scholarly journals Long-read sequencing resolves structural variants in SERPINC1 causing antithrombin deficiency and identifies a complex rearrangement and a retrotransposon insertion not characterized by routine diagnostic methods

2020 ◽  
Author(s):  
Belén de la Morena-Barrio ◽  
Jonathan Stephens ◽  
María Eugenia de la Morena-Barrio ◽  
Luca Stefanucci ◽  
José Padilla ◽  
...  
Keyword(s):  
De Novo ◽  
Pcr Amplification ◽  
Diagnostic Techniques ◽  
Diagnostic Methods ◽  
Clinical Genetics ◽  
Type I ◽  
Structural Variants ◽  
Antithrombin Deficiency ◽  
Complex Rearrangement ◽  
Long Read

AbstractThe identification and characterization of structural variants (SVs) in clinical genetics have remained historically challenging as routine genetic diagnostic techniques have limited ability to evaluate repetitive regions and SVs. Long-read whole-genome sequencing (LR-WGS) has emerged as a powerful approach to resolve SVs. Here, we used LR-WGS to study 19 unrelated cases with type I Antithrombin Deficiency (ATD), the most severe thrombophilia, where routine molecular tests were either negative, ambiguous, or not fully characterized. We developed an analysis workflow to identify disease-associated SVs and resolved 10 cases. For the first time, we identified a germline complex rearrangement involved in ATD previously misclassified as a deletion. Additionally, we provided molecular diagnoses for two unresolved individuals that harbored a novel SINE-VNTR-Alu retroelement insertion that we fully characterized by de novo assembly and confirmed by PCR amplification in all affected relatives. Finally, the nucleotide-level resolution achieved for all the SVs allowed breakpoint analysis, which revealed a replication-based mechanism for most of the cases. Our study underscores the utility of LR-WGS as a complementary diagnostic method to identify, characterize, and unveil the molecular mechanism of formation of disease-causing SVs, and facilitates decision making about long-term thromboprophylaxis in ATD patients.

scholarly journals Genotyping structural variants in pangenome graphs using the vg toolkit

2019 ◽  
Author(s):  
Glenn Hickey ◽  
David Heller ◽  
Jean Monlong ◽  
Jonas A. Sibbesen ◽  
Jouni Sirén ◽  
...  
Keyword(s):  
De Novo ◽  
State Of The Art ◽  
Effective Means ◽  
Point Mutations ◽  
Structural Variants ◽  
Short Read ◽  
Yeast Strains ◽  
Sequencing Studies ◽  
Long Read

AbstractStructural variants (SVs) remain challenging to represent and study relative to point mutations despite their demonstrated importance. We show that variation graphs, as implemented in the vg toolkit, provide an effective means for leveraging SV catalogs for short-read SV genotyping experiments. We benchmarked vg against state-of-the-art SV genotypers using three sequence-resolved SV catalogs generated by recent long-read sequencing studies. In addition, we use assemblies from 12 yeast strains to show that graphs constructed directly from aligned de novo assemblies improve genotyping compared to graphs built from intermediate SV catalogs in the VCF format.

scholarly journals Mapping and phasing of structural variation in patient genomes using nanopore sequencing

2017 ◽  
Author(s):  
Mircea Cretu Stancu ◽  
Markus J. van Roosmalen ◽  
Ivo Renkens ◽  
Marleen Nieboer ◽  
Sjors Middelkamp ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Structural Variants ◽  
Human Genetic Disease ◽  
Structural Genomic ◽  
Short Read ◽  
Sequencing Technologies ◽  
Genome Wide ◽  
Long Read ◽  
Complex Structural

AbstractStructural genomic variants form a common type of genetic alteration underlying human genetic disease and phenotypic variation. Despite major improvements in genome sequencing technology and data analysis, the detection of structural variants still poses challenges, particularly when variants are of high complexity. Emerging long-read single-molecule sequencing technologies provide new opportunities for detection of structural variants. Here, we demonstrate sequencing of the genomes of two patients with congenital abnormalities using the ONT MinION at 11x and 16x mean coverage, respectively. We developed a bioinformatic pipeline - NanoSV - to efficiently map genomic structural variants (SVs) from the long-read data. We demonstrate that the nanopore data are superior to corresponding short-read data with regard to detection of de novo rearrangements originating from complex chromothripsis events in the patients. Additionally, genome-wide surveillance of SVs, revealed 3,253 (33%) novel variants that were missed in short-read data of the same sample, the majority of which are duplications < 200bp in size. Long sequencing reads enabled efficient phasing of genetic variations, allowing the construction of genome-wide maps of phased SVs and SNVs. We employed read-based phasing to show that all de novo chromothripsis breakpoints occurred on paternal chromosomes and we resolved the long-range structure of the chromothripsis. This work demonstrates the value of long-read sequencing for screening whole genomes of patients for complex structural variants.

scholarly journals De novo assembly of a Tibetan genome and identification of novel structural variants associated with high-altitude adaptation

2019 ◽  
Vol 7 (2) ◽  
pp. 391-402 ◽  
Author(s):  
Yaoxi He ◽  
Haiyi Lou ◽  
Chaoying Cui ◽  
Lian Deng ◽  
Yang Gao ◽  
...  
Keyword(s):  
High Altitude ◽  
De Novo Assembly ◽  
De Novo ◽  
Population Analysis ◽  
Extreme Environments ◽  
Structural Variants ◽  
Base Pairs ◽  
High Quality ◽  
Long Read ◽  
Altitude Adaptation

Abstract Structural variants (SVs) may play important roles in human adaptation to extreme environments such as high altitude but have been under-investigated. Here, combining long-read sequencing with multiple scaffolding techniques, we assembled a high-quality Tibetan genome (ZF1), with a contig N50 length of 24.57 mega-base pairs (Mb) and a scaffold N50 length of 58.80 Mb. The ZF1 assembly filled 80 remaining N-gaps (0.25 Mb in total length) in the reference human genome (GRCh38). Markedly, we detected 17 900 SVs, among which the ZF1-specific SVs are enriched in GTPase activity that is required for activation of the hypoxic pathway. Further population analysis uncovered a 163-bp intronic deletion in the MKL1 gene showing large divergence between highland Tibetans and lowland Han Chinese. This deletion is significantly associated with lower systolic pulmonary arterial pressure, one of the key adaptive physiological traits in Tibetans. Moreover, with the use of the high-quality de novo assembly, we observed a much higher rate of genome-wide archaic hominid (Altai Neanderthal and Denisovan) shared non-reference sequences in ZF1 (1.32%–1.53%) compared to other East Asian genomes (0.70%–0.98%), reflecting a unique genomic composition of Tibetans. One such archaic hominid shared sequence—a 662-bp intronic insertion in the SCUBE2 gene—is enriched and associated with better lung function (the FEV1/FVC ratio) in Tibetans. Collectively, we generated the first high-resolution Tibetan reference genome, and the identified SVs may serve as valuable resources for future evolutionary and medical studies.

scholarly journals Trio deep-sequencing does not reveal unexpected off-target and on-target mutations in Cas9-edited rhesus monkeys

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Xin Luo ◽  
Yaoxi He ◽  
Chao Zhang ◽  
Xiechao He ◽  
Lanzhen Yan ◽  
...  
Keyword(s):  
Rhesus Monkeys ◽  
De Novo ◽  
Preclinical Model ◽  
Structural Variants ◽  
Sequencing Data ◽  
De Novo Mutations ◽  
Target Region ◽  
Long Read ◽  
Target Effect

AbstractCRISPR-Cas9 is a widely-used genome editing tool, but its off-target effect and on-target complex mutations remain a concern, especially in view of future clinical applications. Non-human primates (NHPs) share close genetic and physiological similarities with humans, making them an ideal preclinical model for developing Cas9-based therapies. However, to our knowledge no comprehensive in vivo off-target and on-target assessment has been conducted in NHPs. Here, we perform whole genome trio sequencing of Cas9-treated rhesus monkeys. We only find a small number of de novo mutations that can be explained by expected spontaneous mutations, and no unexpected off-target mutations (OTMs) were detected. Furthermore, the long-read sequencing data does not detect large structural variants in the target region.

scholarly journals Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Yaoxi He ◽  
Xin Luo ◽  
Bin Zhou ◽  
Ting Hu ◽  
Xiaoyu Meng ◽  
...  
Keyword(s):  
Rhesus Macaque ◽  
Genome Assembly ◽  
De Novo ◽  
Gene Annotation ◽  
Large Body ◽  
Phenotypic Traits ◽  
Structural Variants ◽  
De Novo Genome Assembly ◽  
Chinese Rhesus Macaque ◽  
Long Read

Abstract We present a high-quality de novo genome assembly (rheMacS) of the Chinese rhesus macaque (Macaca mulatta) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), rheMacS increases sequence contiguity 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). We improve gene annotation by generating more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to ape genomes. Many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a subset that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. The rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.

scholarly journals StrVCTVRE: A supervised learning method to predict the pathogenicity of human structural variants

2020 ◽  
Author(s):  
Andrew G. Sharo ◽  
Zhiqiang Hu ◽  
Steven E. Brenner
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Diagnostic Methods ◽  
Training Dataset ◽  
Disease Genes ◽  
Whole Genome ◽  
Structural Variants ◽  
Coding Region ◽  
Diagnostic Potential ◽  
Long Read

AbstractWhole genome sequencing resolves clinical cases where standard diagnostic methods have failed. However, preliminary studies show that at least half of these cases still remain unresolved, even after whole genome sequencing. Structural variants (genomic variants larger than 50 base pairs) of uncertain significance may be the genetic cause of a portion of these unresolved cases. Historically, structural variants (SVs) have been difficult to detect with confidence from short-read sequencing. As both detection algorithms and long-read/linked-read sequencing methods become more accessible, clinical researchers will have access to thousands of reliable SVs of unknown disease relevance. Filtering these SVs by overlap with cataloged SVs is an imperfect solution. Innovative methods to predict the pathogenicity of these SVs will be needed to realize the full diagnostic potential of long-read sequencing. To address this emerging need, we developed StrVCTVRE (Structural Variant Classifier Trained on Variants Rare and Exonic), a classifier that can be used to distinguish pathogenic SVs from benign SVs that overlap exons. We made use of features that capture gene importance, coding region, conservation, expression, and exon structure in a random forest classifier. We found that some features, such as expression and conservation, are important but are absent from SV classification guidelines. Although databases of SVs reflect size biases from sequencing techniques, we leveraged multiple databases to construct a size-matched training set of rare, putatively benign and pathogenic SVs. In independent test sets, we found our method performs accurately across a wide SV size range, which will allow clinical researchers to eliminate nearly 60% of SVs from consideration at an elevated sensitivity of 90%. However, our method and its assessment are still constrained by a small training dataset and acquisition bias in databases of pathogenic variants. StrVCTVRE fills an empty niche in the clinical evaluation of SVs of unknown significance. We anticipate researchers will use it to prioritize SVs in patients where no variant is immediately compelling, empowering deeper investigation into novel SVs and disease genes to resolve cases.

Identification of two de novo mutations responsible for type I antithrombin deficiency

2012 ◽  
Vol 107 (01) ◽  
pp. 187-189 ◽  
Author(s):  
Willy Lissens ◽  
Daniele Hasaerts ◽  
Kristin Jochmans ◽  
Christelle Orlando
Keyword(s):  
De Novo ◽  
Type I ◽  
De Novo Mutations ◽  
Antithrombin Deficiency

scholarly journals Highly-accurate long-read sequencing improves variant detection and assembly of a human genome

2019 ◽  
Author(s):  
Aaron M. Wenger ◽  
Paul Peluso ◽  
William J. Rowell ◽  
Pi-Chuan Chang ◽  
Richard J. Hall ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Structural Variants ◽  
Short Reads ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Long Read ◽  
Variant Detection ◽  
High Quality Genome ◽  
Circular Consensus Sequencing

AbstractThe major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

scholarly journals Robust Benchmark Structural Variant Calls of An Asian Using the State-of-Art Long Fragment Sequencing Technologies

2020 ◽  
Author(s):  
Xiao Du ◽  
Lili Li ◽  
Fan Liang ◽  
Sanyang Liu ◽  
Wenxin Zhang ◽  
...  
Keyword(s):  
B Lymphocyte ◽  
De Novo ◽  
Structural Variants ◽  
High Confidence ◽  
False Negatives ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Circular Consensus Sequencing

AbstractThe importance of structural variants (SVs) on phenotypes and human diseases is now recognized. Although a variety of SV detection platforms and strategies that vary in sensitivity and specificity have been developed, few benchmarking procedures are available to confidently assess their performances in biological and clinical research. To facilitate the validation and application of those approaches, our work established an Asian reference material comprising identified benchmark regions and high-confidence SV calls. We established a high-confidence SV callset with 8,938 SVs in an EBV immortalized B lymphocyte line, by integrating four alignment-based SV callers [from 109× PacBio continuous long read (CLR), 22× PacBio circular consensus sequencing (CCS) reads, 104× Oxford Nanopore long reads, and 114× optical mapping platform (Bionano)] and one de novo assembly-based SV caller using CCS reads. A total of 544 randomly selected SVs were validated by PCR and Sanger sequencing, proofing the robustness of our SV calls. Combining trio-binning based haplotype assemblies, we established an SV benchmark for identification of false negatives and false positives by constructing the continuous high confident regions (CHCRs), which cover 1.46Gb and 6,882 SVs supported by at least one diploid haplotype assembly. Establishing high-confidence SV calls for a benchmark sample that has been characterized by multiple technologies provides a valuable resource for investigating SVs in human biology, disease, and clinical diagnosis.

scholarly journals Jasmine: Population-scale structural variant comparison and analysis

2021 ◽  
Author(s):  
Melanie Kirsche ◽  
Gautam Prabhu ◽  
Rachel Sherman ◽  
Bohan Ni ◽  
Sergey Aganezov ◽  
...  
Keyword(s):  
De Novo ◽  
Population Analysis ◽  
Accurate Method ◽  
Structural Variants ◽  
Sequencing Data ◽  
1000 Genomes ◽  
Dna And Rna ◽  
Long Reads ◽  
Long Read ◽  
Proximity Graph

The increasing availability of long-reads is revolutionizing studies of structural variants (SVs). However, because SVs vary across individuals and are discovered through imprecise read technologies and methods, they can be difficult to compare. Addressing this, we present Jasmine (https://github.com/mkirsche/Jasmine), a fast and accurate method for SV refinement, comparison, and population analysis. Using an SV proximity graph, Jasmine outperforms five widely-used comparison methods, including reducing the rate of Mendelian discordance in trio datasets by more than five-fold, and reveals a set of high confidence de novo SVs confirmed by multiple long-read technologies. We also present a harmonized callset of 205,192 SVs from 31 samples of diverse ancestry sequenced with long reads. We genotype these SVs in 444 short read samples from the 1000 Genomes Project with both DNA and RNA sequencing data and assess their widespread impact on gene expression, including within several medically relevant genes.

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