Behcet\'s disease (BD) is one of the most vision-threatening clinical entities of uveitis. Although the etiopathogenesis of BD remains obscure, accumulating evidence has demonstrated that both genetic and environmental factors may contribute to the development of BD. Genome-wide association studies (GWAS) and candidate association studies have identified several genetic variants strongly associated with BD, including variants in human leukocyte antigen (HLA) -A02, -A03, -A24, -A26, -A31, -B15, -B27, -B35, -B49, -B51, -B57, -B58, -C0704, CIITA, ERAP1, MICA, IL1A-IL1B, IL10, IL12, IL23R, IL-23R/IL-12RB2, IL1RL1-IL18R1, STAT4, TFCP2L1, TRAF5, TNFAIP3, CCR1/CCR3, RIPK2, ADO-ZNF365-EGR2, KLRC4, LACC1, MEFV, IRF8, FUT2, CEBPB-PTPN1, ZMIZ1, RPS6KA4, IL10RA, SIPA1-FIBP-FOSL1, VAMP1, JRKL/CTCN5, IFNGR1 and miRNA-146a. Epigenetic modifications are also reported to play essential roles in the development of BD, including DNA methylation and histone modification. We review here the recent advances in the genetic and epigenetic factors associated with the BD pathogenesis.

BACKGROUND: Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.
RESULTS: We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.
CONCLUSIONS: The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Bladder cancer (BlCa) is an extensively heterogeneous disease that leads to great variability in tumor evolution scenarios and lifelong patient surveillance, emphasizing the need for modern, minimally invasive precision medicine. Here, we explored the clinical significance of copy number alterations (CNAs) in BlCa. CNA profiling was performed in 15 patient-derived xenografts (PDXs) and validated in The Cancer Genome Atlas BlCa (TCGA-BLCA; n = 408) and Lindgren et al. (n = 143) cohorts. CDKN2A copy number loss was identified as the most frequent CNA in bladder tumors, associated with reduced CDKN2A expression, tumors of a papillary phenotype, and prolonged PDX survival. The study\'s screening cohort consisted of 243 BlCa patients, and CDKN2A copy number was assessed in genomic DNA and cell-free DNA (cfDNA) from 217 tumors and 189 pre-treatment serum samples, respectively. CDKN2A copy number loss was correlated with superior disease-free and progression-free survival of non-muscle-invasive BlCa (NMIBC) patients. Moreover, a higher CDKN2A index (CDKN2A/LEP ratio) in pre-treatment cfDNA was associated with advanced tumor stage and grade and short-term NMIBC progression to invasive disease, while multivariate models fitted for CDKN2A index in pre-treatment cfDNA offered superior risk stratification of T1/high-grade and EORTC high-risk patients, enhancing prediction of treatment outcome. CDKN2A copy number status could serve as a minimally invasive tool to improve risk stratification and support personalized prognosis in BlCa.

The massive structural variations and frequent introgression highly contribute to the genetic diversity of wheat, while the huge and complex genome of polyploid wheat hinders efficient genotyping of abundant varieties towards accurate identification, management, and exploitation of germplasm resources.
We develop a novel workflow that identifies 1240 high-quality large copy number variation blocks (CNVb) in wheat at the pan-genome level, demonstrating that CNVb can serve as an ideal DNA fingerprinting marker for discriminating massive varieties, with the accuracy validated by PCR assay. We then construct a digitalized genotyping CNVb map across 1599 global wheat accessions. Key CNVb markers are linked with trait-associated introgressions, such as the 1RS·1BL translocation and 2NvS translocation, and the beneficial alleles, such as the end-use quality allele Glu-D1d (Dx5 + Dy10) and the semi-dwarf r-e-z allele. Furthermore, we demonstrate that these tagged CNVb markers promote a stable and cost-effective strategy for evaluating wheat germplasm resources with ultra-low-coverage sequencing data, competing with SNP array for applications such as evaluating new varieties, efficient management of collections in gene banks, and describing wheat germplasm resources in a digitalized manner. We also develop a user-friendly interactive platform, WheatCNVb ( http://wheat.cau.edu.cn/WheatCNVb/ ), for exploring the CNVb profiles over ever-increasing wheat accessions, and also propose a QR-code-like representation of individual digital CNVb fingerprint. This platform also allows uploading new CNVb profiles for comparison with stored varieties.
The CNVb-based approach provides a low-cost and high-throughput genotyping strategy for enabling digitalized wheat germplasm management and modern breeding with precise and practical decision-making.

Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome.
While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).
NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

Copy number variation (CNV) serves as a significant source of genetic diversity in mammals and exerts substantial effects on various complex traits. Pingliang red cattle, an outstanding indigenous resource in China, possess remarkable breeding value attributed to their tender meat and superior marbling quality. However, the genetic mechanisms influencing carcass and meat quality traits in Pingliang red cattle are not well understood. We generated a comprehensive genome-wide CNV map for Pingliang red cattle using the GGP Bovine 100K SNP chip. A total of 755 copy number variable regions (CNVRs) spanning 81.03 Mb were identified, accounting for approximately 3.24% of the bovine autosomal genome. Among these, we discovered 270 potentially breed-specific CNVRs in Pingliang red cattle, including 143 gains, 73 losses, and 54 mixed events. Functional annotation analysis revealed significant associations between these specific CNVRs and important traits such as carcass and meat quality, reproduction, exterior traits, growth traits, and health traits. Additionally, our network and transcriptome analysis highlighted CACNA2D1, CYLD, UBXN2B, TG, NADK, and ITGA9 as promising candidate genes associated with carcass weight and intramuscular fat deposition. The current study presents a genome-wide CNV map in Pingliang red cattle, highlighting breed-specific CNVRs, and transcriptome findings provide valuable insights into the underlying genetic characteristics of Pingliang red cattle. These results offer potential avenues for enhancing meat quality through a targeted breeding program.

Understanding the mechanisms of polyploidization in cardiomyocytes is crucial for advancing strategies to stimulate myocardial regeneration. Although endoreplication has long been considered the primary source of polyploid human cardiomyocytes, recent animal work suggests the potential for cardiomyocyte fusion. Moreover, the effects of polyploidization on the genomic-transcriptomic repertoire of human cardiomyocytes have not been studied previously. We applied single-nuclei whole genome sequencing, single nuclei RNA sequencing, and multiome ATAC + gene expression (from the same nuclei) techniques to nuclei isolated from 11 healthy hearts. Utilizing post-zygotic non-inherited somatic mutations occurring during development as \"endogenous barcodes,\" to reconstruct lineage relationships of polyploid cardiomyocytes. Of 482 cardiomyocytes from multiple healthy donor hearts 75.7% can be sorted into several developmental clades marked by one or more somatic single-nucleotide variants (SNVs). At least ~10% of tetraploid cardiomyocytes contain cells from distinct clades, indicating fusion of lineally distinct cells, whereas 60% of higher-ploidy cardiomyocytes contain fused cells from distinct clades. Combined snRNA-seq and snATAC-seq revealed transcriptome and chromatin landscapes of polyploid cardiomyocytes distinct from diploid cardiomyocytes, and show some higher-ploidy cardiomyocytes with transcriptional signatures suggesting fusion between cardiomyocytes and endothelial and fibroblast cells. These observations provide the first evidence for cell and nuclear fusion of human cardiomyocytes, raising the possibility that cell fusion may contribute to developing or maintaining polyploid cardiomyocytes in the human heart.

Copy number variation in large gene families is well characterized for plant resistance genes, but similar studies are rare in animals. The zebrafish (Danio rerio) has hundreds of NLR immune genes, making this species ideal for studying this phenomenon. By sequencing 93 zebrafish from multiple wild and laboratory populations, we identified a total of 1513 NLRs, many more than the previously known 400. Approximately half of those are present in all wild populations, but only 4% were found in 80% or more of the individual fish. Wild fish have up to two times as many NLRs per individual and up to four times as many NLRs per population than laboratory strains. In contrast to the massive variability of gene copies, nucleotide diversity in zebrafish NLR genes is very low: around half of the copies are monomorphic and the remaining ones have very few polymorphisms, likely a signature of purifying selection.
Humans and other animals have immune systems that protect them from bacteria, viruses and other potentially harmful microbes. Members of a family of genes known as the NLR family play various roles in helping to recognize and destroy these microbes. Different species have varying numbers of NLR genes, for example, humans have 22 NLRs, but fish can have hundreds. 400 have been found in the small tropical zebrafish, also known as zebra danios. Zebrafish are commonly used as model animals in research studies because they reproduce quickly and are easy to keep in fish tanks. Much of what we know about fish biology comes from studying strains of those laboratory zebrafish, including the 400 NLRs found in a specific laboratory strain. Many NLRs in zebrafish are extremely similar, suggesting that they have only evolved fairly recently through gene duplication. It remains unclear why laboratory zebrafish have so many almost identical NLRs, or if wild zebrafish also have lots of these genes. To find out more, Schäfer et al. sequenced the DNA of NLRs from almost 100 zebrafish from multiple wild and laboratory populations. The approach identified over 1,500 different NLR genes, most of which, were previously unknown. Computational modelling suggested that each wild population of zebrafish may harbour up to around 2,000 NLR genes, but laboratory strains had much fewer NLRs. The numbers of NLR genes in individual zebrafish varied greatly – only 4% of the genes were present in 80% or more of the fish. Many genes were only found in specific populations or single individuals. Together, these findings suggest that the NLR family has expanded in zebrafish as part of an ongoing evolutionary process that benefits the immune system of the fish. Similar trends have also been observed in the NLR genes of plants, indicating there may be an evolutionary strategy across all living things to continuously diversify large families of genes. Additionally, this work highlights the lack of diversity in the genes of laboratory animals compared with those of their wild relatives, which may impact how results from laboratory studies are used to inform conservation efforts or are interpreted in the context of human health.

Leukocyte immunoglobulin (Ig)-like receptors (LILRs) on human chromosome 19q13.4 encode 11 immunoglobulin superfamily receptors, exhibiting genetic diversity within and between human populations. Among the LILR genes, the genomic region surrounding LILRB3 and LILRA6 has yet to be fully characterized due to their significant sequence homology, which makes it difficult to differentiate between them. To examine the LILRB3 and LILRA6 genomic region, a tool named JoGo-LILR CN Caller, which can call copy number from short-read whole genome sequencing (srWGS) data, was applied to an extensive international srWGS dataset comprising 2,504 samples. During this process, a previously unreported loss of both LILRB3 and LILRA6 was detected in three samples. Using long-read sequencing of these samples, we have discovered a novel large deletion (33,692 bp) in the LILRB3 and LILRA6 genomic regions in the Japanese population. This deletion spanned three genes, LILRB3, LILRA6, and LILRB5, resulting in LILRB3 exons 12-13 being located immediately downstream of LILRB5 exons 1-12 with the loss of LILRA6, suggesting the potential expression of a hybrid gene between LILRB5 and LILRB3 (LILRB5-3). Transcription and subsequent translation of the LILRB5-3 hybrid gene were also verified. The hybrid junction was located within the intracellular domain, resulting in an LILRB5 extracellular domain fused to a partial LILRB3 intracellular domain with three immunoreceptor tyrosine-based inhibitory motifs (ITIMs), suggesting that LILRB5-3 acquired a novel signaling function. Further application of the JoGo-LILR tool to srWGS samples suggested the presence of the LILRB5-3 hybrid gene in the CEU population. Our findings provide insight into the genetic and functional diversity of the LILR family.

Copy number variation (CNV) is an important structural variation used to elucidate complex economic traits. In this study, we sequenced 25 Wannan spotted pigs (WSPs) to detect their CNVs and identify their selection signatures compared with those of 10 Asian wild boars. A total of 14,161 CNVs were detected in the WSPs, accounting for 0.72% of the porcine genome. The fixation index (Fst) was used to identify the selection signatures, and 195 CNVs with the top 1% of the Fst value were selected. Eighty genes were identified in the selected CNV regions. Functional GO and KEGG analyses revealed that the genes within these selected CNVs are associated with key traits such as reproduction (GAL3ST1 and SETD2), fatty acid composition (PRKG1, ACACA, ACSL3, UGT8), immune system (LYZ), ear size (WIF1), and feed efficiency (VIPR2). The findings of this study contribute novel insights into the genetic CNVs underlying WSP characteristics and provide essential information for the protection and utilization of WSP populations.