Identification Of Structural Variants Research Articles

16 Identification of Structural Variants Associated with Mastitis in Holstein Dairy Cows Using Whole Genome Sequencing and RNA-sequencing

Abstract For the dairy industry, animal welfare and economic viability are key factors in determining the long-term sustainability of the industry. One challenge in lactating dairy cows is mastitis, as there are significant costs associated with each mastitis case due to treatment, milk loss, and potential cow culling. Differentially expressed (DE) genes, DE mRNA isoforms and DE long non-coding RNA (lncRNA) candidates were previously identified by our group between healthy and mastitic samples from six Holstein dairy cows. In total, 7 candidate genes, 5 mRNA isoforms and 4 lncRNA were targeted as they play an important role due to their association with mastitis or the immune system. The aim of the current research is to identify new structural variants in the transcriptome of these previously identified potential candidates using RNA-Sequencing. These structural variants could occur in both coding and intergenic regions of the genome and potentially impact the amino acid that is transcribed, creating a new functional or non-functional protein. In addition, whole genome sequencing (WGS) analysis was performed using hair samples collected from ten Holstein dairy cows (first lactation). Five of these animals had no previous reports of mastitis and five animals had at least one report of mastitis in her lifespan. The WGS results will be used to identify additional structural variants, especially within introns, of the previously identified candidates that could cause a genetic variation in individuals and an association to their susceptibility to mastitis disease.

Genomic structural variants constrain and facilitate adaptation in natural populations of Theobroma cacao, the chocolate tree

Genomic structural variants (SVs) can play important roles in adaptation and speciation. Yet the overall fitness effects of SVs are poorly understood, partly because accurate population-level identification of SVs requires multiple high-quality genome assemblies. Here, we use 31 chromosome-scale, haplotype-resolved genome assemblies of Theobroma cacao-an outcrossing, long-lived tree species that is the source of chocolate-to investigate the fitness consequences of SVs in natural populations. Among the 31 accessions, we find over 160,000 SVs, which together cover eight times more of the genome than single-nucleotide polymorphisms and short indels (125 versus 15 Mb). Our results indicate that a vast majority of these SVs are deleterious: they segregate at low frequencies and are depleted from functional regions of the genome. We show that SVs influence gene expression, which likely impairs gene function and contributes to the detrimental effects of SVs. We also provide empirical support for a theoretical prediction that SVs, particularly inversions, increase genetic load through the accumulation of deleterious nucleotide variants as a result of suppressed recombination. Despite the overall detrimental effects, we identify individual SVs bearing signatures of local adaptation, several of which are associated with genes differentially expressed between populations. Genes involved in pathogen resistance are strongly enriched among these candidates, highlighting the contribution of SVs to this important local adaptation trait. Beyond revealing empirical evidence for the evolutionary importance of SVs, these 31 de novo assemblies provide a valuable resource for genetic and breeding studies in Tcacao.

Aperture: alignment-free detection of structural variations and viral integrations in circulating tumor DNA.

The identification of structural variations (SVs) and viral integrations in circulating tumor DNA (ctDNA) is a key step in precision oncology that may assist clinicians in treatment selection and monitoring. However, due to the short fragment size of ctDNA, it is challenging to accurately detect low-frequency SVs or SVs involving complex junctions in ctDNA sequencing data. Here, we describe Aperture, a new fast SV caller that applies a unique strategy of $k$-mer-based searching, binary label-based breakpoint detection and candidate clustering to detect SVs and viral integrations with high sensitivity, especially when junctions span repetitive regions. Aperture also employs a barcode-based filter to ensure specificity. Compared with existing methods, Aperture exhibits superior sensitivity and specificity in simulated, reference and real data tests, especially at low dilutions. Additionally, Aperture is able to predict sites of viral integration and identify complex SVs involving novel insertions and repetitive sequences in real patient data. Aperture is freely available at https://github.com/liuhc8/Aperture.

Identification of structural variation and polymorphisms of a sex co-segregating scaffold in spinach

Spinach is a common vegetable, and dioecy is maintained by a pair of XY sex chromosomes. Due to limited genomic resources and its highly repetitive genome, limited studies were conducted to investigate the genomic landscape of the region near sex-determining loci. In this study, we screened the structure variations (SVs) between Y-linked contigs and a 1.78-Mb X scaffold (Super_scaffold 66), which enabled the development of 12 sex co-segregating DNA markers. These markers were tested in one F1 mapping population and 40 spinach accessions, which comprised 692 individual plants with the strong sex linkage pattern. In addition, we found that Super_scaffold 66 was highly repetitive along with the enriched LTR-RTs insertions and decreased microsatellite distribution compared with the rest genome, which matches extremely low gene density featured by only nine annotated genes. Synteny analysis between Y contigs and Superscaffold_66 revealed a 340-Kb accumulative Y contig (non-continuous) and a 500-Kb X counterpart along with SVs and wide-spread tandem duplications. Among the nine genes, one ABC transporter gene revealed noticeable SVs between Y contig and X counterpart, as an approximate 5-Kb recent Gypsy LTR-RT insertion in the Y-linked allele, but not the X allele. The gene paucity, SVs, and sex-linked polymorphisms attributed to the recombination suppression. We proposed that Super_scaffold 66 is part of the non-recombining region containing the sex determination genes. The spread of 12 sex co-segregating markers from this 1.78Mb genomic region indicated the existence and expansion of sex determination region during progression of the Y chromosome.

Structural Variations of the 3D Genome Architecture in Cervical Cancer Development.

Human papillomavirus (HPV) integration is the major contributor to cervical cancer (CC) development by inducing structural variations (SVs) in the human genome. SVs are directly associated with the three-dimensional (3D) genome structure leading to cancer development. The detection of SVs is not a trivial task, and several genome-wide techniques have greatly helped in the identification of SVs in the cancerous genome. However, in cervical cancer, precise prediction of SVs mainly translocations and their effects on 3D-genome and gene expression still need to be explored. Here, we have used high-throughput chromosome conformation capture (Hi-C) data of cervical cancer to detect the SVs, especially the translocations, and validated it through whole-genome sequencing (WGS) data. We found that the cervical cancer 3D-genome architecture rearranges itself as compared to that in the normal tissue, and 24% of the total genome switches their A/B compartments. Moreover, translocation detection from Hi-C data showed the presence of high-resolution t(4;7) (q13.1; q31.32) and t(1;16) (q21.2; q22.1) translocations, which disrupted the expression of the genes located at and nearby positions. Enrichment analysis suggested that the disrupted genes were mainly involved in controlling cervical cancer-related pathways. In summary, we detect the novel SVs through Hi-C data and unfold the association among genome-reorganization, translocations, and gene expression regulation. The results help understand the underlying pathogenicity mechanism of SVs in cervical cancer development and identify the targeted therapeutics against cervical cancer.

Genomics and Marker-Assisted Improvement of Vegetable Crops

Vegetables are an integral part of the human diet worldwide. Traditional breeding approaches have been used extensively to develop new cultivars of vegetables with desirable characteristics, including resistance/tolerance to biotic and abiotic stresses, high yield, and an elevated content of compounds beneficial to human health. The technological progress since the early 1980s has revolutionized our ability to study and manipulate genetic variation in crop plants. The development of high-throughput sequencing platforms and accompanying analytical methods have led to sequencing and assembly of a large number of plant genomes, construction of dense and ultra-dense molecular linkage maps, identification of structural variants, and application of molecular markers in breeding programs. Linkage mapping and genome-wide association mapping studies have been used to identify chromosomal locations of genes and QTLs associated with plant phenotypic variations important for crop improvement. This review provides up-to-date information on the status of genomics and marker-assisted improvement of vegetable crops with the focus on tomato, pepper, eggplant, lettuce, spinach, cucumber, and chicory. For each vegetable crop, we present the most recent information on genetic resources, mapping populations, genetic maps, genome sequences, mapped genes and QTLs, the status of marker-assisted selection and genomic selection, and discuss future research prospects and application of novel techniques and approaches.

Fast and Accurate Algorithms for Mapping and Aligning Long Reads.

For DNA sequence analysis, we are facing challenging tasks such as the identification of structural variants, sequencing repetitive regions, and phasing of alleles. Those challenging tasks suffer from the short length of sequencing reads, where each read may cover less than 2 single nucleotide polymorphism (SNP), or less than two occurrences of a repeated region. It is believed that long reads can help to solve those challenging tasks. In this study, we have designed new algorithms for mapping long reads to reference genomes. We have also designed efficient and effective heuristic algorithms for local alignments of long reads against the corresponding segments of the reference genome. To design the new mapping algorithm, we formulate the problem as the longest common subsequence with distance constraints. The local alignment heuristic algorithm is based on the idea of recursive alignment of k-mers, where the size of k differs in each round. We have implemented all the algorithms in C++ and produce a software package named mapAlign. Experiments on real data sets showed that the newly proposed approach can generate better alignments in terms of both identity and alignment scores for both Nanopore and single molecule real time sequencing (SMRT) data sets. For human individuals of both Nanopore and SMRT data sets, the new method can successfully math/align 91.53% and 85.36% of letters from reads to identical letters on reference genomes, respectively. In comparison, the best known method can only align 88.44% and 79.08% letters of reads for Nanopore and SMRT data sets, respectively. Our method is also faster than the best known method.

Re-evaluation of single nucleotide variants and identification of structural variants in a cohort of 45 sudden unexplained death cases

Sudden unexplained death (SUD) takes up a considerable part in overall sudden death cases, especially in adolescents and young adults. During the past decade, many channelopathy- and cardiomyopathy-associated single nucleotide variants (SNVs) have been identified in SUD studies by means of postmortem molecular autopsy, yet the number of cases that remain inconclusive is still high. Recent studies had suggested that structural variants (SVs) might play an important role in SUD, but there is no consensus on the impact of SVs on inherited cardiac diseases. In this study, we searched for potentially pathogenic SVs in 244 genes associated with cardiac diseases. Whole-exome sequencing and appropriate data analysis were performed in 45 SUD cases. Re-analysis of the exome data according to the current ACMG guidelines identified 14 pathogenic or likely pathogenic variants in 10 (22.2%) out of the 45 SUD cases, whereof 2 (4.4%) individuals had variants with likely functional effects in the channelopathy-associated genes SCN5A and TRDN and 1 (2.2%) individual in the cardiomyopathy-associated gene DTNA. In addition, 18 structural variants (SVs) were identified in 15 out of the 45 individuals. Two SVs with likely functional impairment were found in the coding regions of PDSS2 and TRPM4 in 2 SUD cases (4.4%). Both were identified as heterozygous deletions, which were confirmed by multiplex ligation-dependent probe amplification. In conclusion, our findings support that SVs could contribute to the pathology of the sudden death event in some of the cases and therefore should be investigated on a routine basis in suspected SUD cases.

EP436 - Identification of structural variation in constitutional disorders by optical genome mapping

eP436 - Identification of structural variation in constitutional disorders by optical genome mapping

EP501 - Generation of a prenatal workflow for identification of structural variation by Optical Genome Mapping (OGM)

eP501 - Generation of a prenatal workflow for identification of structural variation by Optical Genome Mapping (OGM)

Sat-BSA: an NGS-based method using local de novo assembly of long reads for rapid identification of genomic structural variations associated with agronomic traits.

Advances in next generation sequencing (NGS)-based methodologies have accelerated the identifications of simple genetic variants such as point mutations and small insertions/deletions (InDels). Structural variants (SVs) including large InDels and rearrangements provide vital sources of genetic diversity for plant breeding. However, their analysis remains a challenge due to their complex nature. Consequently, novel NGS-based approaches are needed to rapidly and accurately identify SVs. Here, we present an NGS-based bulked-segregant analysis (BSA) technique called Sat-BSA (SVs associated with traits) for identifying SVs controlling traits of interest in crops. Sat-BSA targets allele frequencies at all SNP positions to first identify candidate genomic regions associated with a trait, which is then reconstructed by long reads-based local de novo assembly. Finally, the association between SVs, RNA-seq-based gene expression patterns and trait is evaluated for multiple cultivars to narrow down the candidate genes. We applied Sat-BSA to segregating F2 progeny obtained from crosses between turnip cultivars with different tuber colors and successfully isolated two genes harboring SVs that are responsible for tuber phenotypes. The current study demonstrates the utility of Sat-BSA for the identification of SVs associated with traits of interest in species with large and heterozygous genomes.

Structural Variants Create New Topological-Associated Domains and Ectopic Retinal Enhancer-Gene Contact in Dominant Retinitis Pigmentosa

SummaryThe cause of autosomal-dominant retinitis pigmentosa (adRP), which leads to loss of vision and blindness, was investigated in families lacking a molecular diagnosis. A refined locus for adRP on Chr17q22 (RP17) was delineated through genotyping and genome sequencing, leading to the identification of structural variants (SVs) that segregate with disease. Eight different complex SVs were characterized in 22 adRP-affected families with >300 affected individuals. All RP17 SVs had breakpoints within a genomic region spanning YPEL2 to LINC01476. To investigate the mechanism of disease, we reprogrammed fibroblasts from affected individuals and controls into induced pluripotent stem cells (iPSCs) and differentiated them into photoreceptor precursor cells (PPCs) or retinal organoids (ROs). Hi-C was performed on ROs, and differential expression of regional genes and a retinal enhancer RNA at this locus was assessed by qPCR. The epigenetic landscape of the region, and Hi-C RO data, showed that YPEL2 sits within its own topologically associating domain (TAD), rich in enhancers with binding sites for retinal transcription factors. The Hi-C map of RP17 ROs revealed creation of a neo-TAD with ectopic contacts between GDPD1 and retinal enhancers, and modeling of all RP17 SVs was consistent with neo-TADs leading to ectopic retinal-specific enhancer-GDPD1 accessibility. qPCR confirmed increased expression of GDPD1 and increased expression of the retinal enhancer that enters the neo-TAD. Altered TAD structure resulting in increased retinal expression of GDPD1 is the likely convergent mechanism of disease, consistent with a dominant gain of function. Our study highlights the importance of SVs as a genomic mechanism in unsolved Mendelian diseases.

Comprehensive analysis of structural variants in breast cancer genomes using single-molecule sequencing.

Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of the disease and its progression. We performed whole-genome sequencing of the SKBR3 breast cancer cell line and patient-derived tumor and normal organoids from two breast cancer patients using Illumina/10x Genomics, Pacific Biosciences (PacBio), and Oxford Nanopore Technologies (ONT) sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings show that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long reads even at relatively low coverage (25×–30×). Furthermore, we integrated SV and CNV data into a unifying karyotype-graph structure to present a more accurate representation of the mutated cancer genomes. We find hundreds of variants within known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.

Resolving the dark matter of ABCA4 for 1054 Stargardt disease probands through integrated genomics and transcriptomics

PurposeMissing heritability in human diseases represents a major challenge, and this is particularly true for ABCA4-associated Stargardt disease (STGD1). We aimed to elucidate the genomic and transcriptomic variation in 1054 unsolved STGD and STGD-like probands. MethodsSequencing of the complete 128-kb ABCA4 gene was performed using single-molecule molecular inversion probes (smMIPs), based on a semiautomated and cost-effective method. Structural variants (SVs) were identified using relative read coverage analyses and putative splice defects were studied using in vitro assays. ResultsIn 448 biallelic probands 14 known and 13 novel deep-intronic variants were found, resulting in pseudoexon (PE) insertions or exon elongations in 105 alleles. Intriguingly, intron 13 variants c.1938-621G>A and c.1938-514G>A resulted in dual PE insertions consisting of the same upstream, but different downstream PEs. The intron 44 variant c.6148-84A>T resulted in two PE insertions and flanking exon deletions. Eleven distinct large deletions were found, two of which contained small inverted segments. Uniparental isodisomy of chromosome 1 was identified in one proband. ConclusionDeep sequencing of ABCA4 and midigene-based splice assays allowed the identification of SVs and causal deep-intronic variants in 25% of biallelic STGD1 cases, which represents a model study that can be applied to other inherited diseases.

Hi-C Identifies Complex Genomic Rearrangements and TAD-Shuffling in Developmental Diseases

Genome-wide analysis methods, such as array comparative genomic hybridization (CGH) and whole-genome sequencing (WGS), have greatly advanced the identification of structural variants (SVs) in the human genome. However, even with standard high-throughput sequencing techniques, complex rearrangements with multiple breakpoints are often difficult to resolve, and predicting their effects on gene expression and phenotype remains a challenge. Here, we address these problems by using high-throughput chromosome conformation capture (Hi-C) generated from cultured cells of nine individuals with developmental disorders (DDs). Three individuals had previously been identified as harboring duplications at the SOX9 locus and six had been identified with translocations. Hi-C resolved the positions of the duplications and was instructive in interpreting their distinct pathogenic effects, including the formation of new topologically associating domains (neo-TADs). Hi-C was very sensitive in detecting translocations, and it revealed previously unrecognized complex rearrangements at the breakpoints. In several cases, we observed the formation of fused-TADs promoting ectopic enhancer-promoter interactions that were likely to be involved in the disease pathology. In summary, we show that Hi-C is a sensible method for the detection of complex SVs in a clinical setting. The results help interpret the possible pathogenic effects of the SVs in individuals with DDs.

Identifying barley pan-genome sequence anchors using genetic mapping and machine learning.

We identified 1.844 million barley pan-genome sequence anchors from 12,306 genotypes using genetic mapping and machine learning. There is increasing evidence that genes from a given crop genotype are far to cover all genes in that species; thus, building more comprehensive pan-genomes is of great importance in genetic research and breeding. Obtaining a thousand-genotype scale pan-genome using deep-sequencing data is currently impractical for species like barley which has a huge and highly repetitive genome. To this end, we attempted to identify barley pan-genome sequence anchors from a large quantity of genotype-by-sequencing (GBS) datasets by combining genetic mapping and machine learning algorithms. Based on the GBS sequences from 11,166 domesticated and 1140 wild barley genotypes, we identified 1.844 million pan-genome sequence anchors. Of them, 532,253 were identified as presence/absence variation (PAV) tags. Through aligning these PAV tags to the genome of hulless barley genotype Zangqing320, our analysis resulted in a validation of 83.6% of them from the domesticated genotypes and 88.6% from the wild barley genotypes. Association analyses against flowering time, plant height and kernel size showed that the relative importance of the PAV and non-PAV tags varied for different traits. The pan-genome sequence anchors based on GBS tags can facilitate the construction of a comprehensive pan-genome and greatly assist various genetic studies including identification of structural variation, genetic mapping and breeding in barley.

Sudden death in epilepsy and ectopic neurohypophysis in Joubert syndrome 23 diagnosed using SNVs/indels and structural variants pipelines on WGS data: a case report

BackgroundJoubert syndrome (JBTS) is a genetically heterogeneous group of neurodevelopmental syndromes caused by primary cilia dysfunction. Usually the neurological presentation starts with abnormal neonatal breathing followed by muscular hypotonia, psychomotor delay, and cerebellar ataxia. Cerebral MRI shows mid- and hindbrain anomalies including the molar tooth sign. We report a male patient with atypical presentation of Joubert syndrome type 23, thus expanding the phenotype.Case presentationClinical features were consistent with JBTS already from infancy, yet the syndrome was not suspected before cerebral MRI later in childhood showed the characteristic molar tooth sign and ectopic neurohypophysis. From age 11 years seizures developed and after few years became increasingly difficult to treat, also related to inadequate compliance to therapy. He died at 23 years of sudden unexpected death in epilepsy (SUDEP). The genetic diagnosis remained elusive for many years, despite extensive genetic testing. We reached the genetic diagnosis by performing whole genome sequencing of the family trio and analyzing the data with the combination of one analysis pipeline for single nucleotide variants (SNVs)/indels and one for structural variants (SVs). This lead to the identification of the most common variant detected in patients with JBTS23 (OMIM# 616490), rs534542684, in compound heterozygosity with a 8.3 kb deletion in KIAA0586, not previously reported.ConclusionsWe describe for the first time ectopic neurohypophysis and SUDEP in JBTS23, expanding the phenotype of this condition and raising the attention on the possible severity of the epilepsy in this disease. We also highlight the diagnostic power of WGS, which efficiently detects SNVs/indels and in addition allows the identification of SVs.

Intansv: an R package for integrative analysis of structural variations.

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.

Identification of Structural Variants in Two Novel Genomes of Maize Inbred Lines Possibly Related to Glyphosate Tolerance.

To study genetic variations between genomes of plants that are naturally tolerant and sensitive to glyphosate, we used two Zea mays L. lines traditionally bred in Poland. To overcome the complexity of the maize genome, two sequencing technologies were employed: Illumina and Single Molecule Real-Time (SMRT) PacBio. Eleven thousand structural variants, 4 million SNPs and approximately 800 thousand indels differentiating the two genomes were identified. Detailed analyses allowed to identify 20 variations within the EPSPS gene, but all of them were predicted to have moderate or unknown effects on gene expression. Other genes of the shikimate pathway encoding bifunctional 3-dehydroquinate dehydratase/shikimate dehydrogenase and chorismate synthase were altered by variants predicted to have a high impact on gene expression. Additionally, high-impact variants located within the genes involved in the active transport of glyphosate through the cell membrane encoding phosphate transporters as well as multidrug and toxic compound extrusion have been identified.

SVXplorer: Three-tier approach to identification of structural variants via sequential recombination of discordant cluster signatures.

The identification of structural variants using short-read data remains challenging. Most approaches that use discordant paired-end sequences ignore non-trivial signatures presented by variants containing 3 breakpoints, such as those generated by various copy-paste and cut-paste mechanisms. This can result in lower precision and sensitivity in the identification of the more common structural variants such as deletions and duplications. We present SVXplorer, which uses a graph-based clustering approach streamlined by the integration of non-trivial signatures from discordant paired-end alignments, split-reads and read depth information to improve upon existing methods. We show that SVXplorer is more sensitive and precise compared to several existing approaches on multiple real and simulated datasets. SVXplorer is available for download at https://github.com/kunalkathuria/SVXplorer.