Analyzing copy number variation using SNP array data: protocols for calling CNV and association tests

Rare copy number variant analysis in case-control studies using snp array data: a scalable and automated data analysis pipeline

BACKGROUND

Rare copy number variants (CNVs) significantly influence the human genome and may contribute to disease susceptibility. High-throughput SNP genotyping platforms provide data that can be used for CNV detection, but it requires the complex pipelining of bioinformatic tools. Here, we propose a flexible bioinformatic pipeline for rare CNV analysis from human SNP array data.

RESULTS

The pipeline consists of two major sub-pipelines: (1) Calling and quality control (QC) analysis, and (2) Rare CNV analysis. It is implemented in Snakemake following a rule-based structure that enables automation and scalability while maintaining flexibility.

CONCLUSIONS

Our pipeline automates the detection and analysis of rare CNVs. It implements a rigorous CNV quality control, assesses the frequencies of these rare CNVs in patients versus controls, and evaluates the impact of CNVs on specific genes or pathways. We hence aim to provide an efficient yet flexible bioinformatic framework to investigate rare CNVs in biomedical research.

Rare copy number variation in autoimmune Addison's disease

Autoimmune Addison's disease (AAD) is a rare but life-threatening endocrine disorder caused by an autoimmune destruction of the adrenal cortex. A previous genome-wide association study (GWAS) has shown that common variants near immune-related genes, which mostly encode proteins participating in the immune response, affect the risk of developing this condition. However, little is known about the contribution of copy number variations (CNVs) to AAD susceptibility. We used the genome-wide genotyping data from Norwegian and Swedish individuals (1,182 cases and 3,810 controls) to investigate the putative role of CNVs in the AAD aetiology. Although the frequency of rare CNVs was similar between cases and controls, we observed that larger deletions (>1,000 kb) were more common among patients (OR = 4.23, 95% CI 1.85-9.66, p = 0.0002). Despite this, none of the large case-deletions were conclusively pathogenic, and the clinical presentation and an AAD-polygenic risk score were similar between cases with and without the large CNVs. Among deletions exclusive to individuals with AAD, we highlight two ultra-rare deletions in the genes LRBA and BCL2L11, which we speculate might have contributed to the polygenic risk in these carriers. In conclusion, rare CNVs do not appear to be a major cause of AAD but further studies are needed to ascertain the potential contribution of rare deletions to the polygenic load of AAD susceptibility.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

BACKGROUND

Copy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.

RESULTS

Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake.

CONCLUSIONS

The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

[An analysis of the relationship between genetic factors and the risk of schizophrenia]

The etiology and pathogenesis of schizophrenia remain poorly understood, but it has been established that the contribution of heredity to the development of the disease is about 80-85%. Over the past decade, significant progress has been made in the search for specific genetic variants associated with the development of schizophrenia. The review discusses the results of modern large-scale studies aimed at searching for genetic associations with schizophrenia: genome-wide association studies (GWAS) and the search for rare variants (mutations or copy number variations, CNV), including the use of whole exome sequencing. We synthesize data on currently known genes that are significantly associated with schizophrenia and discuss their biological functions in order to identify the main molecular pathways involved in the pathophysiology of schizophrenia.

Lipolysis and gestational diabetes mellitus onset: a case-cohort genome-wide association study in Chinese

BACKGROUND

Genetic knowledge of gestational diabetes mellitus (GDM) in Chinese women is quite limited. This study aimed to identify the risk factors and mechanism of GDM at the genetic level in a Chinese population.

METHODS

We conducted a genome-wide association study (GWAS) based on single nucleotide polymorphism (SNP) array genotyping (ASA-CHIA Bead chip, Illumina) and a case-cohort study design. Variants including SNPs, copy number variants (CNVs), and insertions-deletions (InDels) were called from genotyping data. A total of 2232 pregnant women were enrolled in their first/second trimester between February 2018 and December 2020 from Anqing Municipal Hospital in Anhui Province, China. The GWAS included 193 GDM patients and 819 subjects without a diabetes diagnosis, and risk ratios (RRs) and their 95% confidence intervals (CIs) were estimated by a regression-based method conditional on the population structure. The calling and quality control of genotyping data were performed following published guidelines. CNVs were merged into CNV regions (CNVR) to simplify analyses. To interpret the GWAS results, gene mapping and overexpression analyses (ORAs) were further performed to prioritize the candidate genes and related biological mechanisms.

RESULTS

We identified 14 CNVRs (false discovery rate corrected P values < 0.05) and two suggestively significant SNPs (P value < 0.00001) associated with GDM, and a total of 19 candidate genes were mapped. Ten genes were significantly enriched in gene sets related to lipase (triglyceride lipase and lipoprotein lipase) activity (LIPF, LIPK, LIPN, and LIPJ genes), oxidoreductase activity (TPH1 and TPH2 genes), and cellular components beta-catenin destruction complex (APC and GSK3B genes), Wnt signalosome (APC and GSK3B genes), and lateral element in the Gene Ontology resource (BRCA1 and SYCP2 genes) by two ORA methods (adjusted P values < 0.05).

CONCLUSIONS

Genes related to lipolysis, redox reaction, and proliferation of islet β-cells are associated with GDM in Chinese women. Energy metabolism, particularly lipolysis, may play an important role in GDM aetiology and pathology, which needs further molecular studies to verify.

Genome-Wide Copy Number Variant and High-Throughput Transcriptomics Analyses of Placental Tissues Underscore Persisting Child Susceptibility in At-Risk Pregnancies Cleared in Standard Genetic Testing

Several studies have shown that children from pregnancies with estimated first-trimester risk based on fetal nuchal translucency thickness and abnormal maternal serum pregnancy protein and hormone levels maintain a higher likelihood of adverse outcomes, even if initial testing for known genetic conditions is negative. We used the Finnish InTraUterine cohort (ITU), which is a comprehensively characterized perinatal cohort consisting of 943 mothers and their babies followed throughout pregnancy and 18 months postnatally, including mothers shortlisted for prenatal genetic testing but cleared for major aneuploidies (cases: n = 544, 57.7%) and control pregnancies (n = 399, 42.3%). Using genome-wide genotyping and RNA sequencing of first-trimester and term placental tissue, combined with medical information from registry data and maternal self-report data, we investigated potential negative medical outcomes and genetic susceptibility to disease and their correlates in placenta gene expression. Case mothers did not present with higher levels of depression, perceived stress, or anxiety during pregnancy. Case children were significantly diagnosed more often with congenital malformations of the circulatory system (4.12 (95% CI [1.22−13.93]) higher hazard) and presented with significantly more copy number duplications as compared to controls (burden analysis, based on all copy number variants (CNVs) with at most 10% frequency, 823 called duplications in 297 cases versus 626 called duplications in 277 controls, p = 0.01). Fifteen genes showed differential gene expression (FDR < 0.1) in association with congenital malformations in first-trimester but not term placenta. These were significantly enriched for genes associated with placental dysfunction. In spite of normal routine follow-up prenatal testing results in early pregnancy, case children presented with an increased likelihood of negative outcomes, which should prompt vigilance in follow-up during pregnancy and after birth.

Copy number variant analysis and expression profiling of the olfactory receptor-rich 11q11 region in obesity predisposition

Genome-wide copy number surveys associated chromosome 11q11 with obesity. As this is an olfactory receptor-rich region, we hypothesize that genetic variation in olfactory receptor genes might be implicated in the pathogenesis of obesity. Multiplex Amplicon Quantification analysis was applied to screen for copy number variants at chromosome 11q11 in 627 patients with obesity and 330 healthy-weight individuals. A ± 80 kb deletion with an internally 1.3 kb retained segment was identified, covering the three olfactory receptor genes OR4C11, OR4P4, and OR4S2. A significant increase in copy number loss(es) was perceived in our patient cohort (MAF = 27%; p = 0.02). Gene expression profiling in metabolic relevant tissues was performed to evaluate the functional impact of the obesity susceptible locus. All three 11q11 genes were present in visceral and subcutaneous adipose tissue while no expression was perceived in the liver. These results support the 'metabolic system' hypothesis and imply that gene disruption of OR4C11, OR4P4, and OR4S2 will negatively influence energy metabolism, ultimately leading to fat accumulation and obesity. Our study thus demonstrates a role for structural variation within olfactory receptor-rich regions in complex diseases and defines the 11q11 deletion as a risk factor for obesity.

A Practical Guide for Structural Variation Detection in the Human Genome

Profiling genetic variants-including single nucleotide variants, small insertions and deletions, copy number variations, and structural variations (SVs)-from both healthy individuals and individuals with disease is a key component of genetic and biomedical research. SVs are large-scale changes in the genome and involve breakage and rejoining of DNA fragments. They may affect thousands to millions of nucleotides and can lead to loss, gain, and reshuffling of genes and regulatory elements. SVs are known to impact gene expression and potentially result in altered phenotypes and diseases. Therefore, identifying SVs from the human genomes is particularly important. In this review, I describe advantages and disadvantages of the available high-throughput assays for the discovery of SVs, which are the most challenging genetic alterations to detect. A practical guide is offered to suggest the most suitable strategies for discovering different types of SVs including common germline, rare, somatic, and complex variants. I also discuss factors to be considered, such as cost and performance, for different strategies when designing experiments. Last, I present several approaches to identify potential SV artifacts caused by samples, experimental procedures, and computational analysis. © 2020 Wiley Periodicals LLC.

Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches?

Copy number aberrations (CNAs) are known to strongly affect oncogenes and tumour suppressor genes. Given the critical role CNAs play in cancer research, it is essential to accurately identify CNAs from tumour genomes. One particular challenge in finding CNAs is the effect of confounding variables. To address this issue, we assessed how commonly used CNA identification algorithms perform on SNP 6.0 genotyping data in the presence of confounding variables. We simulated realistic synthetic data with varying levels of three confounding variables-the tumour purity, the length of a copy number region and the CNA burden (the percentage of CNAs present in a profiled genome)-and evaluated the performance of OncoSNP, ASCAT, GenoCNA, GISTIC and CGHcall. Furthermore, we implemented and assessed CGHcall*, an adjusted version of CGHcall accounting for high CNA burden. Our analysis on synthetic data indicates that tumour purity and the CNA burden strongly influence the performance of all the algorithms. No algorithm can correctly find lost and gained genomic regions across all tumour purities. The length of CNA regions influenced the performance of ASCAT, CGHcall and GISTIC. OncoSNP, GenoCNA and CGHcall* showed little sensitivity. Overall, CGHcall* and OncoSNP showed reasonable performance, particularly in samples with high tumour purity. Our analysis on the HapMap data revealed a good overlap between CGHcall, CGHcall* and GenoCNA results and experimentally validated data. Our exploratory analysis on the TCGA HNSCC data revealed plausible results of CGHcall, CGHcall* and GISTIC in consensus HNSCC CNA regions. Code is available at https://github.com/adspit/PASCAL.

Genome wide analysis of rare copy number variations in alcohol abuse or dependence

Genetics plays an important role in alcohol abuse/dependence. Its heritability has been estimated as 45-65%. Rare copy number variations (CNVs) have been confirmed as relevant genetic factors in other neuropsychiatric disorders, such as autism spectrum disorders, schizophrenia, epilepsy, or Tourette syndrome. In the present study, we analyzed the role of rare CNVs affecting exons of coding genes in a sample from Northwest Spain genotyped using the Illumina Infinium PsychArray Beadchip. After rigorous genotyping quality control procedure, 712 patients with alcohol abuse or dependence and 804 controls were used for CNV detection. CNV calling was performed using PennCNV and cnvPartition, and analyses were restricted to CNVs of at least 100 kb and including at least 10 single nucleotide polymorphisms. Logistic regression was used to test for the effect of CNV as well as number of genes affected by CNVs on case/control status, after adjustment for demographic and experimental covariates. We have found an excess of deletions (p = 0.008) and genes affected by deletions (p = 0.017) in cases. This effect was restricted to the 14.8% of affected genes that are intolerant to loss-of-function mutations (gene count p = 0.009). The importance of this subset of genes is emerging in other psychiatric disorders of neurodevelopmental origin, suggesting that disturbance in neurodevelopment mediated by genetic alterations may be a risk factor for alcohol use disorder.

Genome-wide Association Study (GWAS) of Germline Copy Number Variations (CNVs) Reveal Genetic Risks of Prostate Cancer in Chinese population

Introduction: The associations between Prostate cancer (PCa) and germline copy number variations (CNVs) in genome-wide level based on Chinese population are unknown. The objective of this study was to identify possible PCa-risk associated CNV regions in Chinese population. Materials and Methods: We performed a genome-wide association study for CNV in 1,417 PCa cases and 1,008 controls in Chinese population. Results: 7 risk-associated CNVs were identified for PCa after association analyses (P <7.2×10^-6). Another 34 CNVs were found to be potentially risk-associated CNVs (P<0.05). Among the total 41 CNVs, 27 CNVs were risk variations and the other 14 were found to be protective of PCa. 25 of the CNVs (19 duplications and 6 deletions) were located in gene regions while 16 CNVs (9 duplications and 7 deletions) were located in intergenic regions. We identified a higher burden of gaining PCa-risk CNVs and a lower frequency of protective CNVs in cases than controls. Bioinformatics analyses suggested that genes related to PCa risk-associated CNVs were significantly enriched in some biological processes, cellular components and molecular functions. Conclusion: These results provided additional information of genetic risks for PCa. Several CNV regions involved actionable genes that might be potential gene for target therapy. Additional validation and functional studies are warranted for these results.

Copy Number Variations in Amyotrophic Lateral Sclerosis: Piecing the Mosaic Tiles Together through a Systems Biology Approach

Amyotrophic lateral sclerosis (ALS) is a devastating and still untreatable motor neuron disease. Despite the molecular mechanisms underlying ALS pathogenesis that are still far from being understood, several studies have suggested the importance of a genetic contribution in both familial and sporadic forms of the disease. In addition to single-nucleotide polymorphisms (SNPs), which account for only a limited number of ALS cases, a consistent number of common and rare copy number variations (CNVs) have been associated to ALS. Most of the CNV-based association studies use a traditional candidate-gene approach that is inadequate for uncovering the genetic architectures of complex traits like ALS. The emergent paradigm of “systems biology” may offer a new perspective to better interpret the wide spectrum of CNVs in ALS, enabling the characterization of the complex network of gene products underlying ALS pathogenesis. In this review, we will explore the landscape of CNVs in ALS, putting specific emphasis on the functional impact of common CNV regions and genes consistently associated with increased risk of developing disease. In addition, we will discuss the potential contribution of multiple rare CNVs in ALS pathogenesis, focusing our attention on the complex mechanisms by which these proteins might impact, individually or in combination, the genetic susceptibility of ALS. The comprehensive detection and functional characterization of common and rare candidate risk CNVs in ALS susceptibility may bring new pieces into the intricate mosaic of ALS pathogenesis, providing interesting and important implications for a more precise molecular biomarker-assisted diagnosis and more effective and personalized treatments.

Clinical implications of copy number variations in autoimmune disorders

Human genetic variation is represented by the genetic differences both within and among populations, and most genetic variants do not cause overt diseases but contribute to disease susceptibility and influence drug response. During the last century, various genetic variants, such as copy number variations (CNVs), have been associated with diverse human disorders. Here, we review studies on the associations between CNVs and autoimmune diseases to gain some insight. First, some CNV loci are commonly implicated in various autoimmune diseases, such as Fcγ receptors in patients with systemic lupus erythemoatosus or idiopathic thrombocytopenic purpura and β-defensin genes in patients with psoriasis or Crohn's disease. This means that when a CNV locus is associated with a particular autoimmune disease, we should examine its potential associations with other diseases. Second, interpopulation or interethnic differences in the effects of CNVs on phenotypes exist, including disease susceptibility, and evidence suggests that CNVs are important to understand susceptibility to and pathogenesis of autoimmune diseases. However, many findings need to be replicated in independent populations and different ethnic groups. The validity and reliability of detecting CNVs will improve quickly as genotyping technology advances, which will support the required replication.