Whole-exome sequence analysis highlights the role of unmasked recessive mutations in copy number variants with incomplete penetrance

AbstractGermline copy number variants (CNVs) increase risk for many diseases, yet detection of CNVs and quantifying their contribution to disease risk in large-scale studies is challenging. We developed an approach called CNPBayes to identify latent batch effects, to provide probabilistic estimates of integer copy number across the estimated batches, and to fully integrate the copy number uncertainty in the association model for disease. We demonstrate this approach in a Pancreatic Cancer Case Control study of 7,598 participants where the major sources of technical variation were not captured by study site and varied across the genome. Candidate associations aided by this approach include deletions of 8q24 near regulatory elements of the tumor oncogene MYC and of Tumor Supressor Candidate 3 (TUSC3). This study provides a robust Bayesian inferential framework for estimating copy number and evaluating the role of copy number in heritable diseases.

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The Role of Copy Number Variation in Psychiatric Disorders

Psychiatric Genetics ◽

10.1093/med/9780190221973.003.0006 ◽

2018 ◽

pp. 84-95

Author(s):

Elliott Rees ◽

George Kirov

Keyword(s):

Autism Spectrum Disorders ◽

Copy Number ◽

Selection Pressure ◽

Copy Number Variants ◽

Autism Spectrum ◽

High Odds ◽

Strong Selection ◽

Increase Risk ◽

Number Variation

Copy number variants (CNVs) are deletions, duplications, inversions, or translocations of large DNA segments. They can play a significant role in human disease. Thirteen CNVs have received strong statistical support for involvement in schizophrenia. They are all rare in cases (<1%), much rarer among controls, and have high odds ratios (ORs) for causing disease. The same CNVs also increase risk for autism spectrum disorders, developmental delay, and medical/physical comorbidities. The penetrance of these CNVs for any disorder is relatively high, ranging from 10% for 15q11.2 deletions to nearly 100% for deletions at 22q11.2. Strong selection pressure operates against carriers of these CNVs. Most of these are formed by non-allelic homologous recombination (NAHR), which leads to high mutation rates, thus maintaining the rates of these CNVs in the general population, despite the strong selection forces.

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RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

Cancer Informatics ◽

10.4137/cin.s36612 ◽

2016 ◽

Vol 15 ◽

pp. CIN.S36612 ◽

Cited By ~ 3

Author(s):

Lun-Ching Chang ◽

Biswajit Das ◽

Chih-Jian Lih ◽

Han Si ◽

Corinne E. Camalier ◽

...

Keyword(s):

Exome Sequencing ◽

Whole Exome Sequencing ◽

Copy Number ◽

Copy Number Variants ◽

Estimation Methods ◽

Single Nucleotide Variants ◽

False Positive Error ◽

Reference Set ◽

Genome Wide ◽

Whole Exome

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.

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Increased Frequency of De Novo Copy Number Variants in Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism Array and Exome Sequence Data

Circulation Research ◽

10.1161/circresaha.115.304458 ◽

2014 ◽

Vol 115 (10) ◽

pp. 884-896 ◽

Cited By ~ 146

Author(s):

Joseph T. Glessner ◽

Alexander G. Bick ◽

Kaoru Ito ◽

Jason G. Homsy ◽

Laura Rodriguez-Murillo ◽

...

Keyword(s):

Copy Number ◽

Congenital Heart ◽

De Novo ◽

Sequence Data ◽

Single Nucleotide Polymorphism Array ◽

Copy Number Variants ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Exome Sequence Data ◽

Exome Sequence

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Genetics of Schizophrenia and Bipolar Disorder

10.1093/med/9780190681425.003.0013 ◽

2017 ◽

Author(s):

Alexander Charney ◽

Pamela Sklar

Keyword(s):

Bipolar Disorder ◽

Copy Number ◽

Psychotic Disorders ◽

Copy Number Variants ◽

Nucleotide Polymorphisms ◽

Common Variants ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Number Variation

Schizophrenia and bipolar disorder are the classic psychotic disorders. Both diseases are strongly familial, but have proven recalcitrant to genetic methodologies for identifying the etiology until recently. There is now convincing genetic evidence that indicates a contribution of many DNA changes to the risk of becoming ill. For schizophrenia, there are large contributions of rare copy number variants and common single nucleotide variants, with an overall highly polygenic genetic architecture. For bipolar disorder, the role of copy number variation appears to be much less pronounced. Specific common single nucleotide polymorphisms are associated, and there is evidence for polygenicity. Several surprises have emerged from the genetic data that indicate there is significantly more molecular overlap in copy number variants between autism and schizophrenia, and in common variants between schizophrenia and bipolar disorder.

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Novel COL11A2 Pathogenic Variants in a Child with Autosomal Recessive Otospondylomegaepiphyseal Dysplasia: A Review of the Literature

Journal of Pediatric Genetics ◽

10.1055/s-0039-1698446 ◽

2019 ◽

Vol 09 (02) ◽

pp. 117-120

Author(s):

Pavalan Selvam ◽

Shekhar Singh ◽

Angita Jain ◽

Herjot Atwal ◽

Paldeep S. Atwal

Keyword(s):

Sequence Analysis ◽

Autosomal Recessive ◽

Autosomal Dominant ◽

Review Of The Literature ◽

Pathogenic Variants ◽

Phenotypic Spectrum ◽

Whole Exome ◽

The Family ◽

Type Xi Collagen ◽

Exome Sequence

AbstractOtospondylomegaepiphyseal dysplasia (OSMED) is an inherited autosomal dominant and recessive skeletal dysplasia caused by both heterozygous and homozygous pathogenic variants in COL11A2 encoding the α2(XI) collagen chains, a part of type XI collagen. Here, we describe a 2-year-old girl presenting from birth with a phenotype suggestive of OSMED. On whole exome sequence analysis of the family via commercially available methods, we detected two novel heterozygous pathogenic variants in the proband. In addition, we reviewed the phenotype of autosomal recessive OSMED cases with COL11A2 pathogenic variants reported to date and quantitatively highlighted the phenotypic spectrum.

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