Biology subjects

Hickey, G.

Publications and source records attributed to Hickey, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Temporal resolution of C. vicina compound eyes and ocelli

Most flying insects have two visual systems which serve different purposes depending on the insect. The compound eyes are the main visual system and provide the insect with better spatial vision, while the ocelli act as a secondary visual system and often provide faster processing at a lower spatial resolution. To accomplish this, ocelli can have widely varying characteristics, including temporal resolution. The goal of this study was to examine the critical flicker fusion frequency (CFF) of the blowfly Calliphora vicina's compound eyes and ocelli using electroretinography. We found that C. vicina's compound eyes and ocelli both have a maximum CFF of 240-250 Hz, which is consistent with its natural light environment, flight behaviors, and the CFF values found for other Dipteran species.

physiology↗

bioRxiv2026

Pangenome alignment reveals global diversity and evolution of human centromeric regions

Centromeres play essential roles in chromosome segregation and genome stability, yet they remain among the least characterized regions of the human genome. Despite advances in long-read sequencing and complete genome assembly, the extreme repetitiveness and structural complexity of these regions still challenge population-scale analysis, obscuring their mutational dynamics. The Human Pangenome Reference Consortium has now accurately assembled over 6,000 centromeres, providing an opportunity to catalog global centromere variation. However, centromeric regions have been systematically excluded from pangenome alignments due to the technical challenge of aligning their highly repetitive tandem arrays and extreme structural variability. Here we introduce Centrolign, a graph-based multiple sequence alignment tool that combines a uniqueness-driven objective function with partial-order partial-order alignment to accurately align alpha satellite higher-order repeats. By prioritizing rare matches within tandem arrays and leveraging extended centromere-spanning haplotypes formed by suppressed recombination, Centrolign produces progressive multiple sequence alignments that preserve ancestral repeat organization. Applied across human centromeres, these alignments reveal the phylogenetic structure of similar satellite array haplotypes and enable precise estimation of variation rates, structural variant frequencies, and spatial patterns of mutation within satellite arrays. Integrating Centrolign graphs with repeat annotation tools and pangenome mapping algorithms allows accurate variant calling and genotyping from long reads without prior assembly. Moreover, we show that centromere haplotypes can be accurately subtyped with k-mers alone. Together, these advances establish a robust framework for incorporating centromeres into broader pangenomes, and population genomics in general, advancing our understanding of human genome evolution and diversity.

genomics↗

bioRxiv2026

HPRC2: A human pangenome reference with near-complete coverage of common genetic variation

A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortiums (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.

genomics↗

bioRxiv2026

The complete genome of the KOLF2.1J reference iPSC line

While induced pluripotent stem cells (iPSCs) have gained popularity in studying neurodegenerative diseases, the heterogeneity of stem cells used across studies impacts cross-study comparison. The iPSC Neurodegenerative Disease Initiative (iNDI) selected the KOLF2.1J cell line and prioritized its use as a reference standard for studying the effects of pathogenic variants on cell biology due to its stability and neutral neurodegenerative disease genetic risk. This cell line, and its derivatives expressing over 100 variants related to Alzheimers disease, Parkinsons disease, and other neurological diseases, are available for academic and industry access. Current genomic data analyses are limited by the use of a human reference genome that does not capture the complete genetic background of a given iPSC line. While in the future this issue may be partially mitigated by the creation of a comprehensive human pangenome, previous work has shown that generating custom genomes is of value both to characterize the variation present and to serve as a more appropriate genomic reference. Here, we generated and characterized a custom complete genome assembly from KOLF2.1J. Mapping of sequencing reads to a personalized diploid assembly results in more comprehensive mapping compared to traditional linear references (i.e GRCh38). In addition, we provide a comprehensive custom gene annotation along with isoform expression and differential methylation analyses across multiple cell types. The assembly and all additional data is browsable and publicly available. This resource will enable more accurate investigation of the KOLF2.1J cell line and any genomics data generated compared to using traditional generalized references, while also serving as a foundational approach for establishing custom reference assemblies for other high-value iPSC lines.

genomics↗

bioRxiv2025

Complete genomes of a multi-generational pedigree to expand studies of genetic and epigenetic inheritance

Pedigree analysis remains the gold standard for rare disease diagnostics, yet whole genome sequencing studies typically omit critical regions like centromeres, telomeres, and acrocentric chromosome p-arms. Here, we present telomere-to-telomere (T2T) reference genomes for four self-identified African American individuals of admixed ancestry spanning three generations. Our parent-of-origin assigned, chromosome-level assemblies revealed precise meiotic recombination breakpoints in previously inaccessible regions, including recombination events across acrocentric and subtelomeric sequences. Centromeric regions were highly stable, with multi-megabase arrays inherited intact across three generations, while the position of kinetochore assembly sites remained consistent and predominantly associated with the p-arm proximal region. The relative lengths of telomeres on individual chromosomes were maintained across generations. Using a targeted rDNA assembly approach, we reconstructed a complete megabase-scale ribosomal DNA (rDNA) array corresponding to the paternal chromosome 14. This openly available pedigree provides a benchmark dataset for studying recombination and genetic and epigenetic variation across the complete genome.

genomics↗

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

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

Efficient indexing and querying of annotations in a pangenome graph

The current reference genome is the backbone of diverse and rich annotations. Simple text formats, like VCF or BED, have been widely adopted and helped the critical exchange of genomic information. There is a dire need for tools and formats enabling pangenomic annotation to facilitate such enrichment of pangenomic references. The Graph Alignment Format (GAF) is a text format, tab-delimited like BED/VCF files, which was proposed to represent alignments. GAF could also be used to store paths representing annotations in a pangenome graph, but there are no tools to index and query them efficiently. Here, we present extensions to vg and HTSlib that provide efficient sorting, indexing, and querying for GAF files. With this approach, annotations overlapping a subgraph can be extracted quickly. Paths are sorted based on the IDs of traversed nodes, compressed with BGZIP, and indexed with HTSlib/tabix via our extensions for the GAF format. Compared to the binary GAM format, GAF files are easier to edit or inspect because they are plain text, and we show that they are twice as fast to sort and half as large on disk. In addition, we updated vg annotate, which takes BED or GFF3 annotation files relative to linear sequences and projects them into the pangenome. It can now produce GAF files representing these annotations paths through the pangenome. We showcase these new tools on several applications. We projected annotations for all Human Pangenome Reference Consortium Year 1 haplotypes, including genes, segmental duplications, tandem repeats and repeats annotations, into the Minigraph-Cactus pangenome (GRCh38-based v1.1). We also projected known variants from the GWAS Catalog and expression QTLs from the GTEx project into the pangenome. Finally, we reanalyzed ATAC-seq data from ENCODE to demonstrate what a coverage track could look like in a pangenome graph. These rich annotations can be quickly queried with vg and visualized using existing tools like the Sequence Tube Map or Bandage.

bioinformatics↗

bioRxiv2024

Complex genetic variation in nearly complete human genomes

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in -satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into -satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

genomics↗

bioRxiv2024

Complete sequencing of ape genomes

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives.

genomics↗

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↗

bioRxiv2022

Pangenome Graph Construction from Genome Alignment with Minigraph-Cactus

Reference genomes provide mapping targets and coordinate systems but introduce biases when samples under study diverge sufficiently from them. Pangenome references seek to address this by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but thanks to advances in long-read sequencing, high-quality phased assemblies are becoming widely available. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graphs ability to consistently represent variation at different scales and reduces biases introduced by reference-based variant calls. Pangenome construction in this way is equivalent to multiple genome alignment. Here we present the Minigraph-Cactus pangenome pipeline, a method to create pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium (HPRC). This tool was designed to build graphs containing all forms of genetic variation while still being practical for use with current mapping and genotyping tools. We show that this graph is useful both for studying variation within the input haplotypes, but also as a basis for achieving state of the art performance in short and long read mapping, small variant calling and structural variant genotyping. We further measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes, and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods, even after projecting back to GRCh38. We also demonstrate that our method can apply to nonhuman data by showing improved mapping and variant detection sensitivity with a Drosophila melanogaster pangenome.

bioinformatics↗

bioRxiv2022

A Draft Human Pangenome Reference

The Human Pangenome Reference Consortium (HPRC) presents a first draft human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence and are more than 99% accurate at the structural and base-pair levels. Based on alignments of the assemblies, we generated a draft pangenome that captures known variants and haplotypes, reveals novel alleles at structurally complex loci, and adds 119 million base pairs of euchromatic polymorphic sequence and 1,529 gene duplications relative to the existing reference, GRCh38. Roughly 90 million of the additional base pairs derive from structural variation. Using our draft pangenome to analyze short-read data reduces errors when discovering small variants by 34% and boosts the detected structural variants per haplotype by 104% compared to GRCh38-based workflows, and by 34% compared to using previous diversity sets of genome assemblies.

genomics↗

bioRxiv2022

Gaps and complex structurally variant loci in phased genome assemblies

There has been tremendous progress in the production of phased genome assemblies by combining long-read data with parental information or linking read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than ~140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 77 phased and assembled human genomes (154 unique haplotypes). We find that trio-based approaches using HiFi are the current gold standard although chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. We find two-thirds of defined contig ends cluster near the largest and most identical repeats [including segmental duplications (35.4%) or satellite DNA (22.3%) or to regions enriched in GA/AT rich DNA (27.4%)]. As a result, 1513 protein-coding genes overlap assembly gaps in at least one haplotype and 231 are recurrently disrupted or missing from five or more haplotypes. In addition, we estimate that 6-7 Mbp of DNA are incorrectly orientated per haplotype irrespective of whether trio-free or trio-based approaches are employed. 81% of such misorientations correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large identical segmental duplications. In addition, we also identify large-scale alignment discontinuities consistent with an 11.9 Mbp deletion and 161.4 Mbp of insertion per human haploid genome. While 99% of this variation corresponds to satellite DNA, we identify 230 regions of the euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Although not completely resolved, these regions include copy number polymorphic and biomedically relevant genic regions where complete resolution and a pangenome representation will be most useful, yet most challenging, to realize.

genomics↗

bioRxiv2022

Resource requirements for ecotoxicity testing: A comparison of traditional and new approach methods

Toxicity testing is under transformation as it aims to harness the potential of New Approach Methods (NAMs) as alternative test methods that may be less resource intensive (i.e., fewer animals, cheaper costs, quicker assays) than traditional approaches while also providing more data and information. While many stakeholders are of the opinion that this unfolding transformation holds significant promise as a more efficient and ethical way forward, few studies have compared the resources required for NAMs versus those needed for traditional animal-based toxicity tests, particularly in the field of ecotoxicology. The objective was to compare resources needed for traditional animal-based ecotoxicity tests versus alternative tests using emergent NAMs. From a bibliometric review, we estimate that traditional tests for a single chemical cost $118,000 USD, require 135 animals, and take 8 weeks. In comparison, alternative tests cost $2,600, require 20 animals (or none), and take up to 4 weeks to test 16 (to potentially hundreds of) chemicals. Based on our analysis we conclude that NAMs in ecotoxicology can be more advantageous than traditional methods in terms of resources required (i.e., monetary costs, number of animals needed, and testing times). We note, however, that the evidence underpinning these conclusions is relatively sparse. Moving forward, groups developing and applying NAMs should provide more detailed accounts of the resources required. In addition, there is also a need for carefully designed case studies that demonstrate the domain of applicability of NAMs (and make comparisons to traditional tests) to ultimately build confidence among the user community.

pharmacology and toxicology↗

bioRxiv2020

Genotyping common, large structural variations in 5,202 genomes using pangenomes, the Giraffe mapper, and the vg toolkit

We introduce Giraffe, a pangenome short read mapper that can efficiently map to a collection of haplotypes threaded through a sequence graph. Giraffe, part of the variation graph toolkit (vg)1, maps reads to thousands of human genomes at around the same speed BWA-MEM2 maps reads to a single reference genome, while maintaining comparable accuracy to VG-MAP, vgs original mapper. We have developed efficient genotyping pipelines using Giraffe. We demonstrate improvements in genotyping for single-nucleotide variants (SNVs), small insertions and deletions (indels) and structural variations (SVs) genome-wide. We use Giraffe to genotype about 167 thousand structural variants ascertained from long read studies in 5,202 human genomes sequenced with short reads, including the complete 1000 Genomes Project dataset, at an average cost of $1.50 per sample. We determine the frequency of these variations in diverse human populations, characterize their complex allelic variations and identify thousands of expression quantitative trait loci (eQTLs) driven by these variations.

bioinformatics↗

bioRxiv2020

Succinct dynamic variation graphs

MotivationPangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded progress in this field. ResultsHere we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage is up to an order of magnitude better than the prior graph implementation in the vg toolkit, which has now transitioned to using libbdsgs implementations. Availabilitylibhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg. Contacterik.garrison@ucsc.edu

bioinformatics↗