Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Visualization tools for human structural variations identified by whole-genome sequencing.

ABSTRACT: Visualizing structural variations (SVs) is a critical step for finding associations between SVs and human traits or diseases. Given that there are many sequencing platforms used for SV identification and given that how best to visualize SVs together with other data, such as read alignments and annotations, depends on research goals, there are dozens of SV visualization tools designed for different research goals and sequencing platforms. Here, we provide a comprehensive survey of over 30 SV visualization tools to help users choose which tools to use. This review targets users who wish to visualize a set of SVs identified from the massively parallel sequencing reads of an individual human genome. We first categorize the ways in which SV visualization tools display SVs into ten major categories, which we denote as view modules. View modules allow readers to understand the features of each SV visualization tool quickly. Next, we introduce the features of individual SV visualization tools from several aspects, including whether SV views are integrated with annotations, whether long-read alignment is displayed, whether underlying data structures are graph-based, the type of SVs shown, whether auditing is possible, whether bird's eye view is available, sequencing platforms, and the number of samples. We hope that this review will serve as a guide for readers on the currently available SV visualization tools and lead to the development of new SV visualization tools in the near future.

SUBMITTER: Yokoyama TT

PROVIDER: S-EPMC8075883 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Molecular characterization of PRKN structural variations identified through whole-genome sequencing.

Project description:BackgroundEarly-onset Parkinson's disease (PD) is the most common inherited form of parkinsonism, with the PRKN gene being the most frequently identified mutated. Exon rearrangements, identified in about 43.2% of the reported PD patients and with higher frequency in specific ethnicities, are the most prevalent PRKN mutations reported to date in PD patients.MethodsIn this study, three consanguineous families with early-onset PD were subjected to whole-genome sequencing (WGS) analyses that were followed by Sanger sequencing and droplet digital PCR to validate and confirm the disease segregation of the identified genomic variations and to determine their parental origin.ResultsFive different PRKN structural variations (SVs) were identified. Because the genomic sequences surrounding the break points of the identified SVs might hold important information about their genesis, these were also characterized for the presence of homology and repeated sequences.ConclusionWe concluded that all identified PRKN SVs might originate through retrotransposition events.

| S-EPMC6305656 | biostudies-literature

Whole Genome Sequencing Applied in Familial Hamartomatous Polyposis Identifies Novel Structural Variations.

Project description:Hamartomatous polyposis syndromes (HPS) are rare cancer-predisposing disorders including Juvenile polyposis (JPS), Peutz-Jeghers (PJS) and PTEN hamartomatous syndromes (PHS). Penetrant mutations in corresponding genes (SMAD4, BMPR1A, STK11, PTEN and AKT1), are usually diagnosed via a next-generation-sequencing gene panel (NGS-GP) for tailored surveillance and preimplantation testing for monogenic disorders (PGT-M). Five probands with HPS phenotype, with no genetic diagnosis per genetic workup, underwent whole-genome sequencing (WGS) that identified structural genetic alterations: two novel inversions in BMPRA1 and STK11, two BMPR1A-deletions, known as founders among Bukharan Jews, and BMPR1A microdeletion. BMPR1A inversion was validated by "junction fragment" amplification and direct testing. PGT-M was performed via multiplex-PCR and enabled successful birth of a non-carrier baby. WGS may be considered for HPS patients with no NGS-GP findings to exclude structural alterations.

| S-EPMC9407864 | biostudies-literature

Whole-Genome Sequencing Identified New Structural Variations in the <i>DMD</i> Gene That Cause Duchenne Muscular Dystrophy in Two Girls.

Project description:Dystrophinopathies are the most common muscle diseases, especially in men. In women, on the other hand, a manifestation of Duchenne muscular dystrophy is rare due to X-chromosomal inheritance. We present two young girls with severe muscle weakness, muscular dystrophies, and creatine kinase (CK) levels exceeding 10,000 U/L. In the skeletal muscle tissues, dystrophin staining reaction showed mosaicism. The almost entirely skewed X-inactivation in both cases supported the possibility of a dystrophinopathy. Despite standard molecular diagnostics (including multiplex ligation-dependent probe amplification (MLPA) and next generation sequencing (NGS) gene panel sequencing), the genetic cause of the girls' conditions remained unknown. However, whole-genome sequencing revealed two reciprocal translocations between their X chromosomes and chromosome 5 and chromosome 19, respectively. In both cases, the breakpoints on the X chromosomes were located directly within the DMD gene (in introns 54 and 7, respectively) and were responsible for the patients' phenotypes. Additional techniques such as Sanger sequencing, conventional karyotyping and fluorescence in situ hybridization (FISH) confirmed the disruption of DMD gene in both patients through translocations. These findings underscore the importance of accurate clinical data combined with histopathological analysis in pinpointing the suspected underlying genetic disorder. Moreover, our study illustrates the viability of whole-genome sequencing as a time-saving and highly effective method for identifying genetic factors responsible for complex genetic constellations in Duchenne muscular dystrophy (DMD).

| S-EPMC10488134 | biostudies-literature

Whole exome sequencing identified genetic variations in Chinese hemangioblastoma patients.

Project description:Hemangioblastomas (HBs) are uncommon tumors characterized by the presence of inactivating alterations in the von Hippel-Lindau (VHL) gene in inherited cases and by infrequent somatic mutation in sporadic entities. We performed whole exome sequencing on 11 HB patients to further elucidate the genetics of HBs. A total of 270 somatic variations in 219 genes, of which there were 86 mutations in 67 genes, were found in sporadic HBs, and 184 mutations were found in 154 genes in familial HBs. C: G>T: A and T: A>C: G mutations are relatively common in most HB patients. Genes harboring the most significant mutations include PCDH9, KLHL12, DCAF4L1, and VHL in sporadic HBs, and ZNF814, DLG2, RIMS1, PNN, and MUC7 in familial HBs. The frequency of CNV varied considerably within sporadic HBs but was relatively similar within familial HBs. Five genes, including OTOGL, PLCB4, SCEL, THSD4, and WWOX, have CNVs in the six patients with sporadic HBs, and three genes, including ABCA6, CWC27, and LAMA2, have CNVs in the five patients with familial HBs. We found new genetic mutations and CNVs that might be involved in HBs; these findings highlight the complexity of the tumorigenesis of HBs and pinpoint potential therapeutic targets for the treatment of HBs.

| S-EPMC5603408 | biostudies-literature

Whole genome sequencing of glioblastoma multiforme identifies multiple structural variations involved in EGFR activation.

Project description:Next generation sequencing has become a powerful tool in dissecting and identifying mutations and genomic structural variants that accompany tumourigenesis. Sequence analysis of glioblastoma multiforme (GBM) illustrates the ability to rapidly identify mutations that may affect phenotype. Approximately 50% of human GBMs overexpress epidermal growth factor receptor (EGFR) which renders the EGFR protein a compelling therapeutic target. In brain tumours, attempts to target EGFR as a cancer therapeutic, however, have achieved little or no benefit. The mechanisms that drive therapeutic resistance to EGFR inhibitors in brain tumours are not well defined, and drug resistance contributes to the deadly and aggressive nature of the disease. Whole genome sequencing of four primary GBMs revealed multiple pathways by which EGFR protein abundance becomes deregulated in these tumours and will guide the development of new strategies for treating EGFR overexpressing tumours. Each of the four tumours displayed a different mechanism leading to increased EGFR protein levels. One mechanism is mediated by gene amplification and tandem duplication of the kinase domain. A second involves an intragenic deletion that generates a constitutively active form of the protein. A third combines the loss of a gene which encodes a protein that regulates EGFR abundance as well as an miRNA that modulates EGFR expression. A fourth mechanism entails loss of an ubiquitin ligase docking site in the C-terminal part of the protein whose absence inhibits turnover of the receptor.

| S-EPMC4432462 | biostudies-literature

Whole-Genome Sequencing Reveals Diverse Models of Structural Variations in Esophageal Squamous Cell Carcinoma.

Project description:Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs.

| S-EPMC4746371 | biostudies-literature

Evaluation of tools for identifying large copy number variations from ultra-low-coverage whole-genome sequencing data.

Project description:BackgroundDetection of copy number variations (CNVs) from high-throughput next-generation whole-genome sequencing (WGS) data has become a widely used research method during the recent years. However, only a little is known about the applicability of the developed algorithms to ultra-low-coverage (0.0005-0.8×) data that is used in various research and clinical applications, such as digital karyotyping and single-cell CNV detection.ResultHere, the performance of six popular read-depth based CNV detection algorithms (BIC-seq2, Canvas, CNVnator, FREEC, HMMcopy, and QDNAseq) was studied using ultra-low-coverage WGS data. Real-world array- and karyotyping kit-based validation were used as a benchmark in the evaluation. Additionally, ultra-low-coverage WGS data was simulated to investigate the ability of the algorithms to identify CNVs in the sex chromosomes and the theoretical minimum coverage at which these tools can accurately function. Our results suggest that while all the methods were able to detect large CNVs, many methods were susceptible to producing false positives when smaller CNVs (< 2 Mbp) were detected. There was also significant variability in their ability to identify CNVs in the sex chromosomes. Overall, BIC-seq2 was found to be the best method in terms of statistical performance. However, its significant drawback was by far the slowest runtime among the methods (> 3 h) compared with FREEC (~ 3 min), which we considered the second-best method.ConclusionsOur comparative analysis demonstrates that CNV detection from ultra-low-coverage WGS data can be a highly accurate method for the detection of large copy number variations when their length is in millions of base pairs. These findings facilitate applications that utilize ultra-low-coverage CNV detection.

| S-EPMC8130438 | biostudies-literature

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genome.

Project description:We sequenced the genome of the Yoruban reference individual NA19240 on the long-read sequencing platform Oxford Nanopore PromethION for evaluation and benchmarking of recently published aligners and germline structural variant calling tools, as well as a comparison with the performance of structural variant calling from short-read sequencing data. The structural variant caller Sniffles after NGMLR or minimap2 alignment provides the most accurate results, but additional confidence or sensitivity can be obtained by a combination of multiple variant callers. Sensitive and fast results can be obtained by minimap2 for alignment and a combination of Sniffles and SVIM for variant identification. We describe a scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long-read genome sequencing of an individual or population. By discussing the results of this well-characterized reference individual, we provide an approximation of what can be expected in future long-read sequencing studies aiming for structural variant identification.

| S-EPMC6633254 | biostudies-literature

Pneumococcal 23B Molecular Subtype Identified Using Whole Genome Sequencing.

Project description:The polysaccharide capsule is a major virulence factor of Streptococcus pneumoniae and the target of all currently licensed pneumococcal vaccines. At present, there are 92 serologically distinct pneumococcal serotypes. Structural and antigenic variation of capsular types is the result of genetic variation within the capsular polysaccharide synthesis (CPS) locus; however, genetic variation may not always result in phenotypic differences which produce novel serotypes. With the introduction of high throughput whole genome sequencing, discovery of novel genotypic variants is not unexpected and this study describes a novel variant of the serotype 23B CPS operon. This novel variant was characterized as a novel genotypic subtype (23B1) with ?70% homology to the published 23B CPS sequence. High sequence variability was determined in eight cps genes involved in sugar biosynthesis. However, there was no distinction between the classic 23B serotype and 23B1 serologically or in terms of polysaccharide structure. Phylogenetic and eBURST analysis revealed a distinct lineage for 23B1 with multiple clones (UK, Thailand, and USA) that arose at different points during pneumococcal evolution. Analysis of the UK S. pneumoniae isolates (n?=?121) revealed an upsurge of 23B1 ST2372 in 2011, after which this previously unseen ST increased to reach 50% proportion of the 23B sequenced isolates from 2013 and remained prevalent within our sequenced isolates from later years. Therefore, although the 23B1 variant appears to have no phenotypic impact and cannot be considered as novel serotype, it appears to have led to a genetic restructuring of the UK serotype 23B population.

| S-EPMC5581491 | biostudies-literature

The MI bundle: enabling network and structural biology in genome visualization tools.

Project description:Prioritization of candidate genes emanating from large-scale screens requires integrated analyses at the genomics, molecular, network and structural biology levels. We have extended the Integrated Genome Browser (IGB) to facilitate these tasks. The graphical user interface greatly simplifies building disease networks and zooming in at atomic resolution to identify variations in molecular complexes that may affect molecular interactions in the context of genomic data. All results are summarized in genome tracks and can be visualized and analyzed at the transcript level.The MI Bundle is a plugin for the IGB. The plugin, help, video and tutorial are available at http://cru.genomics.iit.it/igbmibundle/ and https://github.com/CRUiit/igb-mi-bundle/wiki. The source code is released under the Apache License, Version 2.arnaud.ceol@iit.itSupplementary data are available at Bioinformatics online.

| S-EPMC4817051 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data