Large-scale Structural Variations Research Articles

Limitations of homologous recombination status testing and poly (ADP-ribose) polymerase inhibitor treatment in the current management of ovarian cancer.

Homologous recombination (HR) is a highly conserved DNA repair system, in which aberrations can lead to the accumulation of DNA damage and genomic scars known as homologous recombination deficiency (HRD). The identification of mutations in key genes (i.e., BRCA1, and BRCA2 (BRCA)) and the quantification of large-scale structural variants (e.g., loss of heterozygosity) are indicators of the HRD phenotype. HRD is a stable biomarker and remains unchanged during recurrence, but fails to reveal the molecular profile of tumor progression. Moreover, interpretation of the current HRD score lacks comprehensiveness, especially for the HR-proficient group. Poly (ADP-ribose) polymerase (PARP) enzymes play an important role in the repair of DNA single-strand breaks, the blockage of which using PARP inhibitors (PARPi) can generate synthetic lethality in cancer cells with HRD. Although numerous studies have demonstrated that the benefit of PARPi is substantial in ovarian cancer (OC) patients, the efficacy is limited by the development of resistance, and seems to be irrespective of HR and/or BRCA mutation status. Moreover, in addition to improving progression-free survival, long-term benefit as overall survival brought by PARPi for advanced, recurrent and refractory OC patients remains unclear. Therefore, further investigations are needed to uncover the role of HR genes beyond BRCA and their interactions with other oncogenic pathways, to determine the value of HRD in the recurrent setting, and to identify alternative strategies for the precise management of advanced, refractory OC patients.

Genomic variation of 363 diverse tea accessions unveils the genetic diversity, domestication, and structural variations associated with tea adaptation.

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.

DNA structural features and variability of complete MHC locus sequences.

The major histocompatibility (MHC) locus, also known as the Human Leukocyte Antigen (HLA) genes, is located on the short arm of chromosome 6, and contains three regions (Class I, Class II and Class III). This 5Mbp locus is one of the most variable regions of the human genome, yet it also encodes a set of highly conserved and important proteins related to immunological response. Genetic variations in this region are responsible for more diseases than in the entire rest of the human genome. However, information on local structural features of the DNA is largely ignored. With recent advances in long-read sequencing technology, it is now becoming possible to sequence the entire 5Mbp MHC locus, producing complete diploid haplotypes of the whole region. Here, we describe structural maps based on the complete sequences from six different homozygous HLA cell lines. We find long-range structural variability in the different sequences for DNA stacking energy, position preference and curvature, variation in repeats, as well as more local changes in regions forming open chromatin structures, likely to influence gene expression levels. These structural maps can be useful in visualizing large scale structural variation across HLA types, in particular when this can be complemented with epigenetic signals.

Genomic insights into ecological adaptation of oaks revealed by phylogenomic analysis of multiple species

Understanding the ecological adaptation of tree species can not only reveal the evolutionary potential but also benefit biodiversity conservation under global climate change. Quercus is a keystone genus in Northern Hemisphere forests, and its wide distribution in diverse ecosystems and long evolutionary history make it an ideal model for studying the genomic basis of ecological adaptations. Here we used a newly sequenced genome of Quercus gilva, an evergreen oak species from East Asia, with 18 published Fagales genomes to determine how Fagaceae genomes have evolved, identify genomic footprints of ecological adaptability in oaks in general, as well as between evergreen and deciduous oaks. We found that oak species exhibited a higher degree of genomic conservation and stability, as indicated by the absence of large-scale chromosomal structural variations or additional whole-genome duplication events. In addition, we identified expansion and tandem repetitions within gene families that contribute to plant physical and chemical defense (e.g., cuticle biosynthesis and oxidosqualene cyclase genes), which may represent the foundation for the ecological adaptation of oak species. Circadian rhythm and hormone-related genes may regulate the habits of evergreen and deciduous oaks. This study provides a comprehensive perspective on the ecological adaptations of tree species based on phylogenetic, genome evolutionary, and functional genomic analyses.

Abstract 2934: Somatic variant workflow with HiFi sequencing provides new insights in highly challenging cancer cases

Abstract Tumor evolution is a highly heterogeneous process where multiple oncogenic pathways can lead to host defense evasion. Advancements in genome sequencing are allowing us to better understand these processes and their impact. However, critical genomic variations that could be pivotal to the development of tumors may have remained undetected due to technological constraints of short-read sequencing. PacBio HiFi sequencing generates accurate (>99.9%) long reads (>15 kb) with native 5-methylcytosine information that can comprehensively delineate many variations, including ones which were previously inaccessible with short-read sequencing. Unlike standard whole-genome analysis, cancer variant calling must account for somatic variation, where the assumptions of a diploid genome are violated. We have developed and optimized a bioinformatics workflow for somatic variant detection with HiFi sequence data. To validate this pipeline, we sequenced two well-studied cancer cell lines (COLO829, HCC1395) to 60-fold depth and their matched normal lymphoblast cells (40-fold to 60-fold depth) and called all classes of variations (SNVs, INDELS, and structural variants). Next, we compared our calls against the Valle-Inclan (structural variants) and SEQC2 (small variants: SNV/INDEL) datasets. We achieved 92% F1 score for small variants across all variant allele frequencies (VAF) in the HCC1395 experiment. We observed a maintained accuracy (F1=91%) even at lower variant frequencies (10-20), highlighting the ability of HiFi sequencing to detect subclonal mutations. The workflow calls structural variants with high sensitivity, capturing 57/62 (92%) of all previously validated SVs in COLO829 at all VAF. Lastly, we applied our pipeline to five diverse tumor samples that exhibit complex oncogenic phenotypes including homologous recombination deficiency (HRD) and high genomic instability, e.g. unresolved rearrangement breakpoints in repetitive regions and unknown oncogenic drivers when prior sequencing efforts did not provide full clarity as to the molecular drivers of tumorigenesis. Notably, we were able to identify and phase 5mC methylation of promoters together with large-scale structural variants in cancer genes involved in HRD. Taken together, we demonstrated the high accuracy of HiFi reads in resolving somatic variants and its potential to provide novel insights in complex cancer samples. The ability for long reads to resolve complex genomics aberrations and epigenetic markers that underly the tumorigenesis process will become indispensable in the realm of precision oncology. Citation Format: Khi Pin Chua, Ian McLaughlin, Oliver Hofmann, Kym Pham Stewart, Primo Baybayan, Jonathan Bibliowicz, Sean Grimmond, Zev Kronenberg, Michael A. Eberle. Somatic variant workflow with HiFi sequencing provides new insights in highly challenging cancer cases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2934.

Short-read whole genome sequencing identifies causative variants in most individuals with previously unexplained aniridia

BackgroundClassic aniridia is a highly penetrant autosomal dominant disorder characterised by congenital absence of the iris, foveal hypoplasia, optic disc anomalies and progressive opacification of the cornea. >90% of cases...

VariantDetective: an accurate all-in-one pipeline for detecting consensus bacterial SNPs and SVs.

Genomic variations comprise a spectrum of alterations, ranging from single nucleotide polymorphisms (SNPs) to large-scale structural variants (SVs), which play crucial roles in bacterial evolution and species diversification. Accurately identifying SNPs and SVs is beneficial for subsequent evolutionary and epidemiological studies. This study presents VariantDetective (VD), a novel, user-friendly, and all-in-one pipeline combining SNP and SV calling to generate consensus genomic variants using multiple tools. The VD pipeline accepts various file types as input to initiate SNP and/or SV calling, and benchmarking results demonstrate VD's robustness and high accuracy across multiple tested datasets when compared to existing variant calling approaches. The source code, test data, and relevant information for VD are freely accessible at https://github.com/OLF-Bioinformatics/VariantDetective under the MIT License.

Spatial and clonality-resolved 3D cancer genome alterations reveal enhancer-hijacking as a potential prognostic marker for colorectal cancer

The regulatory effect of non-coding large-scale structural variations (SVs) on proto-oncogene activation remains unclear. This study investigated SV-mediated gene dysregulation by profiling 3D cancer genome maps from 40 patients with colorectal cancer (CRC). We developed a machine learning-based method for spatial characterization of the altered 3D cancer genome. This revealed a frequent establishment of "de novo chromatin contacts" that can span multiple topologically associating domains (TADs) in addition to the canonical TAD fusion/shuffle model. Using this information, we precisely identified super-enhancer (SE)-hijacking and its clonal characteristics. Clonal SE-hijacking genes, such as TOP2B, are recurrently associated with cell-cycle/DNA-processing functions, which can potentially be used as CRC prognostic markers. Oncogene activation and increased drug resistance due to SE-hijacking were validated by reconstructing the patient's SV using CRISPR-Cas9. Collectively, the spatial and clonality-resolved analysis of the 3D cancer genome reveals regulatory principles of large-scale SVs in oncogene activation and their clinical implications.

De Novo Structural Variations of Escherichia coli Detected by Nanopore Long-Read Sequencing.

Spontaneous mutations power evolution, whereas large-scale structural variations (SVs) remain poorly studied, primarily because of the lack of long-read sequencing techniques and powerful analytical tools. Here, we explore the SVs of Escherichia coli by running 67 wild-type (WT) and 37 mismatch repair (MMR)-deficient (ΔmutS) mutation accumulation lines, each experiencing more than 4,000 cell divisions, by applying Nanopore long-read sequencing and Illumina PE150 sequencing and verifying the results by Sanger sequencing. In addition to precisely repeating previous mutation rates of base-pair substitutions and insertion and deletion (indel) mutation rates, we do find significant improvement in insertion and deletion detection using long-read sequencing. The long-read sequencing and corresponding software can particularly detect bacterial SVs in both simulated and real data sets with high accuracy. These lead to SV rates of 2.77 × 10-4 (WT) and 5.26 × 10-4 (MMR-deficient) per cell division per genome, which is comparable with previous reports. This study provides the SV rates of E. coli by applying long-read sequencing and SV detection programs, revealing a broader and more accurate picture of spontaneous mutations in bacteria.

Immune gene variation associated with chromosome-scale differences among individual zebrafish genomes

Immune genes have evolved to maintain exceptional diversity, offering robust defense against pathogens. We performed genomic assembly to examine immune gene variation in zebrafish. Gene pathway analysis identified immune genes as significantly enriched among genes with evidence of positive selection. A large subset of genes was absent from analysis of coding sequences due to apparent lack of reads, prompting us to examine genes overlapping zero coverage regions (ZCRs), defined as 2 kb stretches without mapped reads. Immune genes were identified as highly enriched within ZCRs, including over 60% of major histocompatibility complex (MHC) genes and NOD-like receptor (NLR) genes, mediators of direct and indirect pathogen recognition. This variation was most highly concentrated throughout one arm of chromosome 4 carrying a large cluster of NLR genes, associated with large-scale structural variation covering more than half of the chromosome. Our genomic assemblies uncovered alternative haplotypes and distinct complements of immune genes among individual zebrafish, including the MHC Class II locus on chromosome 8 and the NLR gene cluster on chromosome 4. While previous studies have shown marked variation in NLR genes between vertebrate species, our study highlights extensive variation in NLR gene regions between individuals of the same species. Taken together, these findings provide evidence of immune gene variation on a scale previously unknown in other vertebrate species and raise questions about potential impact on immune function.

Gossypium purpurascens genome provides insight into the origin and domestication of upland cotton

IntroductionAllotetraploid upland cotton (Gossypium hirsutum L.) is native to the Mesoamerican and Caribbean regions, had been improved in the southern United States by the mid-eighteenth century, was then dispersed worldwide. However, a Hainan Island Native Cotton (HIC) has long been grown extensively on Hainan Island, China. ObjectivesExplore HIC’s evolutionary relationship and genomic diversity with other tetraploid cottons, its origin and whether it was used for YAZHOUBU (Yazhou cloth, World Intangible Cultural Heritage) weaving, and the role of structural variations (SVs) in upland cotton domestication. MethodsWe assembled a high-quality genome of one HIC plant. We performed phylogenetic analysis, divergence time estimation, principal component analysis and population differentiation estimation using cotton assemblies and/or resequencing data. SVs were detected by whole-genome comparison. A F2 population was used for linkage analysis and to study effects of SVs. Buoyancy and salt water tolerance tests for seeds were conducted. ResultsWe found that the HIC belongs to G. purpurascens. G. purpurascens is best classified as a primitive race of G. hirsutum. The potential for long range transoceanic dispersal of G. purpurascens seeds was proved. A set of SVs, selective sweep regions between G. hirsutum races and cultivars, and quantitative trait loci (QTLs) of eleven agronomic traits were obtained. SVs, especially large-scale SVs, were found to have important effects on cotton domestication and improvement. Of them, eight large-scale inversions strongly associated with yield and fiber quality have probably undergone artificial selection in domestication. ConclusionG. purpurascens including HIC is a primitive race of G. hirsutum, probably disperse to Hainan from Central America by floating on ocean currents, may have been partly domesticated, planted and was likely used for YAZHOUBU weaving in Hainan much earlier than the Pre-Columbian period. SV plays an important role in cotton domestication and improvement.

Genetic Analysis and Fine Mapping of ZmGHT1 Conferring Glufosinate Herbicide Tolerance in Maize (Zea mays L.).

Weed interference in the crop field is one of the major biotic stresses causing dramatic crop yield losses, and the development of herbicide-resistant crops is critical for weed control in the application of herbicide technologies. To identify herbicide-resistant germplasms, we screened 854 maize inbreed lines and 25,620 seedlings by spraying them with 1 g/L glufosinate. One plant (L336R), possibly derived from a natural variation of line L336, was identified to have the potential for glufosinate tolerance. Genetic analysis validated that the glufosinate tolerance of L336R is conferred by a single locus, which was tentatively designated as ZmGHT1. By constructing a bi-parental population derived from L336R, and a glufosinate sensitive line L312, ZmGHT1 was mapped between molecular markers M9 and M10. Interestingly, genomic comparation between the two sequenced reference genomes showed that large scale structural variations (SVs) occurred within the mapped region, resulting in 2.16 Mb in the inbreed line B73, and 11.5 kb in CML277, respectively. During the fine mapping process, we did not detect any additional recombinant, even by using more than 9500 F2 and F3 plants, suspecting that SVs should also have occurred between L336R and L312 in this region, which inhibited recombination. By evaluating the expression of the genes within the mapped interval and using functional annotation, we predict that the gene Zm00001eb361930, encoding an aminotransferase, is the most likely causative gene. After glufosinate treatment, lower levels of ammonia content and a higher activity of glutamine synthetase (GS) in L336R were detected compared with those of L336 and L312, suggesting that the target gene may participate in ammonia elimination involving GS activity. Collectively, our study can provide a material resource for maize herbicide resistant breeding, with the potential to reveal a new mechanism for herbicide resistance.

BnVIR: bridging the genotype-phenotype gap to accelerate mining of candidate variations underlying agronomic traits in Brassica napus

BnVIR: bridging the genotype-phenotype gap to accelerate mining of candidate variations underlying agronomic traits in Brassica napus

Prostate Cancer Epigenetic Plasticity and Enhancer Heterogeneity: Molecular Causes, Consequences and Clinical Implications.

Prostate cancer (PCa) proliferation is dictated by androgen receptor (AR) signaling, which regulates gene expression through cis-regulatory regions including proximal and distal enhancers. The repertoire of AR interactions at enhancers is dependent on tissue and cellular contexts and thus shape a spectrum of phenotypes through such epigenetic heterogeneity. Moreover, PCa is a multifocal disease and displays a high degree of intra- and inter-tumor heterogeneity, adding to the phenotypic complexity. It is increasingly becoming clear that PCa may be considered an epigenetic disease caused by various molecular causes with profound consequences and clinical implications which are underpinned by enhancer interaction heterogeneity.In this review, we provide a detailed overview of molecular interactors that affect prostate cancer epigenetic heterogeneity, such as coding and non-coding somatic variants, large scale structural variations, pioneer factor binding at enhancers and various contexts that influence enhancer engagement heterogeneity in PCa development and progression. Finally, we explore how the vast heterogeneity in epigenetic profiles identified in recent omics studies results in distinct genomic subtypes which predict disease progression and thus offer opportunities in biomarker discovery and further personalizing cancer treatment. As such, heterogeneous enhancer interactions take center stage in elucidating mechanisms of prostate cancer progression, patient prognostication, therapy discovery and overcoming acquired treatment resistance.

Meerkat: An Algorithm to Reliably Identify Structural Variations and Predict Their Forming Mechanisms.

Next-generation sequencing technologies have been widely used to query genetic variants in normal individuals as well as in those with diseases. Large-scale structural variations are a common source of genetic diversity in human population, and some of them have significant contributions to the etiology of diseases. However, the detection of large-scale structural variations from sequencing data remains challenging. Here, we describe Meerkat-an algorithm which can reliably detect structural variations from Illumina short-read sequencing data at basepair resolution. A unique feature of Meerkat is that it can infer the variant forming mechanisms based on the DNA content and features at the breakpoints.

Applications of Optical Mapping for Plant Genome Assembly and Structural Variation Detection.

Optical mapping plays an important role in plant genomics, particularly in plant genome assembly and large-scale structural variation detection. While DNA sequencing provides base-by-base nucleotide information, optical mapping shows the physical locations of selected enzyme restriction sites in a genome. The long single-molecule maps produced by optical mapping make it a useful auxiliary technique to DNA sequencing, which generally cannot span large and complex genomic regions. Although optical mapping, therefore, offers unique advantages to researchers, there are few dedicated tools to assist in optical mapping analyses. In this chapter, we present runBNG2, a successor of runBNG to help optical-mapping data analysis for diverse datasets.

Optical Genome Mapping in Routine Human Genetic Diagnostics—Its Advantages and Limitations

In recent years, optical genome mapping (OGM) has developed into a highly promising method of detecting large-scale structural variants in human genomes. It is capable of detecting structural variants considered difficult to detect by other current methods. Hence, it promises to be feasible as a first-line diagnostic tool, permitting insight into a new realm of previously unknown variants. However, due to its novelty, little experience with OGM is available to infer best practices for its application or to clarify which features cannot be detected. In this study, we used the Saphyr system (Bionano Genomics, San Diego, CA, USA), to explore its capabilities in human genetic diagnostics. To this end, we tested 14 DNA samples to confirm a total of 14 different structural or numerical chromosomal variants originally detected by other means, namely, deletions, duplications, inversions, trisomies, and a translocation. Overall, 12 variants could be confirmed; one deletion and one inversion could not. The prerequisites for detection of similar variants were explored by reviewing the OGM data of 54 samples analyzed in our laboratory. Limitations, some owing to the novelty of the method and some inherent to it, were described. Finally, we tested the successful application of OGM in routine diagnostics and described some of the challenges that merit consideration when utilizing OGM as a diagnostic tool.

Impact of G-Quadruplexes and Chronic Inflammation on Genome Instability: Additive Effects during Carcinogenesis.

Genome instability is an enabling characteristic of cancer, essential for cancer cell evolution. Hotspots of genome instability, from small-scale point mutations to large-scale structural variants, are associated with sequences that potentially form non-B DNA structures. G-quadruplex (G4) forming motifs are enriched at structural variant endpoints in cancer genomes. Chronic inflammation is a physiological state underlying cancer development, and oxidative DNA damage is commonly invoked to explain how inflammation promotes genome instability. We summarize where G4s and oxidative stress overlap, with a focus on DNA replication. Guanine has low ionization potential, making G4s vulnerable to oxidative damage. Impacts to G4 structure are dependent upon lesion type, location, and G4 conformation. Occasionally, G4s pose a challenge to replicative DNA polymerases, requiring specialized DNA polymerases to maintain genome stability. Therefore, chronic inflammation creates a dual challenge for DNA polymerases to maintain genome stability: faithful G4 synthesis and bypassing unrepaired oxidative lesions. Inflammation is also accompanied by global transcriptome changes that may impact mutagenesis. Several studies suggest a regulatory role for G4s within cancer- and inflammatory-related gene promoters. We discuss the extent to which inflammation could influence gene regulation by G4s, thereby impacting genome instability, and highlight key areas for new investigation.

High-quality genome assembly and resequencing of modern cotton cultivars provide resources for crop improvement

Cotton produces natural fiber for the textile industry. The genetic effects of genomic structural variations underlying agronomic traits remain unclear. Here, we generate two high-quality genomes of Gossypium hirsutum cv. NDM8 and Gossypium barbadense acc. Pima90, and identify large-scale structural variations in the two species and 1,081 G. hirsutum accessions. The density of structural variations is higher in the D-subgenome than in the A-subgenome, indicating that the D-subgenome undergoes stronger selection during species formation and variety development. Many structural variations in genes and/or regulatory regions potentially influencing agronomic traits were discovered. Of 446 significantly associated structural variations, those for fiber quality and Verticillium wilt resistance are located mainly in the D-subgenome and those for yield mainly in the A-subgenome. Our research provides insight into the role of structural variations in genotype-to-phenotype relationships and their potential utility in crop improvement.

Mutational patterns and clonal evolution from diagnosis to relapse in pediatric acute lymphoblastic leukemia

The mechanisms driving clonal heterogeneity and evolution in relapsed pediatric acute lymphoblastic leukemia (ALL) are not fully understood. We performed whole genome sequencing of samples collected at diagnosis, relapse(s) and remission from 29 Nordic patients. Somatic point mutations and large-scale structural variants were called using individually matched remission samples as controls, and allelic expression of the mutations was assessed in ALL cells using RNA-sequencing. We observed an increased burden of somatic mutations at relapse, compared to diagnosis, and at second relapse compared to first relapse. In addition to 29 known ALL driver genes, of which nine genes carried recurrent protein-coding mutations in our sample set, we identified putative non-protein coding mutations in regulatory regions of seven additional genes that have not previously been described in ALL. Cluster analysis of hundreds of somatic mutations per sample revealed three distinct evolutionary trajectories during ALL progression from diagnosis to relapse. The evolutionary trajectories provide insight into the mutational mechanisms leading relapse in ALL and could offer biomarkers for improved risk prediction in individual patients.