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BackgroundProgressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).MethodIn this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.ResultsOur analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73 × 10-3) in PSP.ConclusionsThrough WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Background: Certain structural variants (SVs) including large-scale genetic copy number variants, as well as copy number-neutral inversions and translocations may not all be resolved by chromosome karyotype studies. The identification of genetic risk factors for Parkinson's disease (PD) has been primarily focused on the gene-disruptive single nucleotide variants. In contrast, larger SVs, which may significantly influence human phenotypes, have been largely underexplored. Optical genomic mapping (OGM) represents a novel approach that offers greater sensitivity and resolution for detecting SVs. In this study, we used induced pluripotent stem cell (iPSC) lines of patients with PD-linked SNCA and PRKN variants as a proof of concept to (i) show the detection of pathogenic SVs in PD with OGM and (ii) provide a comprehensive screening of genetic abnormalities in iPSCs. Results: OGM detected SNCA gene triplication and duplication in patient-derived iPSC lines, which were not identified by long-read sequencing. Additionally, various exon deletions were confirmed by OGM in the PRKN gene of iPSCs, of which exon 3–5 and exon 2 deletions were unable to phase with conventional multiplex-ligation-dependent probe amplification. In terms of chromosomal abnormalities in iPSCs, no gene fusions, no aneuploidy but two balanced inter-chromosomal translocations were detected in one line that were absent in the parental fibroblasts and not identified by routine single nucleotide variant karyotyping. Conclusions: In summary, OGM can detect pathogenic SVs in PD-linked genes as well as reveal genomic abnormalities for iPSCs that were not identified by other techniques, which is supportive for OGM's future use in gene discovery and iPSC line screening. [ABSTRACT FROM AUTHOR]

Calamus brandisii Becc. is an endangered rattan species indigenous to the Western Ghats of India and used in the furniture and handicraft industries. However, its dioecious nature and longer flowering time pose challenges for conservation efforts. Developing markers for early gender detection in seedlings is crucial for maintaining viable populations for in-situ and ex-situ conservation. Currently, no sex chromosomes or gender-specific genes have been reported in the species. We report the first comprehensive comparative genomics study between the male and female genomes of C. brandisii to identify polymorphisms and potential genes for gender determination. Reference-based assembly was conducted and the male and female genomes were predicted to contain 43,810 and 50,493 protein-coding genes respectively. The haploid genome size was ∼691 Mb and ∼884 Mb for male and female genomes respectively. Comparative analysis revealed significant genetic variation between the two genomes including 619,776 SNPs, 73,659 InDels, 212,123 Structural variants (SVs) and 305 copy number variations (CNVs). A total of 5 male-specific and 11 female-specific genes linked to the sex determining region was predicted. The genomic variants identified between the two genomes could be used in development of markers for early gender identification in C. brandisii for restoration programs. The gender-specific genes identified in this study also provide new insights into the mechanisms of sex determination and differentiation in rattans. [ABSTRACT FROM AUTHOR]

Background: Structural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM). Methods: This study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity. Results: OGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases—two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5′UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5′ and 3′ non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain. Conclusions: SVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs. [ABSTRACT FROM AUTHOR]

Simple Summary: Genomic rearrangements are chromosomal abnormalities that alter the arrangement of genes and are important for diagnosing multiple cancer types and guiding therapy selection. However, current diagnostic tests may not detect all genomic rearrangements. Hi-C sequencing is a promising new method for detecting genomic rearrangements. First, we examined whether Hi-C can detect known genomic rearrangements in pediatric leukemia and sarcoma specimens. Next, we evaluated whether Hi-C can detect genomic rearrangements that were not found using standard diagnostic testing. Hi-C showed complete agreement with other diagnostic methods in identifying known rearrangements. Hi-C also detected previously unknown genomic rearrangements in 5/11 pediatric leukemia cases that could impact diagnosis, prognosis, or treatment choices. These data suggest Hi-C could be beneficial for medical diagnostic testing of pediatric cancers, but more extensive clinical validation is needed. Hi-C sequencing is a DNA-based next-generation sequencing method that preserves the 3D genome conformation and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate Hi-C as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens. Archived viable and non-viable frozen leukemic cells and formalin-fixed paraffin-embedded (FFPE) tumor specimens were analyzed. Pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to Hi-C to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases without known genomic rearrangements based on prior clinical diagnostic testing was evaluated to determine whether Hi-C could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, we observed 100% concordance between Hi-C and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study provides an institutional proof of principle evaluation of Hi-C sequencing to medical diagnostic testing as it identified several clinically relevant rearrangements, including those that were missed by current clinical testing workflows. [ABSTRACT FROM AUTHOR]

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors. We found that while individual misexpression events occur rarely, in aggregate they were found in almost all samples and a third of inactive protein-coding genes. Using 2,821 paired whole-genome and RNA sequencing samples, we identified that misexpression events are enriched in cis for rare structural variants. We established putative mechanisms through which a subset of SVs lead to gene misexpression, including transcriptional readthrough, transcript fusions, and gene inversion. Overall, we develop misexpression as a type of transcriptomic outlier analysis and extend our understanding of the variety of mechanisms by which genetic variants can influence gene expression. Misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences, we have a limited understanding of its wider prevalence and mechanisms. Here, we explore the prevalence of misexpression, the genetic variants associated with misexpression, and their mechanisms of action. [ABSTRACT FROM AUTHOR]

Summary: T/myeloid mixed phenotype acute leukaemia (MPAL) is a rare aggressive acute leukaemia with poorly understood pathogenesis. Herein, we report two cases of T/myeloid MPAL harbouring BCL11B‐associated structural variants that activate TLX3 (TLX3::BCL11B‐TLX3‐activation) by genome sequencing and transcriptomic analyses. Both patients were young males with extramedullary involvement. Cooperative gene alterations characteristic of T/myeloid MPAL and T‐lymphoblastic leukaemia (T‐ALL) were detected. Both patients achieved initial remission following lineage‐matched ALL‐based therapy with one patient requiring a lineage‐switched myeloid‐based therapy. Our study is the first to demonstrate the clinicopathological and genomic features of TLX3::BCL11B‐TLX3‐activated T/myeloid MPAL and provide insights into leukaemogenesis. [ABSTRACT FROM AUTHOR]

A glioma is a solid brain tumor which originates in the brain or brain stem area. The diagnosis of gliomas based on standard-of-care (SOC) techniques includes karyotyping, fluorescence in situ hybridization (FISH), and chromosomal microarray (CMA), for detecting the pathogenic variants and chromosomal abnormalities. But these techniques do not reveal the complete picture of genetic complexity, thus requiring an alternative technology for better characterization of these tumors. The present study aimed to evaluate the clinical performance and feasibility of using optical genome mapping (OGM) for chromosomal characterization of gliomas. Herein, we evaluated 10 cases of gliomas that were previously characterized by CMA. OGM analysis showed concordance with the results of CMA in identifying the characterized Structural Variants (SVs) in these cases. More notably, it also revealed additional clinically relevant aberrations, demonstrating a higher resolution and sensitivity. These clinically relevant SVs included cryptic translocation, and SVs which are beyond the detection capabilities of CMA. Our analysis highlights the unique capability of OGM to detect all classes of SVs within a single assay, thereby unveiling clinically significant data with a shorter turnaround time. Adopting this diagnostic tool as a standard of care for solid tumors like gliomas shows potential for improving therapeutic management, potentially leading to more personalized and timely interventions for patients. [ABSTRACT FROM AUTHOR]

Abstract Background Certain structural variants (SVs) including large-scale genetic copy number variants, as well as copy number-neutral inversions and translocations may not all be resolved by chromosome karyotype studies. The identification of genetic risk factors for Parkinson’s disease (PD) has been primarily focused on the gene-disruptive single nucleotide variants. In contrast, larger SVs, which may significantly influence human phenotypes, have been largely underexplored. Optical genomic mapping (OGM) represents a novel approach that offers greater sensitivity and resolution for detecting SVs. In this study, we used induced pluripotent stem cell (iPSC) lines of patients with PD-linked SNCA and PRKN variants as a proof of concept to (i) show the detection of pathogenic SVs in PD with OGM and (ii) provide a comprehensive screening of genetic abnormalities in iPSCs. Results OGM detected SNCA gene triplication and duplication in patient-derived iPSC lines, which were not identified by long-read sequencing. Additionally, various exon deletions were confirmed by OGM in the PRKN gene of iPSCs, of which exon 3–5 and exon 2 deletions were unable to phase with conventional multiplex-ligation-dependent probe amplification. In terms of chromosomal abnormalities in iPSCs, no gene fusions, no aneuploidy but two balanced inter-chromosomal translocations were detected in one line that were absent in the parental fibroblasts and not identified by routine single nucleotide variant karyotyping. Conclusions In summary, OGM can detect pathogenic SVs in PD-linked genes as well as reveal genomic abnormalities for iPSCs that were not identified by other techniques, which is supportive for OGM’s future use in gene discovery and iPSC line screening.

Abstract Background Structural variations (SVs) are key genetic contributors to neurodevelopmental disorders (NDDs). Exome sequencing (ES), the current first-line tool for genetic testing of NDDs, falls short in SVs detection. This diagnostic gap is being actively addressed by new methods such as optical genome mapping (OGM). Methods This study evaluated the utility of combining OGM and RNA-seq in the detection and interpretation of SVs in ES-negative NDDs. OGM was performed in 43 patients with NDDs with inconclusive ES results. Candidate SVs were selected based on disease association and pathogenicity evaluation, and further validated or reconstructed by alternative methods, including long-read sequencing for a complex rearrangement event. RNA-Seq was performed on blood samples from patients with candidate SVs to facilitate interpretation of pathogenicity. Results OGM detected four candidate SVs, and RNA-seq confirmed the pathogenicity of three SVs in the patient cohort. This combined approach solved three cases—two cases with de novo SVs in genes associated with autosomal dominant NDDs, including a deletion encompassing the promoter and 5′UTR of MBD5 and an intragenic duplication of PAFAH1B1, and a third case possessing an intragenic duplication in trans with a pathogenic single-nucleotide variant of PLA2G6, associated with autosomal recessive NDDs. The expression alteration of the affected genes and the tandem positioning of two intragenic duplications were confirmed by RNA-seq. In the fourth case, OGM detected a complex rearrangement involving chromosomes 2 and 6, much more complex than the de novo t(2:6)(q13;q15) indicated by conventional cytogenetic analysis. Reconstruction showed that 17 segments of 6q15 spanning 9.3 Mb were disarranged and joined 2q11.2, with four breakpoints detected in the 5′ and 3′ non-coding region of the NDD-associated gene SYNCRIP. RNA-seq revealed largely preserved SYNCRIP expression, leaving the pathogenicity of this complex rearrangement event uncertain. Conclusions SVs in ES-negative NDDs can be identified by OGM, which is particularly useful for SVs in non-coding regions not covered by ES. OGM helps to construct complex SVs and provides information on the location and orientation of duplications, which is crucial for pathogenicity interpretation. The integration of RNA-seq facilitates the interpretation of the functional consequences of SVs at the transcriptional level. These findings demonstrate the utility and feasibility of combining OGM and RNA-seq in ES-negative cases with NDDs.

Abstract Background Structural variants (SVs) such as deletions, duplications, and insertions are known to contribute to phenotypic variation but remain challenging to identify and genotype. A more complete, accessible, and assessable collection of SVs will assist efforts to study SV function in cattle and to incorporate SV genotyping into animal evaluation. Results In this work we produced a large and deeply characterized collection of SVs in Holstein cattle using two popular SV callers (Manta and Smoove) and publicly available Illumina whole-genome sequence (WGS) read sets from 310 samples (290 male, 20 female, mean 20X coverage). Manta and Smoove identified 31 K and 68 K SVs, respectively. In total the SVs cover 5% (Manta) and 6% (Smoove) of the reference genome, in contrast to the 1% impacted by SNPs and indels. SV genotypes from each caller were confirmed to accurately recapitulate animal relationships estimated using WGS SNP genotypes from the same dataset, with Manta genotypes outperforming Smoove, and deletions outperforming duplications. To support efforts to link the SVs to phenotypic variation, overlapping and tag SNPs were identified for each SV, using genotype sets extracted from the WGS results corresponding to two bovine SNP chips (BovineSNP50 and BovineHD). 9% (Manta) and 11% (Smoove) of the SVs were found to have overlapping BovineHD panel SNPs, while 21% (Manta) and 9% (Smoove) have BovineHD panel tag SNPs. A custom interactive database ( https://svdb-dc.pslab.ca ) containing the identified sequence variants with extensive annotations, gene feature information, and BAM file content for all SVs was created to enable the evaluation and prioritization of SVs for further study. Illustrative examples involving the genes POPDC3, ORM1, G2E3, FANCI, TFB1M, FOXC2, N4BP2, GSTA3, and COPA show how this resource can be used to find well-supported genic SVs, determine SV breakpoints, design genotyping approaches, and identify processed pseudogenes masquerading as deletions. Conclusions The resources developed through this study can be used to explore sequence variation in Holstein cattle and to develop strategies for studying SVs of interest. The lack of overlapping and tag SNPs from commonly used SNP chips for most of the SVs suggests that other genotyping approaches will be needed (for example direct genotyping) to understand their potential contributions to phenotype. The included SV genotype assessments point to challenges in characterizing SVs, especially duplications, using short-read data and support ongoing efforts to better characterize cattle genomes through long-read sequencing. Lastly, the identification of previously known functional SVs and additional CDS-overlapping SVs supports the phenotypic relevance of this dataset.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high genetic heritability but heterogeneity. Fully understanding its genetics requires whole-genome sequencing (WGS), but the ASD studies utilizing WGS data in Chinese population are limited. In this study, we present a WGS study for 334 individuals, including 112 ASD patients and their non-ASD parents. We identified 146 de novo variants in coding regions in 85 cases and 60 inherited variants in coding regions. By integrating these variants with an association model, we identified 33 potential risk genes (P<0.001) enriched in neuron and regulation related biological process. Besides the well-known ASD genes (SCN2A, NF1, SHANK3, CHD8 etc.), several high confidence genes were highlighted by a series of functional analyses, including CTNND1, DGKZ, LRP1, DDN, ZNF483, NR4A2, SMAD6, INTS1, and MRPL12, with more supported evidence from GO enrichment, expression and network analysis. We also integrated RNA-seq data to analyze the effect of the variants on the gene expression and found 12 genes in the individuals with the related variants had relatively biased expression. We further presented the clinical phenotypes of the proband carrying the risk genes in both our samples and Caucasian samples to show the effect of the risk genes on phenotype. Regarding variants in non-coding regions, a total of 74 de novo variants and 30 inherited variants were predicted as pathogenic with high confidence, which were mapped to specific genes or regulatory features. The number of de novo variants found in patient was significantly associated with the parents' ages at the birth of the child, and gender with trend. We also identified small de novo structural variants in ASD trios. The results in this study provided important evidence for understanding the genetic mechanism of ASD. [ABSTRACT FROM AUTHOR]

Abstract Background Anopheles funestus is a leading vector of malaria in most parts of East and Southern Africa, yet its ecology and responses to vector control remain poorly understood compared with other vectors such as Anopheles gambiae and Anopheles arabiensis. This study presents the first large-scale survey of the genetic and phenotypic expression of insecticide resistance in An. funestus populations in Tanzania. Methods We performed insecticide susceptibility bioassays on An. funestus mosquitoes in nine regions with moderate-to-high malaria prevalence in Tanzania, followed by genotyping for resistance-associated mutations (CYP6P9a, CYP6P9b, L119F-GSTe2) and structural variants (SV4.3 kb, SV6.5 kb). Generalized linear models were used to assess relationships between genetic markers and phenotypic resistance. An interactive R Shiny tool was created to visualize the data and support evidence-based interventions. Results Pyrethroid resistance was universal but reversible by piperonyl-butoxide (PBO). However, carbamate resistance was observed in only five of the nine districts, and dichloro-diphenyl-trichloroethane (DDT) resistance was found only in the Kilombero valley, south-eastern Tanzania. Conversely, there was universal susceptibility to the organophosphate pirimiphos-methyl in all sites. Genetic markers of resistance had distinct geographical patterns, with CYP6P9a-R and CYP6P9b-R alleles, and the SV6.5 kb structural variant absent or undetectable in the north-west but prevalent in all other sites, while SV4.3 kb was prevalent in the north-western and western regions but absent elsewhere. Emergent L119F-GSTe2, associated with deltamethrin resistance, was detected in heterozygous form in districts bordering Mozambique, Malawi and the Democratic Republic of Congo. The resistance landscape was most complex in western Tanzania, in Tanganyika district, where all five genetic markers were detected. There was a notable south-to-north spread of resistance genes, especially CYP6P9a-R, though this appears to be interrupted, possibly by the Rift Valley. Conclusions This study underscores the need to expand resistance monitoring to include An. funestus alongside other vector species, and to screen for both the genetic and phenotypic signatures of resistance. The findings can be visualized online via an interactive user interface and could inform data-driven decision-making for resistance management and vector control. Since this was the first large-scale survey of resistance in Tanzania’s An. funestus, we recommend regular updates with greater geographical and temporal coverage. Graphical Abstract

Abstract While short-read sequencing currently dominates genetic research and diagnostics, it frequently falls short of capturing certain structural variants (SVs), which are often implicated in the etiology of neurodevelopmental disorders (NDDs). Optical genome mapping (OGM) is an innovative technique capable of capturing SVs that are undetectable or challenging-to-detect via short-read methods. This study aimed to investigate NDDs using OGM, specifically focusing on cases that remained unsolved after standard exome sequencing. OGM was performed in 47 families using ultra-high molecular weight DNA. Single-molecule maps were assembled de novo, followed by SV and copy number variant calling. We identified 7 variants of interest, of which 5 (10.6%) were classified as likely pathogenic or pathogenic, located in BCL11A, OPHN1, PHF8, SON, and NFIA. We also identified an inversion disrupting NAALADL2, a gene which previously was found to harbor complex rearrangements in two NDD cases. Variants in known NDD genes or candidate variants of interest missed by exome sequencing mainly consisted of larger insertions (> 1kbp), inversions, and deletions/duplications of a low number of exons (1–4 exons). In conclusion, in addition to improving molecular diagnosis in NDDs, this technique may also reveal novel NDD genes which may harbor complex SVs often missed by standard sequencing techniques.

Inversions have been proposed to facilitate local adaptation, by linking together locally coadapted alleles at different loci. Prior work addressing this question theoretically has considered the spread of inversions in "continent-island" scenarios in which there is a unidirectional flow of maladapted migrants into the island population. In this setting, inversions capturing locally adaptive haplotypes are most likely to invade when selection is weak, because stronger local selection (i) more effectively purges maladaptive alleles and (ii) generates linkage disequilibrium between adaptive alleles, thus lessening the advantage of inversions. We show this finding only holds under limited conditions by studying the establishment of inversions in a more general two-deme model, which explicitly considers the dynamics of allele frequencies in both populations linked by bidirectional migration. In this model, the level of symmetry between demes can be varied from complete asymmetry (continent-island) to complete symmetry. For symmetric selection and migration, strong selection increases the allele frequency divergence between demes thereby increasing the frequency of maladaptive alleles in migrants, favoring inversions—the opposite of the pattern seen in the asymmetric continent-island scenario. We also account for the likelihood that a new inversion captures an adaptive haplotype in the first instance. When considering the combined process of capture and invasion in "continent island" and symmetric scenarios, relatively strong selection increases inversion establishment probability. Migration must also be low enough that the inversion is likely to capture an adaptive allele combination, but not so low as to eliminate the inversion's advantage. Overall, our analysis suggests that inversions are likely to harbor larger effect alleles that experience relatively strong selection. [ABSTRACT FROM AUTHOR]

Gene therapy based on the CRISPR/Cas9 system has emerged as a promising strategy for treating the monogenic fragile skin disorder recessive dystrophic epidermolysis bullosa (RDEB). With this approach problematic wounds could be grafted with gene edited, patient‐specific skin equivalents. Precise gene editing using homology‐directed repair (HDR) is the ultimate goal, however low efficiencies have hindered progress. Reframing strategies based on highly efficient non‐homologous end joining (NHEJ) repair aimed at excising dispensable, mutation‐harboring exons offer a promising alternative approach for restoring the COL7A1 open reading frame. To this end, we employed an exon skipping strategy using dual single guide RNA (sgRNA)/Cas9 ribonucleoproteins (RNPs) targeted at three novel COL7A1 exons (31, 68, and 109) containing pathogenic heterozygous mutations, and achieved exon deletion rates of up to 95%. Deletion of exon 31 in both primary human RDEB keratinocytes and fibroblasts resulted in the restoration of type VII collagen (C7), leading to increased cellular adhesion in vitro and accurate C7 deposition at the dermal‐epidermal junction in a 3D skin model. Taken together, we extend the list of COL7A1 exons amenable to therapeutic deletion. As an incidental finding, we find that long‐read Nanopore sequencing detected large on‐target structural variants comprised of deletions up to >5 kb at a frequency of ~10%. Although this frequency may be acceptable given the high rates of intended editing outcomes, our data demonstrate that standard short‐read sequencing may underestimate the full range of unexpected Cas9‐mediated editing events. [ABSTRACT FROM AUTHOR]

Genomic structural variants (SVs) constitute a significant proportion of genetic variation in the genome. The rapid development of long‐reads sequencing has facilitated the detection of long‐fragment SVs. There is no published study to detect SVs using long‐read data from sheep. We applied a long‐read mapping approach to detect SVs and characterized a total of 30,771 insertions, deletions, inversions and translocations. We identified 716, 916, 842 and 303 specific SVs in Southdown sheep, Alpine merino sheep, Qilian White Tibetan sheep and Oula sheep, respectively. We annotated these SVs and found that these SV‐related genes were primarily enriched in the well‐established pathways involved in the regulation of the immune system, growth and development and environmental adaptability. We detected and annotated SVs based on NGS resequencing data to validate the accuracy based on third‐generation detection. Moreover, five candidate SVs were verified using the PCR method in 50 sheep. Our study is the first to use a long‐reads sequencing approach to construct a novel structural variation map in sheep. We have completed a preliminary exploration of the potential effects of SVs on sheep. [ABSTRACT FROM AUTHOR]

Animal migration is a fascinating phenomenon that has puzzled mankind since the time of ancient Greece. It is a process widespread across a varied range of taxa and it shines especially in birds which, because of their mobility, display an amazing diversity of routes and strategies. With the advances in tracking devices and improvements of sequencing technologies, recent work provides support for a strong genetic influence of several migratory traits across different species. However, there is little to no evidence of any common sequence‐based mechanism behind this complex behaviour, nor any unifying principle explaining it. We review how the focus in understanding the genetic basis for migratory traits should be shifted towards studying regulatory mechanisms of gene expression instead of the traditional candidate gene approach. Importantly, a role for gene expression as the underlying driver of the migratory phenotype can resolve the opposing and often strong views that migration is mainly either under genetic or environmental influence. We emphasise that research should take new directions, reinforcing that there is probably not a common genetic basis for how migration is regulated in birds. Here, we support the notion that 1) migration can only evolve this fast if it is a quantitative trait with a large standing variation; 2) the main drivers for migration evolution seem to be diverse expression–regulation mechanisms rather than gene‐level polymorphisms; and 3) non‐coding sequences of the genome, epigenetics and structural variation might be more important in shaping complex traits than previously thought. Further, we present several hypotheses outlining how these regulatory mechanisms might work across different bird species defining certain migratory traits. [ABSTRACT FROM AUTHOR]

• The occurrence of structural variants leading to duchenne muscular dystrophy is remarkably infrequent. • Our findings emphasize the need for long-read sequence genetic testing in atypical cases of muscle dystrophy. • We report for the first time a novel inversion and balanced translocation in the DMD gene via long-read whole-genome sequencing in a chinese family. • This case underscores the importance of considering structural variants in cases where conventional molecular techniques fail to identify pathogenic variants. Structural variants (SVs) are infrequently observed in Duchenne muscular dystrophy (DMD), a condition mainly marked by deletions and point mutations in the DMD gene. SVs in DMD remain difficult to reliably detect due to the limited SV-detection capacity of conventionally used short-read sequencing technology. Herein, we present a family, a boy and his mother, with clinical signs of muscular dystrophy, elevated creatinine kinase levels, and intellectual disability. A muscle biopsy from the boy showed dystrophin deficiency. Routine molecular techniques failed to detect abnormalities in the DMD gene, however, dystrophin mRNA transcripts analysis revealed an absence of exons 59 to 79. Subsequent long-read whole-genome sequencing identified a rare complex structural variant, a 77 kb novel intragenic inversion, and a balanced translocation t(X;1)(p21.2;p13.3) rearrangement within the DMD gene, expanding the genetic spectrum of dystrophinopathy. Our findings suggested that SVs should be considered in cases where conventional molecular techniques fail to identify pathogenic variants. [ABSTRACT FROM AUTHOR]

Summary: Alfalfa (Medicago sativa L.) is one of the most important forage legumes in the world, including autotetraploid (M. sativa ssp. sativa) and diploid alfalfa (M. sativa ssp. caerulea, progenitor of autotetraploid alfalfa). Here, we reported a high‐quality genome of ZW0012 (diploid alfalfa, 769 Mb, contig N50 = 5.5 Mb), which was grouped into the Northern group in population structure analysis, suggesting that our genome assembly filled a major gap among the members of M. sativa complex. During polyploidization, large phenotypic differences occurred between diploids and tetraploids, and the genetic information underlying its massive phenotypic variations remains largely unexplored. Extensive structural variations (SVs) were identified between ZW0012 and XinJiangDaYe (an autotetraploid alfalfa with released genome). We identified 71 ZW0012‐specific PAV genes and 1296 XinJiangDaYe‐specific PAV genes, mainly involved in defence response, cell growth, and photosynthesis. We have verified the positive roles of MsNCR1 (a XinJiangDaYe‐specific PAV gene) in nodulation using an Agrobacterium rhizobia‐mediated transgenic method. We also demonstrated that MsSKIP23_1 and MsFBL23_1 (two XinJiangDaYe‐specific PAV genes) regulated leaf size by transient overexpression and virus‐induced gene silencing analysis. Our study provides a high‐quality reference genome of an important diploid alfalfa germplasm and a valuable resource of variation landscape between diploid and autotetraploid, which will facilitate the functional gene discovery and molecular‐based breeding for the cultivars in the future. [ABSTRACT FROM AUTHOR]

Despite receiving significant recent attention, the relevance of structural variation (SV) in driving phenotypic diversity remains understudied, although recent advances in long‐read sequencing, bioinformatics and pangenomic approaches have enhanced SV detection. We review the role of SVs in shaping phenotypes in avian model systems, and identify some general patterns in SV type, length and their associated traits. We found that most of the avian SVs so far identified are short indels in chickens, which are frequently associated with changes in body weight and plumage colouration. Overall, we found that relatively short SVs are more frequently detected, likely due to a combination of their prevalence compared to large SVs, and a detection bias, stemming primarily from the widespread use of short‐read sequencing and associated analytical methods. SVs most commonly involve non‐coding regions, especially introns, and when patterns of inheritance were reported, SVs associated primarily with dominant discrete traits. We summarise several examples of phenotypic convergence across different species, mediated by different SVs in the same or different genes and different types of changes in the same gene that can lead to various phenotypes. Complex rearrangements and supergenes, which can simultaneously affect and link several genes, tend to have pleiotropic phenotypic effects. Additionally, SVs commonly co‐occur with single‐nucleotide polymorphisms, highlighting the need to consider all types of genetic changes to understand the basis of phenotypic traits. We end by summarising expectations for when long‐read technologies become commonly implemented in non‐model birds, likely leading to an increase in SV discovery and characterisation. The growing interest in this subject suggests an increase in our understanding of the phenotypic effects of SVs in upcoming years. [ABSTRACT FROM AUTHOR]

ABCA4 is the most frequently mutated gene leading to inherited retinal disease (IRD) with over 2200 pathogenic variants reported to date. Of these, ~1% are copy number variants (CNVs) involving the deletion or duplication of genomic regions, typically >50 nucleotides in length. An in-depth assessment of the current literature based on the public database LOVD, regarding the presence of known CNVs and structural variants in ABCA4, and additional sequencing analysis of ABCA4 using single-molecule Molecular Inversion Probes (smMIPs) for 148 probands highlighted recurrent and novel CNVs associated with ABCA4-associated retinopathies. An analysis of the coverage depth in the sequencing data led to the identification of eleven deletions (six novel and five recurrent), three duplications (one novel and two recurrent) and one complex CNV. Of particular interest was the identification of a complex defect, i.e., a 15.3 kb duplicated segment encompassing exon 31 through intron 41 that was inserted at the junction of a downstream 2.7 kb deletion encompassing intron 44 through intron 47. In addition, we identified a 7.0 kb tandem duplication of intron 1 in three cases. The identification of CNVs in ABCA4 can provide patients and their families with a genetic diagnosis whilst expanding our understanding of the complexity of diseases caused by ABCA4 variants. [ABSTRACT FROM AUTHOR]

Annual breast cancer (BCa) deaths have declined since its apex in 1989 concomitant with widespread adoption of hormone therapies that target estrogen receptor alpha (ERα), the prominent nuclear receptor expressed in ∼80% of BCa. However, up to ∼50% of patients who are ER+ with high-risk disease experience post endocrine therapy relapse and metastasis to distant organs. The vast majority of BCa mortality occurs in this setting, highlighting the inadequacy of current therapies. Genomic abnormalities to ESR1 , the gene encoding ERα, emerge under prolonged selective pressure to enable endocrine therapy resistance. These genetic lesions include focal gene amplifications, hotspot missense mutations in the ligand binding domain, truncations, fusions, and complex interactions with other nuclear receptors. Tumor cells utilize aberrant ERα activity to proliferate, spread, and evade therapy in BCa as well as other cancers. Cutting edge studies on ERα structural and transcriptional relationships are being harnessed to produce new therapies that have shown benefits in patients with ESR1 hotspot mutations. In this review we discuss the history of ERα, current research unlocking unknown aspects of ERα signaling including the structural basis for receptor antagonism, and future directions of ESR1 investigation. In addition, we discuss the development of endocrine therapies from their inception to present day and survey new avenues of drug development to improve pharmaceutical profiles, targeting, and efficacy. [ABSTRACT FROM AUTHOR]

Background: Anopheles funestus is a leading vector of malaria in most parts of East and Southern Africa, yet its ecology and responses to vector control remain poorly understood compared with other vectors such as Anopheles gambiae and Anopheles arabiensis. This study presents the first large-scale survey of the genetic and phenotypic expression of insecticide resistance in An. funestus populations in Tanzania. Methods: We performed insecticide susceptibility bioassays on An. funestus mosquitoes in nine regions with moderate-to-high malaria prevalence in Tanzania, followed by genotyping for resistance-associated mutations (CYP6P9a, CYP6P9b, L119F-GSTe2) and structural variants (SV4.3 kb, SV6.5 kb). Generalized linear models were used to assess relationships between genetic markers and phenotypic resistance. An interactive R Shiny tool was created to visualize the data and support evidence-based interventions. Results: Pyrethroid resistance was universal but reversible by piperonyl-butoxide (PBO). However, carbamate resistance was observed in only five of the nine districts, and dichloro-diphenyl-trichloroethane (DDT) resistance was found only in the Kilombero valley, south-eastern Tanzania. Conversely, there was universal susceptibility to the organophosphate pirimiphos-methyl in all sites. Genetic markers of resistance had distinct geographical patterns, with CYP6P9a-R and CYP6P9b-R alleles, and the SV6.5 kb structural variant absent or undetectable in the north-west but prevalent in all other sites, while SV4.3 kb was prevalent in the north-western and western regions but absent elsewhere. Emergent L119F-GSTe2, associated with deltamethrin resistance, was detected in heterozygous form in districts bordering Mozambique, Malawi and the Democratic Republic of Congo. The resistance landscape was most complex in western Tanzania, in Tanganyika district, where all five genetic markers were detected. There was a notable south-to-north spread of resistance genes, especially CYP6P9a-R, though this appears to be interrupted, possibly by the Rift Valley. Conclusions: This study underscores the need to expand resistance monitoring to include An. funestus alongside other vector species, and to screen for both the genetic and phenotypic signatures of resistance. The findings can be visualized online via an interactive user interface and could inform data-driven decision-making for resistance management and vector control. Since this was the first large-scale survey of resistance in Tanzania's An. funestus, we recommend regular updates with greater geographical and temporal coverage. [ABSTRACT FROM AUTHOR]

While short-read sequencing currently dominates genetic research and diagnostics, it frequently falls short of capturing certain structural variants (SVs), which are often implicated in the etiology of neurodevelopmental disorders (NDDs). Optical genome mapping (OGM) is an innovative technique capable of capturing SVs that are undetectable or challenging-to-detect via short-read methods. This study aimed to investigate NDDs using OGM, specifically focusing on cases that remained unsolved after standard exome sequencing. OGM was performed in 47 families using ultra-high molecular weight DNA. Single-molecule maps were assembled de novo, followed by SV and copy number variant calling. We identified 7 variants of interest, of which 5 (10.6%) were classified as likely pathogenic or pathogenic, located in BCL11A, OPHN1, PHF8, SON, and NFIA. We also identified an inversion disrupting NAALADL2, a gene which previously was found to harbor complex rearrangements in two NDD cases. Variants in known NDD genes or candidate variants of interest missed by exome sequencing mainly consisted of larger insertions (> 1kbp), inversions, and deletions/duplications of a low number of exons (1–4 exons). In conclusion, in addition to improving molecular diagnosis in NDDs, this technique may also reveal novel NDD genes which may harbor complex SVs often missed by standard sequencing techniques. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) significantly impacts millions of individuals worldwide. Although our understanding of the genetic foundations of PD has advanced, a substantial portion of the genetic variation contributing to disease risk remains unknown. Current PD genetic studies have primarily focused on one form of genetic variation, single nucleotide variants (SNVs), while other important forms of genetic variation, such as structural variants (SVs), are mostly ignored due to the complexity of detecting these variants with traditional sequencing methods. Yet, these forms of genetic variation play crucial roles in gene expression and regulation in the human brain and are causative of numerous neurological disorders, including forms of PD. This review aims to provide a comprehensive overview of our current understanding of the involvement of coding and noncoding SVs in the genetic architecture of PD. [ABSTRACT FROM AUTHOR]

This article discusses a case study of a 57-year-old Han Chinese male with dopa-responsive dystonia (DRD) caused by a large inversion affecting the GCH1 gene. The patient experienced abnormal head posturing and gait disturbance following a head injury at age 10. Despite not having an identifiable disease-causing variant through conventional gene sequencing, the patient responded well to low-dose levodopa treatment. The study highlights the importance of using whole genome sequencing, nanopore long-read sequencing, and optical genome mapping to detect and confirm complex structural variants in patients with DRD. [Extracted from the article]

IntroductionAutosomal dominant retinitis pigmentosa type 17 (adRP, type RP17) is caused by complex structural variants (SVs) affecting a locus on chromosome 17 (chr17q22). The SVs disrupt the 3D regulatory landscape by altering the topologically associating domain (TAD) structure of the locus, creating novel TAD structures (neo-TADs) and ectopic enhancer-gene contacts. Currently, screening for RP17-associated SVs is not included in routine diagnostics given the complexity of the variants and a lack of cost-effective detection methods. The aim of this study was to accurately detect novel RP17-SVs by establishing a systematic and efficient workflow.MethodsGenetically unexplained probands diagnosed with adRP (n = 509) from an international cohort were screened using a smMIPs or genomic qPCR-based approach tailored for the RP17 locus. Suspected copy number changes were validated using high-density SNP-array genotyping, and SV breakpoint characterization was performed by mutation-specific breakpoint PCR, genome sequencing and, if required, optical genome mapping. In silico modeling of novel SVs was performed to predict the formation of neo-TADs and whether ectopic contacts between the retinal enhancers and the GDPD1-promoter could be formed.ResultsUsing this workflow, potential RP17-SVs were detected in eight probands of which seven were confirmed. Two novel SVs were identified that are predicted to cause TAD rearrangement and retinal enhancer-GDPD1 contact, one from Germany (DE-SV9) and three with the same SV from the United States (US-SV10). Previously reported RP17-SVs were also identified in three Australian probands, one with UK-SV2 and two with SA-SV3.DiscussionIn summary, we describe a validated multi-step pipeline for reliable and efficient RP17-SV discovery and expand the range of disease-associated SVs. Based on these data, RP17-SVs can be considered a frequent cause of adRP which warrants the inclusion of RP17-screening as a standard diagnostic test for this disease.

The editorial discusses the clinical utility of long read sequencing (LRS) in improving diagnostic yield and uncovering biological mechanisms in rare genetic diseases. LRS technology overcomes limitations of short read sequencing and other techniques, allowing for precise identification of structural variants and novel disease-associated tandem repeats. While LRS is primarily used in research, efforts are being made to promote its application in clinical settings for refractory rare diseases. The article highlights the potential of LRS in diagnosing genetic disorders and emphasizes the need for further research to enhance diagnostic yields and time to diagnosis. [Extracted from the article]

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Abstract About 50% of individuals with developmental and epileptic encephalopathies (DEEs) are unsolved following genetic testing. Deep intronic variants, defined as >100 bp from exon–intron junctions, contribute to disease by affecting the splicing of mRNAs in clinically relevant genes. Identifying deep intronic pathogenic variants is challenging and resource intensive, and interpretation is difficult due to limited functional annotations. We aimed to identify deep intronic variants in individuals suspected to have unsolved single gene DEEs. In a research cohort of unsolved cases of DEEs, we searched for children with a DEE syndrome predominantly caused by variants in specific genes in >80% of described cases. We identified two children with Dravet syndrome and one individual with classic lissencephaly. Multiple sequencing and bioinformatics strategies were employed to interrogate intronic regions in SCN1A and PAFAH1B1. A novel de novo deep intronic 12 kb deletion in PAFAH1B1 was identified in the individual with lissencephaly. We showed experimentally that the deletion disrupts mRNA splicing, which results in partial intron retention after exon 2 and disruption of the highly conserved LisH motif. We demonstrate that targeted interrogation of deep intronic regions using multiple genomics technologies, coupled with functional analysis, can reveal hidden causes of unsolved monogenic DEE syndromes. Plain Language Summary Deep intronic variants can cause disease by affecting the splicing of mRNAs in clinically relevant genes. A deep intronic deletion that caused abnormal splicing of the PAFAH1B1 gene was identified in a patient with classic lissencephaly. Our findings reinforce that targeted interrogation of deep intronic regions and functional analysis can reveal hidden causes of unsolved epilepsy syndromes.

Abstract Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level.

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level. Synopsis: A diallel hybrid panel from diverse parental natural yeast isolates is used to investigate the effects of low- frequency single nucleotide polymorphisms (SNPs) and structural variants (SVs) on gene expression variation in a population. The impact of low-frequency and structural variants is assessed using a diallel panel. Diallel SVs are fully cataloged using long-read sequencing and combined parental types. SVs contribute less than SNPs to expression variation and exhibit lower effect size. Low-frequency variants are overrepresented in associations compared to common ones. A diallel hybrid panel from diverse parental natural yeast isolates is used to investigate the effects of low- frequency single nucleotide polymorphisms (SNPs) and structural variants (SVs) on gene expression variation in a population. [ABSTRACT FROM AUTHOR]

About 50% of individuals with developmental and epileptic encephalopathies (DEEs) are unsolved following genetic testing. Deep intronic variants, defined as >100 bp from exon–intron junctions, contribute to disease by affecting the splicing of mRNAs in clinically relevant genes. Identifying deep intronic pathogenic variants is challenging and resource intensive, and interpretation is difficult due to limited functional annotations. We aimed to identify deep intronic variants in individuals suspected to have unsolved single gene DEEs. In a research cohort of unsolved cases of DEEs, we searched for children with a DEE syndrome predominantly caused by variants in specific genes in >80% of described cases. We identified two children with Dravet syndrome and one individual with classic lissencephaly. Multiple sequencing and bioinformatics strategies were employed to interrogate intronic regions in SCN1A and PAFAH1B1. A novel de novo deep intronic 12 kb deletion in PAFAH1B1 was identified in the individual with lissencephaly. We showed experimentally that the deletion disrupts mRNA splicing, which results in partial intron retention after exon 2 and disruption of the highly conserved LisH motif. We demonstrate that targeted interrogation of deep intronic regions using multiple genomics technologies, coupled with functional analysis, can reveal hidden causes of unsolved monogenic DEE syndromes. Plain Language Summary: Deep intronic variants can cause disease by affecting the splicing of mRNAs in clinically relevant genes. A deep intronic deletion that caused abnormal splicing of the PAFAH1B1 gene was identified in a patient with classic lissencephaly. Our findings reinforce that targeted interrogation of deep intronic regions and functional analysis can reveal hidden causes of unsolved epilepsy syndromes. [ABSTRACT FROM AUTHOR]

The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and lowsensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing. [ABSTRACT FROM AUTHOR]

Genetic predisposition is one of the major risk factors for pediatric cancer, with ~10% of children being carriers of a predisposing germline alteration. It is likely that this is the tip of the iceberg and many children are underdiagnosed, as most of the analysis focuses on single or short nucleotide variants, not considering the full spectrum of DNA alterations. Hence, we applied optical genome mapping (OGM) to our cohort of 34 pediatric cancer patients to perform an unbiased germline screening and analyze the frequency of structural variants (SVs) and their impact on cancer predisposition. All children were clinically highly suspicious for germline alterations (concomitant conditions or congenital anomalies, positive family cancer history, particular cancer type, synchronous or metachronous tumors), but whole exome sequencing (WES) had failed to detect pathogenic variants in cancer predisposing genes. OGM detected a median of 49 rare SVs (range 27‐149) per patient. By analysis of 18 patient‐parent trios, we identified three de novo SVs. Moreover, we discovered a likely pathogenic deletion of exon 3 in the known cancer predisposition gene BRCA2, and identified a duplication in RPA1, which might represent a new cancer predisposition gene. We conclude that optical genome mapping is a suitable tool for detecting potentially predisposing SVs in addition to WES in pediatric cancer patients. [ABSTRACT FROM AUTHOR]

When populations decrease in size and may become isolated, genomic erosion by loss of diversity from genetic drift and accumulation of deleterious mutations is likely an inevitable consequence. In such cases, immigration (genetic rescue) is necessary to restore levels of genetic diversity and counteract inbreeding depression. Recent work in conservation genomics has studied these processes focusing on the genetic diversity of single nucleotide polymorphisms. In contrast, our knowledge about structural genomic variation (insertions, deletions, duplications and inversions) in endangered species is limited. We analysed whole‐genome, short‐read sequences from 212 wolves from the inbred Scandinavian population and from neighbouring populations in Finland and Russia, and detected >35,000 structural variants (SVs) after stringent quality and genotype frequency filtering; >26,000 high‐confidence variants remained after manual curation. The majority of variants were shorter than 1 kb, with a distinct peak in the length distribution of deletions at 190 bp, corresponding to insertion events of SINE/tRNA‐Lys elements. The site frequency spectrum of SVs in protein‐coding regions was significantly shifted towards rare alleles compared to putatively neutral variants, consistent with purifying selection. The realized genetic load of SVs in protein‐coding regions increased with inbreeding levels in the Scandinavian population, but immigration provided a genetic rescue effect by lowering the load and reintroducing ancestral alleles at loci fixed for derived SVs. Our study shows that structural variation comprises a common type of in part deleterious mutations in endangered species and that establishing gene flow is necessary to mitigate the negative consequences of loss of diversity. [ABSTRACT FROM AUTHOR]

Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non‐migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype‐environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change. [ABSTRACT FROM AUTHOR]

Abstract Gene therapy based on the CRISPR/Cas9 system has emerged as a promising strategy for treating the monogenic fragile skin disorder recessive dystrophic epidermolysis bullosa (RDEB). With this approach problematic wounds could be grafted with gene edited, patient‐specific skin equivalents. Precise gene editing using homology‐directed repair (HDR) is the ultimate goal, however low efficiencies have hindered progress. Reframing strategies based on highly efficient non‐homologous end joining (NHEJ) repair aimed at excising dispensable, mutation‐harboring exons offer a promising alternative approach for restoring the COL7A1 open reading frame. To this end, we employed an exon skipping strategy using dual single guide RNA (sgRNA)/Cas9 ribonucleoproteins (RNPs) targeted at three novel COL7A1 exons (31, 68, and 109) containing pathogenic heterozygous mutations, and achieved exon deletion rates of up to 95%. Deletion of exon 31 in both primary human RDEB keratinocytes and fibroblasts resulted in the restoration of type VII collagen (C7), leading to increased cellular adhesion in vitro and accurate C7 deposition at the dermal‐epidermal junction in a 3D skin model. Taken together, we extend the list of COL7A1 exons amenable to therapeutic deletion. As an incidental finding, we find that long‐read Nanopore sequencing detected large on‐target structural variants comprised of deletions up to >5 kb at a frequency of ~10%. Although this frequency may be acceptable given the high rates of intended editing outcomes, our data demonstrate that standard short‐read sequencing may underestimate the full range of unexpected Cas9‐mediated editing events.

Summary: Copy-number variants (CNVs) are genome-wide structural variations involving the duplication or deletion of large nucleotide sequences. While these types of variations can be commonly found in humans, large and rare CNVs are known to contribute to the development of various neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD). Nevertheless, given that these NDD-risk CNVs cover broad regions of the genome, it is particularly challenging to pinpoint the critical gene(s) responsible for the manifestation of the phenotype. In this study, we performed a meta-analysis of CNV data from 11,614 affected individuals with NDDs and 4,031 control individuals from SFARI database to identify 41 NDD-risk CNV loci, including 24 novel regions. We also found evidence for dosage-sensitive genes within these regions being significantly enriched for known NDD-risk genes and pathways. In addition, a significant proportion of these genes was found to (1) converge in protein-protein interaction networks, (2) be among most expressed genes in the brain across all developmental stages, and (3) be hit by deletions that are significantly over-transmitted to individuals with ASD within multiplex ASD families from the iHART cohort. Finally, we conducted a burden analysis using 4,281 NDD cases from Decipher and iHART cohorts, and 2,504 neurotypical control individuals from 1000 Genomes and iHART, which resulted in the validation of the association of 162 dosage-sensitive genes driving risk for NDDs, including 22 novel NDD-risk genes. Importantly, most NDD-risk CNV loci entail multiple NDD-risk genes in agreement with a polygenic model associated with the majority of NDD cases.

With the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium. The database is composed of (i) SNPs that have exhibited genome-wide significant association with traits, primarily disease phenotypes, (ii) newly released structural variants (SVs), and (iii) linkage disequilibrium values calculated from unphased data. All data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available at the SV-SNP LD Database and can be accessed at ‵https://github.com/hliang-SchrodiLab/SV_SNPs. Our analysis results represent a useful fine mapping tool for interrogating SVs in linkage disequilibrium with disease-associated SNPs. We anticipate that this resource may play an important role in subsequent studies which investigate incorporating disease causing SVs into disease risk prediction models.

Copy-number variants and structural variants (CNVs/SVs) drive many neurodevelopmental-related disorders. While many neurodevelopmental-related CNVs/SVs give rise to complex phenotypes, the overlap in phenotypic presentation between independent CNVs can be extensive and provides a motivation for shared approaches. This confluence at the level of clinical phenotype implies convergence in at least some aspects of the underlying genomic mechanisms. With this perspective, our Commission on Novel Technologies for Neurodevelopmental CNVs asserts that the time has arrived to approach neurodevelopmental-related CNVs/SVs as a class of disorders that can be identified, investigated, and treated on the basis of shared mechanisms and/or pathways (e.g., molecular, neurological, or developmental). To identify common etiologic mechanisms among uncommon neurodevelopmental-related disorders and to potentially identify common therapies, it is paramount for teams of scientists, clinicians, and patients to unite their efforts. We bring forward novel, collaborative, and integrative strategies to translational CNV/SV research that engages diverse stakeholders to help expedite therapeutic outcomes. We articulate a clear vision for piloted roadmap strategies to reduce patient/caregiver burden and redundancies, increase efficiency, avoid siloed data, and accelerate translational discovery across CNV/SV-based syndromes.

Abstract Background Feeding costs represent the largest expenditures in beef production. Therefore, the animal efficiency in converting feed in high-quality protein for human consumption plays a major role in the environmental impact of the beef industry and in the beef producers’ profitability. In this context, breeding animals for improved feed efficiency through genomic selection has been considered as a strategic practice in modern breeding programs around the world. Copy number variation (CNV) is a less-studied source of genetic variation that can contribute to phenotypic variability in complex traits. In this context, this study aimed to: (1) identify CNV and CNV regions (CNVRs) in the genome of Nellore cattle (Bos taurus indicus); (2) assess potential associations between the identified CNVR and weaning weight (W210), body weight measured at the time of selection (WSel), average daily gain (ADG), dry matter intake (DMI), residual feed intake (RFI), time spent at the feed bunk (TF), and frequency of visits to the feed bunk (FF); and, (3) perform functional enrichment analyses of the significant CNVR identified for each of the traits evaluated. Results A total of 3,161 CNVs and 561 CNVRs ranging from 4,973 bp to 3,215,394 bp were identified. The CNVRs covered up to 99,221,894 bp (3.99%) of the Nellore autosomal genome. Seventeen CNVR were significantly associated with dry matter intake and feeding frequency (number of daily visits to the feed bunk). The functional annotation of the associated CNVRs revealed important candidate genes related to metabolism that may be associated with the phenotypic expression of the evaluated traits. Furthermore, Gene Ontology (GO) analyses revealed 19 enrichment processes associated with FF. Conclusions A total of 3,161 CNVs and 561 CNVRs were identified and characterized in a Nellore cattle population. Various CNVRs were significantly associated with DMI and FF, indicating that CNVs play an important role in key biological pathways and in the phenotypic expression of feeding behavior and growth traits in Nellore cattle.

SUMMARY: Attenuated strains of the naturally occurring plant pathogen Agrobacterium tumefaciens can transfer virtually any DNA sequence of interest to model plants and crops. This has made Agrobacterium‐mediated transformation (AMT) one of the most commonly used tools in agricultural biotechnology. Understanding AMT, and its functional consequences, is of fundamental importance given that it sits at the intersection of many fundamental fields of study, including plant‐microbe interactions, DNA repair/genome stability, and epigenetic regulation of gene expression. Despite extensive research and use of AMT over the last 40 years, the extent of genomic disruption associated with integrating exogenous DNA into plant genomes using this method remains underappreciated. However, new technologies like long‐read sequencing make this disruption more apparent, complementing previous findings from multiple research groups that have tackled this question in the past. In this review, we cover progress on the molecular mechanisms involved in Agrobacterium‐mediated DNA integration into plant genomes. We also discuss localized mutations at the site of insertion and describe the structure of these DNA insertions, which can range from single copy insertions to large concatemers, consisting of complex DNA originating from different sources. Finally, we discuss the prevalence of large‐scale genomic rearrangements associated with the integration of DNA during AMT with examples. Understanding the intended and unintended effects of AMT on genome stability is critical to all plant researchers who use this methodology to generate new genetic variants. Significance Statement: Agrobacterium‐mediated transformation (AMT) of plants is used extensively as a tool to create new genetic variants for research purposes or agricultural needs. In this work, we summarize the molecular mechanisms involved in AMT and the effects on plant genomes resulting from the integration of exogenous DNA through this method. [ABSTRACT FROM AUTHOR]

The cytogenomics-based methodology of directional genomic hybridization (dGH) enables the detection and quantification of a more comprehensive spectrum of genomic structural variants than any other approach currently available, and importantly, does so on a single-cell basis. Thus, dGH is well-suited for testing and/or validating new advancements in CRISPR-Cas9 gene editing systems. In addition to aberrations detected by traditional cytogenetic approaches, the strand specificity of dGH facilitates detection of otherwise cryptic intra-chromosomal rearrangements, specifically small inversions. As such, dGH represents a powerful, high-resolution approach for the quantitative monitoring of potentially detrimental genomic structural rearrangements resulting from exposure to agents that induce DNA double-strand breaks (DSBs), including restriction endonucleases and ionizing radiations. For intentional genome editing strategies, it is critical that any undesired effects of DSBs induced either by the editing system itself or by mis-repair with other endogenous DSBs are recognized and minimized. In this paper, we discuss the application of dGH for assessing gene editing-associated structural variants and the potential heterogeneity of such rearrangements among cells within an edited population, highlighting its relevance to personalized medicine strategies. [ABSTRACT FROM AUTHOR]

Xishuangbanna (XIS) cucumber (Cucumis sativus L. var. xishuangbannanesis) is a semiwild variety originating from low latitude tropic areas, and therefore shows extreme cold sensitivity and heat tolerance. Here, we mapped the quantitative trait loci (QTLs) that control the cold sensitivity and heat tolerance of XIS cucumber seedlings. Using bulked segregant analysis (BSA), we identified three QTLs (HTT1.1, HTT3.1, and HTT3.2, with a total length of 11.98 Mb) for heat tolerance and two QTLs (LTT6.1 and LTT6.2, with a total length of 8.74 Mb) for cold sensitivity. The QTL LTT6.1 was then narrowed down to a length of 641 kb by using kompetitive allele-specific PCR (KASP) markers. Based on structural variants (SVs) and single-nucleotide polymorphisms (SNPs), we found the LTT6.1 is covered by a high divergent region including a 50 kb deletion in the XIS49 genome, which affects the gene structure of lipase abhydrolase domain containing 6 (ABHD6, Csa_6G032560). Accordingly, there is a very big difference in lipid composition, but not in other osmoprotectants like free amino acids and fatty acids, between XIS49 and cultivated cucumber CL. Moreover, we calculated the composite likelihood ratio (CLR) and identified selective sweeps from 115 resequencing data, and found that lipid- and fatty-acid-related processes are major aspects in the domestication of the XIS group cucumber. LTT6.1 is a particularly special region positioned nearby lipid-related selective sweeps. These studies above suggested that the lipid-related domestication of XIS cucumbers should account for their extreme cold sensitivity. [ABSTRACT FROM AUTHOR]

Structural variants (SVs) are a major source of genetic variation; and descriptions in natural populations and connections with phenotypic traits are beginning to accumulate in the literature. We integrated advances in genomic sequencing and animal tracking to begin filling this knowledge gap in the Eurasian blackcap. Specifically, we (a) characterized the genome-wide distribution, frequency, and overall fitness effects of SVs using haplotype-resolved assemblies for 79 birds, and (b) used these SVs to study the genetics of seasonal migration. We detected >15 K SVs. Many SVs overlapped repetitive regions and exhibited evidence of purifying selection suggesting they have overall deleterious effects on fitness. We used estimates of genomic differentiation to identify SVs exhibiting evidence of selection in blackcaps with different migratory strategies. Insertions and deletions dominated the SVs we identified and were associated with genes that are either directly (e.g., regulatory motifs that maintain circadian rhythms) or indirectly (e.g., through immune response) related to migration. We also broke migration down into individual traits (direction, distance, and timing) using existing tracking data and tested if genetic variation at the SVs we identified could account for phenotypic variation at these traits. This was only the case for 1 trait—direction—and 1 specific SV (a deletion on chromosome 27) accounted for much of this variation. Our results highlight the evolutionary importance of SVs in natural populations and provide insight into the genetic basis of seasonal migration. Lay Summary: Structural variants (SVs) represent a major source of genetic variation that is important for both adaptation and speciation. However, detailed information on how they are distributed in the genome, their frequency, and effects on the fitness of individuals in natural populations (e.g., associations with adaptive traits) is lacking. These knowledge gaps derive in large part from difficulties associated with identifying SVs in the genome (e.g., because they are highly repetitive). We filled this knowledge gap here, using new sequencing technologies to assemble de novo genomes for 79 Eurasian blackcaps. These blackcaps had been tracked on migration in a previous study, allowing us to expand our work to the genetics of migration as well. Migration is a complex behavioral trait that has fascinated researchers and lay people alike for decades as well. The SVs we identified had overall negative effects on fitness but a subset were linked to variation in the migratory behavior of blackcaps. These SVs were linked to genes with functions that may be directly related to migration (e.g., that help maintain circadian rhythms) or are experiencing selection that is secondary to migration (e.g., that help with immune responses). [ABSTRACT FROM AUTHOR]

Background: Causative genetic variants cannot yet be found for many disorders with a clear heritable component, including chronic fatigue disorders like myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). These conditions may involve genes in difficult-to-align genomic regions that are refractory to short read approaches. Structural variants in these regions can be particularly hard to detect or define with short reads, yet may account for a significant number of cases. Long read sequencing can overcome these difficulties but so far little data is available regarding the specific analytical challenges inherent in such regions, which need to be taken into account to ensure that variants are correctly identified. Research into chronic fatigue disorders faces the additional challenge that the heterogeneous patient populations likely encompass multiple aetiologies with overlapping symptoms, rather than a single disease entity, such that each individual abnormality may lack statistical significance within a larger sample. Better delineation of patient subgroups is needed to target research and treatment. Methods: We use nanopore sequencing in a case of unexplained severe fatigue to identify and fully characterise a large inversion in a highly homologous region spanning the AKR1C gene locus, which was indicated but could not be resolved by short-read sequencing. We then use GC–MS/MS serum steroid analysis to investigate the functional consequences. Results: Several commonly used bioinformatics tools are confounded by the homology but a combined approach including visual inspection allows the variant to be accurately resolved. The DNA inversion appears to increase the expression of AKR1C2 while limiting AKR1C1 activity, resulting in a relative increase of inhibitory GABAergic neurosteroids and impaired progesterone metabolism which could suppress neuronal activity and interfere with cellular function in a wide range of tissues. Conclusions: This study provides an example of how long read sequencing can improve diagnostic yield in research and clinical care, and highlights some of the analytical challenges presented by regions containing tandem arrays of genes. It also proposes a novel gene associated with a novel disease aetiology that may be an underlying cause of complex chronic fatigue. It reveals biomarkers that could now be assessed in a larger cohort, potentially identifying a subset of patients who might respond to treatments suggested by the aetiology. [ABSTRACT FROM AUTHOR]

Structural variants (SVs, including large‐scale insertions, deletions, inversions, and translocations) significantly impact the functions of genes in the microbial genome, and SVs in the microbiome are associated with diverse biological processes and human diseases. With the advancements in sequencing and bioinformatics technologies, increasingly, sequencing data and analysis tools are already being extensively utilized for microbiome SV analyses, leading to a higher demand for more dedicated SV analysis workflows. Moreover, due to the unique detection biases of various sequencing technologies, including short‐read sequencing (such as Illumina platforms) and long‐read sequencing (e.g., Oxford Nanopore and PacBio), SV discovery based on multiple platforms is necessary to comprehensively identify the wide variety of SVs. Here, we establish an integrated pipeline MetaSVs combining Nanopore long reads and Illumina short reads to analyze SVs in the microbial genomes from gut microbiome and further identify differential SVs that can be reflective of metabolic differences. Our pipeline provides researchers easy access to SVs and relevant metabolites in the microbial genomes without the requirement of specific technical expertise, which is particularly useful to researchers interested in metagenomic SVs but lacking sophisticated bioinformatic knowledge. Highlights: A bioinformatic pipeline to integrate Nanopore long reads and Illumina short reads is provided, capable of conducting metagenomic structural variant (SV) analyses.The detailed description of each step of the microbial SV pipeline is illustrated by a simplified example of the human gut microbiome.This pipeline will help beginners learn how to conduct microbial SV analyses and enable experienced scientists to improve their efficiency. [ABSTRACT FROM AUTHOR]