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Fungi use the accessory gene content of their pangenomes to adapt to their environments. While gene presence-absence variation contributes to shaping accessory gene reservoirs, the genomic contexts that shape these events remain unclear. Since pangenome studies are typically species-wide and do not analyze different populations separately, it is yet to be uncovered whether presence-absence variation patterns and mechanisms are consistent across populations. Fungal plant pathogens are useful models for studying presence-absence variation because they rely on it to adapt to their hosts, and members of a species often infect distinct hosts. We analyzed gene presence-absence variation in the blast fungus, Magnaporthe oryzae (syn. Pyricularia oryzae), and found that presence-absence variation genes involved in host-pathogen and microbe-microbe interactions may drive the adaptation of the fungus to its environment. We then analyzed genomic and epigenomic features of presence-absence variation and observed that proximity to transposable elements, gene GC content, gene length, expression level in the host, and histone H3K27me3 marks were different between presence-absence variation genes and conserved genes. We used these features to construct a model that was able to predict whether a gene is likely to experience presence-absence variation with high precision (86.06%) and recall (92.88%) in M. oryzae. Finally, we found that presence-absence variation genes in the rice and wheat pathotypes of M. oryzae differed in their number and their genomic context. Our results suggest that genomic and epigenomic features of gene presence-absence variation can be used to better understand and predict fungal pangenome evolution. We also show that substantial intra-species variation can exist in these features.

Summary Chromosomal inversions can preserve combinations of favorable alleles by suppressing recombination. Simultaneously, they reduce the effectiveness of purifying selection enabling deleterious alleles to accumulate. This study explores how areas of low recombination, including centromeric regions and chromosomal inversions, contribute to the accumulation of deleterious and favorable loci in 225 Mangifera indica genomes from the Australian Mango Breeding Program. Here, we identify 17 chromosomal inversions that cover 7.7% (29.7 Mb) of the M. indica genome: eight pericentric (inversion includes the centromere) and nine paracentric (inversion is on one arm of the chromosome). Our results show that these large pericentric inversions are accumulating deleterious loci, while the paracentric inversions show deleterious levels above and below the genome wide average. We find that despite their deleterious load, chromosomal inversions contain small effect loci linked to variation in crucial breeding traits. These results indicate that chromosomal inversions have likely facilitated the evolution of key mango breeding traits. Our study has important implications for selective breeding of favorable combinations of alleles in regions of low recombination. [ABSTRACT FROM AUTHOR]

Complex structural variations (cxSVs) are often overlooked in genome analyses due to detection challenges. We developed ARC-SV, a probabilistic and machine-learning-based method that enables accurate detection and reconstruction of cxSVs from standard datasets. By applying ARC-SV across 4,262 genomes representing all continental populations, we identified cxSVs as a significant source of natural human genetic variation. Rare cxSVs have a propensity to occur in neural genes and loci that underwent rapid human-specific evolution, including those regulating corticogenesis. By performing single-nucleus multiomics in postmortem brains, we discovered cxSVs associated with differential gene expression and chromatin accessibility across various brain regions and cell types. Additionally, cxSVs detected in brains of psychiatric cases are enriched for linkage with psychiatric GWAS risk alleles detected in the same brains. Furthermore, our analysis revealed significantly decreased brain-region- and cell-type-specific expression of cxSV genes, specifically for psychiatric cases, implicating cxSVs in the molecular etiology of major neuropsychiatric disorders. [Display omitted] • ARC-SV uses machine learning on pangenomes to detect cxSVs with high accuracy • Rare cxSVs in the human population are enriched in neural genes • Rare cxSVs are enriched in loci that underwent rapid human-specific evolution • cxSVs contribute to the genetic architecture of major psychiatric disorders ARC-SV enables highly accurate detection and characterization of localized complex rearrangements of multiple DNA segments. Applying ARC-SV across human populations and brain cohorts uncovers connections between complex structural variantion and human-specific evolution, neural genes, and major psychiatric disorders. [ABSTRACT FROM AUTHOR]

The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC, uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets. Synopsis: InfoHiC is developed for cancer 3D genome prediction enabling to find neo-TADs and neo-loops starting from whole genome sequencing reads. InfoHiC is trained from available cancer Hi-C data and predicts Hi-C matrices for patients with cancer, which eliminates the burden of high Hi-C sequencing costs. InfoHiC takes whole genome sequencing reads in contrast to other Hi-C prediction tools requiring pre-defined sequences, enabling Hi-C prediction from cancer genomes where users cannot define sequence inputs easily. It analyzes all structural variation types including those found in non-coding regions, and predicts the impact on cancer development in the 3D genome context. It can lead to personalized medication by discovering neo-TADs and neo-loops in patients where common coding driver mutations or copy number changes are not found. InfoHiC is developed for cancer 3D genome prediction enabling to find neo-TADs and neo-loops starting from whole genome sequencing reads. [ABSTRACT FROM AUTHOR]

The kiang (Equus kiang) can only be observed in the Qinghai–Tibet Plateau (QTP). The kiang displayed excellent athletic performance in the high‐altitude environment, which attracted wide interest in the investigation of the potential adaptive mechanisms to the extreme environment. Here, we assembled a chromosome‐level genome of the kiang based on Hi‐C sequencing technology. A total of 324.14 Gb clean data were generated, and the chromosome‐level genome with 26 chromosomes (25 + X) and scaffold N50 of 101.77 Mb was obtained for the kiang. The genomic synteny analysis revealed large‐scale chromosomal rearrangement during the evolution process of Equus species. Phylogenetic and divergence analyses revealed that the kiang was the sister branch to the ass and diverged from a common ancestor at approximately 13.5 Mya. The expanded gene families were mainly related to the hypoxia response, metabolism, and immunity. The kiang suffered a significant loss of olfaction‐related genes, which might indicate decreased olfactory sensibility. Positively selected genes (PSGs) detected in the kiang were mainly associated with hypoxia response. Especially, there were two species‐specific missense amino acid mutations in the PSG STAT3 annotated in the hypoxia‐inducible factor 1 signal pathway, which may play an important role in the high‐altitude adaptation of the kiang. Moreover, structure variations in the kiang genome were also identified, which possibly contributed to the high‐altitude adaptation of the kiang. Comparative analysis revealed a lot of species‐specific insertions and deletions in the kiang genome, such as PIK3CB and AKT with 3258 and 189 bp insertions in the intron region, respectively, possibly affecting the expression and regulation of hypoxia‐related downstream pathways. This study provided valuable genomic resources, and our findings help a better understanding of the underlying adaptive strategies to the high‐altitude environment in the kiang. [ABSTRACT FROM AUTHOR]

Summary: Structural variations (SVs) are major genetic variants that can be involved in the origin, adaptation and domestication of species. However, the identification and characterization of SVs in Spinacia species are rare due to the lack of a pan‐genome. Here, we report eight chromosome‐scale assemblies of cultivated spinach and its two wild species. After integration with five existing assemblies, we constructed a comprehensive Spinacia pan‐genome and identified 193 661 pan‐SVs, which were genotyped in 452 Spinacia accessions. Our pan‐SVs enabled genome‐wide association study identified signals associated with sex and clarified the evolutionary direction of spinach. Most sex‐linked SVs (86%) were biased to occur on the Y chromosome during the evolution of the sex‐linked region, resulting in reduced Y‐linked gene expression. The frequency of pan‐SVs among Spinacia accessions further illustrated the contribution of these SVs to domestication, such as bolting time and seed dormancy. Furthermore, compared with SNPs, pan‐SVs act as efficient variants in genomic selection (GS) because of their ability to capture missing heritability information and higher prediction accuracy. Overall, this study provides a valuable resource for spinach genomics and highlights the potential utility of pan‐SV in crop improvement and breeding programmes. [ABSTRACT FROM AUTHOR]

How phenotypic diversity originates and persists within populations are classic puzzles in evolutionary biology. While balanced polymorphisms segregate within many species, it remains rare for both the genetic basis and the selective forces to be known, leading to an incomplete understanding of many classes of traits under balancing selection. Here, we uncover the genetic architecture of a balanced sexual mimicry polymorphism and identify behavioral mechanisms that may be involved in its maintenance in the swordtail fish Xiphophorus birchmanni. We find that ∼40% of X. birchmanni males develop a "false gravid spot," a melanic pigmentation pattern that mimics the "pregnancy spot" associated with sexual maturity in female live-bearing fish. Using genome-wide association mapping, we detect a single intergenic region associated with variation in the false gravid spot phenotype, which is upstream of kitlga , a melanophore patterning gene. By performing long-read sequencing within and across populations, we identify complex structural rearrangements between alternate alleles at this locus. The false gravid spot haplotype drives increased allele-specific expression of kitlga , which provides a mechanistic explanation for the increased melanophore abundance that causes the spot. By studying social interactions in the laboratory and in nature, we find that males with the false gravid spot experience less aggression; however, they also receive increased attention from other males and are disdained by females. These behavioral interactions may contribute to the maintenance of this phenotypic polymorphism in natural populations. We speculate that structural variants affecting gene regulation may be an underappreciated driver of balanced polymorphisms across diverse species. [Display omitted] • The false gravid spot is a sexual mimicry polymorphism in swordtail fish • Non-coding structural variation increases expression of kitlga to drive the spot • Several lines of evidence suggest balancing selection maintains the polymorphism • The false gravid spot alters social interactions with both males and females The false gravid spot is a sexual mimicry polymorphism that allows males to mimic females. Dodge et al. link the phenotype to structural variation that increases expression of the nearby kitlga gene. The spot affects multiple social interactions with males and females, which may contribute to the persistence of this balanced polymorphism in nature. [ABSTRACT FROM AUTHOR]

Background: Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed. Results: We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools. Conclusions: This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches. [ABSTRACT FROM AUTHOR]

Plants use extrafloral nectaries (EFNs) as indirect defence mechanisms against herbivores. These structures contain nectar that is offered to ants in exchange for their protection. EFNs display pronounced functional variation, but it is unknown how this variation comes together in phenotypes. Here, we characterized the main functional traits of EFNs and investigated the associations among them. This work was conducted at a study site in the Caatinga that hosts 14 species of woody plants. We characterized the following functional traits: EFN type, position, arrangement, size, and reducing-sugar level. We observed a marked degree of trait variation (~30%) that was manifested in species-specific trait combinations, giving rise to an 'ecological spectrum'. At one end were Fabaceae species with large, vascularized EFNs that occur individually on the leaf petiole and/or rachis and that produce high levels of reducing sugars. At the other end were Euphorbiaceae species with small, nonvascularized EFNs that are generally grouped on the leaf blade and that produce low levels of reducing sugars. Despite its limited geographical and phylogenetic scale, this study represents an important first step in describing an ecological spectrum that can inform our understanding of the ecological interactions and evolutionary history of this functionally relevant group of plants. [ABSTRACT FROM AUTHOR]

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full‐length protein‐encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large‐scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits. [ABSTRACT FROM AUTHOR]

Background: Differences of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. In more than 50% of human DSD cases, a molecular diagnosis is not available. In intensively farmed pig populations, the incidence of XX DSD pigs is relatively high, leading to economic losses for pig breeders. Interestingly, in the majority of 38, XX DSD pigs, gonads still develop into testis-like structures or ovotestes despite the absence of the testis-determining gene (SRY). However, the current understanding of the molecular background of XX DSD pigs remains limited. Methods: Anatomical and histological characteristics of XX DSD pigs were analysed using necropsy and HE staining. We employed whole-genome sequencing (WGS) with 10× Genomics technology and used de novo assembly methodology to study normal female and XX DSD pigs. Finally, the identified variants were validated in 32 XX DSD pigs, and the expression levels of the candidate variants in the gonads of XX DSD pigs were further examined. Results: XX DSD pigs are characterised by the intersex reproductive organs and the absence of germ cells in the seminiferous tubules of the gonads. We identified 4,950 single-nucleotide polymorphisms (SNPs) from non-synonymous mutations in XX DSD pigs. Cohort validation results highlighted two specific SNPs, "c.218T > C" in the "Interferon-induced transmembrane protein 1 gene (IFITM1)" and "c.1043C > G" in the "Newborn ovary homeobox gene (NOBOX)", which were found exclusively in XX DSD pigs. Moreover, we verified 14 candidate structural variants (SVs) from 1,474 SVs, identifying a 70 bp deletion fragment in intron 5 of the WW domain-containing oxidoreductase gene (WWOX) in 62.5% of XX DSD pigs. The expression levels of these three candidate genes in the gonads of XX DSD pigs were significantly different from those of normal female pigs. Conclusion: The nucleotide changes of IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment of the WWOX were the most dominant variants among XX DSD pigs. This study provides a theoretical basis for better understanding the molecular background of XX DSD pigs. Plain language summary: DSD are conditions affecting development of the gonads or genitalia. These disorders can happen in many different types of animals, including pigs, goats, dogs, and people. In people, DSD happens in about 0.02–0.13% of births, and in pigs, the rate is between 0.08% and 0.75%. Pigs have a common type of DSD where the animal has female chromosomes (38, XX) but no SRY gene, which is usually found on the Y chromosome in males. XX DSD pigs may look like both males and females on the outside and have testis-like or ovotestis (a mix of ovary and testis) gonads inside. XX DSD pigs often lead to not being able to have piglets, slower growth, lower chance of survival, and poorer meat quality. Here, we used a method called whole-genome de novo sequencing to look for variants in the DNA of XX DSD pigs. We then checked these differences in a larger group of pigs. Our results reveal the nucleotide changes in IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment in intron 5 of the WWOX, all linked to XX DSD pigs. The expression levels of these three genes were also different in the gonads of XX DSD pigs compared to normal female pigs. These variants are expected to serve as valuable molecular markers for XX DSD pigs. Because pigs are a lot like humans in their genes, physiology, and body structure, this research could help us learn more about what causes DSD in people. Highlights: XX DSD pigs have abnormal development of reproductive organs showing both male and female characteristics and lack of germ cells in the seminiferous tubules. Whole-genome de novo sequencing was used to reveal the characteristics of genomic variants in XX DSD pigs. The nucleotide changes of IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment of WWOX were the dominant variants in XX DSD pigs, and these three genes were significantly changed in the gonadal expression levels of the XX DSD pigs compared to those of normal females. [ABSTRACT FROM AUTHOR]

Alisma L. is a medicinally important genus of aquatic and wetland plants consisting of c. 10 recognized species. However, largely due to polyploidy and limited taxon and gene sampling, the phylogenomic relationships of Alisma remain challenging. In this study, we sequenced 34 accessions of Alismataceae, including eight of the ten species of Alisma, one species of Echinodorus and one species of Luronium, to perform comparative analyses of plastid genomes and phylogenetic analyses. Comparative analysis of plastid genomes revealed high sequence similarity among species within the genus. Our study analyzed structural changes and variations in the plastomes of Alisma, including IR expansion or contraction, and gene duplication or loss. Phylogenetic results suggest that Alisma is monophyletic, and constitutes four groups: (1) A. lanceolatum and A. canaliculatum; (2) the North American clade of A. subcordatum and A. triviale; (3) A. wahlenbergii and A. gramineum; and (4) A. plantago-aquatica from Eurasia and northern Africa with the eastern Asian A. orientale nested within it. Hence the results challenge the recognition of A. orientale as a distinct species and raise the possibility of treating it as a synonym of the widespread A. plantago-aquatica. The well-known Alismatis Rhizoma (Zexie) in Chinese medicine was likely derived from the morphologically variable Alisma plantago-aquatica throughout its long history of cultivation in Asia. The plastome phylogenetic results also support the tetraploid A. lanceolatum as the likely maternal parent of the hexaploid eastern Asian A. canaliculatum [ABSTRACT FROM AUTHOR]

Structural variation (SV) refers to insertions, deletions, inversions, and duplications in human genomes. SVs are present in approximately 1.5% of the human genome. Still, this small subset of genetic variation has been implicated in the pathogenesis of psoriasis, Crohn's disease and other autoimmune disorders, autism spectrum and other neurodevelopmental disorders, and schizophrenia. Since identifying structural variants is an important problem in genetics, several specialized computational techniques have been developed to detect structural variants directly from sequencing data. With advances in whole-genome sequencing (WGS) technologies, a plethora of SV detection methods have been developed. However, dissecting SVs from WGS data remains a challenge, with the majority of SV detection methods prone to a high false-positive rate, and no existing method able to precisely detect a full range of SVs present in a sample. Previous studies have shown that none of the existing SV callers can maintain high accuracy across various SV lengths and genomic coverages. Here, we report an integrated structural variant calling framework, Variant Identification and Structural Variant Analysis (VISTA), that leverages the results of individual callers using a novel and robust filtering and merging algorithm. In contrast to existing consensus-based tools which ignore the length and coverage, VISTA overcomes this limitation by executing various combinations of top-performing callers based on variant length and genomic coverage to generate SV events with high accuracy. We evaluated the performance of VISTA on comprehensive gold-standard datasets across varying organisms and coverage. We benchmarked VISTA using the Genome-in-a-Bottle gold standard SV set, haplotype-resolved de novo assemblies from the Human Pangenome Reference Consortium, along with an in-house polymerase chain reaction (PCR)-validated mouse gold standard set. VISTA maintained the highest F1 score among top consensus-based tools measured using a comprehensive gold standard across both mouse and human genomes. VISTA also has an optimized mode, where the calls can be optimized for precision or recall. VISTA-optimized can attain 100% precision and the highest sensitivity among other variant callers. In conclusion, VISTA represents a significant advancement in structural variant calling, offering a robust and accurate framework that outperforms existing consensus-based tools and sets a new standard for SV detection in genomic research. [ABSTRACT FROM AUTHOR]

Candida glabrata (also called Nakaseomyces glabratus) is an opportunistic pathogen that can resist common antifungals and rapidly acquire multidrug resistance. A large amount of genetic variation exists between isolates, which complicates generalizations. Portable transposon-sequencing (Tn-seq) methods can efficiently provide genome-wide information on strain differences and genetic mechanisms. Using the Hermes transposon, the CBS138 reference strain and a commonly studied derivative termed 2001 were subjected to Tn-seq in control conditions and after exposure to varying doses of the clinical antifungal micafungin. The approach revealed large differences between these strains, including a 131-kb tandem duplication and a variety of fitness differences. Additionally, both strains exhibited up to 1,000-fold increased transposon accessibility in subtelomeric regions relative to the BG2 strain, indicative of open subtelomeric chromatin in these isolates and large epigenetic variation within the species. Unexpectedly, the Pdr1 transcription factor conferred resistance to micafungin through targets other than CDR1. Other micafungin resistance pathways were also revealed including mannosyltransferase activity and biosynthesis of the lipid precursor sphingosine, the inhibition of which by SDZ 90–215 and myriocin enhanced the potency of micafungin in vitro. These findings provide insights into the complexity of the C. glabrata species as well as strategies for improving antifungal efficacy. [ABSTRACT FROM AUTHOR]

Reniform and root-knot nematode are two of the most destructive pests of conventional upland cotton, Gossypium hirsutum L. and continue to be a major threat to cotton fiber production in semiarid regions of the Southern United States and Central America. Fortunately, naturally occurring tolerance to these nematodes has been identified in the Pima cotton species (Gossypium barbadense) and several upland cotton varieties (G. hirsutum), which has led to a robust breeding program that has successfully introgressed and stacked these independent resistant traits into several upland cotton lineages with superior agronomic traits, e.g. BAR 32-30 and BARBREN-713. This work identifies the genomic variations of these nematode-tolerant accessions by comparing their respective genomes to the susceptible, high-quality fiber-producing parental line of this lineage: Phytogen 355 (PSC355). We discover several large genomic differences within marker regions that harbor putative resistance genes as well as expression mechanisms shared by the two resistant lines, with respect to the susceptible PSC355 parental line. This work emphasizes the utility of whole-genome comparisons as a means of elucidating large and small nuclear differences by lineage and phenotype. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. This study aimed to evaluate the impact of copy number variants (CNV) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole-genome sequence data from 126 animals, resulting in 870 high-confidence copy number variant regions (CNVR) on 12,131 animals. Out of these, 54 CNVR had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVR were significantly associated with at least one of the traits analyzed in this study. Specifically, 2 CNVR were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and nonreturn rate), and 2 CNVR were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVR harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVR on the mentioned traits are warranted. [ABSTRACT FROM AUTHOR]

Abstract Background Structural variations (SVs) are widespread across genome and have a great impact on evolution, disease, and phenotypic diversity. Despite the development of numerous bioinformatic tools, commonly referred to as SV callers, tailored for detecting SVs using whole genome sequence (WGS) data and employing diverse algorithms, their performance necessitates rigorous evaluation with real data and validated SVs. Moreover, a considerable proportion of these tools have been primarily designed and optimized using human genome data. Consequently, their applicability and performance in Avian species, characterized by smaller genomes and distinct genomic architectures, remain inadequately assessed. Results We performed a comprehensive assessment of the performance of ten widely used SV callers using population-level real genomic data with the validated five common types of SVs. The performance of SV callers varies with the types and sizes of SVs. As compared with other tools, GRIDSS, Lumpy, Wham, and Manta present better detection accuracy. Pindel can detect more small SVs than others. CNVnator and CNVkit can detect more medium and large copy number variations. Given the poor consistency among different SV callers, the combination calling strategy is not recommended. All tools show poor ability in the detection of insertions (especially with size > 150 bp). At least 50× read depth is required to detect more than 80% of the SVs for most tools. Conclusions This study highlights the importance and necessity of using real sequencing data, rather than simulated data only, with validated SVs for SV caller evaluation. Some practical guidance and suggestions are provided for SV detection in future researches.

Abstract While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.

Abstract In this work, we extend vcfdist to be the first variant call benchmarking tool to jointly evaluate phased single-nucleotide polymorphisms (SNPs), small insertions/deletions (INDELs), and structural variants (SVs) for the whole genome. First, we find that a joint evaluation of small and structural variants uniformly reduces measured errors for SNPs (− 28.9%), INDELs (− 19.3%), and SVs (− 52.4%) across three datasets. vcfdist also corrects a common flaw in phasing evaluations, reducing measured flip errors by over 50%. Lastly, we show that vcfdist is more accurate than previously published works and on par with the newest approaches while providing improved result interpretability.

Abstract The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC , uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets.

Abstract Background Differences of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. In more than 50% of human DSD cases, a molecular diagnosis is not available. In intensively farmed pig populations, the incidence of XX DSD pigs is relatively high, leading to economic losses for pig breeders. Interestingly, in the majority of 38, XX DSD pigs, gonads still develop into testis-like structures or ovotestes despite the absence of the testis-determining gene (SRY). However, the current understanding of the molecular background of XX DSD pigs remains limited. Methods Anatomical and histological characteristics of XX DSD pigs were analysed using necropsy and HE staining. We employed whole-genome sequencing (WGS) with 10× Genomics technology and used de novo assembly methodology to study normal female and XX DSD pigs. Finally, the identified variants were validated in 32 XX DSD pigs, and the expression levels of the candidate variants in the gonads of XX DSD pigs were further examined. Results XX DSD pigs are characterised by the intersex reproductive organs and the absence of germ cells in the seminiferous tubules of the gonads. We identified 4,950 single-nucleotide polymorphisms (SNPs) from non-synonymous mutations in XX DSD pigs. Cohort validation results highlighted two specific SNPs, “c.218T > C” in the “Interferon-induced transmembrane protein 1 gene (IFITM1)” and “c.1043C > G” in the “Newborn ovary homeobox gene (NOBOX)”, which were found exclusively in XX DSD pigs. Moreover, we verified 14 candidate structural variants (SVs) from 1,474 SVs, identifying a 70 bp deletion fragment in intron 5 of the WW domain-containing oxidoreductase gene (WWOX) in 62.5% of XX DSD pigs. The expression levels of these three candidate genes in the gonads of XX DSD pigs were significantly different from those of normal female pigs. Conclusion The nucleotide changes of IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment of the WWOX were the most dominant variants among XX DSD pigs. This study provides a theoretical basis for better understanding the molecular background of XX DSD pigs. Plain language summary DSD are conditions affecting development of the gonads or genitalia. These disorders can happen in many different types of animals, including pigs, goats, dogs, and people. In people, DSD happens in about 0.02–0.13% of births, and in pigs, the rate is between 0.08% and 0.75%. Pigs have a common type of DSD where the animal has female chromosomes (38, XX) but no SRY gene, which is usually found on the Y chromosome in males. XX DSD pigs may look like both males and females on the outside and have testis-like or ovotestis (a mix of ovary and testis) gonads inside. XX DSD pigs often lead to not being able to have piglets, slower growth, lower chance of survival, and poorer meat quality. Here, we used a method called whole-genome de novo sequencing to look for variants in the DNA of XX DSD pigs. We then checked these differences in a larger group of pigs. Our results reveal the nucleotide changes in IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment in intron 5 of the WWOX, all linked to XX DSD pigs. The expression levels of these three genes were also different in the gonads of XX DSD pigs compared to normal female pigs. These variants are expected to serve as valuable molecular markers for XX DSD pigs. Because pigs are a lot like humans in their genes, physiology, and body structure, this research could help us learn more about what causes DSD in people.

ABSTRACT: This study aimed to evaluate the impact of copy number variants (CNV) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole-genome sequence data from 126 animals, resulting in 870 high-confidence copy number variant regions (CNVR) on 12,131 animals. Out of these, 54 CNVR had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVR were significantly associated with at least one of the traits analyzed in this study. Specifically, 2 CNVR were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and nonreturn rate), and 2 CNVR were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVR harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVR on the mentioned traits are warranted.

Understanding somatic mutations and structural variations in domestic pigs (Sus scrofa domestica) is critical due to their increasing importance as model organisms in biomedical research. In this study, we conducted a comprehensive analysis through whole-genome sequencing of skin, organs, and blood samples. By examining two pig pedigrees, we investigated the inheritance and sharedness of structural variants among fathers, mothers, and offsprings. Utilizing single-cell clonal expansion techniques, we observed significant variations in the number of somatic mutations across different tissues. An in-house developed pipeline enabled precise filtering and analysis of these mutations, resulting in the construction of individual phylogenetic trees for two pigs. These trees explored the developmental relationships between different tissues, revealing insights into clonal expansions from various anatomical locations. This study enhances the understanding of pig genomes, affirming their increasing value in clinical and genomic research, and provides a foundation for future studies in other animals, paralleling previous studies in mice and humans. This approach not only deepens our understanding of mammalian genomic variations but also strengthens the role of pigs as a crucial model in human health and disease research. [ABSTRACT FROM AUTHOR]

Despite advances in next generation sequencing (NGS), genetic diagnoses remain elusive for many patients with neurologic syndromes. Long‐read sequencing (LRS) and optical genome mapping (OGM) technologies improve upon existing capabilities in the detection and interpretation of structural variation in repetitive DNA, on a single haplotype, while also providing enhanced breakpoint resolution. We performed LRS and OGM on two patients with known chromosomal rearrangements and inconclusive Sanger or NGS. The first patient, who had epilepsy and developmental delay, had a complex translocation between two chromosomes that included insertion and inversion events. The second patient, who had a movement disorder, had an inversion on a single chromosome disrupted by multiple smaller inversions and insertions. Sequence level resolution of the rearrangements identified pathogenic breaks in noncoding sequence in or near known disease‐causing genes with relevant neurologic phenotypes (MBD5, NKX2‐1). These specific variants have not been reported previously, but expected molecular consequences are consistent with previously reported cases. As the use of LRS and OGM technologies for clinical testing increases and data analyses become more standardized, these methods along with multiomic data to validate noncoding variation effects will improve diagnostic yield and increase the proportion of probands with detectable pathogenic variants for known genes implicated in neurogenetic disease. [ABSTRACT FROM AUTHOR]

Abstract Background Structural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown. Results We used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models. Conclusions Our study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection.

Abstract 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.

Abstract 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 .

MYB transcription factors have been linked to anthocyanin synthesis and various color phenotypes in plants. In apple, MYB10 confers a red‐flesh phenotype due to a minisatellite insertion in its R6 promoter, but R6:MYB10 genotypes exhibit various degrees of red pigmentation in the flesh, suggesting the involvement of other genetic factors. Here, it is shown that MdWRKY10, a transcription factor identified via DNA pull‐down trapping, binds to the promoter of MdMYB10 and activates its transcription. MdWRKY10 specifically interacts with the WDR protein MdTTG1 to join the apple MYB‐bHLH‐WDR (MBW) complex, which significantly enhances its transcriptional activation activity. A 163‐bp InDel detected in the promoter region of the alleles of MdWRKY10 in a hybrid population of identical heterozygous genotypes regarding R6 by structural variation analysis, contains a typical W‐box element that MdWRKY10 binds to for transactivation. This leads to increased transcript levels of MdWRKY10 and MdMYB10 and enhanced anthocyanin synthesis in the flesh, largely accounting for the various degrees of flesh red pigmentation in the R6 background. These findings reveal a novel regulatory role of the WRKY‐containing protein complex in the formation of red flesh apple phenotypes and provide broader insights into the molecular mechanism governing anthocyanin synthesis in plants. [ABSTRACT FROM AUTHOR]

The future survival of coral reefs in the Anthropocene depends on the capacity of corals to adapt as oceans warm and extreme weather events become more frequent. Targeted interventions designed to assist evolutionary processes in corals require a comprehensive understanding of the distribution and structure of standing variation, however, efforts to map genomic variation in corals have so far focussed almost exclusively on SNPs, overlooking structural variants that have been shown to drive adaptive processes in other taxa. Here, we show that the reef‐building coral, Acropora kenti, harbours at least five large, highly polymorphic structural variants, all of which exhibit signatures of strongly suppressed recombination in heterokaryotypes, a feature commonly associated with chromosomal inversions. Based on their high minor allele frequency, uniform distribution across habitats and elevated genetic load, we propose that these inversions in A. kenti are likely to be under balancing selection. An excess of SNPs with high impact on protein‐coding genes within these loci elevates their importance both as potential targets for adaptive selection and as contributors to genetic decline if coral populations become fragmented or inbred in future. [ABSTRACT FROM AUTHOR]

Simple Summary: Our previous investigation identified a 67-bp variable duplication in the ADIPOQ promoter region, which may impact cow ovarian development. Our researchers looked into the relationship between ADIPOQ promoter variants and ovarian traits and mRNA expression in Chinese Holstein cows in order to gain a better understanding of how to maximize the milk production of these cows while preserving their reproductive efficiency. Three genotypes were found in 2219 samples, and there was a strong correlation between this mutation and ovarian traits. Moreover, the mutant phenotype dramatically decreased the expression of the ADIPOQ gene mRNA in ovarian tissue. To increase dairy cow fertility, it is crucial to identify the genes that govern ovarian features, given the significance of the ovarian in the female reproductive system. In order to enhance the reproductive quality of Chinese Holstein dairy cows, this study offers a theoretical framework and molecular breeding signals. ADIPOQ plays a crucial role in regulating the reproductive system, but there are few reports on the effects of ADIPOQ on ovarian in dairy cows. Previous studies have verified the presence of a 67-bp mutation in the promoter region of the ADIPOQ gene. Hence, we employed ovarian tissues (n = 2111) and blood samples (n = 108) from Chinese Holstein cows as experimental samples to examine the association between ADIPOQ promoter variants and ovarian traits. We extracted DNA from these samples and conducted genetic typing identification on each sample using advanced techniques like PCR and agarose gel electrophoresis. Consequently, the DD, ID, and II genotypes were discovered. and it has been observed that the mutation frequency of this locus is low in the Chinese Holstein cow. Importantly, the correlational analysis unveiled a significant relationship (p < 0.05) between the weight of ovaries in late estrus and the width of ovaries during the estrus interval with the mutation. Result of the RT-PCR revealed that the ID genotype partially diminished the expression of the ADIPOQ gene. The results of this study suggest that the identified variable duplication could serve as a potential genetic marker for enhancing the ovarian traits of Chinese Holstein cows. [ABSTRACT FROM AUTHOR]

Background: Tuberous sclerosis is a multi-system disorder caused by mutations in either TSC1 or TSC2. The majority of affected patients (85%--90%) have heterozygous variants, and a smaller number (around 5%) have mosaic variants. Despite using various techniques, some patients still have "no mutation identified" (NMI). Methods: We hypothesized that the causal variants of patients with NMI may be structural variants or deep intronic variants. To investigate this, we sequenced the DNA of 26 tuberous sclerosis patients with NMI using targeted long-read sequencing. Results: We identified likely pathogenic/pathogenic variants in 13 of the cases, of which 6 were large deletions, four were InDels, two were deep intronic variants, one had retrotransposon insertion in either TSC1 or TSC2, and one was complex rearrangement. Furthermore, there was a de novo Alu element insertion with a high suspicion of pathogenicity that was classified as a variant of unknown significance. Conclusion: Our findings expand the current knowledge of known pathogenic variants related to tuberous sclerosis, particularly uncovering mosaic complex structural variations and retrotransposon insertions that have not been previously reported in tuberous sclerosis. Our findings suggest a higher prevalence of mosaicism among tuberous sclerosis patients than previously recognized. Our results indicate that long-read sequencing is a valuable approach for tuberous sclerosis cases with no mutation identified (NMI). [ABSTRACT FROM AUTHOR]

Background: Structural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown. Results: We used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models. Conclusions: Our study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection. [ABSTRACT FROM AUTHOR]

Many previously unsuspected single-nucleotide polymorphisms (SNPs) can cause phenotypic variation by affecting transcript splicing and protein translation. Small RNAs are more challenging to study than protein-coding genes but are important contributors to phenotypic evolution. Structural variation (e.g., transposable element insertion, gene copy number variation, chromosomal inversion) is an extremely common source of phenotypic divergence. The sequence composition of supergenes that control complex multi-trait polymorphisms has been elucidated at an unprecedented pace by long-read sequencing. Taxon-specific genes, including non-coding RNAs, can have a profound impact on lineage-specific phenotypic diversification and adaptation. It has been well documented that mutations in coding DNA or cis -regulatory elements underlie natural phenotypic variation in many organisms. However, the development of sophisticated functional tools in recent years in a wide range of traditionally non-model systems have revealed many 'unusual suspects' in the molecular bases of phenotypic evolution, including upstream open reading frames (uORFs), cryptic splice sites, and small RNAs. Furthermore, large-scale genome sequencing, especially long-read sequencing, has identified a cornucopia of structural variation underlying phenotypic divergence and elucidated the composition of supergenes that control complex multi-trait polymorphisms. In this review article we highlight recent studies that demonstrate this great diversity of molecular mechanisms producing adaptive genetic variation and the panoply of evolutionary paths leading to the 'grandeur of life'. [ABSTRACT FROM AUTHOR]

The plant Arabidopsis thaliana is a model system used by researchers through much of plant research. Recent efforts have focused on discovering the genomic variation found in naturally occurring ecotypes isolated from around the world. These ecotypes have come from diverse climates and therefore have faced and adapted to a variety of abiotic and biotic stressors. The sequencing and comparative analysis of these genomes can offer insight into the adaptive strategies of plants. While there are a large number of ecotype genome sequences available, the majority were created using short-read technology. Mapping of short-reads containing structural variation to a reference genome bereft of that variation leads to incorrect mapping of those reads, resulting in a loss of genetic information and introduction of false heterozygosity. For this reason, long-read de novo sequencing of genomes is required to resolve structural variation events. In this article, we sequenced the genomes of eight natural variants of A. thaliana using nanopore sequencing. This resulted in highly contiguous assemblies with >95% of the genome contained within five contigs. The sequencing results from this study include five ecotypes from relict and African populations, an area of untapped genetic diversity. With this study, we increase the knowledge of diversity we have across A. thaliana ecotypes and contribute to ongoing production of an A. thaliana pan-genome. [ABSTRACT FROM AUTHOR]

Advancements in genome sequencing and assembly techniques have increased the documentation of structural variants in wild organisms. Of these variants, chromosomal inversions are especially prominent due to their large size and active recombination suppression between alternative homokaryotypes. This suppression enables the 2 forms of the inversion to be maintained and allows the preservation of locally adapted alleles. The Barramundi Perch (BP; Lates calcarifer) is a widespread species complex with 3 main genetic lineages located in the biogeographic regions of Australia and New Guinea (AUS + NG), Southeast Asia (SEA), and the Indian Subcontinent (IND). BP are typically considered to be a protandrous sequential hermaphrodite species that exhibits catadromy. Freshwater occupancy and intraspecific variation in life history (e.g. partially migratory populations) exist and provide opportunities for strongly divergent selection associated with, for example, salinity tolerance, swimming ability, and marine dispersal. Herein, we utilize genomic data generated from all 3 genetic lineages to identify and describe 3 polymorphic candidate chromosomal inversions. These candidate chromosomal inversions appear to be fixed for ancestral variants in the IND lineage and for inverted versions in the AUS + NG lineage and exhibit variation in all 3 inversions in the SEA lineage. BP have a diverse portfolio of life history options that includes migratory strategy as well as sexual system (i.e. hermaphroditism and gonochorism). We propose that the some of the life history variabilities observed in BP may be linked to inversions and, in doing so, we present genetic data that might be useful in enhancing aquaculture production and population management. [ABSTRACT FROM AUTHOR]

Autistic spectrum disorder (ASD) is a neurodevelopmental disability characterised by the impairment of social interaction and communication ability. The alarming increase in its prevalence in children urged researchers to obtain a better understanding of the causes of this disease. Genetic factors are considered to be crucial, as ASD has a tendency to run in families. In recent years, with technological advances, the importance of structural variations (SVs) in ASD began to emerge. Most of these studies, however, focus on the Caucasian population. As a populated ethnicity, ASD shall be a significant health issue in China. This systematic review aims to summarise current case-control studies of SVs associated with ASD in the Chinese population. A list of genes identified in the nine included studies is provided. It also reveals that similar research focusing on other genetic backgrounds is demanded to manifest the disease etiology in different ethnic groups, and assist the development of accurate ethnic-oriented genetic diagnosis. [ABSTRACT FROM AUTHOR]

Human cytomegalovirus has a linear DNA genome with a total length of approximately 235 kb. This large genome is divided into two domains, "Long" and "Short". There are four isomers of the cytomegalovirus genome with different orientations of each domain. To confirm the presence of four types of isomers, it is necessary to identify the sequence of the junction between the domains. However, due to the presence of repeat sequences, it is difficult to determine the junction sequences by next-generation sequencing analysis. To solve this problem, long-read sequencing was performed using the Oxford Nanopore sequencer and the junctions were successfully identified in four isomers in strain Merin and ATCC-2011-3. Nanopore sequencing also revealed the presence of multiple copies of the "a" sequence (a-seq) in the junctions, indicating the diversity of the junction sequences. These results strongly suggest that long-read sequencing using the nanopore sequencer would be beneficial for identifying the complex structure of the cytomegalovirus genome. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Multiple studies in a range of taxa have found links between structural variants and the development of ecologically important traits. Such variants are becoming easier to find due, in large part, to the increase in the amount of genome-wide sequence data in nonmodel organisms. The salmonids (salmon, trout, and charr) are a taxonomic group with abundant genome-wide datasets due to their importance in aquaculture, fisheries, and variation in multiple ecologically important life-history traits. Previous research on rainbow trout (Oncorhynchus mykiss) has documented a large pericentric (∼55 Mb) chromosomal inversion (CI) on chromosome 5 (Omy05) and a second smaller (∼14 Mb) chromosome inversion on Omy20. While the Omy05 inversion appears to be associated with multiple adaptive traits, the inversion on Omy20 has received far less attention. In this study, we re-analyze RAD-seq and amplicon data from several populations of rainbow trout (O. mykiss) to better document the structure and geographic distribution of variation in the Omy20 CI. Moreover, we utilize phylogenomic techniques to characterize both the age- and the protein-coding gene content of the Omy20 CI. We find that the age of the Omy20 inversion dates to the early stages of O. mykiss speciation and predates the Omy05 inversion by ∼450,000 years. The 2 CIs differ further in terms of the frequency of the homokaryotypes. While both forms of the Omy05 CI are found across the eastern Pacific, the ancestral version of the Omy20 CI is restricted to the southern portion of the species range in California. Furthermore, the Omy20 inverted haplotype is comparable in genetic diversity to the ancestral form, whereas derived CIs typically show substantially reduced genetic diversity. These data contribute to our understanding of the age and distribution of a large CI in rainbow trout and provide a framework for researchers looking to document CIs in other nonmodel species. [ABSTRACT FROM AUTHOR]

The bacterium Deinococcus radiodurans is known to efficiently and accurately reassemble its genome after hundreds of DNA double-strand breaks (DSBs). Only at very large amounts of radiation-induced DSBs is this accuracy affected in the wild-type D. radiodurans, causing rearrangements in its genome structure. However, changes in its genome structure may also be possible during the propagation and storage of cell cultures. We investigate this possibility by listing structural differences between three completely sequenced genomes of D. radiodurans strains with a recent common ancestor—the type strain stored and sequenced in two different laboratories (of the ATCC 13939 lineage) and the first sequenced strain historically used as the reference (ATCC BAA-816). We detected a number of structural differences and found the most likely mechanisms behind them: (i) transposition/copy number change in mobile interspersed repeats—insertion sequences and small non-coding repeats, (ii) variable number of monomers within tandem repeats, (iii) deletions between long direct DNA repeats, and (iv) deletions between short (4–10 bp) direct DNA repeats. The most surprising finding was the deletions between short repeats because it indicates the utilization of a less accurate DSB repair mechanism in conditions in which a more accurate one should be both available and preferred. The detected structural differences, as well as SNPs and short indels, while being important footprints of deinococcal DNA metabolism and repair, are also a valuable resource for researchers using these D. radiodurans strains. [ABSTRACT FROM AUTHOR]

Genome sequencing data have become increasingly important in the field of personalized medicine and diagnosis. However, accurately detecting genomic variations remains a challenging task. Traditional variation detection methods rely on manual inspection or predefined rules, which can be time-consuming and prone to errors. Consequently, deep learning–based approaches for variation detection have gained attention due to their ability to automatically learn genomic features that distinguish between variants. In our review, we discuss the recent advancements in deep learning–based algorithms for detecting small variations and structural variations in genomic data, as well as their advantages and limitations. [ABSTRACT FROM AUTHOR]

Advances in technology have led to a large increase in the number of plant organellar sequences, but sampling remains uneven. Most land-plant mitogenomes are difficult to assemble accurately due to alternative structural configurations and interference from transferred sequences. Pan-organellar genomes have provided new evolutionary insights and have provided targets for editing to study changes in gene function during lineage divergence. Organellar genome editing – such as mitochondrially targeted transcription activator-like effector nucleases (TALENs) and double-stranded DNA-specific cytidine deaminase (DddA)-derived cytosine base editors – enables the functional verification of open reading frames (ORFs) and non-coding regions. Plastid transformation has been used in an array of modifications – such as to improve photosynthetic efficiency, and the biosynthesis of vaccines – while mitochondrial transformation lags far behind due to technical challenges. Plastids and mitochondria are the only organelles that possess genomes of endosymbiotic origin. In recent decades, advances in sequencing technologies have contributed to a meteoric rise in the number of published organellar genomes, and have revealed greatly divergent evolutionary trajectories. In this review, we quantify the abundance and distribution of sequenced plant organellar genomes across the plant tree of life. We compare numerous genomic features between the two organellar genomes, with an emphasis on evolutionary trajectories, transfers, the current state of organellar genome editing by transcriptional activator-like effector nucleases (TALENs), transcription activator-like effector (TALE)-mediated deaminase, and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas), as well as genetic transformation. Finally, we propose future research to understand these different evolutionary trajectories, and genome-editing strategies to promote functional studies and eventually improve organellar genomes. [ABSTRACT FROM AUTHOR]

Luffa spp. is an important worldwide cultivated vegetable and medicinal plant from the Cucurbitaceae family. In this study, we report a high-quality chromosome-level genome of the high-generation inbred line SG261 of Luffa acutangula. The genomic sequence was determined by PacBio long reads, Hi-C sequencing reads, and 10× Genomics sequencing, with an assembly size of 739.82 Mb, contig N50 of 18.38 Mb, and scaffold N50 of 56.08 Mb. The genome of L. acutangula SG261 was predicted to contain 27,312 protein-coding genes and 72.56% repetitive sequences, of which long terminal repeats (LTRs) were an important form of repetitive sequences, accounting for 67.84% of the genome. Phylogenetic analysis reveals that L. acutangula evolved later than Luffa cylindrica, and Luffa is closely related to Momodica charantia. Comparing the genome of L. acutangula SG261 and L. cylindrica with PacBio data, 67,128 high-quality structural variations (SVs) and 55,978 presence-absence variations (PAVs) were identified in SG261, resulting in 2424 and 1094 genes with variation in the CDS region, respectively, and there are 287 identical genes affected by two different structural variation analyses. In addition, we found that the transcription factor FY (FLOWERING LOCUS Y) families had a large expansion in L. acutangula SG261 (flowering in the morning) compared to L. cylindrica (flowering in the afternoon), which may result in the early flowering time in L. acutangula SG261. This study provides valuable reference for the breeding of and pan-genome research into Luffa species. [ABSTRACT FROM AUTHOR]

Structural rearrangements, such as inversions, translocations, duplications, and large insertions and deletions, are large-scale genomic variants that can play an important role in shaping phenotypic variation and in genome adaptation and evolution. We used chromosomal-level assemblies from eight Fusarium graminearum isolates to study structural variants and their role in fungal evolution. We generated the assemblies of four of these genomes after Oxford Nanopore sequencing. A total of 87 inversions, 159 translocations, 245 duplications, 58,489 insertions, and 34,102 deletions were detected. Regions of high recombination rate are associated with structural rearrangements, and a significant proportion of inversions, translocations, and duplications overlap with the repeat content of the genome, suggesting recombination and repeat elements are major factors in the origin of structural rearrangements in F. graminearum. Large insertions and deletions introduce presence–absence polymorphisms for many genes, including secondary metabolite biosynthesis cluster genes and predicted effectors genes. Translocation events were found to be shuffling predicted effector-rich regions of the genomes and are likely contributing to the gain and loss of effectors facilitated by recombination. Breakpoints of some structural rearrangements fall within coding sequences and are likely altering the protein products. Structural rearrangements in F. graminearum thus have an important role to play in shaping pathogen–host interactions and broader evolution through genome reorganization, the introduction of presence–absence polymorphisms, and changing protein products and gene regulation. [ABSTRACT FROM AUTHOR]

Structural variants (SVs) pose a challenge to detect and interpret, but their study provides novel biological insights and molecular diagnosis underlying rare diseases. The aim of this study was to resolve a 9p24 rearrangement segregating in a family through five generations with a congenital heart defect (congenital pulmonary and aortic valvular stenosis and pulmonary artery stenosis), by applying a combined genomic analysis. The analysis involved multiple techniques, including karyotype, chromosomal microarray analysis (CMA), FISH, genome sequencing (GS), RNA-seq, and optical genome mapping (OGM). A complex 9p24 SV was hinted at by CMA results, showing three interspersed duplicated segments. Combined GS and OGM analyses revealed that the 9p24 duplications constitute a complex SV, on which a set of breakpoints matches the boundaries of the CMA duplicated sequences. The proposed structure for this complex rearrangement implies three duplications associated with an inversion of ~ 2 Mb region on chromosome 9 and a SINE element insertion at the more distal breakpoint. Interestingly, this genomic structure of rearrangement forms a chimeric transcript of the KANK1/DMRT1 loci, which was confirmed by both RNA-seq and Sanger sequencing on blood samples from 9p24 rearrangement carriers. Altogether with breakpoint amplification and FISH analysis, this combined approach allowed a deep characterization of this complex rearrangement. Although the genotype–phenotype correlation remains elusive from the molecular mechanism point of view, this study identified a large genomic rearrangement at 9p24 segregating with a familial congenital heart defect, revealing a genetic biomarker that was successfully applied for embryo selection, changing the reproductive perspective of affected individuals. [ABSTRACT FROM AUTHOR]

Parasitic lifestyle can often relax the constraint on the plastome, leading to gene pseudogenization and loss, and resulting in diverse genomic structures and rampant genome degradation. Although several plastomes of parasitic Cuscuta have been reported, the evolution of parasitism in the family Convolvulaceae which is linked to structural variations and reduction of plastome has not been well investigated. In this study, we assembled and collected 40 plastid genomes belonging to 23 species representing four subgenera of Cuscuta and ten species of autotrophic Convolvulaceae. Our findings revealed nine types of structural variations and six types of inverted repeat (IR) boundary variations in the plastome of Convolvulaceae spp. These structural variations were associated with the shift of parasitic lifestyle, and IR boundary shift, as well as the abundance of long repeats. Overall, the degradation of Cuscuta plastome proceeded gradually, with one clade exhibiting an accelerated degradation rate. We observed five stages of gene loss in Cuscuta, including NAD(P)H complex → PEP complex → Photosynthesis-related → Ribosomal protein subunits → ATP synthase complex. Based on our results, we speculated that the shift of parasitic lifestyle in early divergent time promoted relaxed selection on plastomes, leading to the accumulation of microvariations, which ultimately resulted in the plastome reduction. This study provides new evidence towards a better understanding of plastomic evolution, variation, and reduction in the genus Cuscuta.Key message: The gain of parasitism in Cuscuta does trigger structural variations of the plastome, and it may initiate the relaxed selection in plastid genes, which leads to accumulation of microvariations, subsequent plastome reduction and gene loss. [ABSTRACT FROM AUTHOR]

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

BackgroundIn the context of rapid economic and social development, there has been a continuous intensification of population aging, transformation of disease patterns, and wide application of new medical technologies. As a result, health expenditures in various countries have sharply soared. How to utilize limited medical resources to maximize the improvement of health levels has become a hot and challenging issue related to the well-being of all humanity. The relevant indicators of total health expenditure play a crucial role in monitoring and evaluating the fairness of health financing and health security in the region.ObjectiveThis study explores the changes in the main expenses that constitute China’s total health expenditure and uses indicators related to health expenditure to observe the changes and future development trends of China’s health expenditure. Based on this, the utilization of China’s health expenditure is monitored to identify possible problems, and thereby targeted suggestions for promoting the development of China’s health and wellness cause are put forward.MethodsBased on the comparison of previous literature, this paper analyzes the changes and future development trends in China’s health expenditure by using the relevant indicators of China’s health expenditure through the structural variation analysis method and the gray prediction model.ResultsThe results show that the scale of government, social, and out-of-pocket health expenditures has continuously expanded, with social health expenditures becoming the main funding source for total health expenditures. The burden of medical expenditures on individuals has been further reduced. In the institutional method of total health expenditures, hospital expenditures account for about 60% of the total and are the main component. The expenditures of health administration and medical insurance management institutions are the main driving force behind the growth of total health expenditures. However, the proportion of health expenditures in China’s GDP is relatively low, so more investment is needed in the healthcare sector, and the burden of individual medical expenses also needs to be continuously reduced.DiscussionIn the future, China should further increase its investment in the medical and health sector. Specifically, the government should persist in investing in fundamental medical and health services. Simultaneously, efforts should be made to establish a scientific cost control mechanism for pharmaceuticals and broaden financing channels for healthcare, such as accelerating the development of commercial health insurance.