Genomic Structural Variation Research Articles

Unexpectedly high prevalence of structural genomic variations in the Long QT Syndrome: evidence for broader clinical uptake

Abstract Background Long QT syndrome (LQTS) is an inherited channelopathy predisposing young and otherwise healthy individuals to ventricular arrhythmias causing syncope or sudden cardiac death. Point mutations in the KCNQ1, KCNH2, and SCN5A genes are the most common causes of LQTS, and up to 75% of patients can be genotyped by standard DNA sequencing. However, standard genetic testing fails to detect structural genomic rearrangements - including large deletions or duplications of DNA segments - known as copy number variants (CNVs). While previous studies suggested that CNVs account for less than 5% of genotype-negative cases(1-2), no recent data have been reported. Purpose The study aimed to determine the prevalence and spectrum of CNVs in LQTS susceptibility genes in unrelated patients who tested negative for point mutations in a panel of 16 genes associated with LQTS. Methods Next-generation sequencing (NGS) was used to screen CNVs in unrelated, clinically diagnosed LQTS patients without point mutations in 16 genes associated with LQTS. Loss of heterozygosity in LQTS-associated genes was used to assess the presence of CNVs using standard commercial software. The multiplex ligation-dependent probe amplification (MLPA) assay was used to confirm the CNVs identified by NGS. Results The cohort included 48 patients (63% women; mean age 31±19 years, range 3 years to 68 years) with definitive clinical diagnosis of LQTS (mean QTc 490±33 ms) according to the 2022 ESC guidelines(3). Overall, 7/48 patients (15%, 95% CI 6-28%) had CNVs. Six of the seven CNVs involved KCNQ1 in the heterozygous state, including three large deletions (exons 3-6, exons 12-15, and exon 16) and three duplications (exon 2, exons 3-6, and exons 3-15), whereas the remaining patient had a complete KCNH2 deletion. MLPA confirmed all CNVs identified by NGS. Of note, no CNVs were identified in LQTS-related genes whose pathogenicity has been questioned. Conclusions Our study highlights the unexpectedly high prevalence of structural genomic rearrangements in the KCNQ1 and KCNH2 genes in LQTS patients. Routine screening for copy number variants in LQTS patients is critical for accurate diagnosis, risk stratification, and personalized treatment strategies.Figure 1

High-Resolution Proximity-Guided Cytogenomics Improves Patient Stratification and Uncovers New Variants in Acute Myeloid Leukemia

Cytogenetic methods are a cornerstone of the modern diagnostic workflow for acute myeloid leukemia and related disorders. The goal of these methods is to identify structural genomic aberrations that drive the cancer or otherwise act as an indicator of patient risk. Despite their success, any one cytogenetic test is limited either in resolution, ability to provide unbiased survey of the genome, or ability to detect balanced aberrations. To address these limitations, we have applied proximity ligation sequencing (PLS) to characterize structural variants (SV) in AML genomes. PLS captures ultra-long-range sequence information without high-molecular-weight DNA and requires a modest (5-7x) sequence coverage of the genome. Applying this method to AML diagnostic specimens, we find that PLS identifies cytogenetically defined translocations (reciprocal and non-reciprocal) and inversions with specificity and sensitivity >0.95. The high resolution of PLS (<10kb) detected non-canonical variants missed by standard methods as well as structural variants below limits of detection by karyotyping, identifying variants in over half the patients previously determined to have a normal karyotype (Table 1). This included previously described variants of clinical significance as well as a recurrent inversion not previously described in AML. These observations highlight the effectiveness of PLS to provide high-resolution insights into known clinically relevant variants and discover variants missed by traditional methodologies.

11. Evaluation of Hi-C versus optical genome mapping for diagnosing constitutional genomic structural variants

11. Evaluation of Hi-C versus optical genome mapping for diagnosing constitutional genomic structural variants

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method — multiple genetic abnormality sequencing (MGA-Seq) — to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA’s transcriptional regulatory function.

Genomic vulnerability of a freshwater salmonid under climate change.

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.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize.

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Genome-wide analysis identifies non-reference transposable element polymorphisms associated with Parkinson’s disease

Parkinson’s disease (PD) is a common neurodegenerative disease that primarily affects the elderly, significantly impacting patients’ health and quality of life. While most genetic studies on PD have focused on single nucleotide polymorphisms, the effects of other forms of genomic variation in PD are yet to be fully elucidated. Transposable elements (TEs) are one of the main sources of human genome structural variation, with known associations with many human diseases. However, their potential connection to PD remains unclear. In this study, we investigated non-reference TE polymorphisms in three independent PD cohorts and explored their associations with both PD risk and progression. Our findings revealed that one non-reference TE is associated with the risk of PD, while two TEs are associated with disease progression. Furthermore, through expression quantitative trait locus (eQTL) analysis, we identified 18 cis TE-eQTLs in an interaction model and 290 cis TE-eQTLs in a non-interaction model. Several non-reference TE polymorphisms are correlated with specific PD-gene expression patterns in trans. These results indicate the feasibility of delving into the genetics of PD through the study of complex genomic variations. Advances in genomics research have the potential to deepen our understanding of this disease and pave the way for further translational medicine research in PD.

Searching for sequencing signal anomalies associated with genome structural variations

Genomic structural variations (SVs) are one of the main sources of genetic diversity. Structural variants as mutagens may have a significant impact on human health and lead to hereditary diseases and cancers. Existing methods of finding structural variants are based on analysis of high-throughput sequencing data and despite significant progress in the development of the detection methods, there is still a need for improving the identification of structural variations with accuracy appropriate for use in a diagnostic procedure. Analysis of the signal of sequencing coverage (i.e., the number of sequencing fragments that aligned to every point of a genome) holds new potential for the design of approaches for structural variations discovery, and can be used as time-series analysis. Here, we present an approach for identification of patterns in the coverage signal. The method has been developed based on algorithms used for analysis of time series data, namely KNN (K-nearest neighbour) search algorithm and the SAX (Symbolic Aggregation Approximation) method. Using the rich dataset encompassing full genomes of 911 individuals with different ethnic backgrounds generated by the Human Genome Diversity Project initiative, we constructed generalized patterns of signal coverage in the vicinity of breakpoints corresponding to various structural variant types. Also, with the benefit of the SAX models of the motifs we developed a software package for fast detection of anomalies in the coverage signal.

Genome-Wide Detection of Copy Number Variations Associated with Miniature Features in Horses.

Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9, and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.

A 4.43-Kb deletion of chromosomal segment containing an ovate family protein confers long capsule in sesame (Sesamum indicum L.).

A 4.43-Kb structural variation in the sesame genome results in the deletion of the Siofp1 gene and induces the long capsule length trait. Capsule length (CL) has a positive effect on seed weight and yield in various agronomically important species; however, the molecular mechanism underlying long capsule trait regulation in sesame remains unknown. The inheritance analysis showed that long capsule traits (CL > 4.0cm) were dominant over normal length (average CL = 3.0cm) and were controlled by a single gene pair. Association mapping with a RIL population and 259 natural sesame germplasm accessions indicated that the target interval was 52,830-730,961bp of SiChr.10 in sesame. Meanwhile, the structural variation (SV) of the association mapping revealed that only SV_414325 on chromosome 10 was significantly associated with the CL trait, with a P value of 1.1135E-19. SV_414325 represents a 4430-bp deletion from 414,325 to 418,756bp on SiChr.10, covering Sindi_2155000 (named SiOFP1). In the normal length type, Siofp1 encodes 411 amino acids of the ovate family proteins and is highly expressed in the leaf, stem, bud, and capsule tissues of sesame. In accordance with the transcriptional repressor character, Siofp1 overexpression in transgenic Arabidopsis (T0 and T1 generations) induced a 25-39% greater shortening of silique length than the wild type (P < 0.05), as well as round cauline leaves and short carpels. These results confirm that SiOFP1 plays a key role in regulating CL trait in sesame and other flowering plants. These findings provide a theoretical and material basis for sesame capsule development and high-yield breeding research.

Structural genomic variation and migratory behavior in a wild songbird.

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.

The pan-genome and local adaptation of Arabidopsis thaliana

Arabidopsis thaliana serves as a model species for investigating various aspects of plant biology. However, the contribution of genomic structural variations (SVs) and their associate genes to the local adaptation of this widely distribute species remains unclear. Here, we de novo assemble chromosome-level genomes of 32 A. thaliana ecotypes and determine that variable genes expand the gene pool in different ecotypes and thus assist local adaptation. We develop a graph-based pan-genome and identify 61,332 SVs that overlap with 18,883 genes, some of which are highly involved in ecological adaptation of this species. For instance, we observe a specific 332 bp insertion in the promoter region of the HPCA1 gene in the Tibet-0 ecotype that enhances gene expression, thereby promotes adaptation to alpine environments. These findings augment our understanding of the molecular mechanisms underlying the local adaptation of A. thaliana across diverse habitats.

Searching for Sequencing Signal Anomalies Associated with Genomic Structural Variations

Searching for Sequencing Signal Anomalies Associated with Genomic Structural Variations

Assessing the Expression of Long INterspersed Elements (LINEs) via Long-Read Sequencing in Diverse Human Tissues and Cell Lines.

Transposable elements, such as Long INterspersed Elements (LINEs), are DNA sequences that can replicate within genomes. LINEs replicate using an RNA intermediate followed by reverse transcription and are typically a few kilobases in length. LINE activity creates genomic structural variants in human populations and leads to somatic alterations in cancer genomes. Long-read RNA sequencing technologies, including Oxford Nanopore and PacBio, can directly sequence relatively long transcripts, thus providing the opportunity to examine full-length LINE transcripts. This study focuses on the development of a new bioinformatics pipeline for the identification and quantification of active, full-length LINE transcripts in diverse human tissues and cell lines. In our pipeline, we utilized RepeatMasker to identify LINE-1 (L1) transcripts from long-read transcriptome data and incorporated several criteria, such as transcript start position, divergence, and length, to remove likely false positives. Comparisons between cancerous and normal cell lines, as well as human tissue samples, revealed elevated expression levels of young LINEs in cancer, particularly at intact L1 loci. By employing bioinformatics methodologies on long-read transcriptome data, this study demonstrates the landscape of L1 expression in tissues and cell lines.

High levels of intra-strain structural variation in Drosophila simulans X pericentric heterochromatin.

Large genome structural variations can impact genome regulation and integrity. Repeat-rich regions like pericentric heterochromatin are vulnerable to structural rearrangements although we know little about how often these rearrangements occur over evolutionary time. Repetitive genome regions are particularly difficult to study with genomic approaches, as they are missing from most genome assemblies. However, cytogenetic approaches offer a direct way to detect large rearrangements involving pericentric heterochromatin. Here, we use a cytogenetic approach to reveal large structural rearrangements associated with the X pericentromeric region of Drosophila simulans. These rearrangements involve large blocks of satellite DNA-the 500-bp and Rsp-like satellites-which colocalize in the X pericentromeric heterochromatin. We find that this region is polymorphic not only among different strains, but between isolates of the same strain from different labs, and even within individual isolates. On the one hand, our observations raise questions regarding the potential impact of such variation at the phenotypic level and our ability to control for such genetic variability. On the other hand, this highlights the very rapid turnover of the pericentric heterochromatin most likely associated with genomic instability of the X pericentromere. It represents a unique opportunity to study the dynamics of pericentric heterochromatin, the evolution of associated satellites on a very short time scale, and to better understand how structural variation arises.

Comparative genomics analysis of three conserved plasmid families in the Western Hemisphere soft tick-borne relapsing fever borreliae provides insight into variation in genome structure and antigenic variation systems.

Borrelia spirochetes, causative agents of Lyme disease and relapsing fever (RF), have uniquely complex genomes, consisting of a linear chromosome and both circular and linear plasmids. The plasmids harbor genes important for the vector-host life cycle of these tick-borne bacteria. The role of plasmids from Lyme disease causing spirochetes is more refined compared to RF Borrelia because of limited plasmid-resolved genome assemblies for the latter. We recently addressed this limitation and found that three linear plasmid families (F6, F27, and F28) were syntenic across all the RF Borrelia species that we examined. Given this conservation, we further investigated the three plasmid families. The F6 family, also known as the megaplasmid, contained regions of repetitive DNA. The F27 was the smallest, encoding genes with unknown function. The F28 family encoded the putative expression locus for antigenic variation in all species except Borrelia hermsii and Borrelia anserina. Taken together, this work provides a foundation for future investigations to identify essential plasmid-localized genes that drive the vector-host life cycle of RF Borrelia. IMPORTANCE Borrelia spp. spirochetes are arthropod-borne bacteria found globally that infect humans and other vertebrates. RF borreliae are understudied and misdiagnosed pathogens because of the vague clinical presentation of disease and the elusive feeding behavior of argasid ticks. Consequently, genomics resources for RF spirochetes have been limited. Analyses of Borrelia plasmids have been challenging because they are often highly fragmented and unassembled in most available genome assemblies. By utilizing Oxford Nanopore Technologies, we recently generated plasmid-resolved genome assemblies for seven Borrelia spp. found in the Western Hemisphere. This current study is an in-depth investigation into the linear plasmids that were conserved and syntenic across species. We identified differences in genome structure and, importantly, in antigenic variation systems between species. This work is an important step in identifying crucial plasmid-localized genetic elements essential for the life cycle of RF spirochetes.

Detection of copy number variations based on a local distance using next-generation sequencing data.

As one of the main types of structural variation in the human genome, copy number variation (CNV) plays an important role in the occurrence and development of human cancers. Next-generation sequencing (NGS) technology can provide base-level resolution, which provides favorable conditions for the accurate detection of CNVs. However, it is still a very challenging task to accurately detect CNVs from cancer samples with different purity and low sequencing coverage. Local distance-based CNV detection (LDCNV), an innovative computational approach to predict CNVs using NGS data, is proposed in this work. LDCNV calculates the average distance between each read depth (RD) and its k nearest neighbors (KNNs) to define the distance of KNNs of each RD, and the average distance between the KNNs for each RD to define their internal distance. Based on the above definitions, a local distance score is constructed using the ratio between the distance of KNNs and the internal distance of KNNs for each RD. The local distance scores are used to fit a normal distribution to evaluate the significance level of each RDS, and then use the hypothesis test method to predict the CNVs. The performance of the proposed method is verified with simulated and real data and compared with several popular methods. The experimental results show that the proposed method is superior to various other techniques. Therefore, the proposed method can be helpful for cancer diagnosis and targeted drug development.

Identification of copy number variation in Tibetan sheep using whole genome resequencing reveals evidence of genomic selection

BackgroundCopy number variation (CNV) is an important source of structural variation in the mammalian genome. CNV assays present a new method to explore the genomic diversity of environmental adaptations in animals and plants and genes associated with complex traits. In this study, the genome-wide CNV distribution characteristics of 20 Tibetan sheep from two breeds (10 Oula sheep and 10 Panou sheep) were analysed using whole-genome resequencing to investigate the variation in the genomic structure of Tibetan sheep during breeding.ResultsCNVs were detected using CNVnator, and the overlapping regions of CNVs between individual sheep were combined. Among them, a total of 60,429 CNV events were detected between the indigenous sheep breed (Oula) and the synthetic sheep breed (Panou). After merging the overlapping CNVs, 4927 CNV regions (CNVRs) were finally obtained. Of these, 4559 CNVRs were shared by two breeds, and there were 368 differential CNVRs. Deletion events have a higher percentage of occurrences than duplication events. Functional enrichment analysis showed that the shared CNVRs were significantly enriched in 163 GO terms and 62 KEGG pathways, which were mainly associated with organ development, neural regulation, immune regulation, digestion and metabolism. In addition, 140 QTLs overlapped with some of the CNVRs at more than 1 kb, such as average daily gain QTL, body weight QTL, and total lambs born QTL. Many of the CNV-overlapping genes such as PPP3CA, SSTR1 and FASN, overlap with the average daily weight gain and carcass weight QTL regions. Moreover, VST analysis showed that XIRP2, ABCB1, CA1, ASPA and EEF2 differed significantly between the synthetic breed and local sheep breed. The duplication of the ABCB1 gene may be closely related to adaptation to the plateau environment in Panou sheep, which deserves further study. Additionally, cluster analysis, based on all individuals, showed that the CNV clustering could be divided into two origins, indicating that some Tibetan sheep CNVs are likely to arise independently in different populations and contribute to population differences.ConclusionsCollectively, we demonstrated the genome-wide distribution characteristics of CNVs in Panou sheep by whole genome resequencing. The results provides a valuable genetic variation resource and help to understand the genetic characteristics of Tibetan sheep. This study also provides useful information for the improvement and breeding of Tibetan sheep in the future.

Evolutionary origin of genomic structural variations in domestic yaks

Yak has been subject to natural selection, human domestication and interspecific introgression during its evolution. However, genetic variants favored by each of these processes have not been distinguished previously. We constructed a graph-genome for 47 genomes of 7 cross-fertile bovine species. This allowed detection of 57,432 high-resolution structural variants (SVs) within and across the species, which were genotyped in 386 individuals. We distinguished the evolutionary origins of diverse SVs in domestic yaks by phylogenetic analyses. We further identified 334 genes overlapping with SVs in domestic yaks that bore potential signals of selection from wild yaks, plus an additional 686 genes introgressed from cattle. Nearly 90% of the domestic yaks were introgressed by cattle. Introgression of an SV spanning the KIT gene triggered the breeding of white domestic yaks. We validated a significant association of the selected stratified SVs with gene expression, which contributes to phenotypic variations. Our results highlight that SVs of different origins contribute to the phenotypic diversity of domestic yaks.

Whole genome assessment of a declining game bird reveals cryptic genetic structure and insights for population management.

Population genomics applied to game species conservation can help delineate management units, ensure appropriate harvest levels and identify populations needing genetic rescue to safeguard their adaptive potential. The ruffed grouse (Bonasa umbellus) is rapidly declining in much of the eastern USA due to a combination of forest maturation and habitat fragmentation. More recently, mortality from West Nile Virus may have affected connectivity of local populations; however, genetic approaches have never explicitly investigated this issue. In this study, we sequenced 54 individual low-coverage (~5X) grouse genomes to characterize population structure, assess migration rates across the landscape to detect potential barriers to gene flow and identify genomic regions with high differentiation. We identified two genomic clusters with no clear geographic correlation, with large blocks of genomic differentiation associated with chromosomes 4 and 20, likely due to chromosomal inversions. After excluding these putative inversions from the data set, we found weak but nonsignificant signals of population subdivision. Estimated gene flow revealed reduced rates of migration in areas with extensive habitat fragmentation and increased genetic connectivity in areas with less habitat fragmentation. Our findings provide a benchmark for wildlife managers to compare and scale the genetic diversity and structure of ruffed grouse populations in Pennsylvania and across the eastern USA, and we also reveal structural variation in the grouse genome that requires further study to understand its possible effects on individual fitness and population distribution.