Biology subjects

Carroll, A.

Publications and source records attributed to Carroll, A..

At least 19 recordsLinked to original sources

bioRxiv2026

The Genome In A Bottle HG002 assembly-based variant benchmark set enables comprehensive benchmarking of small and structural variants.

High-accuracy, high-resolution benchmark data are fundamental to improving the accuracy and generalizability of sequencing technologies and associated algorithms. Most existing benchmarks for DNA sequencing rely on mapping to a single linear reference, omitting inaccessible and highly repetitive complex genomic regions. Here, we present the Genome in a Bottle (GIAB) Consortium's HG002 v5.0q benchmark set, a more comprehensive variant benchmark derived from a fully phased, highly curated, and accurate diploid assembly of HG002. Our approach leverages recent advances in long-read sequencing and assembly to provide confident small- and structural-variant calls across previously inaccessible regions, including segmental duplications, homopolymers, tandem repeats, and complex immune loci. The v5.0 benchmark significantly expands the callable genome relative to v4.2.1, adding x200 Mbp of sequence and increasing variant detection by 18 % for small variants and 3-fold for structural variants compared to previous benchmarks. The benchmark regions include more variants in repetitive regions, including 1.2 x segmental duplications, 1.8 x tandem repeats, and 2.0 x homopolymers, compared to v4.2.1. Separate and combined small- and structural-variant benchmarks are available for three versions of the human reference genome (GRCh37, GRCh38, and CHM13). We validate the reliability of this benchmark set by comparing multiple sequencing technologies and variant calling pipelines and curating differences. The v5.0q benchmark provides a critical resource for the development and validation of next-generation sequencing technologies and analysis methods.

genomics↗

bioRxiv2026

WNK-SPAK/OSR1 signaling pathway facilitates ictal activity via reduced neuronal chloride extrusion rate

Seizures upregulate Na+-K+-2Cl- (NKCC1)-mediated Cl- influx and downregulate K+-Cl- (KCC2)-mediated Cl- efflux via the WNK-SPAK/OSR1 kinases, leading to cytoplasmic chloride ([Cl-]i) accumulation, reduced GABAergic inhibition and anticonvulsant failure. Early studies found that inhibiting WNK-kinase reduced baseline [Cl-]i (ECl) and seizures via increased KCC2 activity. However, increased KCC2 activity alone should not affect ECl whose determinants are more complex. We determined the net effects of WNK-SPAK/OSR1 pathway inhibitor WNK463 on ECl and [Cl-]i transients during spontaneous ictal-like discharges (ILDs). We found that WNK463 reduced interictal [Cl-]i but did not change baseline [Cl-]i measured in the presence of TTX. WNK463 enhanced neuronal Cl- extrusion during and after ILDs, before abolishing ILDs. Pharmacological inhibition and targeted siRNA silencing demonstrated that the anti-ictal effects of WNK463 involved both NKCC1 and KCC2. Our data support a mechanism whereby mutual NKCC1 inhibition and KCC2 activation via the WNK-SPAK/OSR1 pathway exert powerful anti-ictal effects by facilitating [Cl-]i extrusion during ILDs.

neuroscience↗

bioRxiv2026

Unlocking the venom vault: Museum venomics reveals an untapped biochemical archive in natural history collections

Venoms are powerful weapons that shape ecological interactions across the animal kingdom. They also have high medical importance, causing thousands of human fatalities annually, while offering a rich resource for drug discovery. Despite this, considerable logistical, safety and ethical challenges mean only a fraction of the worlds venoms have been profiled quantitatively. Natural history collections offer opportunities to greatly expand our knowledge of venom systems. We used quantitative proteomic mass spectrometry on preserved venom glands, spanning 0-57 years in age, from 37 venomous snake species (32 elapids and 5 viperids), alongside fresh venom samples from most of the same taxa. Preserved glands and fresh venoms from the same species showed strong concordance in venom composition across multiple metrics. Critically, specimen age did not degrade data quality, indicating that decades-old material yields reliable quantitative profiles, opening the possibility for vast quantities of existing museum specimens to be used. When we integrate our data with published profiles, we confirm known elapid vs viper broad diversity patterns while revealing substantial Australasian elapid venom diversity. Our findings demonstrate the potential of natural history collections as a vast, largely untapped biochemical archive for high-throughput "museum venomics," enabling evolutionary and temporal analyses of venom diversity at unprecedented scale.

molecular biology↗

bioRxiv2026

A complete human pancreatic cancer genome

Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine.1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions.1-3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres.4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

genomics↗

bioRxiv2026

PanVariants: Best Practice for Pangenome-based Variant Calling Pipeline and Framework

BackgroundAlthough pangenome references offer richer population diversity compared to linear references, current mainstream pangenome-based variant callers are limited to detecting only known variants stored in the graph. To address this limitation, we developed PanVariants, a novel pipeline designed to improve the detection of both known and novel variants accurately. We systematically evaluated its performance against the traditional linear alignment solution (BWA+GATK/Manta) and the existing pangenome-aware solution (DRAGEN/PanGenie) in three contexts: small variants (SNVs/indels) and structural variants (SVs) accuracy in Genome in a Bottle samples, clinical detection on positive samples, and application in cohort-based joint calling. ResultsBy integrating k-mer-based and mapping-based methods, PanVariants significantly reduced variant errors (FPs + FNs), achieving a 73% reduction compared to BWA+GATK and a 45% reduction compared to DRAGEN for SNVs. Retraining the DeepVariant model with high-quality DNBSEQ data further decreased errors by 15%. For SVs detection, PanVariants attained an F1-score of 89.39%, markedly outperforming DRAGEN (68.18%) and BWA+Manta (58.33%), approaching long-read sequencing performance (95.22%). In validation using clinical positive samples, PanVariants successfully detected all expected pathogenic variants while PanGenie failed. In the cohort joint-calling analysis, PanVariants detected more variants, made fewer Mendelian inheritance errors, and gave better per-sample accuracy than GATK. ConclusionsPanVariants establishes a robust framework and best-practice pipeline for pangenome-based variant detection, achieving both sensitive novel variant discovery and high accuracy for SNVs, indels and SVs. Our systematic evaluation of optional processing steps and input variables offers practical guidance for users. Validated across diagnostic and population-based applications, our findings strongly support the transition from linear to pangenome references in future genomics.

bioinformatics↗

bioRxiv2026

The 3D Ultrastructure of C. elegans Gut Granules

We identify an endoderm-restricted organelle in published volume electron microscopy datasets of C. elegans embryos. The organelle consists of a tubular ring surrounding a membrane-bound compartment harboring a prominent dense particle and exhibits a basal polarity and size concordant with canonical gut granules. This finding offers ultrastructural detail to recent evidence that gut granules are bi-lobed organelles with two distinct compartments.

cell biology↗

bioRxiv2026

Australian giant kelp genome assemblies show distinct Southern Hemisphere genetics

Giant kelp, Macrocystis pyrifera, occurs across northern and southern Hemisphere temperate coasts and is at high risk from ocean warming. Few giant kelp forests remain across the Southeast Australian shelf, while a handful of forests are actively being restored. Genomic resources can greatly aid in the conservation of remnant populations and enhance restoration efforts. Reference genomes are a fundamental resource as they are a prerequisite to, or enhance, many analyses used in conservation genomics. A single reference genome is available for giant kelp, assembled from a Californian haploid specimen. However, increasing evidence of genetic divergence between Northern and Southern Hemisphere populations highlights the need for regionally representative reference genomes. Here, we present two genome assemblies from the diploid vegetative tissue of Australian giant kelp specimens. We performed de novo genome assembly using long-read sequencing (PacBio HiFi and ONT R10.4 Simplex) and scaffolded the assemblies with the ONT reads, assembling 98-99% of the genomes into 35 pseudo-chromosomes. Genome sizes ranged from 528-534 Mbp, with BUSCO completeness scores of 97-98% and QV scores of 51-52. Genome annotation identified 17,565-17,800 genes in the Australian genomes. Genomic divergence between the Australian and Californian giant kelp genomes was seven-fold greater than between Australian genomes (1.5% vs 0.2%), supporting a Northern-Southern Hemisphere genetic divergence. Functional divergence was also observed between Australian and Californian genomes, reflected by differing patterns of enrichment in gene ontologies linked to energy metabolism, proteostasis and stress responses. These two new genome assemblies will serve as valuable resources for ongoing research into Southern Hemisphere giant kelp genetics, while providing the basis for genomic-guided conservation and restoration of remnant giant kelp forests in Australia.

genomics↗

bioRxiv2025

Kruppel-like factor 1 acts upstream of the SKN-1/Nrf transcription factors to modulate oxidative stress, lipid homeostasis and longevity

Maintenance of lipid and redox homeostasis are essential for stress resistance and longevity, but the transcriptional networks coordinating these processes remain incompletely understood. In Caenorhabditis elegans, the transcription factors SKN-1A/Nrf1 and SKN-1C/Nrf2 mediate distinct stress responses that promote proteostasis, lipid homeostasis, and oxidative stress. Here we identify the Kruppel-like factor KLF-1 as a critical upstream regulator of both SKN-1A and SKN-1C. We show that KLF-1 is required for the oxidative stress resistance and longevity of germline-deficient animals. Genetic interaction studies showed that KLF-1 acts in parallel to the lipogenic regulator Sterol regulatory element-Binding Protein 1 (SBP-1/SREBP1), whereas the related KLF-2 exerts opposing effects on lipid accumulation through SBP-1. Together, these findings place KLF-1 and KLF-2 within a transcriptional network that integrates lipid metabolism, oxidative stress responses, and aging. This work uncovers a conserved regulatory network linking KLFs and SKN-1/Nrf transcription factors in the maintenance of lipid homeostasis and longevity assurance.

cell biology↗

bioRxiv2025

Rapid, accurate long- and short-read mapping to large pangenome graphs with vg Giraffe

1We previously introduced Giraffe, a short-read-to-pangenome graph mapper available in the vg pangenomics toolkit. Giraffe was fast and accurate for mapping short reads to human-scale pangenomes, but struggled with long reads. Long reads present a unique challenge to pangenome mapping algorithms due to their length and error profile, which allow them to take more topologically complex paths through the pangenome graph and increase the possible search space for the algorithm. We present updates to Giraffe that allow it to quickly and accurately map long reads to pangenome graphs. For both short and long reads, Giraffe mapping to a pangenome containing data from more than 450 human haplotypes, generated by the Human Pangenome Reference Consortium, is comparable in speed to linear mappers to human reference genomes; Giraffe is also over an order of magnitude faster than GraphAligner, the current state-of-the-art long-read-to-pangenome mapper. Its alignments produce similar or improved small and structural variant calling results, compared to those from commonly used graph-based and linear mappers. We additionally demonstrate using Giraffes long read alignments in a pangenome-guided assembly workflow, which is capable of producing more contiguous local assemblies than Hifiasm in our test regions.

bioinformatics↗

bioRxiv2025

A complete diploid human genome benchmark for personalized genomics

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein-coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2-7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

genomics↗

bioRxiv2025

Pangenome-aware DeepVariant

Population-scale genomics information provides valuable prior knowledge for various genomic analyses, especially variant calling. A notable example of such application is the human pangenome reference released by the Human Pangenome Reference Consortium, which has been shown to improve read mapping and structural variant genotyping. In this work, we introduce pangenome-aware DeepVariant, a variant caller that uses a pangenome reference alongside sample-specific read alignments. It generates pileup images of both reads and pangenome haplotypes near potential variants and uses a Convolutional Neural Network to infer genotypes. This approach allows directly using a pangenome for distinguishing true variant signals from sequencing or alignment noise. We assessed its performance on various short-read sequencing platforms and read mappers. Across all settings, pangenome-aware DeepVariant outperformed the linear-reference-based DeepVariant, reducing errors by up to 25.5%. We also show that Element reads with pangenome-aware DeepVariant can achieve 23.6% more accurate variant calling performance compared to existing methods.

bioinformatics↗

bioRxiv2024

A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.

Somatic mosaicism is an important cause of disease, but mosaic and somatic variants are often challenging to detect because they exist in only a fraction of cells. To address the need for benchmarking subclonal variants in normal cell populations, we developed a benchmark containing mosaic variants in the Genome in a Bottle Consortium (GIAB) HG002 reference material DNA from a large batch of a normal lymphoblastoid cell line. First, we used a somatic variant caller with high coverage (300x) Illumina whole genome sequencing data from the Ashkenazi Jewish trio to detect variants in HG002 not detected in at least 5% of cells from the combined parental data. These candidate mosaic variants were subsequently evaluated using >100x BGI, Element, and PacBio HiFi data. High confidence candidate SNVs with variant allele fractions above 5% were included in the HG002 draft mosaic variant benchmark, with 13/85 occurring in medically relevant gene regions. We also delineated a 2.45 Gbp subset of the previously defined germline autosomal benchmark regions for HG002 in which no additional mosaic variants >2% exist, enabling robust assessment of false positives. The variant allele fraction of some mosaic variants is different between batches of cells, so using data from the homogeneous batch of reference material DNA is critical for benchmarking these variants. External validation of this mosaic benchmark showed it can be used to reliably identify both false negatives and false positives for a variety of technologies and detection algorithms, demonstrating its utility for optimization and validation. By adding our characterization of mosaic variants in this widely-used cell line, we support extensive benchmarking efforts using it in simulation, spike-in, and mixture studies.

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

Highly accurate assembly polishing with DeepPolisher

Accurate genome assemblies are essential for biological research, but even the highest quality assemblies retain errors caused by the technologies used to construct them. Base-level errors are typically fixed with an additional polishing step that uses reads aligned to the draft assembly to identify necessary edits. However, current methods struggle to find a balance between over- and under-polishing. Here, we present an encoder-only transformer model for assembly polishing called DeepPolisher, which predicts corrections to the underlying sequence using Pacbio HiFi read alignments to a diploid assembly. Our pipeline introduces a method, PHARAOH (Phasing Reads in Areas Of Homozygosity), which uses ultra-long ONT data to ensure alignments are accurately phased and to correctly introduce heterozygous edits in falsely homozygous regions. We demonstrate that the DeepPolisher pipeline can reduce assembly errors by half, with a greater than 70% reduction in indel errors. We have applied our DeepPolisher-based pipeline to 180 assemblies from the next Human Pangenome Reference Consortium (HPRC) data release, producing an average predicted Quality Value (QV) improvement of 3.4 (54% error reduction) for the majority of the genome.

bioinformatics↗

bioRxiv2024

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies

Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms of repeat mapping and variant phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs and insertions and deletions (indels) from both short-read and long-read data, with modes for whole-genome and exome sequencing, and able to run on tumor-normal, tumor-only, and with FFPE-prepared samples. To help address the dearth of publicly available training and benchmarking data for somatic variant detection, we generated and make openly available a dataset of five matched tumor-normal cell line pairs sequenced with Illumina, PacBio HiFi, and Oxford Nanopore Technologies, along with benchmark variant sets. Across samples and technologies (short-read and long-read), DeepSomatic consistently outperforms existing callers, particularly for indels.

bioinformatics↗

bioRxiv2023

Personalized Pangenome References

Pangenomes, by including genetic diversity, should reduce reference bias by better representing new samples compared to them. Yet when comparing a new sample to a pangenome, variants in the pangenome that are not part of the sample can be misleading, for example, causing false read mappings. These irrelevant variants are generally rarer in terms of allele frequency, and have previously been dealt with using allele frequency filters. However, this is a blunt heuristic that both fails to remove some irrelevant variants and removes many relevant variants. We propose a new approach, inspired by local ancestry inference methods, that imputes a personalized pangenome subgraph based on sampling local haplotypes according to k-mer counts in the reads. Our approach is tailored for the Giraffe short read aligner, as the indexes it needs for read mapping can be built quickly. We compare the accuracy of our approach to state-of-the-art methods using graphs from the Human Pangenome Reference Consortium. The resulting personalized pangenome pipelines provide faster pangenome read mapping than comparable pipelines that use a linear reference, reduce small variant genotyping errors by 4x relative to the Genome Analysis Toolkit (GATK) best-practice pipeline, and for the first time make short-read structural variant genotyping competitive with long-read discovery methods.

bioinformatics↗

bioRxiv2023

The Complete Sequence and Comparative Analysis of Ape Sex Chromosomes

Apes possess two sex chromosomes--the male-specific Y and the X shared by males and females. The Y chromosome is crucial for male reproduction, with deletions linked to infertility1. The X chromosome carries genes vital for reproduction and cognition2. Variation in mating patterns and brain function among great apes suggests corresponding differences in their sex chromosomes. However, due to their highly repetitive nature and incomplete reference assemblies, ape sex chromosomes have been challenging to study. Here, using the methodology developed for the telomere-to-telomere (T2T) human genome, we produced gapless assemblies of the X and Y chromosomes for five great apes (chimpanzee, bonobo, gorilla, Bornean and Sumatran orangutans) and a lesser ape, the siamang gibbon. These assemblies allowed us to untangle the intricacies of ape sex chromosome evolution. We found that, compared to the Xs, the ape Ys vary greatly in size and have low alignability and high levels of structural rearrangements. This divergence on the Y arises from the accumulation of lineage-specific ampliconic regions, palindromes, transposable elements, and satellites. Our analysis of Y chromosome genes revealed expansions of multi-copy gene families and signatures of purifying selection. Thus, the Y exhibits dynamic evolution, while the X is more stable. Mapping short-read sequencing data to these assemblies revealed diversity and selection patterns on sex chromosomes of >100 great ape individuals. These reference assemblies are expected to inform human evolution and conservation genetics of nonhuman apes, all of which are endangered species.

genomics↗

bioRxiv2023

Testing of putative antiseizure drugs in a preclinical Dravet syndrome zebrafish model

Dravet syndrome (DS) is a severe genetic epilepsy primarily caused by de novo mutations in a voltage-activated sodium channel gene (SCN1A). Patients face life-threatening seizures that are largely resistant to available anti-seizure medications (ASM). Preclinical DS animal models are a valuable tool to identify candidate ASMs for these patients. Among these, scn1lab mutant zebrafish exhibiting spontaneous seizure-like activity are particularly amenable to large-scale drug screening. Prior screening in a scn1lab mutant zebrafish line generated using N-ethyl-N-nitrosourea (ENU) identified valproate, stiripentol, and fenfluramine e.g., Federal Drug Administration (FDA) approved drugs with clinical application in the DS population. Successful phenotypic screening in scn1lab mutant zebrafish consists of two stages: (i) a locomotion-based assay measuring high-velocity convulsive swim behavior and (ii) an electrophysiology-based assay, using in vivo local field potential (LFP) recordings, to quantify electrographic seizure-like events. Using this strategy more than 3000 drug candidates have been screened in scn1lab zebrafish mutants. Here, we curated a list of nine additional anti-seizure drug candidates recently identified in preclinical models: 1-EBIO, AA43279, chlorzoxazone, donepezil, lisuride, mifepristone, pargyline, soticlestat and vorinostat. First-stage locomotion-based assays in scn1lab mutant zebrafish identified only 1-EBIO, chlorzoxazone and lisuride. However, second-stage LFP recording assays did not show significant suppression of spontaneous electrographic seizure activity for any of the nine anti-seizure drug candidates. Surprisingly, soticlestat induced frank electrographic seizure-like discharges in wild-type control zebrafish. Taken together, our results failed to replicate clear anti-seizure efficacy for these drug candidates highlighting a necessity for strict scientific standards in preclinical identification of ASMs.

neuroscience↗