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Garrison, E.

Publications and source records attributed to Garrison, E..

At least 19 recordsLinked to original sources

Concerted evolution and unorthodox recombination of human subtelomeres

Human subtelomeres contain duplicated sequence that is shared among the ends of non-homologous chromosomes and provides a substrate for ectopic exchange [1-6]. However, incomplete reference assemblies and chromosome-by-chromosome analyses have prevented a population-scale view of the extent and organization of subtelomeric exchange [7-9]. Here we apply a reference-free pangenome approach to 465 near-complete human assemblies, comparing every chromosome end against every other, and find that high-identity pseudo-homolog regions [10] occur on 41 of 48 chromosome arms. These regions group into sequence communities, sets of chromosome ends that share duplicated sequence. Across these communities, copy-number enrichment is concentrated in gene modules associated with chromosome dynamics, intracellular organization and germ-cell development. Human chromosome-contact maps show preferential proximity between subtelomeres with similar sequences, persisting even in adjacent flanks that lack the shared sequence used to define each pair. Mouse contact maps show the same preference, strongest in meiosis at the zygotene bouquet, when telomeres cluster at the nuclear envelope. In a three-generation telomere-to-telomere pedigree, whole-genome comparison identifies putative recombination between subtelomeric regions on non-homologous chromosomes from the same sequence communities, while recovering the obligate X-Y crossover in PAR1, the pseudoautosomal region shared by the X and Y chromosomes, during male meiosis. These results generalize known subtelomeric exchange systems into a near-ubiquitous architecture and support recurrent ectopic exchange as a genome-wide force in the concerted evolution of human chromosome ends.

genomics↗

A Pan-pangenome illuminates complex structural variation and selection in humans, chimpanzees, and bonobos

Complete, haplotype-resolved genome assemblies have provided unprecedented insight into the evolution of structurally complex, rapidly evolving regions of human genomes1-6; however, population-scale pangenome resources of our closest relatives, chimpanzees and bonobos (genus, Pan), are necessary to ascertain the origins and evolutionary context of these loci. Here, we sequence and assemble 58 haplotypes from four distinct Pan clades to high contiguity (median contig NG50=54 Mb), including eight near-T2T genomes. These genomes reveal previously intractable genetic variation increasing estimates of genome-wide genetic diversity 6-37% across populations compared to short-read estimates7. We identify recurrent structural polymorphisms across species impacting genes associated with immune response and host-pathogen interaction and find that structural variants (SVs) are 170- to 260-fold more likely than single nucleotide variants (SNVs) to exhibit high-impact effects across species. Contrasting SV patterns across primates we find that transposable element mutation rates differ by as much as threefold between species. We show that human disease-associated short tandem repeat (TR) loci have uniquely expanded in humans sensitizing our species to these TR-expansion disorders. Physically phased haplotypes enable reconstruction of genome-wide genealogical histories, uncovering ancient, functional genetic variation maintained by balancing selection, as well as signatures of recent adaptation in chimpanzee subspecies. Several malaria-associated loci exhibit ancient structural polymorphism, including the African great ape-specific glycophorin (GYP) gene expansion. We characterize the sequence, structure, and composition of diverse glycophorin haplotypes in humans and chimpanzees. We identify independent malaria-protective GYPA-B fusion events in humans and novel chimpanzee glycophorin genes resulting from both ancient and recent fusion events demonstrating parallel adaptations to pathogen resistance across hominins. Together, our resource highlights the critical importance of nonhuman primate population-scale pangenomics for understanding the evolution of complex genome structures and the biodiversity of our endangered closest living relatives.

evolutionary biology↗

Adaptive Tracepoints for Pangenome Alignment Compression

MotivationStoring millions of sequence alignments from large-scale genomic comparisons requires efficient compression methods. While fixed-size alignment encodings offer uniform spacing and bounded reconstruction cost, they cannot adapt to variable alignment complexity across sequences, missing compression opportunities in conserved regions. ResultsWe present adaptive tracepoints, a complexity-aware alignment encoding that segments alignments using configurable complexity metrics (edit distance or diagonal distance) rather than fixed intervals. Segments are bounded by either the number of differences or the deviation from the main diagonal, adapting to local alignment characteristics. Reconstruction guarantees that alignments maintain identical or improved alignment scores. We validate the correctness of our method on simulated and real pangenomes with varying lengths and divergences. Diagonal-bounded tracepoints achieve 10.5-13.7x better compression than fixed-length encodings (l=100) on simulated long sequence alignments (100 Kb), while edit-bounded tracepoints provide a tunable trade-off between compression and reconstruction cost, approaching diagonal-bounded compression at higher thresholds with substantially lower memory and runtime. On real pangenomes (390M alignments), these methods compress alignments by 23-139x relative to uncompressed representations, with no score degradation and reconstruction time linear in alignment length. AvailabilityCode and documentation are publicly available at https://github.com/AndreaGuarracino/tracepoints, https://github.com/AndreaGuarracino/tpa, and https://github.com/AndreaGuarracino/cigzip. Contactaguarracino@tgen.org Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

Population-scalable genotyping from low-coverage sequencing data using pangenome graphs

Pangenome-based genotyping of structurally complex loci remains challenging at low sequencing depths, particularly when samples are of low quality, such as in ancient DNA. We present COSIGT (COsine SImilarity-based GenoTyper), a method that infers structural genotypes by matching short-read coverage patterns to pangenome haplotypes using cosine similarity. COSIGT maintains robust accuracy at low coverage (1-2X), outperforming existing methods where depth-sensitive approaches degrade. We demonstrate scalability to thousands of modern and ancient genomes, enabling population-scale analyses of complex variation from low-coverage data.

bioinformatics↗

Origin and evolution of acrocentric chromosomes in human and great apes

The short arms of human acrocentric chromosomes are characterized by nucleolar organizer regions essential for ribosome biogenesis, but their highly repetitive nature has hindered genomic analysis. Leveraging the recently completed genomes of all major ape lineages, we identified recurrent features of their acrocentrics, including enriched repeat classes, centromere repositioning by whole-arm inversion, interchromosomal sequence exchange, and birth-and-death evolution of multiple gene families. Together, these processes have enabled the repeated amplification and diversification of the FRG1 gene family over 25 million years of ape evolution, and, in gorilla, the formation and amplification of a novel IGSF3-GGT fusion gene under positive selection. Similar evolutionary events also explain the distribution of segmental duplications and heterochromatin in the modern human genome, predisposing it to karyotypic abnormalities such as Robertsonian translocations. Our findings highlight acrocentric chromosomes as key drivers of evolution in the great apes, with implications for speciation, adaptation, and clinical genomics.

genomics↗

Scalable PBWT Queries with Minimum-Length SMEMConstraints

Detecting long shared ancestry tracts in large haplotype panels is central to IBD analysis, imputation, and local ancestry inference, and can be approximated computationally by finding Set-Maximal Exact Matches (SMEMs) between sequences. The Positional Burrows-Wheeler Transform (PBWT) provides an efficient index for these panels, yet current methods often enumerate all SMEMs, producing a large number of short, uninformative matches. We introduce Positional Boyer- Moore-Li (PBML), which restricts enumeration to SMEMs occurring in at least k haplotypes and spanning at least L sites (kL-SMEMs). PBML is the first algorithm for computing KL-SMEMs on top of a single compressed run-length encoded PBWT index reusable for any (k, L) without rebuilding. On the 1000 Genomes Project, PBML achieves 4.6x faster query time than {micro}-PBWT and 2.4x over Durbins PBWT with lower memory, scaling to 15.9x over {micro}-PBWT at 16 threads. On a 10,000-haplotype panel from the Tennessee BIG Initiative, a diverse admixed cohort, PBML outperforms {micro}-PBWT by up to 4.7x in k-SMEM finding. By applying both thresholds during traversal, PBML extracts biologically informative, population-shared segments while filtering millions of short matches, a capability not available in current tools. On the BIG panel, in about 10 seconds PBML finds 2,441 long tracts at (k = 50, L = 5000) shared by an average of 60 haplotypes against 1000 queries, significantly reducing the 4.8 million unfiltered SMEMs shared on average by 2 haplotypes. These results establish PBML as a scalable tool for targeted long-range shared ancestry detection in large, diverse panels.

bioinformatics↗

Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocations

Centromeres are among the most diverse and dynamically evolving regions of the human genome and are commonly affected in various human cancers. However, organized into highly repetitive -satellite higher-order repeats (HORs), human centromere sequences have long resisted detailed genomic analysis. Although the development of long-read sequencing platforms has enabled the analysis of complete centromere sequences, their application to a large set of samples is still largely limited, preventing our understanding of centromere variation and haplotype structures across large human populations and the structural basis of centromere-involving translocations in cancer. Here we show that rare k-mers present in centromeric regions can serve as effective markers for dissecting the complexity of centromere structure, particularly that of active -satellite HOR arrays (aHOR arrays), across human populations and for understanding centromere-involving abnormalities in cancer. Based on rare k-mer-based clustering, centromere aHOR arrays are clustered into discrete haplogroups (aHOR-HGs) with distinct structural features. These k-mers were also used to develop a framework that enables the inference of haplogroups in a given sample based on short-read whole genome sequencing (WGS) data (ascairn). By applying ascairn to large-scale human population datasets (n > 3,300), we revealed the diversity of aHOR-HGs and their geographic histories across populations. The rare k-mer-based approach was also applied to investigate the structure of 1p/19q co-deletion, a highly recurrent centromere-involving translocation in IDH-mutated oligodendrogliomas. Analyzing short-read WGS data from 142 cases with 1p/19q co-deletion using rare k-mers, we showed that breakpoints of 1p/19q co-deletion were mapped to aHOR arrays in chromosomes 1 (D1Z7) and 19 (D19Z3), which was validated by long-read sequencing of two 1p/19q co-deletion-positive cases. Notably, the translocation preferentially involved haplogroups composed of haplotypes containing larger regions susceptible to rearrangement. These results highlight the role of rare k-mers in dissecting the complexity of centromere sequences and their evolutionary history as well as understanding centromere-involving abnormalities associated with human diseases.

genomics↗

The mouse pangenome reveals the structural complexity of the murine protein coding landscape

We present the first mouse pangenome consisting of 17 high-quality inbred mouse strain genomes with complete annotation. This collection includes 12 widely used classical laboratory strains and 5 wild-derived strains. We have fully resolved previously incomplete genomic regions, including the major histocompatibility complex (MHC), the defensin cluster, T-cell receptor, and Ly49 complexes. Hundreds of non-reference genes identified in previous publications not found in GRCm39, like Defa1, Raet1a, and Klra20 (Ly49T), were localised in the new reference genomes. We conducted the first genome-wide scan of variable number tandem repeats (VNTRs) within the coding regions of mice, identifying over 400 genes with VNTR polymorphisms up to more than 600 repeat copies and repeat units reaching 990 nucleotides. Our strain-specific annotations enhance RNA-Seq analyses, as demonstrated in PWK/PhJ, where we observed a 5.1% improvement in read mapping and expression level differences in 2.1% of coding genes compared to using GRCm39.

genomics↗

Comparative population pangenomes reveal unexpected complexity and fitness effects of structural variants

Structural variants (SVs) are widespread in vertebrate genomes, yet their evolutionary dynamics remain poorly understood. Using 45 long-read de novo genome assemblies and pangenome tools, we analyze SVs within three closely related species of North American jays (Aphelocoma, scrub-jays) displaying a 60-fold range in effective population size. We find rapid evolution of genome architecture, including [~]100 Mb variation in genome size driven by dynamic satellite landscapes with unexpectedly long (> 10 kb) repeat units and widespread variation in gene content, influencing gene expression. SVs exhibit slightly deleterious dynamics modulated by variant length and population size, with strong evidence of adaptive fixation only in large populations. Our results demonstrate how population size shapes the distribution of SVs and the importance of pangenomes to characterizing genomic diversity.

evolutionary biology↗

Creating a biomedical knowledge base by addressing GPT inaccurate responses and benchmarking context

We created GNQA, a generative pre-trained transformer (GPT) knowledge base driven by a performant retrieval augmented generation (RAG) with a focus on aging, dementia, Alzheimers and diabetes. We uploaded a corpus of three thousand peer reviewed publications on these topics into the RAG. To address concerns about inaccurate responses and GPT hallucinations, we implemented a context provenance tracking mechanism that enables researchers to validate responses against the original material and to get references to the original papers. To assess the effectiveness of contextual information we collected evaluations and feedback from both domain expert users and citizen scientists on the relevance of GPT responses. A key innovation of our study is automated evaluation by way of a RAG assessment system (RAGAS). RAGAS combines human expert assessment with AI-driven evaluation to measure the effectiveness of RAG systems. When evaluating the responses to their questions, human respondents give a "thumbs-up" 76% of the time. Meanwhile, RAGAS scores 90% on answer relevance on questions posed by experts. And when GPT-generates questions, RAGAS scores 74% on answer relevance. With RAGAS we created a benchmark that can be used to continuously assess the performance of our knowledge base. Full GNQA functionality is embedded in the free GeneNetwork.org web service, an open-source system containing over 25 years of experimental data on model organisms and human. The code developed for this study is published under a free and open-source software license at https://git.genenetwork.org/gn-ai/tree/README.md.

scientific communication and education↗

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↗

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↗

The formation and propagation of human Robertsonian chromosomes

Robertsonian chromosomes are a type of variant chromosome found commonly in nature. Present in one in 800 humans, these chromosomes can underlie infertility, trisomies, and increased cancer incidence. Recognized cytogenetically for more than a century, their origins have remained mysterious. Recent advances in genomics allowed us to assemble three human Robertsonian chromosomes completely. We identify a common breakpoint and epigenetic changes in centromeres that provide insight into the formation and propagation of common Robertsonian translocations. Further investigation of the assembled genomes of chimpanzee and bonobo highlights the structural features of the human genome that uniquely enable the specific crossover event that creates these chromosomes. Resolving the structure and epigenetic features of human Robertsonian chromosomes at a molecular level paves the way to understanding how chromosomal structural variation occurs more generally, and how chromosomes evolve.

genomics↗

Pangenome-Informed Language Models for Privacy-Preserving Synthetic Genome Sequence Generation

Language Models (LM) have been extensively utilized for learning DNA sequence patterns and generating synthetic sequences. In this paper, we present a novel approach for the generation of synthetic DNA data using pangenomes in combination with LM. We introduce three innovative pangenome-based tokenization schemes that enhance DNA sequence generation. Our experimental results demonstrate the superiority of pangenome-based tokenization over classical methods in generating high-utility synthetic DNA sequences, highlighting significant improvements in training efficiency and sequence quality.

bioinformatics↗

Epigenetic control and inheritance of rDNA arrays

Ribosomal RNA (rRNA) genes exist in multiple copies arranged in tandem arrays known as ribosomal DNA (rDNA). The total number of gene copies is variable, and the mechanisms buffering this copy number variation remain unresolved. We surveyed the number, distribution, and activity of rDNA arrays at the level of individual chromosomes across multiple human and primate genomes. Each individual possessed a unique fingerprint of copy number distribution and activity of rDNA arrays. In some cases, entire rDNA arrays were transcriptionally silent. Silent rDNA arrays showed reduced association with the nucleolus and decreased interchromosomal interactions, indicating that the nucleolar organizer function of rDNA depends on transcriptional activity. Methyl-sequencing of flow-sorted chromosomes, combined with long read sequencing, showed epigenetic modification of rDNA promoter and coding region by DNA methylation. Silent arrays were in a closed chromatin state, as indicated by the accessibility profiles derived from Fiber-seq. Removing DNA methylation restored the transcriptional activity of silent arrays. Array activity status remained stable through the iPS cell re-programming. Family trio analysis demonstrated that the inactive rDNA haplotype can be traced to one of the parental genomes, suggesting that the epigenetic state of rDNA arrays may be heritable. We propose that the dosage of rRNA genes is epigenetically regulated by DNA methylation, and these methylation patterns specify nucleolar organizer function and can propagate transgenerationally.

genomics↗

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↗

Panacus: fast and exact pangenome growth and core size estimation

MotivationUsing a single linear reference genome poses a limitation to exploring the full genomic diversity of a species. The release of a draft human pangenome underscores the increasing relevance of pangenomics to overcome these limitations. Pangenomes are commonly represented as graphs, which can represent billions of base pairs of sequence. Presently, there is a lack of scalable software able to perform key tasks on pangenomes, such as quantifying universally shared sequence across genomes (the core genome) and measuring the extent of genomic variability as a function of sample size (pangenome growth). ResultsWe introduce Panacus (pangenome-abacus), a tool designed to rapidly perform these tasks and visualize the results in interactive plots. Panacus can process GFA files, the accepted standard for pangenome graphs, and is able to analyze a human pangenome graph with 110 million nodes in less than one hour. AvailabilityPanacus is implemented in Rust and is published as Open Source software under the MIT license. The source code and documentation are available at https://github.com/marschall-lab/panacus. Panacus can be installed via Bioconda at https://bioconda.github.io/recipes/panacus/README.html. ContactLuca Parmigiani (luca.parmigiani@uni-bielefeld.de), Daniel Doerr (daniel.doerr@hhu.de).

bioinformatics↗

Cluster efficient pangenome graph construction with nf-core/pangenome

MotivationPangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. ResultsTo overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-cores best practices. Leveraging biocontainers ensures portability and seamless deployment in HPC environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 E. coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. Availabilitynf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/1.1.2/docs/usage. Contactsimon.heumos@qbic.uni-tuebingen.de, sven.nahnsen@qbic.uni-tuebingen.de

bioinformatics↗