Discovery Of Variants Research Articles

Integrating Optical Genome Mapping and Whole Genome Sequencing in Somatic Structural Variant Detection.

Structural variants drive tumorigenesis by disrupting normal gene function through insertions, inversions, translocations, and copy number changes, including deletions and duplications. Detecting structural variants is crucial for revealing their roles in tumor development, clinical outcomes, and personalized therapy. Presently, most studies rely on short-read data from next-generation sequencing that aligns back to a reference genome to determine if and, if so, where a structural variant occurs. However, structural variant discovery by short-read sequencing is challenging, primarily because of the difficulty in mapping regions of repetitive sequences. Optical genome mapping (OGM) is a recent technology used for imaging and assembling long DNA strands to detect structural variations. To capture the structural variant landscape more thoroughly in the human genome, we developed an integrated pipeline that combines Bionano OGM and Illumina whole-genome sequencing and applied it to samples from 29 pediatric B-ALL patients. The addition of OGM allowed us to identify 511 deletions, 506 insertions, 93 duplications/gains, and 145 translocations that were otherwise missed in the short-read data. Moreover, we identified several novel gene fusions, the expression of which was confirmed by RNA sequencing. Our results highlight the benefit of integrating OGM and short-read detection methods to obtain a comprehensive analysis of genetic variation that can aid in clinical diagnosis, provide new therapeutic targets, and improve personalized medicine in cancers driven by structural variation.

Large-Scale Cytochrome C Oxidase Subunit I Gene Data Analysis for the Development of a Multiplex Polymerase Chain Reaction Test Capable of Identifying Biting Midge Vector Species and Haplotypes (Diptera: Ceratopogonidae) of the Culicoides Subgenus Avaritia Fox, 1955.

The emergence of culicoid-transmitted bluetongue and Schmallenberg viruses in several European countries demonstrated the ability of indigenous biting midge species to transmit pathogens. Entomologic research programs identified members of the Obsoletus Group (Culicoides subgenus Avaritia) as keyplayers in disease epidemiology in Europe. However, morphological identification of potential vectors is challenging due to the recent discovery of new genetic variants (haplotypes) of C. obsoletus sensu stricto (s.s.), forming distinct clades. In this study, 4422 GenBank entries of the mitochondrial cytochrome c oxidase subunit I (COI) gene of subgenus Avaritia members of the genus Culicoides were analyzed to develop a conventional multiplex PCR, capable of detecting all vector species and clades of the Western Palearctic in this subgenus. Numerous GenBank entries incorrectly assigned to a species were identified, analyzed and reassigned. The results suggest that the three C. obsoletus clades represent independent species, whereas C. montanus should rather be regarded as a genetic variant of C. obsoletus s.s. Based on these findings, specific primers were designed and validated with DNA material from field-caught biting midges which achieved very high diagnostic sensitivity (100%) when compared to an established reference PCR (82.6%).

178P Germline testing in non-small cell lung cancer (NSCLC): Real-world impact of the discovery of germline pathogenic variants (PGV) in the INHERITY LC (ILC) study

178P Germline testing in non-small cell lung cancer (NSCLC): Real-world impact of the discovery of germline pathogenic variants (PGV) in the INHERITY LC (ILC) study

Investigating structural variant, indel and single nucleotide polymorphism differentiation between locally adapted Atlantic salmon populations.

Genomic structural variants (SVs) are now recognized as an integral component of intraspecific polymorphism and are known to contribute to evolutionary processes in various organisms. However, they are inherently difficult to detect and genotype from readily available short-read sequencing data, and therefore remain poorly documented in wild populations. Salmonid species displaying strong interpopulation variability in both life history traits and habitat characteristics, such as Atlantic salmon (Salmo salar), offer a prime context for studying adaptive polymorphism, but the contribution of SVs to fine-scale local adaptation has yet to be explored. Here, we performed a comparative analysis of SVs, single nucleotide polymorphisms (SNPs) and small indels (<50 bp) segregating in the Romaine and Puyjalon salmon, two putatively locally adapted populations inhabiting neighboring rivers (Québec, Canada) and showing pronounced variation in life history traits, namely growth, fecundity, and age at maturity and smoltification. We first catalogued polymorphism using a hybrid SV characterization approach pairing both short- (16X) and long-read sequencing (20X) for variant discovery with graph-based genotyping of SVs across 60 salmon genomes, along with characterization of SNPs and small indels from short reads. We thus identified 115,907 SVs, 8,777,832 SNPs and 1,089,321 short indels, with SVs covering 4.8 times more base pairs than SNPs. All three variant types revealed a highly congruent population structure and similar patterns of F ST and density variation along the genome. Finally, we performed outlier detection and redundancy analysis (RDA) to identify variants of interest in the putative local adaptation of Romaine and Puyjalon salmon. Genes located near these variants were enriched for biological processes related to nervous system function, suggesting that observed variation in traits such as age at smoltification could arise from differences in neural development. This study therefore demonstrates the feasibility of large-scale SV characterization and highlights its relevance for salmonid population genomics.

Development and Assessment of SNP Genotyping Arrays for Citrus and Its Close Relatives.

Rapid advancements in technologies provide various tools to analyze fruit crop genomes to better understand genetic diversity and relationships and aid in breeding. Genome-wide single nucleotide polymorphism (SNP) genotyping arrays offer highly multiplexed assays at a relatively low cost per data point. We report the development and validation of 1.4M SNP Axiom® Citrus HD Genotyping Array (Citrus 15AX 1 and Citrus 15AX 2) and 58K SNP Axiom® Citrus Genotyping Arrays for Citrus and close relatives. SNPs represented were chosen from a citrus variant discovery panel consisting of 41 diverse whole-genome re-sequenced accessions of Citrus and close relatives, including eight progenitor citrus species. SNPs chosen mainly target putative genic regions of the genome and are accurately called in both Citrus and its closely related genera while providing good coverage of the nuclear and chloroplast genomes. Reproducibility of the arrays was nearly 100%, with a large majority of the SNPs classified as the most stringent class of markers, "PolyHighResolution" (PHR) polymorphisms. Concordance between SNP calls in sequence data and array data average 98%. Phylogenies generated with array data were similar to those with comparable sequence data and little affected by 3 to 5% genotyping error. Both arrays are publicly available.

A repertoire of single nucleotide polymorphisms (SNPs) of major fecundity BMPR1B gene among 75 sheep breeds worldwide

The BMPR1B gene is a major determinant of sheep reproductive capacity. Previous studies revealed that Q249R (FecB) is a profound variant of BMPR1B that influences the ovulation rate and litter size in sheep. However, unlike Q249R locus, the full spectrum of single nucleotide polymorphisms (SNPs) within BMPR1B has not been extensively studied. A systematic screen of SNPs in BMPR1B would facilitate the discovery of novel variants that are associated with litter size. This study aimed to investigate SNPs in the BMPR1B gene via whole genome sequence (WGS) data from 2409 individuals of 75 sheep breeds worldwide. Herein, a total of 9688 variants were screened, among which 15 were coding variants and 8 were novel changes. Specifically, we presented the most comprehensive frequency distribution map of the well-known FecB mutation to date. Besides, among the above-mentioned SNPs, one synonymous mutation (g.30050773C > T) was found to be likely under selection and is potentially associated with fecundity in Duolang sheep. Thus, our study greatly expands the variation repertoire of the ovine BMPR1B gene and provides a valuable resource for exploring causative mutations and genetic markers associated with litter size.

123VCF: an intuitive and efficient tool for filtering VCF files

BackgroundThe advent of Next-Generation Sequencing (NGS) has catalyzed a paradigm shift in medical genetics, enabling the identification of disease-associated variants. However, the vast quantum of data produced by NGS necessitates a robust and dependable mechanism for filtering irrelevant variants. Annotation-based variant filtering, a pivotal step in this process, demands a profound understanding of the case-specific conditions and the relevant annotation instruments. To tackle this complex task, we sought to design an accessible, efficient and more importantly easy to understand variant filtering tool.ResultsOur efforts culminated in the creation of 123VCF, a tool capable of processing both compressed and uncompressed Variant Calling Format (VCF) files. Built on a Java framework, the tool employs a disk-streaming real-time filtering algorithm, allowing it to manage sizable variant files on conventional desktop computers. 123VCF filters input variants in accordance with a predefined filter sequence applied to the input variants. Users are provided the flexibility to define various filtering parameters, such as quality, coverage depth, and variant frequency within the populations. Additionally, 123VCF accommodates user-defined filters tailored to specific case requirements, affording users enhanced control over the filtering process. We evaluated the performance of 123VCF by analyzing different types of variant files and comparing its runtimes to the most similar algorithms like BCFtools filter and GATK VariantFiltration. The results indicated that 123VCF performs relatively well. The tool's intuitive interface and potential for reproducibility make it a valuable asset for both researchers and clinicians.ConclusionThe 123VCF filtering tool provides an effective, dependable approach for filtering variants in both research and clinical settings. As an open-source tool available at https://project123vcf.sourceforge.io, it is accessible to the global scientific and clinical community, paving the way for the discovery of disease-causing variants and facilitating the advancement of personalized medicine.

A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome

Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call “Whole Exome Genome Sequencing” (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7–2.0 times cheaper than standard WES (no-plexing), 1.8–2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.

The Inclusion of Underrepresented Populations in Cardiovascular Genetics and Epidemiology.

Novel genetic risk markers have helped us to advance the field of cardiovascular epidemiology and refine our current understanding and risk stratification paradigms. The discovery and analysis of variants can help us to tailor prognostication and management. However, populations underrepresented in cardiovascular epidemiology and cardiogenetics research may experience inequities in care if prediction tools are not applicable to them clinically. Therefore, the purpose of this article is to outline the barriers that underrepresented populations can face in participating in genetics research, to describe the current efforts to diversify cardiogenetics research, and to outline strategies that researchers in cardiovascular epidemiology can implement to include underrepresented populations. Mistrust, a lack of diverse research teams, the improper use of sensitive biodata, and the constraints of genetic analyses are all barriers for including diverse populations in genetics studies. The current work is beginning to address the paucity of ethnically diverse genetics research and has already begun to shed light on the potential benefits of including underrepresented and diverse populations. Reducing barriers for individuals, utilizing community-driven research processes, adopting novel recruitment strategies, and pushing for organizational support for diverse genetics research are key steps that clinicians and researchers can take to develop equitable risk stratification tools and improve patient care.

Redescription of the tiger beetle Cicindelidia aeneicollis (Bates 1881) (Coleoptera: Cicindelidae) and discovery of new morphological variants from the Pacific Slope of Mexico.

The tiger beetle species, Cicindelidia aeneicollis (Bates 1881) is redescribed, as Bates original description was inadequate and did not accurately capture the character states or variation found within the species. The specific epithet aeneicollis is partially misleading as the proepisternum is mostly aeneous (bronze/copper) with the basal quarter to third being polychromatic, which the description does not convey. Some populations of this species from the western coast of Mexico exhibit significant variation in maculations, with individuals ranging from weakly marked (as in Bates description) to much more extensively marked.

Accurate top protein variant discovery via low-N pick-and-validate machine learning

A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein engineering. Toward this goal, we present a simple and effective machine learning-based strategy that outperforms other state-of-the-art methods. Our strategy integrates zero-shot prediction and multi-round sampling to direct active learning via experimenting with only a few predicted top variants. We find that four rounds of low-N pick-and-validate sampling of 12 variants for machine learning yielded the best accuracy of up to 92.6% in selecting the true top 1% variants in combinatorial mutant libraries, whereas two rounds of 24 variants can also be used. We demonstrate our strategy in successfully discovering high-performance protein variants from diverse families including the CRISPR-based genome editors, supporting its generalizable application for solving protein engineering tasks. A record of this paper's transparent peer review process is included in the supplemental information.

An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome

Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is increasing, and consequently, the need for data analysis pipelines is likewise growing. Most NGS data analysis solutions to date do not support mouse data or require highly specific configuration for their use. Here, we present a genome analysis pipeline for mouse tumour NGS data including the whole-genome sequence (WGS) data analysis flow for somatic variant discovery, and the RNA-seq data flow for differential expression, functional analysis and neoantigen prediction. The pipeline is based on standards and best practices and integrates mouse genome references and annotations. In a recent study, the pipeline was applied to demonstrate the efficacy of low dose 6-thioguanine (6TG) treatment on low-mutation melanoma in a pre-clinical mouse model. Here, we further this study and describe in detail the pipeline and the results obtained in terms of tumour mutational burden (TMB) and number of predicted neoantigens, and correlate these with 6TG effects on tumour volume. Our pipeline was expanded to include a neoantigen analysis, resulting in neopeptide prediction and MHC class I antigen presentation evaluation. We observed that the number of predicted neoepitopes were more accurate indicators of tumour immune control than TMB. In conclusion, this study demonstrates the usability of the proposed pipeline, and suggests it could be an essential robust genome analysis platform for future mouse genomic analysis.

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

Lessons Learned from Translating Genome Sequencing to Clinical Routine: Understanding the Accuracy of a Diagnostic Pipeline.

The potential of genome sequencing (GS), which allows detection of almost all types of genetic variation across nearly the entire genome of an individual, greatly expands the possibility for diagnosing genetic disorders. The opportunities provided with this single test are enticing to researchers and clinicians worldwide for human genetic research as well as clinical application. Multiple studies have highlighted the advantages of GS for genetic variant discovery, emphasizing its added value for routine clinical use. We have implemented GS as first-line genetic testing for patients with rare diseases. Here, we report on our experiences in establishing GS as a reliable diagnostic method for almost all types of genetic disorders, from validating diagnostic accuracy of sequencing pipelines to clinical implementation in routine practice.

Improving prenatal diagnosis through standards and aggregation.

Advances in sequencing and imaging technologies enable enhanced assessment in the prenatal space, with a goal to diagnose and predict the natural history of disease, to direct targeted therapies, and to implement clinical management, including transfer of care, election of supportive care, and selection of surgical interventions. The current lack of standardization and aggregation stymies variant interpretation and gene discovery, which hinders the provision of prenatal precision medicine, leaving clinicians and patients without an accurate diagnosis. With large amounts of data generated, it is imperative to establish standards for data collection, processing, and aggregation. Aggregated and homogeneously processed genetic and phenotypic data permits dissection of the genomic architecture of prenatal presentations of disease and provides a dataset on which data analysis algorithms can be tuned to the prenatal space. Here we discuss the importance of generating aggregate data sets and how the prenatal space is driving the development of interoperable standards and phenotype-driven tools.

Varijante u GATOR1 genima u fokalnoj epilepsiji

Significant genetic contributions to focal epilepsy have only recently been recognized, despite the well-established hereditary nature of other epilepsy syndromes. In 2013, the significant role of the DEPDC5 gene in a rare familial focal epilepsy syndrome was described, followed by the discovery of variants in NPRL2 and NPRL3 genes in patients with similar clinical features three years later. The genes listed above code the three subunits that comprise the GTPase-activating protein (GAP) activity towards Rags 1 (GATOR1) complex, a negative regulator of the mechanistic target of rapamycin (mTOR) complex 1 (mTORC1). Loss of function of GATOR1 leads to constitutive mTORC1 activation that is linked to various malformations of cortical development (MCD), most notoriously focal cortical dysplasia (FCD), but has also been linked to epilepsy in the absence of overt MCD. Variants in GATOR1 genes have been detected in multiplex families with rare familial focal epilepsy syndromes where they demonstrate an autosomal dominant inheritance pattern with reduced penetrance. More recently, they have also been defined as major contributors in common nonacquired focal epilepsy in which they are detected in 3% of familial and 0.2% of sporadic cases and are particularly common in familial epilepsy associated with FCD where up to 11% of affected subjects carry gene variants. Clinical features of carriers include a propensity for nocturnal seizures, a poor response to antiseizure medication as well and an increased risk of sudden unexpected death in epilepsy, which is why other forms of treatment have been explored, including epilepsy surgery after which GATOR1 gene variant carriers have similar outcomes to other patients with focal epilepsy. A particularly promising avenue of exploration is the utilization of mTOR inhibitors like everolimus in epilepsy treatment, but further investigation into this option is warranted.

Avidity sequencing of whole genomes from retinal degeneration pedigrees identifies causal variants.

Whole genome sequencing has been an effective tool in the discovery of variants that cause rare diseases. In this study, we determined the suitability of a novel avidity sequencing approach for rare disease applications. We built a sample to results workflow, combining this sequencing technology with standard library preparation kits, analysis workflows, and interpretation tools. We applied the workflow to ten pedigrees with inherited retinal degeneration (IRD) phenotype. Candidate variants of interest identified through whole genome sequencing were further evaluated using segregation analysis in the additional family members. Potentially causal variants in known IRD genes were detected in five of the ten cases. These high confidence variants were found in ABCA4, CERKL, MAK, PEX6 and RDH12 genes associated with retinal degeneration, that could be sufficient to cause pathology. Pending confirmatory clinical evaluation, we observed a 50% diagnostic yield, consistent with previously reported outcomes of IRD patient analysis. The study confirms that avidity sequencing is effective in detection of causal variants when used for whole genome sequencing in rare disease applications.

Glaucoma pharmacogenetics. Role in neuroprotection

Glaucoma is a blinding disease that can occur at all ages, with Mendelian inheritance typical for the rare early onset disease (before age 40) and complex inheritance evident in common adult‐onset forms of disease. Genetic and genomic studies, including genome‐wide association studies (GWAS) have identified new genetic variants contributing to glaucoma in the last years. Genes correlating with glaucoma risk may involve: ocular development, intraocular pressure, trabecular meshwork function or some of them are directly related to optic nerve susceptibility such as retinal ganglion cell membranes, mitochondrial function, reactive oxygen species production and management, and mechanisms controlling apoptosis. These findings are providing new insights into the underlying molecular mechanisms responsible for glaucoma that could eventually lead to novel gene‐based therapies, including strategies for neuroprotection.We present our study about the genetic analysis of a cohort of Spanish patients with primary open‐angle glaucoma to determine the contribution of rare variants associated with this disease through next generation sequencing (NGS) glaucoma gene panel, as a future method of diagnosis and early treatment. We found some rare variants associated with optic disk parameters and function in some families with high and normal tension glaucoma with allelic frequencies significantly higher than the frequency in the general population by NGS. Those rare variants are located in SIX6, CARD10, MFN1, OPTN, and WDR36 glaucoma‐related genes.These risk variants have been associated to the alteration of retinal ganglion cells through different mechanisms, thereby increasing the risk of glaucoma‐associated vision loss.The discovery of new genetic variants associated with augmented susceptibility of the optic nerve may in the future open the door to designing new neuroprotection gene therapies aimed at repairing damaged genes or providing them through different vectors.

Non-coding genome contribution to ALS.

The majority of amyotrophic lateral sclerosis (ALS) is caused by a complex gene-environment interaction. Despite high estimates of heritability, the genetic basis of disease in the majority of ALS patients are unknown. This limits the development of targeted genetic therapies which require an understanding of patient-specific genetic drivers. There is good evidence that the majority of these missing genetic risk factors are likely to be found within the non-coding genome. However, a major challenge in the discovery of non-coding risk variants is determining which variants are functional in which specific CNS cell type. We summarise current discoveries of ALS-associated genetic drivers within the non-coding genome and we make the case that improved cell-specific annotation of genomic function is required to advance this field, particularly via single-cell epigenetic profiling and spatial transcriptomics. We highlight the example of TBK1 where an apparent paradox exists between pathogenic coding variants which cause loss of protein function, and protective non-coding variants which cause reduced gene expression; the paradox is resolved when it is understood that the non-coding variants are acting primarily via change in gene expression within microglia, and the effect of coding variants is most prominent in neurons. We propose that cell-specific functional annotation of ALS-associated genetic variants will accelerate discovery of the genetic architecture underpinning disease in the vast majority of patients.

Leksikon dan Distribusi Bahasa Melayu Riau Melalui Fitur Fonologi di Kabupaten Kampar

The lexicon and distribution of Riau Malay emerged because of causes that are closely related to language changes observed in certain elements found in the variety of dialects, regional boundaries, number of speakers, residence, identity and cultural pride, and economic conditions. The purpose of this study was to determine (1) the lexical form of phonology and (2) the geographical distribution of phonological forms that experience variations in Riau Malay in Kampar Regency. This research uses a descriptive method with listening, interviewing, recording, and recording techniques. The methods and analytical techniques used are the padan method and the banding technique. This research was conducted at nine observation points in Kampar Regency. The sample of informants at each observation point amounted to one person. The research instrument used for the interview was a list of questions containing 441 questions. The results of this study are based on its realization: the determination of phonetic innovations based on the discovery of variants that show a phonotactic change from the original variant at the Riau Malay observation point in Kampar Regency. Its geographical phonological distribution is based on observation points and the results of data phenomena in the field that often experience dispersal at observation points (1), (2), (3), (8), and geographically.