scholarly journals Frequency of the STRC-CATSPER2 deletion in STRC-associated hearing loss patients

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Shin-ya Nishio ◽  
Shin-ichi Usami
Keyword(s):  
Hearing Loss ◽  
Male Infertility ◽  
Genetic Counselling ◽  
Copy Number ◽  
Read Depth ◽  
Copy Number Variations ◽  
Genomic Region ◽  
High Prevalence ◽  
Homozygous Deletions ◽  
Next Generation Sequencing Ngs

AbstractThe STRC gene, located on chromosome 15q15.3, is one of the genetic causes of autosomal recessive mild-to-moderate sensorineural hearing loss. One of the unique characteristics of STRC-associated hearing loss is the high prevalence of long deletions or copy number variations observed on chromosome 15q15.3. Further, the deletion of chromosome 15q15.3 from STRC to CATSPER2 is also known to be a genetic cause of deafness infertility syndrome (DIS), which is associated with not only hearing loss but also male infertility, as CATSPER2 plays crucial roles in sperm motility. Thus, information regarding the deletion range for each patient is important to the provision of appropriate genetic counselling for hearing loss and male infertility. In the present study, we performed next-generation sequencing (NGS) analysis for 9956 Japanese hearing loss patients and analyzed copy number variations in the STRC gene based on NGS read depth data. In addition, we performed Multiplex Ligation-dependent Probe Amplification analysis to determine the deletion range including the PPIP5K1, CKMT1B, STRC and CATSPER2 genomic region to estimate the prevalence of the STRC-CATSPER deletion, which is causative for DIS among the STRC-associated hearing loss patients. As a result, we identified 276 cases with STRC-associated hearing loss. The prevalence of STRC-associated hearing loss in Japanese hearing loss patients was 2.77% (276/9956). In addition, 77.1% of cases with STRC homozygous deletions carried a two copy loss of the entire CKMT1B-STRC-CATSPER2 gene region. This information will be useful for the provision of more appropriate genetic counselling regarding hearing loss and male infertility for the patients with a STRC deletion.

scholarly journals GROM-RD: Resolving genomic biases to improve read depth detection of copy number variants

2014 ◽  
Author(s):  
Sean D Smith ◽  
Joseph K Kawash ◽  
Andrey Grigoriev
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Read Depth ◽  
Read Coverage ◽  
Novel Approach ◽  
Depth Analysis ◽  
Gc Bias ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Cnv Detection

Amplifications or deletions of genome segments, known as copy number variants (CNVs), have been associated with many diseases. Read depth analysis of next-generation sequencing (NGS) is an essential method of detecting CNVs. However, genome read coverage is frequently distorted by various biases of NGS platforms, which reduce predictive capabilities of existing approaches. Additionally, the use of read depth tools has been somewhat hindered by imprecise breakpoint identification. We developed GROM-RD, an algorithm that analyzes multiple biases in read coverage to detect CNVs in NGS data. We found non-uniform variance across distinct GC regions after using existing GC bias correction methods and developed a novel approach to normalize such variance. Although complex and repetitive genome segments complicate CNV detection, GROM-RD adjusts for repeat bias and uses a two-pipeline masking approach to detect CNVs in complex and repetitive segments while improving sensitivity in less complicated regions. To overcome a typical weakness of RD methods, GROM-RD employs a CNV search using size-varying overlapping windows to improve breakpoint resolution. We compared our method to two widely used programs based on read depth methods, CNVnator and RDXplorer, and observed improved CNV detection and breakpoint accuracy for GROM-RD. GROM-RD is available at http://grigoriev.rutgers.edu/software/

scholarly journals CNV-P: a machine-learning framework for predicting high confident copy number variations

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12564
Author(s):  
Taifu Wang ◽  
Jinghua Sun ◽  
Xiuqing Zhang ◽  
Wen-Jing Wang ◽  
Qing Zhou
Keyword(s):  
Machine Learning ◽  
False Positive ◽  
Copy Number ◽  
Genetic Disorders ◽  
Genetic Diseases ◽  
Basic Research ◽  
Read Depth ◽  
Copy Number Variations ◽  
Sequencing Data ◽  
Learning Framework

Background Copy-number variants (CNVs) have been recognized as one of the major causes of genetic disorders. Reliable detection of CNVs from genome sequencing data has been a strong demand for disease research. However, current software for detecting CNVs has high false-positive rates, which needs further improvement. Methods Here, we proposed a novel and post-processing approach for CNVs prediction (CNV-P), a machine-learning framework that could efficiently remove false-positive fragments from results of CNVs detecting tools. A series of CNVs signals such as read depth (RD), split reads (SR) and read pair (RP) around the putative CNV fragments were defined as features to train a classifier. Results The prediction results on several real biological datasets showed that our models could accurately classify the CNVs at over 90% precision rate and 85% recall rate, which greatly improves the performance of state-of-the-art algorithms. Furthermore, our results indicate that CNV-P is robust to different sizes of CNVs and the platforms of sequencing. Conclusions Our framework for classifying high-confident CNVs could improve both basic research and clinical diagnosis of genetic diseases.

scholarly journals Mid-Frequency Hearing Loss Is Characteristic Clinical Feature of OTOA-Associated Hearing Loss

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 715 ◽  
Author(s):  
Sugiyama ◽  
Moteki ◽  
Kitajiri ◽  
Kitano ◽  
Nishio ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Clinical Features ◽  
Autosomal Recessive ◽  
Japanese Patients ◽  
Copy Number Variations ◽  
Clinical Feature ◽  
Single Nucleotide Variants ◽  
Characteristic Clinical Feature ◽  
Or Gene ◽  
Homozygous Deletions

The OTOA gene (Locus: DFNB22) is reported to be one of the causative genes for non-syndromic autosomal recessive hearing loss. The copy number variations (CNVs) identified in this gene are also known to cause hearing loss, but have not been identified in Japanese patients with hearing loss. Furthermore, the clinical features of OTOA-associated hearing loss have not yet been clarified. In this study, we performed CNV analyses of a large Japanese hearing loss cohort, and identified CNVs in 234 of 2262 (10.3%, 234/2262) patients with autosomal recessive hearing loss. Among the identified CNVs, OTOA gene-related CNVs were the second most frequent (0.6%, 14/2262). Among the 14 cases, 2 individuals carried OTOA homozygous deletions, 4 carried heterozygous deletions with single nucleotide variants (SNVs) in another allele. Additionally, 1 individual with homozygous SNVs in the OTOA gene was also identified. Finally, we identified 7 probands with OTOA-associated hearing loss, so that its prevalence in Japanese patients with autosomal recessive hearing loss was calculated to be 0.3% (7/2262). As novel clinical features identified in this study, the audiometric configurations of patients with OTOA-associated hearing loss were found to be mid-frequency. This is the first study focused on the detailed clinical features of hearing loss caused by this gene mutation and/or gene deletion.

Frequency of Common Copy-Number Variations at 15q11.2q13 in Sperm of Healthy Men

2019 ◽  
Vol 159 (2) ◽  
pp. 66-73 ◽  
Author(s):  
Takahiro Kinoshita ◽  
Masashi Mikami ◽  
Tadayuki Ayabe ◽  
Keiko Matsubara ◽  
Hiromi Ono ◽  
...  
Keyword(s):  
Copy Number ◽  
Alcohol Intake ◽  
Negative Binomial ◽  
Smoking Status ◽  
Clinical Information ◽  
Estimating Equation ◽  
Copy Number Variations ◽  
Genomic Region ◽  
Healthy Men ◽  
Significant Difference

The genomic region at 15q11.2q13 represents a hotspot for copy-number variations (CNVs) due to nonallelic homologous recombination. Previous studies have suggested that the development of 15q11.2q13 deletions in sperm may be affected by seasonal factors because patients with Prader-Willi syndrome resulting from 15q11.2q13 deletions on paternally derived chromosomes showed autumn-dominant birth seasonality. The present study aimed to determine the frequency of 15q11.2q13 CNVs in sperm of healthy men and clarify the effects of various environmental factors, i.e., age, smoking status, alcohol intake, and season, on the frequency. Thirty volunteers were asked to provide semen samples and clinical information once in each season of a year. The rates of 15q11.2q13 CNVs were examined using 2-color FISH. The results were statistically analyzed using a generalized estimating equation with negative binomial distribution and a log link function. Consequently, informative data were obtained from 83 samples of 26 individuals. The rates of deletions and duplications ranged from 0.04 to 0.48% and from 0.08 to 0.30%, respectively. The rates were not correlated with the age, smoking status, or alcohol intake. Sperm produced in winter showed 1.2 to 1.4-fold high rates for both deletions and duplications as compared with sperm produced in the other seasons; however, there was no significant difference. These results demonstrate high and variable CNV rates at 15q11.2q13 in sperm of healthy men. These CNVs appear to occur independent of the age, smoking status, or alcohol intake, while the effect of season remains inconclusive. Our results merit further validation.

scholarly journals RBV: Read balance validator, a tool for prioritising copy number variations in germline conditions

2018 ◽  
Author(s):  
Whitney Whitford ◽  
Klaus Lehnert ◽  
Russell G. Snell ◽  
Jessie C. Jacobsen
Keyword(s):  
Copy Number ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Relative Proportion ◽  
Copy Number Variants ◽  
Read Depth ◽  
Copy Number Variations ◽  
Single Nucleotide Variants ◽  
Software Packages ◽  
Bioinformatic Tool

AbstractBackgroundThe popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However the additional source of information from read balance, defined as relative proportion of reads of each allele at each position, has been underutilised in the existing applications.ResultsWe present Read Balance Validator (RBV), a bioinformatic tool which uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report.ConclusionsRBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV

scholarly journals The Role of Number of Copies, Structure, Behavior and Copy Number Variations (CNV) of the Y Chromosome in Male Infertility

Genes ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 40 ◽  
Author(s):  
Fabrizio Signore ◽  
Caterina Gulìa ◽  
Raffaella Votino ◽  
Vincenzo De Leo ◽  
Simona Zaami ◽  
...  
Keyword(s):  
Male Infertility ◽  
Y Chromosome ◽  
Copy Number ◽  
Significant Proportion ◽  
Copy Number Variations ◽  
World Health ◽  
Idiopathic Male Infertility ◽  
Negative Results ◽  
Pubmed Database ◽  
Structural Anomalies

The World Health Organization (WHO) defines infertility as the inability of a sexually active, non-contracepting couple to achieve spontaneous pregnancy within one year. Statistics show that the two sexes are equally at risk. Several causes may be responsible for male infertility; however, in 30–40% of cases a diagnosis of idiopathic male infertility is made in men with normal urogenital anatomy, no history of familial fertility-related diseases and a normal panel of values as for endocrine, genetic and biochemical markers. Idiopathic male infertility may be the result of gene/environment interactions, genetic and epigenetic abnormalities. Numerical and structural anomalies of the Y chromosome represent a minor yet significant proportion and are the topic discussed in this review. We searched the PubMed database and major search engines for reports about Y-linked male infertility. We present cases of Y-linked male infertility in terms of (i) anomalies of the Y chromosome structure/number; (ii) Y chromosome misbehavior in a normal genetic background; (iii) Y chromosome copy number variations (CNVs). We discuss possible explanations of male infertility caused by mutations, lower or higher number of copies of otherwise wild type, Y-linked sequences. Despite Y chromosome structural anomalies are not a major cause of male infertility, in case of negative results and of normal DNA sequencing of the ascertained genes causing infertility and mapping on this chromosome, we recommend an analysis of the karyotype integrity in all cases of idiopathic fertility impairment, with an emphasis on the structure and number of this chromosome.

scholarly journals Detection of copy-number variations from NGS data using read depth information: a diagnostic performance evaluation

2020 ◽  
Vol 29 (1) ◽  
pp. 99-109 ◽  
Author(s):  
Olivier Quenez ◽  
◽  
Kevin Cassinari ◽  
Sophie Coutant ◽  
François Lecoquierre ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Copy Number ◽  
Diagnostic Performance ◽  
Read Depth ◽  
Copy Number Variations ◽  
Depth Information ◽  
Ngs Data

scholarly journals Analysis of Copy Number Variations in Solid Tumors Using a Next Generation Sequencing Custom Panel

2021 ◽  
Vol 2 (2) ◽  
pp. 123-134
Author(s):  
Marta Vives-Usano ◽  
Beatriz García Pelaez ◽  
Ruth Román Lladó ◽  
Mónica Garzón Ibañez ◽  
Erika Aldeguer ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number ◽  
Copy Number Variations ◽  
Next Generation ◽  
Ffpe Samples ◽  
Custom Panel ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing ◽  
Approach Time ◽  
Selection Of

Somatic copy number variations (CNV; i.e., amplifications and deletions) have been implicated in the origin and development of multiple cancers and some of these aberrations are designated targets for therapies. Although FISH is still considered the gold standard for CNV detection, the increasing number of potentially druggable amplifications to be assessed makes a gene-by-gene approach time- and tissue-consuming. Here we investigated the potential of next generation sequencing (NGS) custom panels to simultaneously determine CNVs across FFPE solid tumor samples. DNA was purified from cell lines and FFPE samples and analyzed by NGS sequencing using a 20-gene custom panel in the GeneReader Platform®. CNVs were identified using an in-house algorithm based on the UMI read coverage. Retrospective validation of in-house algorithm to identify CNVs showed 97.1% concordance rate with the NGS custom panel. The prospective analysis was performed in a cohort of 243 FFPE samples from patients arriving at our hospital, which included 74 NSCLC tumors, 148 CRC tumors, and 21 other tumors. Of them, 33% presented CNVs by NGS and in 14 cases (5.9%) the CNV was the only alteration detected. We have identified CNV alterations in about one-third of our cohort, including FGFR1, CDK6, CDK4, EGFR, MET, ERBB2, BRAF, or KRAS. Our work highlights the need to include CNV testing as a part of routine NGS analysis in order to uncover clinically relevant gene amplifications that can guide the selection of therapies.

scholarly journals A Cluster-Based Approach for the Discovery of Copy Number Variations From Next-Generation Sequencing Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Guojun Liu ◽  
Junying Zhang
Keyword(s):  
Next Generation Sequencing ◽  
Copy Number ◽  
Read Depth ◽  
Copy Number Variations ◽  
Experimental Results ◽  
Data Sets ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing ◽  
Cnv Detection

The next-generation sequencing technology offers a wealth of data resources for the detection of copy number variations (CNVs) at a high resolution. However, it is still challenging to correctly detect CNVs of different lengths. It is necessary to develop new CNV detection tools to meet this demand. In this work, we propose a new CNV detection method, called CBCNV, for the detection of CNVs of different lengths from whole genome sequencing data. CBCNV uses a clustering algorithm to divide the read depth segment profile, and assigns an abnormal score to each read depth segment. Based on the abnormal score profile, Tukey’s fences method is adopted in CBCNV to forecast CNVs. The performance of the proposed method is evaluated on simulated data sets, and is compared with those of several existing methods. The experimental results prove that the performance of CBCNV is better than those of several existing methods. The proposed method is further tested and verified on real data sets, and the experimental results are found to be consistent with the simulation results. Therefore, the proposed method can be expected to become a routine tool in the analysis of CNVs from tumor-normal matched samples.

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