Search PubMedSearch

SEARCH · Search PubMed

Results for “Genomic Structural Variation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

Pan-genome-based resequencing of 2,320 accessions reveals structural variations and accelerates breeding advances in cultivated peanut.

The cultivated peanut is a crucial global legume crop that is essential for food security and nutrition, particularly in developing regions. However, its limited genetic variation hampers breeding progress and yield improvement. Here we constructed a graph-based pan-genome for peanut, incorporating 14 genomes that represent all 6 peanut varieties. Using this pan-genome, we genotyped 2,320 accessions, covering 88.03% of ICRISAT and 59.21% of USDA core germplasm, enriching valuable resources for genomic studies and breeding. We cataloged genomic structural variations and investigated the role of homoeologous exchanges in population divergence. Through our pan-genome approach, we overcame the challenges of genotyping posed by homoeologous exchanges and identified key genes associated with flowering and dwarfism in peanut. By integrating superior haplotypes and germplasm resources guided by the pan-genome, we further developed high-yield dwarf lines. This work provides essential genomic resources to accelerate functional gene discovery and modern peanut breeding.

Journal Article

Chromosome-scale genome remodeling in tumor evolution: Copy number alterations and structural variants as two sides of the same coin.

Chromosome-scale genomic rearrangements are a dominant force in tumor evolution. Copy-number alterations (CNAs) and structural variants (SVs) constitute two complementary axes of this process. Although detection technologies now deliver near-comprehensive catalogs, technical resolution has outpaced conceptual integration. In this review, we frame CNAs and SVs as inextricable facets of chromosomal aberrations. They reshape cancer genomes through altered gene dosage and three-dimensional regulatory rewiring. CNAs quantify the gene-dosage imbalance, yet arise through mechanistically distinct routes. Segmental CNAs typically require chromosomal breakage, and therefore often coincide with SV junctions. By contrast, whole-chromosome aneuploidy and whole-genome doubling (WGD) primarily reflect mitotic or cytokinetic failure and can occur without local breakpoints, while nevertheless reshaping the karyotypic landscape and seeding subsequent structural complexity. SVs, in turn, range from unbalanced events that alter copy number to ostensibly balanced exchanges that predominantly rewire regulatory architecture. Despite their diverse and sometimes catastrophic architectures, SVs are ultimately rooted in double-strand break formation and error-prone resolution. By integrating CNAs and SVs within a unified mechanistic and functional framework, we aim to convert catalogs into concepts and distill the organizing principles that govern tumor genome evolution.

Humans

Comparative genomics reveals lineage-associated structural variation and diversification in a barley fungal pathogen.

Leaf rust, caused by Puccinia hordei, is a major barley disease worldwide. Despite repeated shifts in virulence, contrasting reproductive histories, and emerging fungicide insensitivity, the genomic basis of its diversification and adaptation remains poorly understood. In this study, we generated haplotype-resolved, chromosome-level genome assemblies for two isolates with contrasting virulence and analyzed 41 Australian isolates collected over 54 yr (1966-2020), integrating comparative and population genomics, mating-type gene phylogenies, chromosome-specific k-mer profiling, genome-wide copy-number variation (CNV) analysis, and gene-expression analysis. We identified a structurally dynamic chromosome characterized by repeat-associated rearrangements, structural variation, and lineage-associated CNV, representing the first evidence in a rust fungus of chromosome-scale structural diversification of this extent. Population analyses distinguished clonally expanded lineages from recombination-associated lineages, with mating-type gene phylogenies providing further support for lineage differentiation. More recently collected isolates showed increased duplication-associated variation, and CNV boundaries were associated with structural-variant breakpoints. We also identified lineage-associated amplification of Cyp51, with increased copy number associated with higher transcript abundance, supporting a potential role in fungicide adaptation. Overall, our findings highlight structural variation, contrasting reproductive histories, and lineage-associated CNV as important contributors to diversification in P. hordei, providing insights for future rust pathogen surveillance and management strategies.

Cyp51 gene

insilicoSV: a flexible grammar-based framework for structural variant simulation and placement.

SUMMARY: Structural variants (SVs) are key drivers of genetic variation and disease in the genome. Their discovery remains challenging, however, in large part due to the scarcity of validated SV callsets and comprehensive benchmarks, which are essential for method development and evaluation. The growing number of data-driven learning-based approaches for SV discovery, in particular, requires large, diverse, and well-balanced training datasets to achieve reliable performance. To address this need, SV simulation has served as a key tool for assessing method performance and training SV models. However, existing SV simulators only support a fixed and limited set of SV classes and do not provide fine-grained control over the placement of SVs within specific contexts of the genome. Here we present insilicoSV, a versatile framework for SV simulation, which models SVs using a simple and flexible grammar, allowing users to easily define standard and custom arbitrary genome rearrangements, as well as encode genome placement constraints. This design allows insilicoSV to naturally support new and bespoke SV types, such as the complex rearrangements of cancer genomes. In addition to grammar-based modeling, insilicoSV provides built-in support for 26 predefined SV types, placement of user-provided SVs, small variant simulation, streamlined workflows for the simulation of genome evolution and genome mixtures, read simulation, alignment, and visualization. These features enable the creation of comprehensive genomic datasets for a variety of downstream applications, such as in-depth benchmarking of alignment and variant calling methods, as well as training of data-driven learning-based approaches for SV detection. AVAILABILITY AND IMPLEMENTATION: insilicoSV is available under the MIT license at https://github.com/PopicLab/insilicoSV and https://doi.org/10.5281/zenodo.17402009.

Software

Pan-Genome Analysis Reveals Local Adaptation to Climate Driven by Introgression in Oak Species.

The genetic base of local adaptation has been extensively studied in natural populations. However, a comprehensive genome-wide perspective on the contribution of structural variants (SVs) and adaptive introgression to local adaptation remains limited. In this study, we performed de novo assembly and annotation of 22 representative accessions of Quercus variabilis, identifying a total of 543,372 SVs. These SVs play crucial roles in shaping genomic structure and influencing gene expression. By analyzing range-wide genomic data, we identified both SNPs and SVs associated with local adaptation in Q. variabilis and Quercus acutissima. Notably, SV-outliers exhibit selection signals that did not overlap with SNP-outliers, indicating that SNP-based analyses may not detect the same candidate genes associated with SV-outliers. Remarkably, 29%-37% of candidate SNPs were located in a 250 kb region on chromosome 9, referred to as Chr9-ERF. This region contains 8 duplicated ethylene-responsive factor (ERF) genes, which may have contributed to local adaptation of Q. variabilis and Q. acutissima. We also found that a considerable number of candidate SNPs were shared between Q. variabilis and Q. acutissima in the Chr9-ERF region, suggesting a pattern of repeated selection. We further demonstrated that advantageous variants in this region were introgressed from western populations of Q. acutissima into Q. variabilis, providing compelling evidence that introgression facilitates local adaptation. This study offers a valuable genomic resource for future studies on oak species and highlights the importance of pan-genome analysis in understating mechanism driving adaptation and evolution.

Quercus

Long-read based detection of large copy number variants with potential functional significance using the ContextSV structural variant caller.

Long-read sequencing enables improved detection of structural variants (SVs) in the human genome due to its substantially increased read lengths. However, currently widely used long-read SV callers primarily rely on alignment-based evidence, limiting their ability to detect large and complex SVs and potentially missing disease-relevant events. To address these limitations, we developed ContextSV, a framework that integrates alignment evidence with copy number predictions derived from sequencing coverage and single-nucleotide variant allele frequencies to improve SV detection, particularly for large copy number variants (CNVs). We additionally developed ContextScore, a machine learning-based classification model to assign SV confidence scores based on genomic context features and integrated it within ContextSV. Through benchmarking analyses on both simulated and real datasets, we demonstrate that ContextSV improves detection of large CNVs and inversions that may be missed by existing long-read SV callers. We further illustrate its utility by identifying and experimentally validating multiple large SVs in the KOLF2.1J reference stem cell line that were not detected by other methods. Collectively, our results demonstrate that ContextSV serves as a valuable complement to existing long-read SV detection approaches by improving sensitivity for large and clinically relevant SVs.

Humans

Crawling under the radar: Two novel Paulinella species expand knowledge about the ecology and evolution of a primary plastid-containing amoeba lineage.

The genus Paulinella represents a rare, independent case of primary endosymbiosis, providing a unique system to study the early stages of organelle evolution. Here, we expand current understanding of primary plastid endosymbiosis through the discovery and characterization of two novel photosynthetic amoebae, Paulinella marae sp. nov. and Paulinella murrayi sp. nov., isolated from a brackish water habitat in North Carolina, United States. Complete chromatophore genomes and mitochondrial data revealed conserved gene content but notable structural variation, including genome rearrangements and inversion events. Phylogenetic analyses uncovered significant discordance between nuclear and organelle datasets, likely driven by substitution saturation, limited taxon sampling, and differing evolutionary signals across loci. Ecological observations over multiple years indicate that both species are in low abundance but consistently present, and when coupled with hobbyist data, support the hypothesis that photosynthetic Paulinella species are globally distributed yet under-sampled. These results increase known species diversity within the clade from four to six and highlight the importance of integrating field-based observations with genomic approaches. Overall, this work advances Paulinella as a model for studying ongoing primary endosymbiosis, lineage divergence, and the ecological strategies of low-abundance microbial eukaryotes.

Paulinella

OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.

MOTIVATION: Structural variants (SVs) influence gene regulation, disease progression, and diagnostics, yet integrating SV calls across platforms remains difficult due to inconsistent annotations, limited merging flexibility, and fragmented workflows. Ambiguous breakend (BND) annotations, which comprise many variant calls, are often discarded or misclassified, hindering variant characterization. Existing tools lack advanced merging operations essential for precise identification of disease-specific or somatic variants across samples or patient groups. Additionally, current SV analysis pipelines require extensive manual intervention and complex parameter tuning, compromising reproducibility and scalability. Addressing these gaps is crucial for improving the accuracy, interpretability, and clinical utility of SV analyses. RESULTS: We developed OctopuSV and TentacleSV to address these long-standing challenges in SV analysis. OctopuSV features a specialized BND correction module that converts ambiguous BND annotations into canonical SV types, recovering important variants that are often overlooked by existing tools. Additionally, it provides advanced set operations (difference, complement, custom-defined) that enable sophisticated variant filtering without programming expertise, critical for identifying tumor-specific SVs or variants unique to specific sample groups. TentacleSV completes our solution by automating the entire SV analysis process from raw sequencing data to high-confidence callsets, ensuring consistency and reproducibility across projects. Benchmarking across short-read and long-read platforms showed superior F1 score, complete SV type consistency compared to existing tools. Our framework enables experimental biologists and clinical researchers to perform sophisticated analyses ranging from cancer subtype-specific SV identification to multi-sample comparative studies without requiring specialized programming skills. AVAILABILITY AND IMPLEMENTATION: All codes are available at https://github.com/ylab-hi/OctopuSV; https://github.com/ylab-hi/TentacleSV.

Software

Genome-wide variation analysis of two Salvia hispanica L. genotypes and implication for associations with metabolic and adaptive traits.

BACKGROUND: Advances in next-generation sequencing have accelerated genome-wide exploration of genetic diversity in underutilized oilseed crops. Salvia hispanica L. (chia), a high-nutrient pseudocereal rich in omega-3 fatty acids, is increasingly valued for its health benefits and commercial potential, yet it remains poorly characterized at the genomic level. Understanding the scale and nature of genomic variation is essential for improving complex traits such as oil yield, stress tolerance, and seed quality. METHODS: Two contrasting chia genotypes, Black-chia (CACH-B) and White- chia (CACH-W), were resequenced using the Bio-Resequencing Toolkit (BRT) pipeline. High-coverage sequencing, with a mapping rate exceeding 99% and an average depth of approximately 28×, facilitated the detection and annotation of single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variations (CNVs), and structural variants (SVs). The functional classification of variant impacts enabled the identification of genes potentially linked to metabolic and adaptive traits. RESULTS: A total of 1.97 million SNPs, 401,493 InDels, 836 CNVs, and 15,288 SVs were identified across the chia genome. Notably, approximately 53% of exonic SNPs were non-synonymous (dN/dS ≈ 1.28), predominantly affecting lipid metabolism, transcriptional regulation, and stress response pathways, potentially altering key agronomic traits. In addition, CNV hotspots were concentrated in chromosomes 3 and 6, overlapping MYB, WRKY, and bZIP transcription factor loci, may potentially be involved in stress tolerance and yield. Furthermore, structural rearrangements, including inversions and duplications within the FAD2, FAD3, and CYP450 gene clusters, were potentially associated with seed pigmentation and omega-3 biosynthesis, pointing to their potential breeding relevance. Observed heterozygosity (Hₒ ≈ 0.71) and nucleotide diversity (π ≈ 7 × 10-3) indicated moderate to high allelic richness. In addition, the low FST value (0.038) indicates substantial genomic similarity between the two genotypes. CONCLUSION: This study presents the first comprehensive map integrating SNPs, CNVs, and SVs in S. hispanica L. The results reveal a structurally dynamic genome characterized by substantial sequence and structural variation, providing valuable insights into genomic diversity and potential adaptive mechanisms in chia. The coexistence of high SNP diversity and abundant structural variation underpins chia's nutritional specialization and environmental resilience. These results deliver a foundational genomic resource for marker-assisted breeding, genome-wide association studies, and the development of climate-resilient chia cultivars.

Copy-number variation, structural variation

Structural variants linked to Alzheimer's disease and other common age-related clinical and neuropathologic traits.

BACKGROUND: Alzheimer's disease (AD) is a complex neurodegenerative disorder with substantial genetic influence. While genome-wide association studies (GWAS) have identified numerous risk loci for late-onset AD (LOAD), the functional mechanisms underlying most of these associations remain unresolved. Large genomic rearrangements, known as structural variants (SVs), represent a promising avenue for elucidating such mechanisms within some of these loci. METHODS: By leveraging data from two ongoing cohort studies of aging and dementia, the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP), we performed genome-wide association analysis testing 20,205 common SVs from 1088 participants with whole genome sequencing (WGS) data. A range of Alzheimer's disease and other common age-related clinical and neuropathologic traits were examined. RESULTS: First, we mapped SVs across 81 AD risk loci and discovered 22 SVs in linkage disequilibrium (LD) with GWAS lead variants and directly associated with the phenotypes tested. The strongest association was a deletion of an Alu element in the 3'UTR of the TMEM106B gene, in high LD with the respective AD GWAS locus and associated with multiple AD and AD-related disorders (ADRD) phenotypes, including tangles density, TDP-43, and cognitive resilience. The deletion of this element was also linked to lower TMEM106B protein abundance. We also found a 22-kb deletion associated with depression in ROS/MAP and bearing similar association patterns as GWAS SNPs at the IQCK locus. In addition, we leveraged our catalog of SV-GWAS to replicate and characterize independent findings in SV-based GWAS for AD and five other neurodegenerative diseases. Among these findings, we highlight the replication of genome-wide significant SVs for progressive supranuclear palsy (PSP), including markers for the 17q21.31 MAPT locus inversion and a 1483-bp deletion at the CYP2A13 locus, along with other suggestive associations, such as a 994-bp duplication in the LMNTD1 locus, suggestively linked to AD and a 3958-bp deletion at the DOCK5 locus linked to Lewy body disease (LBD) (P = 3.36 × 10-4). CONCLUSIONS: While still limited in sample size, this study highlights the utility of including analysis of SVs for elucidating mechanisms underlying GWAS loci and provides a valuable resource for the characterization of the effects of SVs in neurodegenerative disease pathogenesis.

Humans

European ash pangenome reveals widespread structural variation and genetic basis of low ash dieback susceptibility.

European Ash (Fraxinus excelsior) is a keystone tree species, whose populations are being decimated by ash dieback disease (ADB) - better characterisation of genetic variants associated with low susceptibility to the disease is needed. Here, we develop a F. excelsior pangenome to more fully capture sequence variability within this species compared with a linear reference genome, using a geographically diverse set of fifty F. excelsior samples. We identify 362,965 structural variants (SVs), including 174 Mb of sequence absent from the linear reference genome (22% of the linear reference size), and identify 3,412 high-confidence dispensable genes (those present only in some individuals). We use the pangenome to analyse existing genomic data from over 1,200 individuals, revealing 220 single nucleotide polymorphisms (SNPs) showing consistent allele frequency shifts between healthy individuals and those highly damaged by ADB, across UK seed sources, explicitly demonstrating the existence of a shared genetic component to low ADB susceptibility.

Polymorphism, Single Nucleotide

Structural variation detection and association analysis of whole-genome-sequence data from 16,543 Alzheimer's disease sequencing project subjects.

INTRODUCTION: The role of structural variations (SVs) in Alzheimer's disease (AD) remains understudied. METHODS: We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N&#xa0;=&#xa0;16,543) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). RESULTS: We found a burden of singletons (odds ratio [OR]&#xa0;=&#xa0;1.07, p&#xa0;=&#xa0;0.0017) and homozygous deletions (OR&#xa0;=&#xa0;1.14, p&#xa0;<&#xa0;0.0001) in cases. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in LD (R2&#xa0;=&#xa0;0.99) with rs143080277 in NCK2. We identified a rare deletion near RNA5SP293 associated with AD (OR&#xa0;=&#xa0;1.99, p&#xa0;=&#xa0;1.3&#xa0;&#xd7;&#xa0;10-5), which was replicated using an independent dataset. DISCUSSION: This study highlights the pivotal role of SVs in AD genetics. HIGHLIGHTS: Observed a significant burden of singletons and homozygous deletions in Alzheimer's disease (AD) patients. Identified rare protein-altering structural variations (SVs) in ABCA7, APP, PLCG2, and SORL1. Established linkages between SVs and AD risk-associated single nucleotide variants (SNVs). Discovered a novel deletion near RNA5SP293 linked to AD, replicated independently. Uncovered over-representation of SVs in neuronal function pathways.

Humans

Optimizing GRIDSS for clinical use: A targeted NGS filtering strategy for germline structural variant detection.

Detecting intermediate-sized structural variants (SVs) remains challenging in diagnostics, as tools for single-nucleotide and copy-number variants, particularly read-depth-based methods, are often insufficient. GRIDSS addresses this gap by integrating paired-end mapping, split-read analysis, and assembly-based approaches. However, its use in targeted sequencing and diagnostic workflows remains complex. NGS panel data from 9726 patients with suspected hereditary cancer were analyzed using GRIDSS. A filtering strategy was developed to prioritize clinically relevant germline SVs. Multiple parameter settings were tested to optimize performance. The initial dataset of 1,307,592 variants was reduced to 89 candidates after applying the selected filtering strategy. Of these, 24 had been previously detected by routine callers and were not further analyzed. Among the remaining 65, 13 were considered likely true positives after visual inspection using IGV. Experimental validation was performed by Sanger/Nanopore long-read sequencing for these variants, all of which were confirmed. Eight were classified as (likely) pathogenic, including two frameshift duplications in MSH6, one splicing variant in BARD1, and five mobile element insertions in APC, BRCA2, and PALB2. Altogether, GRIDSS implementation increased diagnostic yield while maintaining feasibility for diagnostic workflows. Comprehensive workflow scheme for germline structural variant detection and results in our diagnostic setting.

Humans

Complex de novo structural variants are an underestimated cause of rare disorders.

Complex de novo structural variants (dnSVs) are crucial genetic factors in rare disorders, yet their prevalence and characteristics in rare disorders remain poorly understood. Here, we conduct a comprehensive analysis of whole-genome sequencing data of 12,568 families, including 13,698 offspring with rare diseases, obtained as part of the UK 100,000 Genomes Project. We identify 1,870 dnSVs, constituting the largest dnSV dataset reported to date. Complex dnSVs (n&#x2009;=&#x2009;158; 8.4%) emerge as the third most common type of SV, following simple deletions and duplications. We classify 65% of these complex dnSVs into 11 subtypes. Among probands with dnSVs (n&#x2009;=&#x2009;1,696), 9% exhibit exon-disrupting pathogenic dnSVs associated with the probands' phenotype. Notably, 12% of exon-disrupting pathogenic dnSVs and 22% of de novo deletions or duplications previously identified by array-based or whole-exome sequencing methods are found to be complex dnSVs. We also find distinct genomic properties of de novo deletions depending on the parent of origin. This study highlights the importance of complex dnSVs in the cause of rare disorders and demonstrates the necessity of specific genomic analysis to avoid overlooking these variants.

Humans

De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.

Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We develop a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implement it in the SuPreMo-Akita software. With this tool, we rank hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This reveals that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritize candidate variants that disrupt ASD CREints and validate our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study suggests that disrupted genome folding is a potential genetic mechanism in a subset of ASD cases and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.

Humans

Aplf/Dna2 variants drive chromosomal fission and accelerate speciation in zokors.

Chromosomal fissions and fusions are common, yet the molecular mechanisms and implications in speciation remain poorly understood. Here, we confirm a fission event in one zokor species through multiple-omics and functional analyses. We traced this event to a mutation in a splicing enhancer of the DNA repair gene Aplf in the fission-bearing species, which caused exon skipping and produced a truncated protein that disrupted DNA repair. An intronic deletion in Dna2, known to facilitate neo-telomere formation when knocked out, reduced gene activity. These variants collectively drove chromosomal fission in this zokor species. The newly formed chromosome became fixed due to carrying essential genes and strong selective pressure. While geographic isolation likely initiated the divergence of this species and the sister one, the fission event and associated decline at the chromosome level in gene flow probably exacerbated the speciation process. Our work elucidates the genetic basis of chromosomal fission and underscores its role in speciation dynamics.

Multiomics

Integrative Genotyping and Analysis of Canine Structural Variation Using Long-read and Short-read Data.

Structural variation makes an important contribution to canine evolution and phenotypic differences. Although recent advances in long-read sequencing have enabled the generation of multiple canine genome assemblies, most prior analyses of structural variation have relied on short-read sequencing. To offer a more complete assessment of structural variation in canines, we performed an integrative analysis of structural variants present in 12 canine samples with available long-read and short-read sequencing data along with genome assemblies. Use of long-reads permits the discovery of heterozygous variation that is absent in existing haploid assembly representations while offering a marked increase in the ability to identify insertion variants relative to short-read approaches. Examination of the size spectrum of structural variants shows that dimorphic LINE-1 and SINE variants account for over 45% of all deletions and identified 1,410 LINE-1s with intact open reading frames that show presence-absence dimorphism. Using a graph-based approach, we genotype newly discovered structural variants in an existing collection of 1,879 resequenced dogs and wolves, generating a variant catalog containing a 56.5% increase in the number of deletions and 705% increase in the number of insertions previously found in the analyzed samples. Examination of allele frequencies across admixture components present across breed clades identified 283 structural variants evolving with a signature of selection.

Animals

A chromosome-level, haplotype-resolved genome assembly for the barn owl, Tyto alba.

Recent advances in long-read sequencing have enabled near telomere-to-telomere (T2T) assemblies across diverse taxa. However, avian genomes remain challenging due to numerous microchromosomes, small, typically < 20Mb, DNA molecules that are gene-, GC-, and repeat-rich. As a consequence, microchromosomes are often missing from genome assemblies. Here, we present a chromosome-level, haplotype-resolved genome assembly for the Western barn owl (Tyto alba). Using a trio-binning strategy with Illumina parental reads combined with PacBio HiFi and Oxford Nanopore Technologies data, we generated two phased contig sets. These were scaffolded into 40 linkage groups using a linkage map. Comparative analyses identified unplaced HiFi scaffolds corresponding to microchromosomes, which we integrated into six additional microchromosomes using long reads information. The two assemblies present 46 chromosomes, matching the karyotype of the species. They exhibit strong synteny between parental haplotypes, except for a &#x223c;38 Mb complex region on chromosome 7 containing nested inversions. This high-quality reference provides a haplotype-resolved and chromosome-level genome for Strigiformes, enabling fine-scale studies of structural variation and avian genome evolution.

Tyto alba