The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

A method to comprehensively identify germline SNVs, INDELs and CNVs from whole exome sequencing data of BRCA1/2 negative breast cancer patients

In the rapidly evolving field of genomics, understanding the genetic basis of complex diseases like breast cancer, particularly its familial/hereditary forms, is crucial. Current methods often examine genomic variants-such as Single Nucleotide Variants (SNVs), insertions/deletions (Indels), and Copy Number Variations (CNVs)-separately, lacking an integrated approach. Here, we introduced a robust, flexible methodology for a comprehensive variants' analysis using Whole Exome Sequencing (WES) data. Our approach uniquely combines meticulous validation with an effective variant filtering strategy. By reanalyzing two germline WES datasets from BRCA1/2 negative breast cancer patients, we demonstrated our tool's efficiency and adaptability, uncovering both known and novel variants. This contributed new insights for potential diagnostic, preventive, and therapeutic strategies. Our method stands out for its comprehensive inclusion of key genomic variants in a unified analysis, and its practical resolution of technical challenges, offering a pioneering solution in genomic research. This tool presents a breakthrough in providing detailed insights into the genetic alterations in genomes, with significant implications for understanding and managing hereditary breast cancer.

Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations

Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

CNVs Associated with Different Clinical Phenotypes of Psoriasis and Anti-TNF-Induced Palmoplantar Pustulosis

Background: Psoriasis can present different phenotypes and could affect diverse body areas. In contrast to the high effectiveness of biological drugs in the treatment of trunk and extremities plaque psoriasis, in palmoplantar phenotypes and in plaque scalp psoriasis, these same drugs usually have reduced efficacy. Anti-TNF drugs could induce the appearance of palmoplantar pustulosis (PPP) in patients with other inflammatory diseases. The objective of this study is to identify if there are DNA Copy Number Variations (CNVs) associated with these different clinical phenotypes, which could justify the differences found in clinical practice. Moreover, we intend to elucidate if anti-TNF-induced PPP has a similar genetic background to idiopathic PPP. Methods: Skin samples were collected from 39 patients with different patterns of psoriasis and six patients with anti-TNF-induced PPP. The CNVs were obtained from methylation array data (Illumina Infinium Human Methylation) using the conumee R package. Results: No significant CNVs were found between the different phenotypes and the locations of psoriasis compared. Nevertheless, we found two significant bins harboring five different genes associated with anti-TNF-induced PPP in patients with a different background other than psoriasis. Conclusions: Our results may help to predict which patients could develop anti-TNF-induced PPP.

The individual and global impact of copy-number variants on complex human traits

The impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.

Copy number alteration signatures as biomarkers in cancer: a review

Within certain cancers, extensive copy number alterations (CNAs) contribute to a complex and heterogenic genomic profile. This makes it difficult to understand and unravel the distinct molecular dynamics shaping the disease while preventing clinically effective patient stratification. CNA signature analysis represents a novel genomic stratification tool for probing this complexity, offering an intricate framework for deriving CNA patterns at the molecular level. This allows the underlying genomic mechanisms of specific cancers to be revealed, leading to the potential identification of therapeutic targets and prognostic associations. This review outlines the molecular and methodological basis of CNA signatures and focuses on recent advances highlighting their clinical utility, limitations and prospective future as novel diagnostic and prognostic cancer biomarkers.

Comprehensive characterization of copy number variation (CNV) called from array, long- and short-read data

BACKGROUND

SNP arrays, short- and long-read genome sequencing are genome-wide high-throughput technologies that may be used to assay copy number variants (CNVs) in a personal genome. Each of these technologies comes with its own limitations and biases, many of which are well-known, but not all of them are thoroughly quantified.

RESULTS

We assembled an ensemble of public datasets of published CNV calls and raw data for the well-studied Genome in a Bottle individual NA12878. This assembly represents a variety of methods and pipelines used for CNV calling from array, short- and long-read technologies. We then performed cross-technology comparisons regarding their ability to call CNVs. Different from other studies, we refrained from using the golden standard. Instead, we attempted to validate the CNV calls by the raw data of each technology.

CONCLUSIONS

Our study confirms that long-read platforms enable recalling CNVs in genomic regions inaccessible to arrays or short reads. We also found that the reproducibility of a CNV by different pipelines within each technology is strongly linked to other CNV evidence measures. Importantly, the three technologies show distinct public database frequency profiles, which differ depending on what technology the database was built on.

Identification of Tumor Antigens and Immune Landscape in Glioblastoma for mRNA Vaccine Development

Background: Clinical benefits from standard therapies against glioblastoma (GBM) are limited in part due to the intrinsic radio- and chemo-resistance. As an essential part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against GBM remains undefined. Therefore, this study aims to find the possible tumor antigens of GBM and identify the suitable population for cancer vaccination through immunophenotyping. Method: The genomic and responding clinical data of 169 GBM samples and five normal brain samples were obtained from The Cancer Genome Atlas (TCGA). The mRNA_seq data of 940 normal brain tissue were downloaded from Genotype-Tissue Expression (GTEx). Potential GBM mRNA antigens were screened out by differential expression, copy number variant (CNV), and mutation analysis. K-M survival and Cox analysis were carried out to investigate the prognostic association of potential tumor antigens. Tumor Immune Estimation Resource (TIMER) was used to explore the association between the antigens and tumor immune infiltrating cells (TIICs). Immunophenotyping of 169 samples was performed through consensus clustering based on the abundance of 22 kinds of immune cells. The characteristics of the tumor immune microenvironment (TIME) in each cluster were explored through single-sample gene set enrichment analysis based on 29 kinds of immune-related hallmarks and pathways. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the genes related to immune subtypes. Finally, pathway enrichment analyses were performed to annotate the potential function of modules screened through WGCNA. Results: Two potential tumor antigens selected were significantly positively associated with the antigen-presenting immune cells (APCs) in GBM. Furthermore, the expression of antigens was verified at the protein level by Immunohistochemistry. Two robust immune subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2), representing immune status "immune inhibition" and "immune inflamed", respectively, had distinct clinical outcomes in GBM. Conclusion: ARPC1B and HK3 were potential mRNA antigens for developing GBM mRNA vaccination, and the patients in IS2 were considered the most suitable population for vaccination in GBM.

MLPA analysis of 32 foetuses with a congenital heart defect and 1 foetus with renal defects - pilot study. The significant frequency rate of presented pathological CNV

AIMS

The aim of this retrospective study was to determine the detection rate of the pathogenic copy number variants (CNVs) in a cohort of 33 foetuses - 32 with CHD (congenital heart defects) and 1 with kidney defect, after exclusion of common aneuploidies (trisomy 13, 18, 21, and monosomy X) by karyotyping, Multiplex ligation - dependent probe amplification (MLPA) and chromosomal microarray analysis (CMA). We also assess the effectivity of MLPA as a method of the first tier for quick and inexpensive detection of mutations, causing congenital malformations in foetuses.

METHODS

MLPA with probe mixes P070, P036 - Telomere 3 and 5, P245 - microdeletions, P250 - DiGeorge syndrome, and P311 - CHD (Congenital heart defects) was performed in 33 samples of amniotic fluid and chorionic villi. CMA was performed in 10 relevant cases.

RESULTS

Pathogenic CNVs were found in 5 samples: microdeletions in region 22q11.2 (≈2 Mb) in two foetuses, one distal microdeletion of the 22q11.2 region containing genes LZTR1, CRKL, AIFM3 and SNAP29 (≈416 kb) in the foetus with bilateral renal agenesis, 8p23.1 (3.8 Mb) microdeletion syndrome and microdeletion in area 9q34.3 (1.7 Mb, Kleefstra syndrome). MLPA as an initial screening method revealed unambiguously pathogenic CNVs in 15.2 % of samples.

CONCLUSION

Our study suggests that MLPA and CMA are a reliable and high-resolution technology and should be used as the first-tier test for prenatal diagnosis of congenital heart disease. Determination of the cause of the abnormality is crucial for genetic counselling and further management of the pregnancy.

ClinSV: clinical grade structural and copy number variant detection from whole genome sequencing data

Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5-4.5%) and reproducibility high (95-99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35-63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV .

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

Genetically-regulated transcriptomics & copy number variation of proctitis points to altered mitochondrial and DNA repair mechanisms in individuals of European ancestry

Background

Proctitis is an inflammation of the rectum and may be induced by radiation treatment for cancer. The genetic heritability of developing radiotoxicity and prior role of genetic variants as being associated with side-effects of radiotherapy necessitates further investigation for underlying molecular mechanisms. In this study, we investigated gene expression regulated by genetic variants, and copy number variation in prostate cancer survivors with radiotoxicity.

Methods

We investigated proctitis as a radiotoxic endpoint in prostate cancer patients who received radiotherapy (n = 222). We analyzed the copy number variation and genetically regulated gene expression profiles of whole-blood and prostate tissue associated with proctitis. The SNP and copy number data were genotyped on Affymetrix® Genome-wide Human SNP Array 6.0. Following QC measures, the genotypes were used to obtain gene expression by leveraging GTEx, a reference dataset for gene expression association based on genotype and RNA-seq information for prostate (n = 132) and whole-blood tissue (n = 369).

Results

In prostate tissue, 62 genes were significantly associated with proctitis, and 98 genes in whole-blood tissue. Six genes - CABLES2, ATP6AP1L, IFIT5, ATRIP, TELO2, and PARD6G were common to both tissues. The copy number analysis identified seven regions associated with proctitis, one of which (ALG1L2) was also associated with proctitis based on transcriptomic profiles in the whole-blood tissue. The genes identified via transcriptomics and copy number variation association were further investigated for enriched pathways and gene ontology. Some of the enriched processes were DNA repair, mitochondrial apoptosis regulation, cell-to-cell signaling interaction processes for renal and urological system, and organismal injury.

Conclusions

We report gene expression changes based on genetic polymorphisms. Integrating gene-network information identified these genes to relate to canonical DNA repair genes and processes. This investigation highlights genes involved in DNA repair processes and mitochondrial malfunction possibly via inflammation. Therefore, it is suggested that larger studies will provide more power to infer the extent of underlying genetic contribution for an individual’s susceptibility to developing radiotoxicity.

Genetic Causes of Severe Childhood Obesity: A Remarkably High Prevalence in an Inbred Population of Pakistan

Monogenic forms of obesity have been identified in ≤10% of severely obese European patients. However, the overall spectrum of deleterious variants (point mutations and structural variants) responsible for childhood severe obesity remains elusive. In this study, we genetically screened 225 severely obese children from consanguineous Pakistani families through a combination of techniques, including an in-house-developed augmented whole-exome sequencing method (CoDE-seq) that enables simultaneous detection of whole-exome copy number variations (CNVs) and point mutations in coding regions. We identified 110 (49%) probands carrying 55 different pathogenic point mutations and CNVs in 13 genes/loci responsible for nonsyndromic and syndromic monofactorial obesity. CoDE-seq also identified 28 rare or novel CNVs associated with intellectual disability in 22 additional obese subjects (10%). Additionally, we highlight variants in candidate genes for obesity warranting further investigation. Altogether, 59% of cases in the studied cohort are likely to have a discrete genetic cause, with 13% of these as a result of CNVs, demonstrating a remarkably higher prevalence of monofactorial obesity than hitherto reported and a plausible overlapping of obesity and intellectual disabilities in several cases. Finally, inbred populations with a high prevalence of obesity provide unique, genetically enriched material in the quest of new genes/variants influencing energy balance.

Sudden Cardiac Death and Copy Number Variants: What Do We Know after 10 Years of Genetic Analysis?

Over the last ten years, analysis of copy number variants has increasingly been applied to the study of arrhythmogenic pathologies associated with sudden death, mainly due to significant advances in the field of massive genetic sequencing. Nevertheless, few published reports have focused on the prevalence of copy number variants associated with sudden cardiac death. As a result, the frequency of these genetic alterations in arrhythmogenic diseases as well as their genetic interpretation and clinical translation has not been established. This review summarizes the current available data concerning copy number variants in sudden cardiac death-related diseases.

Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke

Background and Purpose- We sought to explore the effect of genetic imbalance on functional outcome after ischemic stroke (IS). Methods- Copy number variation was identified in high-density single-nucleotide polymorphism microarray data of IS patients from the CADISP (Cervical Artery Dissection and Ischemic Stroke Patients) and SiGN (Stroke Genetics Network)/GISCOME (Genetics of Ischaemic Stroke Functional Outcome) networks. Genetic imbalance, defined as total number of protein-coding genes affected by copy number variations in an individual, was compared between patients with favorable (modified Rankin Scale score of 0-2) and unfavorable (modified Rankin Scale score of ≥3) outcome after 3 months. Subgroup analyses were confined to patients with imbalance affecting ohnologs-a class of dose-sensitive genes, or to those with imbalance not affecting ohnologs. The association of imbalance with outcome was analyzed by logistic regression analysis, adjusted for age, sex, stroke subtype, stroke severity, and ancestry. Results- The study sample comprised 816 CADISP patients (age 44.2±10.3 years) and 2498 SiGN/GISCOME patients (age 67.7±14.2 years). Outcome was unfavorable in 122 CADISP and 889 SiGN/GISCOME patients. Multivariate logistic regression analysis revealed that increased genetic imbalance was associated with less favorable outcome in both samples (CADISP: P=0.0007; odds ratio=0.89; 95% CI, 0.82-0.95 and SiGN/GISCOME: P=0.0036; odds ratio=0.94; 95% CI, 0.91-0.98). The association was independent of age, sex, stroke severity on admission, stroke subtype, and ancestry. On subgroup analysis, imbalance affecting ohnologs was associated with outcome (CADISP: odds ratio=0.88; 95% CI, 0.80-0.95 and SiGN/GISCOME: odds ratio=0.93; 95% CI, 0.89-0.98) whereas imbalance without ohnologs lacked such an association. Conclusions- Increased genetic imbalance was associated with poorer functional outcome after IS in both study populations. Subgroup analysis revealed that this association was driven by presence of ohnologs in the respective copy number variations, suggesting a causal role of the deleterious effects of genetic imbalance.

Partial LPL deletions: rare copy-number variants contributing towards severe hypertriglyceridemia

Severe hypertriglyceridemia (HTG) is a relatively common form of dyslipidemia with a complex pathophysiology and serious health complications. HTG can develop in the presence of rare genetic factors disrupting genes involved in the triglyceride (TG) metabolic pathway, including large-scale copy-number variants (CNVs). Improvements in next-generation sequencing technologies and bioinformatic analyses have better allowed assessment of CNVs as possible causes of or contributors to severe HTG. We screened targeted sequencing data of 632 patients with severe HTG and identified partial deletions of the LPL gene, encoding the central enzyme involved in the metabolism of TG-rich lipoproteins, in four individuals (0.63%). We confirmed the genomic breakpoints in each patient with Sanger sequencing. Three patients carried an identical heterozygous deletion spanning the 5' untranslated region (UTR) to LPL exon 2, and one patient carried a heterozygous deletion spanning the 5'UTR to LPL exon 1. All four heterozygous CNV carriers were determined to have multifactorial severe HTG. The predicted null nature of our identified LPL deletions may contribute to relatively higher TG levels and a more severe clinical phenotype than other forms of genetic variation associated with the disease, particularly in the polygenic state. The identification of novel CNVs in patients with severe HTG suggests that methods for CNV detection should be included in the diagnostic workup and molecular genetic evaluation of patients with high TG levels.

Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing

Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study.

Progress in finding pathogenic DNA copy number variations in dyslipidemia

PURPOSE OF REVIEW

DNA copy number variations (CNVs) are large-scale mutations that include deletions and duplications larger than 50 bp in size. In the era when single-nucleotide variations were the major focus of genetic technology and research, CNVs were largely overlooked. However, CNVs clearly underlie a substantial proportion of clinical disorders. Here, we update recent progress in identifying CNVs in dyslipidemias.

RECENT FINDINGS

Until last year, only the LDLR and LPA genes were appreciated as loci within which clinically relevant CNVs contributed to familial hypercholesterolemia and variation in Lp(a) levels, respectively. Since 2017, next-generation sequencing panels have identified pathogenic CNVs in at least five more genes underlying dyslipidemias, including a PCSK9 whole-gene duplication in familial hypercholesterolemia; LPL, GPIHBP1, and APOC2 deletions in hypertriglyceridemia; and ABCA1 deletions in hypoalphalipoproteinemia.

SUMMARY

CNVs are an important class of mutation that contribute to the molecular genetic heterogeneity underlying dyslipidemias. Clinical applications of next-generation sequencing technologies need to consider CNVs concurrently with familiar small-scale genetic variation, given the likely implications for improved diagnosis and treatment.

Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

Multistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

A Rare Case of Concomitant Deletions in 15q11.2 and 19p13.3

A female individual with concomitant deletions in 15q11.2 and 19p13.3 is reported. She presents facial dysmorphisms, motor delay, learning difficulties, and mild behavioral impairment. After chromosomal microarray analysis, the final karyotype was established as 46,XX.arr[GRCh37] 15q11.2 (22770421_23282798)×1,19p13.3(3793904_4816330)×1. The deletion in 15q11.2 is 507 kb in size involving 7 non-imprinted genes, 4 of which are registered in the OMIM database and are implicated in neuropsychiatric or neurodevelopmental disorders. The deletion in 19p13.3 is 1,022 kb in size and encompasses 47 genes, most of which do not have a well-known function. The genotype-phenotype correlation is discussed, and most of the features could be related to the 19p13.3 deletion, except for velopharyngeal insufficiency. Other genes encompassed in the deleted region, as well as unrecognized epistatic factors could also be involved. Nevertheless, the two-hit model related to the 15q11.2 deletion would be an important hypothesis to be considered.

Noise-robust assessment of SNP array based CNV calls through local noise estimation of log R ratios

Arrays based on single nucleotide polymorphisms (SNPs) have been successful for the large scale discovery of copy number variants (CNVs). However, current CNV calling algorithms still have limitations in detecting CNVs with high specificity and sensitivity, especially in case of small (<100 kb) CNVs. Therefore, this study presents a simple statistical analysis to evaluate CNV calls from SNP arrays in order to improve the noise-robustness of existing CNV calling algorithms. The proposed approach estimates local noise of log R ratios and returns the probability that a certain observation is different from this log R ratio noise level. This probability can be triggered at different thresholds to tailor specificity and/or sensitivity in a flexible way. Moreover, a comparison based on qPCR experiments showed that the proposed noise-robust CNV calls outperformed original ones for multiple threshold values.

Copy Number Variation

Differences between genomes can be due to single nucleotide variants (SNPs), translocations, inversions and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 250 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease or phenotypic traits.While the link between SNPs and disease susceptibility has been well studied, to date there are still very few published CNV genome-wide association studies; probably owing to the fact that CNV analysis remains a slightly more complex task than SNP analysis (both in term of bioinformatics workflow and uncertainty in the CNV calling leading to high false positive rates and unknown false negative rates). This chapter aims at explaining computational methods for the analysis of CNVs, ranging from study design, data processing and quality control, up to genome-wide association study with clinical traits.

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing

Background

Copy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches.

Results

We report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions.

Conclusions

Our study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-017-0352-z) contains supplementary material, which is available to authorized users.

Clinical interpretation of copy number variants in the human genome

Molecular methods, by which copy number variants (CNVs) detection is available, have been gradually introduced into routine diagnostics over the last 15 years. Despite this, some CNVs continue to be a huge challenge when it comes to clinical interpretation. CNVs are an important source of normal and pathogenic variants, but, in many cases, their impact on human health depends on factors that are not yet known. Therefore, perception of their clinical consequences can change over time, as our knowledge grows. This review summarises guidelines that facilitate correct classification of identified changes and discusses difficulties with the interpretation of rare, small CNVs.

Towards standardization of next-generation sequencing of FFPE samples for clinical oncology: intrinsic obstacles and possible solutions

BACKGROUND

Next generation sequencing has a potential to revolutionize the management of cancer patients within the framework of precision oncology. Nevertheless, lack of standardization decelerated entering of the technology into the clinical testing space. Here we dissected a number of common problems of NGS diagnostics in oncology and introduced ways they can be resolved.

METHODS

DNA was extracted from 26 formalin fixed paraffin embedded (FFPE) specimens and processed with the TrueSeq Amplicon Cancer Panel (Illumina Inc, San Diego, California) targeting 48 cancer-related genes and sequenced in single run. Sequencing data were comparatively analyzed by several bioinformatics pipelines.

RESULTS

Libraries yielded sufficient coverage to detect even low prevalent mutations. We found that the number of FFPE sequence artifacts significantly correlates with pre-normalization concentration of libraries (rank correlation -0.81; p < 1e-10), thus, contributing to sample-specific variant detection cut-offs. Surprisingly, extensive validation of EGFR mutation calls by a combination of aligners and variant callers resulted in identification of two false negatives and one false positive that were due to complexity of underlying genomic change, confirmed by Sanger sequencing. Additionally, the study of the non-EGFR amplicons revealed 33 confirmed unique mutations in 17 genes, with TP53 being the most frequently mutated. Clinical relevance of these finding is discussed.

CONCLUSIONS

Reporting of entire mutational spectrum revealed by targeted sequencing is questionable, at least until the clinically-driven guidelines on reporting of somatic mutations are established. The standardization of sequencing protocols, especially their data analysis components, requires assay-, disease-, and, in many cases, even sample-specific customization that could be performed only in cooperation with clinicians.

Clinical detection of deletion structural variants in whole-genome sequences

Optimal management of acutely ill infants with monogenetic diseases requires rapid identification of causative haplotypes. Whole-genome sequencing (WGS) has been shown to identify pathogenic nucleotide variants in such infants. Deletion structural variants (DSVs, >50 nt) are implicated in many genetic diseases, and tools have been designed to identify DSVs using short-read WGS. Optimisation and integration of these tools into a WGS pipeline could improve diagnostic sensitivity and specificity of WGS. In addition, it may improve turnaround time when compared with current CNV assays, enhancing utility in acute settings. Here we describe DSV detection methods for use in WGS for rapid diagnosis in acutely ill infants: SKALD (Screening Konsensus and Annotation of Large Deletions) combines calls from two tools (Breakdancer and GenomeStrip) with calibrated filters and clinical interpretation rules. In four WGS runs, the average analytic precision (positive predictive value) of SKALD was 78%, and recall (sensitivity) was 27%, when compared with validated reference DSV calls. When retrospectively applied to a cohort of 36 families with acutely ill infants SKALD identified causative DSVs in two. The first was heterozygous deletion of exons 1–3 of MMP21 in trans with a heterozygous frame-shift deletion in two siblings with transposition of the great arteries and heterotaxy. In a newborn female with dysmorphic features, ventricular septal defect and persistent pulmonary hypertension, SKALD identified the breakpoints of a heterozygous, de novo 1p36.32p36.13 deletion. In summary, consensus DSV calling, implemented in an 8-h computational pipeline with parameterised filtering, has the potential to increase the diagnostic yield of WGS in acutely ill neonates and discover novel disease genes.

Tracking Cancer Genetic Evolution using OncoTrack

It is difficult for existing methods to quantify, and track the constant evolution of cancers due to high heterogeneity of mutations. However, structural variations associated with nucleotide number changes show repeatable patterns in localized regions of the genome. Here we introduce SPKMG, which generalizes nucleotide number based properties of genes, in statistical terms, at the genome-wide scale. It is measured from the normalized amount of aligned NGS reads in exonic regions of a gene. SPKMG values are calculated within OncoTrack. SPKMG values being continuous numeric variables provide a statistical metric to track DNA level changes. We show that SPKMG measures of cancer DNA show a normative pattern at the genome-wide scale. The analysis leads to the discovery of core cancer genes and also provides novel dynamic insights into the stage of cancer, including cancer development, progression, and metastasis. This technique will allow exome data to also be used for quantitative LOH/CNV analysis for tracking tumour progression and evolution with a higher efficiency.

New quality measure for SNP array based CNV detection

MOTIVATION

Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software.

RESULTS

Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations.

AVAILABILITY AND IMPLEMENTATION

http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.

Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals

The Tohoku Medical Megabank Organization reports the whole-genome sequences of 1,070 healthy Japanese individuals and construction of a Japanese population reference panel (1KJPN). Here we identify through this high-coverage sequencing (32.4 × on average), 21.2 million, including 12 million novel, single-nucleotide variants (SNVs) at an estimated false discovery rate of <1.0%. This detailed analysis detected signatures for purifying selection on regulatory elements as well as coding regions. We also catalogue structural variants, including 3.4 million insertions and deletions, and 25,923 genic copy-number variants. The 1KJPN was effective for imputing genotypes of the Japanese population genome wide. These data demonstrate the value of high-coverage sequencing for constructing population-specific variant panels, which covers 99.0% SNVs of minor allele frequency ≥0.1%, and its value for identifying causal rare variants of complex human disease phenotypes in genetic association studies.

The Tohoku Medical Megabank Organization establishes a biobank with detailed patient health care and genome information. Here the authors analyse whole-genome sequences of 1,070 Japanese individuals, allowing them to catalogue 21 million single-nucleotide variants including 12 million novel ones.

Genomic copy number variation in Mus musculus

BACKGROUND

Copy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously.

RESULTS

We found 9634 putative autosomal CNVs across the samples affecting 6.87% of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR).

CONCLUSION

The analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies.

Function of cancer associated genes revealed by modern univariate and multivariate association tests

Copy number variation (CNV) plays a role in pathogenesis of many human diseases, especially cancer. Several whole genome CNV association studies have been performed for the purpose of identifying cancer associated CNVs. Here we undertook a novel approach to whole genome CNV analysis, with the goal being identification of associations between CNV of different genes (CNV-CNV) across 60 human cancer cell lines. We hypothesize that these associations point to the roles of the associated genes in cancer, and can be indicators of their position in gene networks of cancer-driving processes. Recent studies show that gene associations are often non-linear and non-monotone. In order to obtain a more complete picture of all CNV associations, we performed omnibus univariate analysis by utilizing dCov, MIC, and HHG association tests, which are capable of detecting any type of association, including non-monotone relationships. For comparison we used Spearman and Pearson association tests, which detect only linear or monotone relationships. Application of dCov, MIC and HHG tests resulted in identification of twice as many associations compared to those found by Spearman and Pearson alone. Interestingly, most of the new associations were detected by the HHG test. Next, we utilized dCov's and HHG's ability to perform multivariate analysis. We tested for association between genes of unknown function and known cancer-related pathways. Our results indicate that multivariate analysis is much more effective than univariate analysis for the purpose of ascribing biological roles to genes of unknown function. We conclude that a combination of multivariate and univariate omnibus association tests can reveal significant information about gene networks of disease-driving processes. These methods can be applied to any large gene or pathway dataset, allowing more comprehensive analysis of biological processes.

Detection and correction of artefacts in estimation of rare copy number variants and analysis of rare deletions in type 1 diabetes

Copy number variants (CNVs) have been proposed as a possible source of ‘missing heritability’ in complex human diseases. Two studies of type 1 diabetes (T1D) found null associations with common copy number polymorphisms, but CNVs of low frequency and high penetrance could still play a role. We used the Log-R-ratio intensity data from a dense single nucleotide polymorphism (SNP) array, ImmunoChip, to detect rare CNV deletions (rDELs) and duplications (rDUPs) in 6808 T1D cases, 9954 controls and 2206 families with T1D-affected offspring. Initial analyses detected CNV associations. However, these were shown to be false-positive findings, failing replication with polymerase chain reaction. We developed a pipeline of quality control (QC) tests that were calibrated using systematic testing of sensitivity and specificity. The case–control odds ratios (OR) of CNV burden on T1D risk resulting from this QC pipeline converged on unity, suggesting no global frequency difference in rDELs or rDUPs. There was evidence that deletions could impact T1D risk for a small minority of cases, with enrichment for rDELs longer than 400 kb (OR = 1.57, P = 0.005). There were also 18 de novo rDELs detected in affected offspring but none for unaffected siblings (P = 0.03). No specific CNV regions showed robust evidence for association with T1D, although frequencies were lower than expected (most less than 0.1%), substantially reducing statistical power, which was examined in detail. We present an R-package, plumbCNV, which provides an automated approach for QC and detection of rare CNVs that can facilitate equivalent analyses of large-scale SNP array datasets.

Investigation of copy number variation in children with conotruncal heart defects

BACKGROUND

Congenital heart defects (CHD) are the most prevalent group of structural abnormalities at birth and one of the main causes of infant morbidity and mortality. Studies have shown a contribution of the copy number variation in the genesis of cardiac malformations.

OBJECTIVES

Investigate gene copy number variation (CNV) in children with conotruncal heart defect.

METHODS

Multiplex ligation-dependent probe amplification (MLPA) was performed in 39 patients with conotruncal heart defect. Clinical and laboratory assessments were conducted in all patients. The parents of the probands who presented abnormal findings were also investigated.

RESULTS

Gene copy number variation was detected in 7/39 patients: 22q11.2 deletion, 22q11.2 duplication, 15q11.2 duplication, 20p12.2 duplication, 19p deletion, 15q and 8p23.2 duplication with 10p12.31 duplication. The clinical characteristics were consistent with those reported in the literature associated with the encountered microdeletion/microduplication. None of these changes was inherited from the parents.

CONCLUSIONS

Our results demonstrate that the technique of MLPA is useful in the investigation of microdeletions and microduplications in conotruncal congenital heart defects. Early diagnosis of the copy number variation in patients with congenital heart defect assists in the prevention of morbidity and decreased mortality in these patients.

Amplification of Chromosome 1q Genes Encoding the Phosphoinositide Signalling Enzymes PI4KB, AKT3, PIP5K1A and PI3KC2B in Breast Cancer

Little is known about the possible oncogenic roles of genes encoding for the phosphatidylinositol 4-kinases, a family of enzymes that regulate an early step in phosphoinositide signalling. To address this issue, the mutational status of all four human phosphatidylinositol 4-kinases genes was analyzed across 852 breast cancer samples using the COSMIC data resource. Point mutations in the phosphatidylinositol 4-kinase genes were uncommon and appeared in less than 1% of the patient samples however, 62% of the tumours had increases in gene copy number for PI4KB which encodes the phosphatidylinositol 4-kinase IIIbeta isozyme. Extending this analysis to subsequent enzymes in the phosphoinositide signalling cascades revealed that the only PIP5K1A, PI3KC2B and AKT3 genes exhibited similar patterns of gene copy number variation. By comparison, gene copy number increases for established oncogenes such as EGFR and HER2/Neu were only evident in 20% of the samples. The PI4KB, PIP5K1A, PI3KC2B and AKT3 genes are related in that they all localize to chromosome 1q which is often structurally and numerically abnormal in breast cancer. These results demonstrate that a gene quartet encoding a potential phosphoinositide signalling pathway is amplified in a subset of breast cancers.

Clinical interpretation of CNVs with cross-species phenotype data

BACKGROUND

Clinical evaluation of CNVs identified via techniques such as array comparative genome hybridisation (aCGH) involves the inspection of lists of known and unknown duplications and deletions with the goal of distinguishing pathogenic from benign CNVs. A key step in this process is the comparison of the individual's phenotypic abnormalities with those associated with Mendelian disorders of the genes affected by the CNV. However, because often there is not much known about these human genes, an additional source of data that could be used is model organism phenotype data. Currently, almost 6000 genes in mouse and zebrafish are, when knocked out, associated with a phenotype in the model organism, but no disease is known to be caused by mutations in the human ortholog. Yet, searching model organism databases and comparing model organism phenotypes with patient phenotypes for identifying novel disease genes and medical evaluation of CNVs is hindered by the difficulty in integrating phenotype information across species and the lack of appropriate software tools.

METHODS

Here, we present an integrated ranking scheme based on phenotypic matching, degree of overlap with known benign or pathogenic CNVs and the haploinsufficiency score for the prioritisation of CNVs responsible for a patient's clinical findings.

RESULTS

We show that this scheme leads to significant improvements compared with rankings that do not exploit phenotypic information. We provide a software tool called PhenogramViz, which supports phenotype-driven interpretation of aCGH findings based on multiple data sources, including the integrated cross-species phenotype ontology Uberpheno, in order to visualise gene-to-phenotype relations.

CONCLUSIONS

Integrating and visualising cross-species phenotype information on the affected genes may help in routine diagnostics of CNVs.

Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

In the present study, recurrent copy number variations (CNVs) from non-tumor blood cell DNAs of Caucasian non-cancer subjects and glioma, myeloma, and colorectal cancer-patients, and Korean non-cancer subjects and hepatocellular carcinoma, gastric cancer, and colorectal cancer patients, were found to reveal for each of the two ethnic cohorts highly significant differences between cancer patients and controls with respect to the number of CN-losses and size-distribution of CN-gains, suggesting the existence of recurrent constitutional CNV-features useful for prediction of predisposition to cancer. Upon identification by machine learning, such CNV-features could extensively discriminate between cancer-patient and control DNAs. When the CNV-features selected from a learning-group of Caucasian or Korean mixed DNAs consisting of both cancer-patient and control DNAs were employed to make predictions on the cancer predisposition of an unseen test group of mixed DNAs, the average prediction accuracy was 93.6% for the Caucasian cohort and 86.5% for the Korean cohort.

ADaCGH2: parallelized analysis of (big) CNA data

MOTIVATION

Studies of genomic DNA copy number alteration can deal with datasets with several million probes and thousands of subjects. Analyzing these data with currently available software (e.g. as available from BioConductor) can be extremely slow and may not be feasible because of memory requirements.

RESULTS

We have developed a BioConductor package, ADaCGH2, that parallelizes the main segmentation algorithms (using forking on multicore computers or parallelization via message passing interface, etc., in clusters of computers) and uses ff objects for reading and data storage. We show examples of data with 6 million probes per array; we can analyze data that would otherwise not fit in memory, and compared with the non-parallelized versions we can achieve speedups of 25-40 times on a 64-cores machine.

AVAILABILITY AND IMPLEMENTATION

ADaCGH2 is an R package available from BioConductor. Version 2.3.11 or higher is available from the development branch: http://www.bioconductor.org/packages/devel/bioc/html/ADaCGH2.html.

PBHoney: identifying genomic variants via long-read discordance and interrupted mapping

Background

As resequencing projects become more prevalent across a larger number of species, accurate variant identification will further elucidate the nature of genetic diversity and become increasingly relevant in genomic studies. However, the identification of larger genomic variants via DNA sequencing is limited by both the incomplete information provided by sequencing reads and the nature of the genome itself. Long-read sequencing technologies provide high-resolution access to structural variants often inaccessible to shorter reads.

Results

We present PBHoney, software that considers both intra-read discordance and soft-clipped tails of long reads (>10,000 bp) to identify structural variants. As a proof of concept, we identify four structural variants and two genomic features in a strain of Escherichia coli with PBHoney and validate them via de novo assembly. PBHoney is available for download at http://sourceforge.net/projects/pb-jelly/.

Conclusions

Implementing two variant-identification approaches that exploit the high mappability of long reads, PBHoney is demonstrated as being effective at detecting larger structural variants using whole-genome Pacific Biosciences RS II Continuous Long Reads. Furthermore, PBHoney is able to discover two genomic features: the existence of Rac-Phage in isolate; evidence of E. coli’s circular genome.

Opposite effects on facial morphology due to gene dosage sensitivity

Sequencing technology is increasingly demonstrating the impact of genomic copy number variation (CNV) on phenotypes. Opposing variation in growth, head size, cognition and behaviour is known to result from deletions and reciprocal duplications of some genomic regions. We propose normative inversion of face shape, opposing difference from a matched norm, as a basis for investigating the effects of gene dosage on craniofacial development. We use dense surface modelling techniques to match any face (or part of a face) to a facial norm of unaffected individuals of matched age, sex and ethnicity and then we reverse the individual’s face shape differences from the matched norm to produce the normative inversion. We demonstrate for five genomic regions, 4p16.3, 7q11.23, 11p15, 16p13.3 and 17p11.2, that such inversion for individuals with a duplication or (epi)-mutation produces facial forms remarkably similar to those associated with a deletion or opposite (epi-)mutation of the same region, and vice versa. The ability to visualise and quantify face shape effects of gene dosage is of major benefit for determining whether a CNV is the cause of the phenotype of an individual and for predicting reciprocal consequences. It enables face shape to be used as a relatively simple and inexpensive functional analysis of the gene(s) involved.