African swine fever (ASF) is a rapidly fatal viral haemorrhagic fever in Chinese domestic pigs. Although very high mortality is observed in pig farms after an ASF outbreak, clinically healthy and antibody-positive pigs are found in those farms, and viral detection is rare from these pigs. The ability of pigs to resist ASF viral infection may be modulated by host genetic variations. However, the genetic basis of the resistance of domestic pigs against ASF remains unclear. We generated a comprehensive set of structural variations (SVs) in a Chinese indigenous Xiang pig with ASF-resistant (Xiang-R) and ASF-susceptible (Xiang-S) phenotypes using whole-genome resequencing method. A total of 53,589 nonredundant SVs were identified, with an average of 25,656 SVs per individual in the Xiang pig genome, including insertion, deletion, inversion and duplication variations. The Xiang-R group harboured more SVs than the Xiang-S group. The F-statistics (FST) was carried out to reveal genetic differences between two populations using the resequencing data at each SV locus. We identified 2,414 population-stratified SVs and annotated 1,152 Ensembl genes (including 986 protein-coding genes), in which 1,326 SVs might disturb the structure and expression of the Ensembl genes. Those protein-coding genes were mainly enriched in the Wnt, Hippo, and calcium signalling pathways. Other important pathways associated with the ASF viral infection were also identified, such as the endocytosis, apoptosis, focal adhesion, Fc gamma R-mediated phagocytosis, junction, NOD-like receptor, PI3K-Akt, and c-type lectin receptor signalling pathways. Finally, we identified 135 candidate adaptive genes overlapping 166 SVs that were involved in the virus entry and virus-host cell interactions. The fact that some of population-stratified SVs regions detected as selective sweep signals gave another support for the genetic variations affecting pig resistance against ASF. The research indicates that SVs play an important role in the evolutionary processes of Xiang pig adaptation to ASF infection.

BACKGROUND: Structural variation (SV) detection methods using third-generation sequencing data are widely employed, yet accurately detecting SVs remains challenging. Different methods often yield inconsistent results for certain SV types, complicating tool selection and revealing biases in detection.
RESULTS: This study comprehensively evaluates 53 SV detection pipelines using simulated and real data from PacBio (CLR: Continuous Long Read, CCS: Circular Consensus Sequencing) and Nanopore (ONT) platforms. We assess their performance in detecting various sizes and types of SVs, breakpoint biases, and genotyping accuracy with various sequencing depths. Notably, pipelines such as Minimap2-cuteSV2, NGMLR-SVIM, PBMM2-pbsv, Winnowmap-Sniffles2, and Winnowmap-SVision exhibit comparatively higher recall and precision. Our findings also show that combining multiple pipelines with the same aligner, like pbmm2 or winnowmap, can significantly enhance performance. The individual pipelines\' detailed ranking and performance metrics can be viewed in a dynamic table: http://pmglab.top/SVPipelinesRanking .
CONCLUSIONS: This study comprehensively characterizes the strengths and weaknesses of numerous pipelines, providing valuable insights that can improve SV detection in third-generation sequencing data and inform SV annotation and function prediction.

Structural variation (SV) is an important form of genomic variation that influences gene function and expression by altering the structure of the genome. Although long-read data have been proven to better characterize SVs, SVs detected from noisy long-read data still include a considerable portion of false-positive calls. To accurately detect SVs in long-read data, we present SVDF, a method that employs a learning-based noise filtering strategy and an SV signature-adaptive clustering algorithm, for effectively reducing the likelihood of false-positive events. Benchmarking results from multiple orthogonal experiments demonstrate that, across different sequencing platforms and depths, SVDF achieves higher calling accuracy for each sample compared to several existing general SV calling tools. We believe that, with its meticulous and sensitive SV detection capability, SVDF can bring new opportunities and advancements to cutting-edge genomic research.

Tibetan sheep were introduced to the Qinghai Tibet plateau roughly 3,000 B.P., making this species a good model for investigating genetic mechanisms of high-altitude adaptation over a relatively short timescale. Here, we characterize genomic structural variants (SVs) that distinguish Tibetan sheep from closely related, low-altitude Hu sheep, and we examine associated changes in tissue-specific gene expression. We document differentiation between the two sheep breeds in frequencies of SVs associated with genes involved in cardiac function and circulation. In Tibetan sheep, we identified high-frequency SVs in a total of 462 genes, including EPAS1, PAPSS2, and PTPRD. Single-cell RNA-Seq data and luciferase reporter assays revealed that the SVs had cis-acting effects on the expression levels of these three genes in specific tissues and cell types. In Tibetan sheep, we identified a high-frequency chromosomal inversion that exhibited modified chromatin architectures relative to the noninverted allele that predominates in Hu sheep. The inversion harbors several genes with altered expression patterns related to heart protection, brown adipocyte proliferation, angiogenesis, and DNA repair. These findings indicate that SVs represent an important source of genetic variation in gene expression and may have contributed to high-altitude adaptation in Tibetan sheep.

Sheep and goats have undergone domestication and improvement to produce similar phenotypes, which have been greatly impacted by structural variants (SVs). Here, we report a high-quality chromosome-level reference genome of Asiatic mouflon, and implement a comprehensive analysis of SVs in 897 genomes of worldwide wild and domestic populations of sheep and goats to reveal genetic signatures underlying convergent evolution.
We characterize the SV landscapes in terms of genetic diversity, chromosomal distribution and their links with genes, QTLs and transposable elements, and examine their impacts on regulatory elements. We identify several novel SVs and annotate corresponding genes (e.g., BMPR1B, BMPR2, RALYL, COL21A1, and LRP1B) associated with important production traits such as fertility, meat and milk production, and wool/hair fineness. We detect signatures of selection involving the parallel evolution of orthologous SV-associated genes during domestication, local environmental adaptation, and improvement. In particular, we find that fecundity traits experienced convergent selection targeting the gene BMPR1B, with the DEL00067921 deletion explaining ~10.4% of the phenotypic variation observed in goats.
Our results provide new insights into the convergent evolution of SVs and serve as a rich resource for the future improvement of sheep, goats, and related livestock.

CONCLUSIONS: A wild melon reference genome elucidates the genomic basis of fruit acidity domestication. Structural variants (SVs) have been reported to impose major effects on agronomic traits, representing a significant contributor to crop domestication. However, the landscape of SVs between wild and cultivated melons is elusive and how SVs have contributed to melon domestication remains largely unexplored. Here, we report a 379-Mb chromosome-scale genome of a wild progenitor melon accession \"P84\", with a contig N50 of 14.9 Mb. Genome comparison identifies 10,589 SVs between P84 and four cultivated melons with 6937 not characterized in previously analysis of 25 melon genome sequences. Furthermore, the population-scale genotyping of these SVs was determined in 1175 accessions, and 18 GWAS signals including fruit acidity, fruit length, fruit weight, fruit color and sex determination were detected. Based on these genotyped SVs, we identified 3317 highly diverged SVs between wild and cultivated melons, which could be the potential SVs associated with domestication-related traits. Furthermore, we identify novel SVs affecting fruit acidity and proposed the diverged evolutionary trajectories of CmPH, a key regulator of melon fruit acidity, during domestication and selection of different populations. These results will offer valuable resources for genomic studies and genetic improvement in melon.

Multiple types of variations have been postulated to confer risk of schizophrenia and bipolar disorder, but majority of present GWAS solely focused on SNPs or small indels, and the impacts of structural variations (SVs) remain less understood. Nevertheless, accumulating evidence suggest that SVs may explain the association signals in certain GWAS hits. Here, we conducted pairwise linkage disequilibrium (LD) analyses of SNPs and SVs in populations from 1000 Genomes Project. Among the 299 psychiatric GWAS loci, 1213 SVs showed an LD of r2 > 0.1 with GWAS risk SNPs, and 66 of them were in moderate to strong LD (r2 > 0.6) with at least one GWAS risk SNP. Nine SVs were subject to further explorative analyses, including eQTL analysis in DLPFC, luciferase reporter gene assays, CRISPR/Cas9-mediated genome deletion and RT-qPCR. These assays highlighted several functional SVs showing regulatory effects on transcriptional activities, and some risk genes (e.g., BORCS7, GNL3) affected by the SVs were also annotated. Finally, mice overexpressing Borcs7 in the mPFC exhibited schizophrenia-like behaviors, such as abnormal prepulse inhibition and social dysfunction. These data suggest that SNPs association signals at GWAS loci might be driven by SVs, highlighting the necessities of considering such variants in future.

Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.
We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV\'s impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.
This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.

Structural variations (SVs) are a feature of plant genomes that has been largely unexplored despite their significant impact on plant phenotypic traits and local adaptation to abiotic and biotic stress. In this study, we employed woolly grape (Vitis retordii), a species native to the tropical and subtropical regions of East Asia with both coastal and inland habitats, as a valuable model for examining the impact of SVs on local adaptation. We assembled a haplotype-resolved chromosomal reference genome for woolly grape, and conducted population genetic analyses based on whole-genome sequencing (WGS) data from coastal and inland populations. The demographic analyses revealed recent bottlenecks in all populations and asymmetric gene flow from the inland to the coastal population. In total, 1,035 genes associated with plant adaptive regulation for salt stress, radiation, and environmental adaptation were detected underlying local selection by SVs and SNPs in the coastal population, of which 37.29% and 65.26% were detected by SVs and SNPs, respectively. Candidate genes such as FSD2, RGA1, and AAP8 associated with salt tolerance were found to be highly differentiated and selected during the process of local adaptation to coastal habitats in SV regions. Our study highlights the importance of SVs in local adaptation; candidate genes related to salt stress and climatic adaptation to tropical and subtropical environments are important genomic resources for future breeding programs of grapevine and its rootstocks.

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