Jointly benchmarking small and structural variant calls with vcfdist.

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.

Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders.

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.

Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences.

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.

Pan-genome analyses of eleven Fraxinus species provide insights into salt adaptation in ash trees.

Ash trees (Fraxinus) exhibit rich genetic diversity and wide adaptation to various ecological environments, several of which are highly salt-tolerant. Dissecting the genomic basis underlying ash tree salt adaptation is vital for its resistance breeding. Here, we presented eleven high-quality chromosome-level genome assemblies for Fraxinus species, revealing two unequal sub-genome compositions and two more recent whole-genome triplication events in evolutionary history. A Fraxinus structural variation-based pan-genome was constructed and revealed that presence-absence variations (PAVs) of transmembrane transport genes likely contribute to Fraxinus salt adaptation. Through whole-genome resequencing of an inter-species cross F1-population of F. velutina 'Lula 3' (salt-tolerant) × F. pennsylvanica 'Lula 5' (salt-sensitive), we performed a salt tolerance PAV-based quantitative trait loci (QTL) mapping and pinpointed two PAV-QTLs and candidate genes associated with Fraxinus salt tolerance. Mechanismly, FvbHLH85 enhanced salt tolerance by mediating reactive oxygen species and Na+/K+ homeostasis, while FvSWEET5 by mediating osmotic homeostasis. Collectively, these findings provide valuable genomic resources for Fraxinus salt resistance breeding and research community.

Structural genomic variation and behavioral interactions underpin a balanced sexual mimicry polymorphism.

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.

Prediction of the 3D cancer genome from whole-genome sequencing using InfoHiC.

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.

Comparative and phylogenetic analyses of plastid genomes of the medicinally important genus Alisma (Alismataceae).

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.

In-Silico Method for Predicting Pathogenic Missense Variants Using Online Tools: AURKA Gene as a Model.

Background: In-silico analysis provides a fast, simple, and cost-free method for identifying potentially pathogenic single nucleotide variants. Objective: To propose a simple and relatively fast method for the prediction of variant pathogenicity using free online in-silico (IS) tools with AURKA gene as a model. Materials and Methods: We aim to propose a methodology to predict variants with high pathogenic potential using computational analysis, using AURKA gene as model. We predicted a protein model and analyzed 209 out of 64,369 AURKA variants obtained from Ensembl database. We used bioinformatic tools to predict pathogenicity. The results were compared through the VarSome website, which includes its own pathogenicity score and the American College of Medical Genetics (ACMG) classification. Results: Out of the 209 analyzed variants, 16 were considered pathogenic, and 13 were located in the catalytic domain. The most frequent protein changes were size and hydrophobicity modifications of amino acids. Proline and Glycine amino acid substitutions were the most frequent changes predicted as pathogenic. These bioinformatic tools predicted functional changes, such as protein up or down-regulation, gain or loss of molecule interactions, and structural protein modifications. When compared to the ACMG classification, 10 out of 16 variants were considered likely pathogenic, with 7 out of 10 changes at Proline/Glycine substitutions. Conclusion: This method allows quick and cost-free bulk variant screening to identify variants with pathogenic potential for further association and/or functional studies.

Structural variation discovery in wheat using PacBio high-fidelity sequencing.

Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.

Whole-genome de novo sequencing reveals genomic variants associated with differences of sex development in SRY negative pigs.

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. 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.

Comparative analysis of 12 water lily plastid genomes reveals genomic divergence and evolutionary relationships in early flowering plants.

The aquatic plant Nymphaea, a model genus of the early flowering plant lineage Nymphaeales and family Nymphaeaceae, has been extensively studied. However, the availability of chloroplast genome data for this genus is incomplete, and phylogenetic relationships within the order Nymphaeales remain controversial. In this study, 12 chloroplast genomes of Nymphaea were assembled and analyzed for the first time. These genomes were 158,290-160,042 bp in size and contained 113 non-repeat genes, including 79 protein-coding genes, 30 tRNA genes, and four rRNA genes. We also report on codon usage, RNA editing sites, microsatellite structures, and new repetitive sequences in this genus. Comparative genomics revealed that expansion and contraction of IR regions can lead to changes in the gene numbers. Additionally, it was observed that the highly variable regions of the chloroplast genome were mainly located in intergenic regions. Furthermore, the phylogenetic tree showed the order Nymphaeales was divided into three families, and the genus Nymphaea can be divided into five (or three) subgenera, with the subgenus Nymphaea being the oldest. The divergence times of nymphaealean taxa were analyzed, with origins of the order Nymphaeales and family Nymphaeaceae being about 194 and 131 million years, respectively. The results of the phylogenetic analysis and estimated divergence times will be useful for future evolutionary studies of basal angiosperm lineages. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-024-00242-0.

VISTA: an integrated framework for structural variant discovery.

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.

Impacts of parental genomic divergence in non-syntenic regions on cotton heterosis.

INTRODUCTION: Heterosis has revolutionized crop breeding, enhancing global agricultural production. However, the mechanisms underlying heterosis remain obscure. Xiangzamian 2# (XZM2), a super hybrid upland cotton (Gossypium hirsutum L.) characterized by high-yield heterosis, has been developed and extensively planted in China. OBJECTIVES: We conducted a systematic analysis of CRI12 and J8891, two parents of XZM2. We aimed to reveal the precise genetic information and the role of non-syntenic divergence in shaping heterosis, laying a foundation for advancing understanding of heterosis. METHODS: We de novo assembled high-quality genomes of CRI12 and J8891, and further uncovered abundant genetic variations and non-syntenic regions between the parents. Whole-genome comparison, association analysis, transcriptomic analysis and relative identity-by-descent (rIBD) estimation were conducted to identify structural variations (SVs) and introgressions within non-syntenic blocks and to analyze their impacts on promoting heterosis. RESULTS: Parental genetic divergence increased in non-syntenic regions. Furthermore, these regions, accounting for only 16.71% of the total genome, contained more loci with significantly higher heterotic effects, far exceeding the syntenic background. SVs covered 97.26% of non-syntenic sequences and caused widespread gene expression differences in these regions, driving dynamic complementation of gene expression in the hybrid. A set of SVs were responsible for trait improvement and had positive effects on heterosis, contributing larger heritability than short variations. We characterized numerous parental-specific introgressions from G. barbadense. Specifically, a functional introgression segment within non-syntenic blocks introduced an elite haplotype, which significantly increased lint yield and enhanced heterosis. CONCLUSION: Our study clarified non-syntenic regions to harbor more loci with higher heterotic effects, revealed their importance in promoting heterosis and supported the crucial role of genetic complementation in heterosis. SVs and introgressions were identified as key factors responsible for non-syntenic divergence between the parents. They had important effects on gene expression and trait improvement, positively contributing to heterosis.

[Juvenile Pompe disease: Undescribed genotype. First report in Quintana Roo]. / Enfermedad de Pompe juvenil: genotipo no descrito. Primer reporte en Quintana Roo.

Background: Pompe disease (PD) is a rare autosomal recessive genetic disorder (1 in 14,000) which affects the synthesis of acid alpha-glucosidase (AGA), leading to intralysosomal glycogen accumulation in muscle tissue. The clinical presentation is heterogeneous, with variable degrees of involvement and progression, classifiable based on the age of onset into infantile (classic or non-classic) and late-onset forms (juvenile or adult). The diagnostic test of choice is the enzymatic analysis of AGA, and the only pharmacological treatment is enzyme replacement therapy (ERT). This document aims to report a clinical case of late-onset PD. Clinical case: 14-year-old male who started at the age of 5 with postural alterations, gait changes, and decreased physical performance compared to his peers. A diagnostic evaluation was initiated in 2022 due to worsening neuromuscular symptoms, accompanied by dyspnea, tachycardia, and chest pain. A suspicion of a lysosomal storage myopathy was established, and through enzymatic determination of AGA the diagnosis of PD was confirmed. The study of the GAA gene revealed the association of 2 previously unreported genomic variants. ERT was initiated, resulting in clinical improvement. Conclusions: The age of symptom onset, severity of clinical presentation, and prognosis of the disease depend on the specific mutations involved. In this case, the identified genetic alterations are associated with different phenotypes. However, based on the clinical presentation, it is categorized as juvenile PD with an indeterminate prognosis.

Introducción: la enfermedad de Pompe (EP) es un padecimiento genético autosómico recesivo poco frecuente (1:14,000) que afecta la síntesis de alfa-glucosidasa ácida (AGA) y condiciona un depósito de glucógeno intralisosomal en tejido muscular. La presentación clínica es heterogénea, con grados variables de afectación y progresión, clasificable según la edad de aparición en infantil (clásica y no clásica) y de inicio tardío (juvenil o de adultez). La prueba diagnóstica de elección es el análisis enzimático de AGA y el único tratamiento farmacológico es la terapia de reemplazo enzimático (TRE). Este documento tiene como objetivo reportar un caso clínico de EP de inicio tardío. Caso clínico: paciente de sexo masculino de 14 años que comenzó a los 5 años con alteraciones de la postura, marcha y desempeño físico. Se inició protocolo de estudio ante agravamiento de los síntomas neuromusculares, a los que se agregaron disnea, taquicardia y dolor torácico. Se sospechó de una miopatía metabólica de depósito lisosomal y mediante determinación enzimática de AGA se confirmó el diagnóstico de EP. El estudio molecular del gen GAA reportó una asociación de 2 variantes genómicas no descritas previamente. Se empleó la TRE con mejoría clínica. Conclusiones: la edad de inicio del cuadro clínico, severidad y pronóstico dependen de las mutaciones presentadas. En este caso, las alteraciones genéticas encontradas están relacionadas con diferentes fenotipos; no obstante, por clínica es categorizado como una EP juvenil con pronóstico indeterminado.

Pan-genome analysis of 13 Spinacia accessions reveals structural variations associated with sex chromosome evolution and domestication traits in spinach.

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.

Chromosome-Scale Assembly and Annotation of Eight Arabidopsis thaliana Ecotypes.

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.

Genome-wide characterization of structure variations in the Xiang pig for genetic resistance to African swine fever.

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

Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants.

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.

A Functional 67-bp Duplication Locating at the Core Promoter Region within the Bovine ADIPOQ Gene Is Associated with Ovarian Traits and mRNA Expression.

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.

Uncovering hidden genetic variations: long-read sequencing reveals new insights into tuberous sclerosis complex.

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).