related sequences, we developed an open-source computational workflow (IDPlot) to measure nucleotide identity, locate recombination breakpoints, and infer phylogenetic relationships. We analyzed recombination dynamics among three groups of coronaviruses with noteworthy impacts on human health and agriculture: SARSr-CoV, Betacoronavirus-1, and SADSr-CoV. We found that all three groups undergo recombination with highly diverged viruses from sparsely sampled or undescribed lineages, which can disrupt the inference of phylogenetic relationships. In most cases, no parental origin of recombinant regions could be found in genetic databases, suggesting that much coronavirus diversity remains unknown. These patterns of recombination expand the genetic pool that may contribute to future zoonotic events. Our results also illustrate the limitations of current sampling approaches for anticipating zoonotic threats to human and animal health.

evolutionary biology↗

bioRxiv2021

Unfazed: parent-of-origin detection for large and small de novo variants

SummaryUnfazed is a command-line tool to determine the parental gamete of origin for de novo mutations from paired-end Illumina DNA sequencing reads. Unfazed uses variant information for a sequenced trio to identify the parental gamete of origin by linking phase-informative inherited variants to de novo mutations using read-based phasing. It achieves a high success rate by chaining reads into haplotype groups, thus increasing the search space for informative sites. Unfazed provides a simple command-line interface and scales well to large inputs, determining parent-of-origin for nearly 30,000 de novo variants in under 60 hours. AvailabilityUnfazed is available at https://github.com/ibelyeu/unfazed.

genomics↗