scholarly journals Genome‐wide detection of copy number variants in European autochthonous and commercial pig breeds by whole‐genome sequencing of DNA pools identified breed‐characterising copy number states

2020 ◽  
Vol 51 (4) ◽  
pp. 541-556
Author(s):  
S. Bovo ◽  
A. Ribani ◽  
M. Muñoz ◽  
E. Alves ◽  
J. P. Araujo ◽  
...  
2019 ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Fang Chen ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  

AbstractBackgroundNext-generation sequence (NGS) has rapidly developed in past years which makes whole-genome sequencing (WGS) becoming a more cost- and time-efficient choice in wide range of biological researches. We usually focus on some variant detection via WGS data, such as detection of single nucleotide polymorphism (SNP), insertion and deletion (Indel) and copy number variant (CNV), which playing an important role in many human diseases. However, the feasibility of CNV detection based on WGS by DNBSEQ™ platforms was unclear. We systematically analysed the genome-wide CNV detection power of DNBSEQ™ platforms and Illumina platforms on NA12878 with five commonly used tools, respectively.ResultsDNBSEQ™ platforms showed stable ability to detect slighter more CNVs on genome-wide (average 1.24-fold than Illumina platforms). Then, CNVs based on DNBSEQ™ platforms and Illumina platforms were evaluated with two public benchmarks of NA12878, respectively. DNBSEQ™ and Illumina platforms showed similar sensitivities and precisions on both two benchmarks. Further, the difference between tools for CNV detection was analyzed, and indicated the selection of tool for CNV detection could affected the CNV performance, such as count, distribution, sensitivity and precision.ConclusionThe major contribution of this paper is providing a comprehensive guide for CNV detection based on WGS by DNBSEQ™ platforms for the first time.


2017 ◽  
Author(s):  
Jean Monlong ◽  
Simon L. Girard ◽  
Caroline Meloche ◽  
Maxime Cadieux-Dion ◽  
Danielle M. Andrade ◽  
...  

AbstractEpilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.Author summaryEpilepsy is a common neurological disorder affecting around 3% of the population. In some cases, epilepsy is caused by brain trauma or other brain anomalies but there are often no clear causes. Genetic factors have been associated with epilepsy in the past such as rare genetic variations found by linkage studies as well as common genetic variations found by genome-wide association studies and large copy-number variants. We sequenced the genome of ∼200 epilepsy patients and ∼300 healthy controls and compared the distribution of deletion (loss of a copy) and duplication (additional copy) of genomic regions. Thanks to the sequencing technology and a new method that takes advantage of the large sample size, we could compare the distribution of small copy- number variants between epilepsy patients and controls. Overall, we found that small variants are also associated with epilepsy. Indeed, the genome of epilepsy patients had more exonic copy- number variants, especially when rare or affecting genes with predicted loss-of-function intolerance. Focusing on regions around genes that have been previously associated with epilepsy, we also found more non-coding variants in epilepsy patients, especially deletions or variants in regulatory regions. Finally, we provide a list of 21 regions in which we found likely pathogenic variants.


2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  

2017 ◽  
Vol 94 (1) ◽  
Author(s):  
Zirui Dong ◽  
Weiwei Xie ◽  
Haixiao Chen ◽  
Jinjin Xu ◽  
Huilin Wang ◽  
...  

2019 ◽  
Author(s):  
Yue Xing ◽  
Alan R. Dabney ◽  
Xiao Li ◽  
Guosong Wang ◽  
Clare A. Gill ◽  
...  

AbstractCopy number variants are insertions and deletions of 1 kb or larger in a genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.


Author(s):  
Marie Coutelier ◽  
Manuel Holtgrewe ◽  
Marten Jäger ◽  
Ricarda Flöttman ◽  
Martin A. Mensah ◽  
...  

AbstractCopy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing.


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Xinming Liang ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  

Abstract Background DNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small insertions and deletions (indels) has proven to be quite effective, while the feasibility of copy number variants (CNVs) detection is unclear. Results Here, we first benchmarked different CNV detection tools based on Illumina whole-genome sequencing (WGS) data of NA12878 and then assessed these tools in CNV detection based on DNBSEQ™ sequencing data from the same sample. When the same tool was used, the CNVs detected based on DNBSEQ™ and Illumina data were similar in quantity, length and distribution, while great differences existed within results from different tools and even based on data from a single platform. We further estimated the CNV detection power based on available CNV benchmarks of NA12878 and found similar precision and sensitivity between the DNBSEQ™ and Illumina platforms. We also found higher precision of CNVs shorter than 1 kbp based on DNBSEQ™ platforms than those based on Illumina platforms by using Pindel, DELLY and LUMPY. We carefully compared these two available benchmarks and found a large proportion of specific CNVs between them. Thus, we constructed a more complete CNV benchmark of NA12878 containing 3512 CNV regions. Conclusions We assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies.


2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Farah Qaiser ◽  
Tara Sadoway ◽  
Yue Yin ◽  
Quratulain Zulfiqar Ali ◽  
Charlotte M Nguyen ◽  
...  

Abstract Epilepsies are a group of common neurological disorders with a substantial genetic basis. Despite this, the molecular diagnosis of epilepsies remains challenging due to its heterogeneity. Studies utilizing whole-genome sequencing may provide additional insights into genetic causes of epilepsies of unknown aetiology. Whole-genome sequencing was used to evaluate a cohort of adults with unexplained developmental and epileptic encephalopathies (n = 30), for whom prior genetic tests, including whole-exome sequencing in some cases, were negative or inconclusive. Rare single nucleotide variants, insertions/deletions, copy number variants and tandem repeat expansions were analysed. Seven pathogenic or likely pathogenic single nucleotide variants, and two pathogenic deleterious copy number variants were identified in nine patients (32.1% of the cohort). One of the copy number variants, identified in a patient with Lennox–Gastaut syndrome, was too small to be detected by chromosomal microarray techniques. We also identified two tandem repeat expansions with clinical implications in two other patients with Lennox–Gastaut syndrome: a CGG repeat expansion in the 5′untranslated region of DIP2B, and a CTG expansion in ATXN8OS (previously implicated in spinocerebellar ataxia type 8). Three patients had KCNA2 pathogenic variants. One of them died of sudden unexpected death in epilepsy. The other two patients had, in addition to a KCNA2 variant, a second de novo variant impacting potential epilepsy-relevant genes (KCNIP4 and UBR5). Overall, whole-genome sequencing provided a genetic explanation in 32.1% of the total cohort. This is also the first report of coding and non-coding tandem repeat expansions identified in patients with Lennox–Gastaut syndrome. This study demonstrates that using whole-genome sequencing, the examination of multiple types of rare genetic variation, including those found in the non-coding region of the genome, can help resolve unexplained epilepsies.


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