Assessment of copy number variation using the Illumina Infinium 1M SNP-array: a comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study

Descriptive Statistics and Genome-Wide Copy Number Analysis of Milk Production Traits of Jiangsu Chinese Holstein Cows

Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation (p < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits (p < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.

Saliva DNA: An alternative biospecimen for single nucleotide polymorphism chromosomal microarray analysis in autism

Chromosomal microarray analysis (CMA) is typically performed for investigation of autism using blood DNA. However, blood collection poses significant challenges for autistic children with repetitive behaviors and sensory and communication issues, often necessitating physical restraint or sedation. Noninvasive saliva collection offers an alternative, however, no published studies to date have evaluated saliva DNA for CMA in autism. Furthermore, previous reports suggest that saliva is suboptimal for detecting copy number variation. We therefore aimed to evaluate saliva DNA for single nucleotide polymorphism (SNP) CMA in autistic children. Saliva DNA from 48 probands and parents (n = 133) was obtained with a mean concentration of 141.7 ng/μL. SNP CMA was successful in 131/133 (98.5%) patients from which we correlated the size and accuracy of a copy number variant(s) called between a proband and carrier parent, and for a subgroup (n = 17 probands) who had a previous CMA using blood sample. There were no discordant copy number variant results between the proband and carrier parent, or the subgroup, however, there was an acceptable mean size difference of 0.009 and 0.07 Mb, respectively. Our findings demonstrate that saliva DNA can be an alternative for SNP CMA in autism, which avoids blood collection with significant implications for clinical practice guidelines.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Copy number variants in genomes of local sheep breeds from Russia

Copy number variants (CNVs) are genomic structural variations that contribute to many adaptive and economically important traits in livestock. In this study, we detected CNVs in 354 animals from 16 Russian indigenous sheep breeds and analysed their possible functional roles. Our analysis of the entire sample set resulted in 4527 CNVs forming 1450 CNV regions (CNVRs). When constructing CNVRs for individual breeds, a total of 2715 regions ranging from 88 in Groznensk to 337 in Osetin breeds were identified. To make interbreed CNVR frequency comparison possible, we also identified core CNVRs using CNVs with overlapping chromosomal locations found in different breeds. This resulted in 137 interbreed CNVRs with frequency >15% in at least one breed. Functional enrichment analysis of genes affected by CNVRs in individual breeds revealed 12 breeds with significant enrichments in olfactory perception, PRAME family proteins, and immune response. Function of genes affected by interbreed and breed-specific CNVRs revealed candidates related to domestication, adaptation to high altitudes and cold climates, reproduction, parasite resistance, milk and meat qualities, wool traits, fat storage, and fat metabolism. Our work is the first attempt to uncover and characterise the CNV makeup of Russian indigenous sheep breeds. Further experimental and functional validation of CNVRs would help in developing new and improving existing sheep breeds.

Genome-wide CNV investigation suggests a role for cadherin, Wnt, and p53 pathways in primary open-angle glaucoma

BACKGROUND

To investigate whether copy number variations (CNVs) are implicated in molecular mechanisms underlying primary open-angle glaucoma (POAG), we used genotype data of POAG individuals and healthy controls from two case-control studies, AGS (n = 278) and GLGS-UGLI (n = 1292). PennCNV, QuantiSNP, and cnvPartition programs were used to detect CNV. Stringent quality controls at both sample and marker levels were applied. The identified CNVs were intersected in CNV region (CNVR). After, we performed burden analysis, CNV-genome-wide association analysis, gene set overrepresentation and pathway analysis. In addition, in human eye tissues we assessed the expression of the genes lying within significant CNVRs.

RESULTS

We reported a statistically significant greater burden of CNVs in POAG cases compared to controls (p-value = 0,007). In common between the two cohorts, CNV-association analysis identified statistically significant CNVRs associated with POAG that span 11 genes (APC, BRCA2, COL3A1, HLA-DRB1, HLA-DRB5, HLA-DRB6, MFSD8, NIPBL, SCN1A, SDHB, and ZDHHC11). Functional annotation and pathway analysis suggested the involvement of cadherin, Wnt signalling, and p53 pathways.

CONCLUSIONS

Our data suggest that CNVs may have a role in the susceptibility of POAG and they can reveal more information on the mechanism behind this disease. Additional genetic and functional studies are warranted to ascertain the contribution of CNVs in POAG.

A global analysis of CNVs in Chinese indigenous fine-wool sheep populations using whole-genome resequencing

Background

Copy number variation (CNV) is an important source of genetic variation that has a significant influence on phenotypic diversity, economically important traits and the evolution of livestock species. In this study, the genome-wide CNV distribution characteristics of 32 fine-wool sheep from three breeds were analyzed using resequencing.

Results

A total of 1,747,604 CNVs were detected in this study, and 7228 CNV regions (CNVR) were obtained after merging overlapping CNVs; these regions accounted for 2.17% of the sheep reference genome. The average length of the CNVRs was 4307.17 bp. “Deletion” events took place more frequently than “duplication” or “both” events. The CNVRs obtained overlapped with previously reported sheep CNVRs to variable extents (4.39–55.46%). Functional enrichment analysis showed that the CNVR-harboring genes were mainly involved in sensory perception systems, nutrient metabolism processes, and growth and development processes. Furthermore, 1855 of the CNVRs were associated with 166 quantitative trait loci (QTL), including milk QTLs, carcass QTLs, and health-related QTLs, among others. In addition, the 32 fine-wool sheep were divided into horned and polled groups to analyze for the selective sweep of CNVRs, and it was found that the relaxin family peptide receptor 2 (RXFP2) gene was strongly influenced by selection.

Conclusions

In summary, we constructed a genomic CNV map for Chinese indigenous fine-wool sheep using resequencing, thereby providing a valuable genetic variation resource for sheep genome research, which will contribute to the study of complex traits in sheep.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07387-7.

Increasing the resolution and precision of psychiatric genome-wide association studies by re-imputing summary statistics using a large, diverse reference panel

Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large-scale genome-wide association studies (GWAS). Methods for direct imputation of GWAS summary-statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage-disequilibrium (LD) and that most of the methods using a small reference panel for example, ~2,500-subject coming from the 1000 Genome-Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: (a) uses a much larger and more diverse reference panel compared to traditional reference panels, and (b) can estimate weights of ethnic-mixture based solely on Z-scores, when allele frequencies are not available. We applied DISTMIX2 to GWAS summary-statistics from the psychiatric genetic consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post-traumatic stress disorder GWAS found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most psychiatric GWAS-studies.

Analysis of copy number variation in dogs implicates genomic structural variation in the development of anterior cruciate ligament rupture

Anterior cruciate ligament (ACL) rupture is an important condition of the human knee. Second ruptures are common and societal costs are substantial. Canine cranial cruciate ligament (CCL) rupture closely models the human disease. CCL rupture is common in the Labrador Retriever (5.79% prevalence), ~100-fold more prevalent than in humans. Labrador Retriever CCL rupture is a polygenic complex disease, based on genome-wide association study (GWAS) of single nucleotide polymorphism (SNP) markers. Dissection of genetic variation in complex traits can be enhanced by studying structural variation, including copy number variants (CNVs). Dogs are an ideal model for CNV research because of reduced genetic variability within breeds and extensive phenotypic diversity across breeds. We studied the genetic etiology of CCL rupture by association analysis of CNV regions (CNVRs) using 110 case and 164 control Labrador Retrievers. CNVs were called from SNPs using three different programs (PennCNV, CNVPartition, and QuantiSNP). After quality control, CNV calls were combined to create CNVRs using ParseCNV and an association analysis was performed. We found no strong effect CNVRs but found 46 small effect (max(T) permutation P<0.05) CCL rupture associated CNVRs in 22 autosomes; 25 were deletions and 21 were duplications. Of the 46 CCL rupture associated CNVRs, we identified 39 unique regions. Thirty four were identified by a single calling algorithm, 3 were identified by two calling algorithms, and 2 were identified by all three algorithms. For 42 of the associated CNVRs, frequency in the population was <10% while 4 occurred at a frequency in the population ranging from 10–25%. Average CNVR length was 198,872bp and CNVRs covered 0.11 to 0.15% of the genome. All CNVRs were associated with case status. CNVRs did not overlap previous canine CCL rupture risk loci identified by GWAS. Associated CNVRs contained 152 annotated genes; 12 CNVRs did not have genes mapped to CanFam3.1. Using pathway analysis, a cluster of 19 homeobox domain transcript regulator genes was associated with CCL rupture (P = 6.6E-13). This gene cluster influences cranial-caudal body pattern formation during embryonic limb development. Clustered genes were found in 3 CNVRs on chromosome 14 (HoxA), 28 (NKX6-2), and 36 (HoxD). When analysis was limited to deletion CNVRs, the association was strengthened (P = 8.7E-16). This study suggests a component of the polygenic risk of CCL rupture in Labrador Retrievers is associated with small effect CNVs and may include aspects of stifle morphology regulated by homeobox domain transcript regulator genes.

Genome-wide copy number variation-, validation- and screening study implicates a new copy number polymorphism associated with suicide attempts in major depressive disorder

BACKGROUND

The genetic basis of suicide attempts (SA) remains unclear. Especially the role of copy number variations (CNVs) remains to be elucidated. The present study aimed to identify susceptibility variants associated with SA among Chinese with major depressive disorder (MDD), covering both CNVs and single-nucleotide polymorphisms (SNPs).

METHODS

We conducted a genome-wide association study (GWAS) on MDD patients with and without SA and top results were tested in a replication study. A genome-wide CNV study was also performed. Subsequently, a validation assay using qRT-PCR technology was performed to confirm any associated CNVs and then applied to the entire cohort to examine the association.

RESULTS

Although GWAS did not identify any SNPs reaching genome-wide significance, we identified TPH2 as the top susceptibility gene (p-value = 2.75e-05) in gene-based analysis, which is a strong biological candidate for its role in the serotonergic system. As for CNV analysis, we found that the global rate of CNV was higher in SA than that in non-SA subjects (p-value = 0.023). Genome-wide CNV study revealed an SA-associated CNV region that achieved genome-wide significance (corrected p-value = 0.014). The associated CNV was successfully validated with a more rigorous qRT-PCR assay and identified to be a common variant in this cohort. Its deletion rate was higher in SA subjects [OR = 2.05 (1.02-4.12), adjusted p-value = 0.045]. Based on the GTEx database, genetic variants that probed this CNV were significantly associated with the expression level of ZNF33B in two brain regions (p-value < 4.2e-05). In stratified analysis, the CNV showed a significant effect [OR = 2.58 (1.06-6.27), p-value = 0.039] in those with high neuroticism but not in those with average or low neuroticism.

CONCLUSIONS

We identified a new common CNV likely involved in the etiology of SA. This finding sheds light on an important role of common CNVs in the pathophysiology of SA, suggesting a new promising avenue for investigating its genetic architecture.

Detection and analysis of genome-wide copy number variation in the pig genome using an 80 K SNP Beadchip

Copy number variation (CNV) is an important source of genetic variability in human or animal genomes and play key roles in phenotypic diversity and disease susceptibility. In the present study, we performed a genome-wide analysis for CNV detection using SNP genotyping data of 857 Large White pigs. A total of 312 CNV regions (CNVRs) were detected with the PennCNV algorithm, which covered 57.76 Mb of the pig genome and correspond to 2.36% of the genome sequence. The length of the CNVRs on autosomes ranged from 1.77 Kb to 1.76 Mb with an average of 185.11 Kb. Of these, 220 completely or partially overlapped with 1,092 annotated genes, which enriched a wide variety of biological processes. Comparisons with previously reported pig CNVR revealed 92 (29.49%) novel CNVRs. Experimentally, 80% of CNVRs selected randomly were validated by quantitative PCR (qPCR). We also performed an association analysis between some of the CNVRs and reproductive traits, with results demonstrating the potential importance of CNVR61 and CNVR283 associated with litter sizes. Notably, the GPER1 gene located in CNVR61 plays a key role in reproduction. Our study is an important complement to the CNV map in the pig genome and provides valuable information for investigating the association between genomic variation and economic traits.

Detection of copy number variation and selection signatures on the X chromosome in Chinese indigenous sheep with different types of tail

Objective

Chinese indigenous sheep breeds can be classified into the following three categories by their tail morphology: fat-tailed, fat-rumped and thin-tailed sheep. The typical sheep breeds corresponding to fat-tailed, fat-rumped, and thin-tailed sheep are large-tailed Han, Altay, and Tibetan sheep, respectively. Detection of copy number variation (CNV) and selection signatures provides information on the genetic mechanisms underlying the phenotypic differences of the different sheep types.

Methods

In this study, PennCNV software and F-statistics (F_ST) were implemented to detect CNV and selection signatures, respectively, on the X chromosome in three Chinese indigenous sheep breeds using ovine high-density 600K single nucleotide polymorphism arrays.

Results

In large-tailed Han, Altay, and Tibetan sheep, respectively, a total of six, four and 22 CNV regions (CNVRs) with lengths of 1.23, 0.93, and 7.02 Mb were identified on the X chromosome. In addition, 49, 34, and 55 candidate selection regions with respective lengths of 27.49, 16.47, and 25.42 Mb were identified in large-tailed Han, Altay, and Tibetan sheep, respectively. The bioinformatics analysis results indicated several genes in these regions were associated with fat, including dehydrogenase/reductase X-linked, calcium voltage-gated channel subunit alpha1 F, and patatin like phospholipase domain containing 4. In addition, three other genes were identified from this analysis: the family with sequence similarity 58 member A gene was associated with energy metabolism, the serine/arginine-rich protein specific kinase 3 gene was associated with skeletal muscle development, and the interleukin 2 receptor subunit gamma gene was associated with the immune system.

Conclusion

The results of this study indicated CNVRs and selection regions on the X chromosome of Chinese indigenous sheep contained several genes associated with various heritable traits.

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 detection of CNVs associated with beak deformity in chickens using high-density 600K SNP arrays

Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing-You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome-wide CNV detection using Affymetrix chicken high-density 600K data on 48 deformed-beak and 48 normal birds using penncnv. As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed-beak and normal birds respectively. Further RT-qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed-beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed-beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT-qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.

Successful use of whole genome amplified DNA from multiple source types for high-density Illumina SNP microarrays

BACKGROUND

The recommended genomic DNA input requirements for whole genome single nucleotide polymorphism microarrays can limit the scope of molecular epidemiological studies. We performed a large-scale evaluation of whole genome amplified DNA as input into high-density, whole-genome Illumina® Infinium® SNP microarray.

RESULTS

Overall, 6622 DNA samples from 5970 individuals were obtained from three distinct biospecimen sources and genotyped using gDNA and/or wgaDNA inputs. When genotypes from the same individual were compared with standard, native gDNA input amount, we observed 99.94% mean concordance with wgaDNA input.

CONCLUSIONS

Our results demonstrate that carefully conducted studies with wgaDNA inputs can yield high-quality genotyping results. These findings should enable investigators to consider expansion of ongoing studies using high-density SNP microarrays, currently challenged by small amounts of available DNA.

Mapping of genome-wide copy number variations in the Iranian indigenous cattle using a dense SNP data set

The objective of this study was to present the first map of the copy number variations (CNVs) in Iranian indigenous cattle based on a high-density single nucleotide polymorphism (SNP) dataset. A total of 90 individuals were genotyped using the Illumina BovineHD BeadChip containing 777 962 SNPs. The QuantiSNP algorithm was used to perform a genome-wide CNV detection across autosomal genome. After merging the overlapping CNV, a total of 221 CNV regions were identified encompassing 36.4 Mb or 1.44% of the bovine autosomal genome. The length of the CNV regions ranged from 3.5 to 2252.8 Kb with an average of 163.8 Kb. These regions included 147 loss (66.52%) and 74 gain (33.48%) events containing a total of 637 annotated Ensembl genes. Gene ontology analysis revealed that most of genes in the CNV regions were involved in environmental responses, disease susceptibility and immune system functions. Furthermore, 543 of these genes corresponded to the human orthologous genes, which involved in a wide range of biological functions. Altogether, 73% of the 221 CNV regions overlapped either completely or partially with those previously reported in other cattle studies. Moreover, novel CNV regions involved several quantitative trait loci (QTL)-related to adaptative traits of Iranian indigenous cattle. These results provided a basis to conduct future studies on association between CNV regions and phenotypic variations in the Iranian indigenous cattle.

Identification of Copy Number Variants from SNP Arrays Using PennCNV

High-resolution single-nucleotide polymorphism (SNP) genotyping arrays offer a sensitive and affordable method for genome-wide detection of copy number variants (CNVs). PennCNV is a hidden Markov model (HMM)-based CNV caller for SNP arrays, first released 10 years ago. A typical CNV calling procedure using PennCNV includes preparation of input files, CNV calling, filtering CNV calls, CNV annotation, and CNV visualization. Here we describe several protocols for CNV calling using PennCNV, together with descriptions on several recent improvements to the software tool.

Cytogenomic assessment of the diagnosis of 93 patients with developmental delay and multiple congenital abnormalities: The Brazilian experience

OBJECTIVE

The human genome contains several types of variations, such as copy number variations, that can generate specific clinical abnormalities. Different techniques are used to detect these changes, and obtaining an unequivocal diagnosis is important to understand the physiopathology of the diseases. The objective of this study was to assess the diagnostic capacity of multiplex ligation-dependent probe amplification and array techniques for etiologic diagnosis of syndromic patients.

METHODS

We analyzed 93 patients with developmental delay and multiple congenital abnormalities using multiplex ligation-dependent probe amplifications and arrays.

RESULTS

Multiplex ligation-dependent probe amplification using different kits revealed several changes in approximately 33.3% of patients. The use of arrays with different platforms showed an approximately 53.75% detection rate for at least one pathogenic change and a 46.25% detection rate for patients with benign changes. A concomitant assessment of the two techniques showed an approximately 97.8% rate of concordance, although the results were not the same in all cases. In contrast with the array results, the MLPA technique detected ∼70.6% of pathogenic changes.

CONCLUSION

The obtained results corroborated data reported in the literature, but the overall detection rate was higher than the rates previously reported, due in part to the criteria used to select patients. Although arrays are the most efficient tool for diagnosis, they are not always suitable as a first-line diagnostic approach because of their high cost for large-scale use in developing countries. Thus, clinical and laboratory interactions with skilled technicians are required to target patients for the most effective and beneficial molecular diagnosis.

Genomic landscape of copy number variation and copy neutral loss of heterozygosity events in equine sarcoids reveals increased instability of the sarcoid genome

Although they are the most common neoplasms in equids, sarcoids are not fully characterized at the molecular level. Therefore, the objective of this study was to characterize the landscape of structural rearrangements, such as copy number variation (CNV) and copy neutral loss of heterozygosity (cnLOH), in the genomes of sarcoid tumor cells. This information will not only broaden our understanding of the characteristics of this genome but will also improve the general knowledge of this tumor and the mechanisms involved in its generation. To this end, Equine SNP64K Illumina microarrays were applied along with bioinformatics tools dedicated for signal intensity analysis. The analysis revealed increased instability of the genome of sarcoid cells compared with unaltered skin tissue samples, which was manifested by the prevalence of CNV and cnLOH events. Many of the identified CNVs overlapped with the other research results, but the simultaneously observed variability in the number and sizes of detected aberrations indicated a need for further studies and the development of more reliable bioinformatics algorithms. The functional analysis of genes co-localized with the identified aberrations revealed that these genes are engaged in vital cellular processes. In addition, a number of these genes directly contribute to neoplastic transformation. Furthermore, large numbers of cnLOH events identified in the sarcoids suggested that they may play no less significant roles than CNVs in the carcinogenesis of this tumor. Thus, our results indicate the importance of cnLOH and CNV in equine sarcoid oncogenesis and present a direction of future research.

Genome-wide detection of copy number variation in Chinese indigenous sheep using an ovine high-density 600 K SNP array

Copy number variants (CNVs) represent a form of genomic structural variation underlying phenotypic diversity. In this study, we used the Illumina Ovine SNP 600 K BeadChip array for genome-wide detection of CNVs in 48 Chinese Tan sheep. A total of 1,296 CNV regions (CNVRs), ranging from 1.2 kb to 2.3 Mb in length, were detected, representing approximately 4.7% of the entire ovine genome (Oar_v3.1). We combined our findings with five existing CNVR reports to generate a composite genome-wide dataset of 4,321 CNVRs, which revealed 556 (43%) novel CNVRs. Subsequently, ten novel CNVRs were randomly chosen for further quantitative real-time PCR (qPCR) confirmation, and eight were successfully validated. Gene functional enrichment revealed that these CNVRs cluster into Gene Ontology (GO) categories of homeobox and embryonic skeletal system morphogenesis. One CNVR overlapping with the homeobox transcription factor DLX3 and previously shown to be associated with curly hair in sheep was identified as the candidate CNV for the special curly fleece phenotype in Tan sheep. We constructed a Chinese indigenous sheep genomic CNV map based on the Illumina Ovine SNP 600 K BeadChip array, providing an important addition to published sheep CNVs, which will be helpful for future investigations of the genomic structural variations underlying traits of interest in sheep.

Chromosomal Microarray Detection of Constitutional Copy Number Variation Using Saliva DNA

Chromosomal microarray (CMA) testing to detect copy number aberrations among individuals with multiple congenital anomalies and/or developmental delay is typically performed on peripheral blood DNA. However, the use of saliva DNA may be preferred for some patients, which prompted our validation study using six saliva DNA samples with a range of bacterial content (approximately 3% to 21%) and 20 paired blood and saliva specimens on the Agilent Technologies, Illumina, and Affymetrix CMA platforms. Ten of the 20 paired specimens were previously determined to carry clinically significant copy number aberrations by clinical CMA testing on blood DNA (100 kb to 2.56 Mb; five deletions, eight duplications). Notably, the quality of saliva DNA (DNA Genotek) was equivalent to blood DNA regardless of bacterial content, as was CMA quality and single-nucleotide polymorphism genotyping quality with all CMA platforms. The number of copy number variants and absence of heterozygosity regions detected by CMA were comparable between paired blood and saliva DNA and, more important, all 13 clinically significant copy number aberrations were detected in saliva DNA by all CMA platforms. These data confirm that the quality of saliva DNA is comparable to blood DNA regardless of bacterial content, including important CMA and single-nucleotide polymorphism quality metrics, and that saliva DNA is a reliable alternative for the detection of clinically significant copy number aberrations by clinical CMA testing.

Differences in AMY1 Gene Copy Numbers Derived from Blood, Buccal Cells and Saliva Using Quantitative and Droplet Digital PCR Methods: Flagging the Pitfall

Introduction

The human salivary (AMY1) gene, encoding salivary α-amylase, has variable copy number variants (CNVs) in the human genome. We aimed to determine if real-time quantitative polymerase chain reaction (qPCR) and the more recently available Droplet Digital PCR (ddPCR) can provide a precise quantification of the AMY1 gene copy number in blood, buccal cells and saliva samples derived from the same individual.

Methods

Seven participants were recruited and DNA was extracted from the blood, buccal cells and saliva samples provided by each participant. Taqman assay real-time qPCR and ddPCR were conducted to quantify AMY1 gene copy numbers. Statistical analysis was carried out to determine the difference in AMY1 gene copy number between the different biological specimens and different assay methods.

Results

We found significant within-individual difference (p<0.01) in AMY1 gene copy number between different biological samples as determined by qPCR. However, there was no significant within-individual difference in AMY1 gene copy number between different biological samples as determined by ddPCR. We also found that AMY1 gene copy number of blood samples were comparable between qPCR and ddPCR, while there is a significant difference (p<0.01) between AMY1 gene copy numbers measured by qPCR and ddPCR for both buccal swab and saliva samples.

Conclusions

Despite buccal cells and saliva samples being possible sources of DNA, it is pertinent that ddPCR or a single biological sample, preferably blood sample, be used for determining highly polymorphic gene copy numbers like AMY1, due to the large within-individual variability between different biological samples if real time qPCR is employed.

Genome-wide detection of CNVs in Chinese indigenous sheep with different types of tails using ovine high-density 600K SNP arrays

Chinese indigenous sheep can be classified into three types based on tail morphology: fat-tailed, fat-rumped, and thin-tailed sheep, of which the typical breeds are large-tailed Han sheep, Altay sheep, and Tibetan sheep, respectively. To unravel the genetic mechanisms underlying the phenotypic differences among Chinese indigenous sheep with tails of three different types, we used ovine high-density 600K SNP arrays to detect genome-wide copy number variation (CNV). In large-tailed Han sheep, Altay sheep, and Tibetan sheep, 371, 301, and 66 CNV regions (CNVRs) with lengths of 71.35 Mb, 51.65 Mb, and 10.56 Mb, respectively, were identified on autosomal chromosomes. Ten CNVRs were randomly chosen for confirmation, of which eight were successfully validated. The detected CNVRs harboured 3130 genes, including genes associated with fat deposition, such as PPARA, RXRA, KLF11, ADD1, FASN, PPP1CA, PDGFA, and PEX6. Moreover, multilevel bioinformatics analyses of the detected candidate genes were significantly enriched for involvement in fat deposition, GTPase regulator, and peptide receptor activities. This is the first high-resolution sheep CNV map for Chinese indigenous sheep breeds with three types of tails. Our results provide valuable information that will support investigations of genomic structural variation underlying traits of interest in sheep.

One CNV Discordance in NRXN1 Observed Upon Genome-wide Screening in 38 Pairs of Adult Healthy Monozygotic Twins

Monozygotic (MZ) twins stem from the same single fertilized egg and therefore share all their inherited genetic variation. This is one of the unequivocal facts on which genetic epidemiology and twin studies are based. To what extent this also implies that MZ twins share genotypes in adult tissues is not precisely established, but a common pragmatic assumption is that MZ twins are 100% genetically identical also in adult tissues. During the past decade, this view has been challenged by several reports, with observations of differences in post-zygotic copy number variations (CNVs) between members of the same MZ pair. In this study, we performed a systematic search for differences of CNVs within 38 adult MZ pairs who had been misclassified as dizygotic (DZ) twins by questionnaire-based assessment. Initial scoring by PennCNV suggested a total of 967 CNV discordances. The within-pair correlation in number of CNVs detected was strongly dependent on confidence score filtering and reached a plateau of r = 0.8 when restricting to CNVs detected with confidence score larger than 50. The top-ranked discordances were subsequently selected for validation by quantitative polymerase chain reaction (qPCR), from which one single ~120kb deletion in NRXN1 on chromosome 2 (bp 51017111–51136802) was validated. Despite involving an exon, no sign of cognitive/mental consequences was apparent in the affected twin pair, potentially reflecting limited or lack of expression of the transcripts containing this exon in nerve/brain.

Causes of genome instability: the effect of low dose chemical exposures in modern society

Genome instability is a prerequisite for the development of cancer. It occurs when genome maintenance systems fail to safeguard the genome's integrity, whether as a consequence of inherited defects or induced via exposure to environmental agents (chemicals, biological agents and radiation). Thus, genome instability can be defined as an enhanced tendency for the genome to acquire mutations; ranging from changes to the nucleotide sequence to chromosomal gain, rearrangements or loss. This review raises the hypothesis that in addition to known human carcinogens, exposure to low dose of other chemicals present in our modern society could contribute to carcinogenesis by indirectly affecting genome stability. The selected chemicals with their mechanisms of action proposed to indirectly contribute to genome instability are: heavy metals (DNA repair, epigenetic modification, DNA damage signaling, telomere length), acrylamide (DNA repair, chromosome segregation), bisphenol A (epigenetic modification, DNA damage signaling, mitochondrial function, chromosome segregation), benomyl (chromosome segregation), quinones (epigenetic modification) and nano-sized particles (epigenetic pathways, mitochondrial function, chromosome segregation, telomere length). The purpose of this review is to describe the crucial aspects of genome instability, to outline the ways in which environmental chemicals can affect this cancer hallmark and to identify candidate chemicals for further study. The overall aim is to make scientists aware of the increasing need to unravel the underlying mechanisms via which chemicals at low doses can induce genome instability and thus promote carcinogenesis.

The Role of Constitutional Copy Number Variants in Breast Cancer

Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans.

A genome-wide scan for copy number variations using high-density single nucleotide polymorphism array in Simmental cattle

Copy number variations (CNVs) have recently been identified as promising sources of genetic variation, complementary to single nucleotide polymorphisms (SNPs). As a result, detection of CNVs has attracted a great deal of attention. In this study, we performed genome-wide CNV detection using Illumina Bovine HD BeadChip (770k) data on 792 Simmental cattle. A total of 263 CNV regions (CNVRs) were identified, which included 137 losses, 102 gains and 24 regions classified as both loss and gain, covering 35.48 Mb (1.41%) of the bovine genome. The length of these CNVRs ranged from 10.18 kb to 1.76 Mb, with an average length of 134.78 kb and a median length of 61.95 kb. In 136 of these regions, a total of 313 genes were identified related to biological functions such as transmembrane activity and olfactory transduction activity. To validate the results, we performed quantitative PCR to detect nine randomly selected CNVRs and successfully confirmed seven (77.6%) of them. Our results present a map of cattle CNVs derived from high-density SNP data, which expands the current CNV map of the cattle genome and provides useful information for investigation of genomic structural variation in cattle.

Rare germline copy number deletions of likely functional importance are implicated in endometrial cancer predisposition

Endometrial cancer is the most common invasive gynaecological cancer in women, and relatively little is known about inherited risk factors for this disease. This is the first genome-wide study to explore the role of common and rare germline copy number variants (CNVs) in predisposition to endometrial cancer. CNVs were called from germline DNA of 1,209 endometrioid endometrial cancer cases and 528 cancer-unaffected female controls. Overall CNV load of deletions or DNA gains did not differ significantly between cases and controls (P > 0.05), but cases presented with an excess of rare germline deletions overlapping likely functional genomic regions including genes (P = 8 × 10(-10)), CpG islands (P = 1 × 10(-7)) and sno/miRNAs regions (P = 3 × 10(-9)). On average, at least one additional gene and two additional CpG islands were disrupted by rare deletions in cases compared to controls. The most pronounced difference was that over 30 sno/miRNAs were disrupted by rare deletions in cases for every single disruption event in controls. A total of 13 DNA repair genes were disrupted by rare deletions in 19/1,209 cases (1.6%) compared to one gene in 1/528 controls (0.2%; P = 0.007), and this increased DNA repair gene loss in cases persisted after excluding five individuals carrying CNVs disrupting mismatch repair genes MLH1, MSH2 and MSH6 (P = 0.03). There were 34 miRNA regions deleted in at least one case but not in controls, the most frequent of which encompassed hsa-mir-661 and hsa-mir-203. Our study implicates rare germline deletions of functional and regulatory regions as possible mechanisms conferring endometrial cancer risk, and has identified specific regulatory elements as candidates for further investigation.

Hidden Markov Model-Based CNV Detection Algorithms for Illumina Genotyping Microarrays

Somatic alterations in DNA copy number have been well studied in numerous malignancies, yet the role of germline DNA copy number variation in cancer is still emerging. Genotyping microarrays generate allele-specific signal intensities to determine genotype, but may also be used to infer DNA copy number using additional computational approaches. Numerous tools have been developed to analyze Illumina genotype microarray data for copy number variant (CNV) discovery, although commonly utilized algorithms freely available to the public employ approaches based upon the use of hidden Markov models (HMMs). QuantiSNP, PennCNV, and GenoCN utilize HMMs with six copy number states but vary in how transition and emission probabilities are calculated. Performance of these CNV detection algorithms has been shown to be variable between both genotyping platforms and data sets, although HMM approaches generally outperform other current methods. Low sensitivity is prevalent with HMM-based algorithms, suggesting the need for continued improvement in CNV detection methodologies.

Rare structural genetic variation in human prion diseases

Prion diseases are a diverse group of neurodegenerative conditions, caused by the templated misfolding of prion protein. Aside from the strong genetic risk conferred by multiple variants of the prion protein gene (PRNP), several other variants have been suggested to confer risk in the most common type, sporadic Creutzfeldt-Jakob disease (sCJD) or in the acquired prion diseases. Large and rare copy number variants (CNVs) are known to confer risk in several related disorders including Alzheimer's disease (at APP), schizophrenia, epilepsy, mental retardation, and autism. Here, we report the first genome-wide analysis for CNV-associated risk using data derived from a recent international collaborative association study in sCJD (n = 1147 after quality control) and publicly available controls (n = 5427). We also investigated UK patients with variant Creutzfeldt-Jakob disease (n = 114) and elderly women from the Eastern Highlands of Papua New Guinea who proved highly resistant to the epidemic prion disease kuru, who were compared with healthy young Fore population controls (n = 395). There were no statistically significant alterations in the burden of CNVs >100, >500, or >1000 kb, duplications, or deletions in any disease group or geographic region. After correction for multiple testing, no statistically significant associations were found. A UK blood service control sample showed a duplication CNV that overlapped PRNP, but these were not found in prion disease. Heterozygous deletions of a 3' region of the PARK2 gene were found in 3 sCJD patients and no controls (p = 0.001, uncorrected). A cell-based prion infection assay did not provide supportive evidence for a role for PARK2 in prion disease susceptibility. These data are consistent with a modest impact of CNVs on risk of late-onset neurologic conditions and suggest that, unlike APP, PRNP duplication is not a causal high-risk mutation.

Copy number variation analysis on a non-Hodgkin lymphoma case-control study identifies an 11q25 duplication associated with diffuse large B-cell lymphoma

Recent GWAS have identified several susceptibility loci for NHL. Despite these successes, much of the heritable variation in NHL risk remains to be explained. Common copy-number variants are important genomic sources of variability, and hence a potential source to explain part of this missing heritability. In this study, we carried out a CNV analysis using GWAS data from 681 NHL cases and 749 controls to explore the relationship between common structural variation and lymphoma susceptibility. Here we found a novel association with diffuse large B-cell lymphoma (DLBCL) risk involving a partial duplication of the C-terminus region of the LOC283177 long non-coding RNA that was further confirmed by quantitative PCR. For chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), known somatic deletions were identified on chromosomes 13q14, 11q22-23, 14q32 and 22q11.22. Our study shows that GWAS data can be used to identify germline CNVs associated with disease risk for DLBCL and somatic CNVs for CLL/SLL.

General assessment of copy number variation in normal and tumor tissues of the domestic dog (Canis lupus familiaris)

In recent years, characterization of a copy number variation (CNV) of the genomic DNA has provided evidence for the relationship of this type of genetic variation with the occurrence of a broad spectrum of diseases, including cancer lesions. Copy number variants (CNVs) also occur in the genomes of healthy individuals as a result of abnormal recombination processes in germ cells and have a hereditary character contributing to the natural genetic diversity. Recent image analysis methods and advanced computational techniques allow for identification of CNVs using SNPs genotyping microarrays based on the analysis of signal intensity observed for markers located in the specific genomic regions. In this study we used CanineHD BeadChip assay (Illumina) to identify both natural and cancer-induced CNVs in the genomes of different dog breeds and in different cancer types occurring in this species. The obtained results showed that structural aberrations are a common phenomenon arising during a tumor progression and are more complex and widespread in tumors of mesenchymal tissue origin than in epithelial tissue originating tumors. The tumor derived CNVs, in comparison to healthy samples, were characterized by larger sizes of regions, higher number of amplifications, and in some cases encompassed genes with potential effect on tumor progression.

A genome-wide investigation of copy number variation in patients with sporadic brain arteriovenous malformation

BACKGROUND

Brain arteriovenous malformations (BAVM) are clusters of abnormal blood vessels, with shunting of blood from the arterial to venous circulation and a high risk of rupture and intracranial hemorrhage. Most BAVMs are sporadic, but also occur in patients with Hereditary Hemorrhagic Telangiectasia, a Mendelian disorder caused by mutations in genes in the transforming growth factor beta (TGFβ) signaling pathway.

METHODS

To investigate whether copy number variations (CNVs) contribute to risk of sporadic BAVM, we performed a genome-wide association study in 371 sporadic BAVM cases and 563 healthy controls, all Caucasian. Cases and controls were genotyped using the Affymetrix 6.0 array. CNVs were called using the PennCNV and Birdsuite algorithms and analyzed via segment-based and gene-based approaches. Common and rare CNVs were evaluated for association with BAVM.

RESULTS

A CNV region on 1p36.13, containing the neuroblastoma breakpoint family, member 1 gene (NBPF1), was significantly enriched with duplications in BAVM cases compared to controls (P = 2.2×10(-9)); NBPF1 was also significantly associated with BAVM in gene-based analysis using both PennCNV and Birdsuite. We experimentally validated the 1p36.13 duplication; however, the association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls (OR = 0.81, P = 0.8). Rare CNV analysis did not identify genes significantly associated with BAVM.

CONCLUSION

We did not identify common CNVs associated with sporadic BAVM that replicated in an independent cohort. Replication in larger cohorts is required to elucidate the possible role of common or rare CNVs in BAVM pathogenesis.

Advantage of using allele-specific copy numbers when testing for association in regions with common copy number variants

Copy number variants (CNV) can be called from SNP-arrays; however, few studies have attempted to combine both CNV and SNP calls to test for association with complex diseases. Even when SNPs are located within CNVs, two separate association analyses are necessary, to compare the distribution of bi-allelic genotypes in cases and controls (referred to as SNP-only strategy) and the number of copies of a region (referred to as CNV-only strategy). However, when disease susceptibility is actually associated with allele specific copy-number states, the two strategies may not yield comparable results, raising a series of questions about the optimal analytical approach. We performed simulations of the performance of association testing under different scenarios that varied genotype frequencies and inheritance models. We show that the SNP-only strategy lacks power under most scenarios when the SNP is located within a CNV; frequently it is excluded from analysis as it does not pass quality control metrics either because of an increased rate of missing calls or a departure from fitness for Hardy-Weinberg proportion. The CNV-only strategy also lacks power because the association testing depends on the allele which copy number varies. The combined strategy performs well in most of the scenarios. Hence, we advocate the use of this combined strategy when testing for association with SNPs located within CNVs.

Analysis of copy number variants by three detection algorithms and their association with body size in horses

Background

Copy number variants (CNVs) have been shown to play an important role in genetic diversity of mammals and in the development of many complex phenotypic traits. The aim of this study was to perform a standard comparative evaluation of CNVs in horses using three different CNV detection programs and to identify genomic regions associated with body size in horses.

Results

Analysis was performed using the Illumina Equine SNP50 genotyping beadchip for 854 horses. CNVs were detected by three different algorithms, CNVPartition, PennCNV and QuantiSNP. Comparative analysis revealed 50 CNVs that affected 153 different genes mainly involved in sensory perception, signal transduction and cellular components. Genome-wide association analysis for body size showed highly significant deleted regions on ECA1, ECA8 and ECA9. Homologous regions to the detected CNVs on ECA1 and ECA9 have also been shown to be correlated with human height.

Conclusions

Comparative analysis of CNV detection algorithms was useful to increase the specificity of CNV detection but had certain limitations dependent on the detection tool. GWAS revealed genome-wide associated CNVs for body size in horses.

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

Could inbred cases identified in GWAS data succeed in detecting rare recessive variants where affected sib-pairs have failed?

To detect fully penetrant rare recessive variants that could constitute Mendelian subentities of complex diseases, we propose a novel strategy, the HBD-GWAS strategy, which can be applied to genome-wide association study (GWAS) data. This strategy first involves the identification of inbred individuals among cases using the genome-wide SNP data and then focuses on these inbred affected individuals and searches for genomic regions of shared homozygosity by descent that could harbor rare recessive disease-causing variants. In this second step, analogous to homozygosity mapping, a heterogeneity lod-score, HFLOD, is computed to quantify the evidence of linkage provided by the data. In this paper, we evaluate this strategy theoretically under different scenarios and compare its performances with those of linkage analysis using affected sib-pair (ASP) data. If cases affected by these Mendelian subentities are not enriched in the sample of cases, the HBD-GWAS strategy has almost no power to detect them, unless they explain an important part of the disease prevalence. The HBD-GWAS strategy outperforms the ASP linkage strategy only in a very limited number of situations where there exists a strong allelic heterogeneity. When several rare recessive variants within the same gene are involved, the ASP design indeed often fails to detect the gene, whereas, by focusing on inbred individuals using the HBD-GWAS strategy, the gene might be detected provided very large samples of cases are available.

Gene-environment interactions in asthma and allergic diseases: challenges and perspectives

The concept of gene-environment (GxE) interactions has dramatically evolved in the last century and has now become a central theme in studies that assess the causes of human disease. Despite the numerous efforts to discover genes associated in asthma and allergy through various approaches, including the recent genome-wide association studies, investigation of GxE interactions has been mainly limited to candidate genes, candidate environmental exposures, or both. This review discusses the various strategies from hypothesis-driven strategies to the full agnostic search of GxE interactions with an illustration from recently published articles. Challenges raised by each piece of the puzzle (ie, phenotype, environment, gene, and analysis of GxE interaction) are put forward, and tentative solutions are proposed. New perspectives to integrate various types of data generated by new sequencing technologies and to progress toward a systems biology approach of disease are outlined. The future of a molecular network-based approach of disease to which GxE interactions are related requires space for innovative and multidisciplinary research. Assembling the various parts of a puzzle in a complex system could well occur in a way that might not necessarily follow the rules of logic.

Genome-wide detection of copy number variations using high-density SNP genotyping platforms in Holsteins

Background

Copy number variations (CNVs) are widespread in the human or animal genome and are a significant source of genetic variation, which has been demonstrated to play an important role in phenotypic diversity. Advances in technology have allowed for identification of a large number of CNVs in cattle. Comprehensive explore novel CNVs in the bovine genome would provide valuable information for functional analyses of genome structural variation and facilitating follow-up association studies between complex traits and genetic variants.

Results

In this study, we performed a genome-wide CNV detection based on high-density SNP genotyping data of 96 Chinese Holstein cattle. A total of 367 CNV regions (CNVRs) across the genome were identified, which cover 42.74Mb of the cattle genome and correspond to 1.61% of the genome sequence. The length of the CNVRs on autosomes range from 10.76 to 2,806.42 Kb with an average of 96.23 Kb. 218 out of these CNVRs contain 610 annotated genes, which possess a wide spectrum of molecular functions. To confirm these findings, quantitative PCR (qPCR) was performed for 17 CNVRs and 13(76.5%) of them were successfully validated.

Conclusions

Our study demonstrates the high density SNP array can significantly improve the accuracy and sensitivity of CNV calling. Integration of different platforms can enhance the detection of genomic structure variants. Our results provide a significant replenishment for the high resolution map of copy number variation in the bovine genome and valuable information for investigation of genomic structural variation underlying traits of interest in cattle.

A comprehensive survey of copy number variation in 18 diverse pig populations and identification of candidate copy number variable genes associated with complex traits

Background

Copy number variation (CNV) is a major source of structural variants and has been commonly identified in mammalian genome. It is associated with gene expression and may present a major genetic component of phenotypic diversity. Unlike many other mammalian genomes where CNVs have been well annotated, studies of porcine CNV in diverse breeds are still limited.

Result

Here we used Porcine SNP60 BeadChip and PennCNV algorithm to identify 1,315 putative CNVs belonging to 565 CNV regions (CNVRs) in 1,693 pigs from 18 diverse populations. Total 538 out of 683 CNVs identified in a White Duroc × Erhualian F₂ population fit Mendelian transmission and 6 out of 7 randomly selected CNVRs were confirmed by quantitative real time PCR. CNVRs were non-randomly distributed in the pig genome. Several CNV hotspots were found on pig chromosomes 6, 11, 13, 14 and 17. CNV numbers differ greatly among different pig populations. The Duroc pigs were identified to have the most number of CNVs per individual. Among 1,765 transcripts located within the CNVRs, 634 genes have been reported to be copy number variable genes in the human genome. By integrating analysis of QTL mapping, CNVRs and the description of phenotypes in knockout mice, we identified 7 copy number variable genes as candidate genes for phenotypes related to carcass length, backfat thickness, abdominal fat weight, length of scapular, intermuscle fat content of logissimus muscle, body weight at 240 day, glycolytic potential of logissimus muscle, mean corpuscular hemoglobin, mean corpuscular volume and humerus diameter.

Conclusion

We revealed the distribution of the unprecedented number of 565 CNVRs in pig genome and investigated copy number variable genes as the possible candidate genes for phenotypic traits. These findings give novel insights into porcine CNVs and provide resources to facilitate the identification of trait-related CNVs.

Effect of Combining Multiple CNV Defining Algorithms on the Reliability of CNV Calls from SNP Genotyping Data

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

Genome-wide CNV analysis replicates the association between GSTM1 deletion and bladder cancer: a support for using continuous measurement from SNP-array data

Background

Structural variations such as copy number variants (CNV) influence the expression of different phenotypic traits. Algorithms to identify CNVs through SNP-array platforms are available. The ability to evaluate well-characterized CNVs such as GSTM1 (1p13.3) deletion provides an important opportunity to assess their performance.

Results

773 cases and 759 controls from the SBC/EPICURO Study were genotyped in the GSTM1 region using TaqMan, Multiplex Ligation-dependent Probe Amplification (MLPA), and Illumina Infinium 1 M SNP-array platforms. CNV callings provided by TaqMan and MLPA were highly concordant and replicated the association between GSTM1 and bladder cancer. This was not the case when CNVs were called using Illumina 1 M data through available algorithms since no deletion was detected across the study samples. In contrast, when the Log R Ratio (LRR) was used as a continuous measure for the 5 probes contained in this locus, we were able to detect their association with bladder cancer using simple regression models or more sophisticated methods such as the ones implemented in the CNVtools package.

Conclusions

This study highlights an important limitation in the CNV calling from SNP-array data in regions of common aberrations and suggests that there may be added advantage for using LRR as a continuous measure in association tests rather than relying on calling algorithms.

Inheritance model introduces differential bias in CNV calls between parents and offspring

Copy Number Variation (CNV) is increasingly implicated in disease pathogenesis. CNVs are often identified by statistical models applied to data from single nucleotide polymorphism panels. Family information for samples provides additional information for CNV inference. Two modes of PennCNV (the Joint-call and Posterior-call), which are some of the most well-developed family-based CNV calling methods, use a "Joint-model" as a main component. This models all family members' CNV states together with Mendelian inheritance. Methods based on the Joint-model are used to infer CNV calls of cases and controls in a pedigree, which may be compared to each other to test an association. Although benefits from the Joint-model have been shown elsewhere, equality of call rates in parents and offspring has not been evaluated previously. This can affect downstream analyses in studies that compare CNV rates in cases vs. controls in pedigrees. In this paper, we show that the Joint-model can introduce different CNV call rates among family members in the absence of a true difference. We show that the Joint-model may analytically introduce differential CNV calls because of asymmetry of the model. We demonstrate these differential call rates using single-marker simulations. We show that call rates using the two modes of PennCNV also differ between parents and offspring in one multimarker simulated dataset and two real datasets. Our results advise need for caution in use of the Joint-model calls in CNV association studies with family-based datasets.

Cheek swabs, SNP chips, and CNVs: assessing the quality of copy number variant calls generated with subject-collected mail-in buccal brush DNA samples on a high-density genotyping microarray

Background

Multiple investigators have established the feasibility of using buccal brush samples to genotype single nucleotide polymorphisms (SNPs) with high-density genome-wide microarrays, but there is currently no consensus on the accuracy of copy number variants (CNVs) inferred from these data. Regardless of the source of DNA, it is more difficult to detect CNVs than to genotype SNPs using these microarrays, and it therefore remains an open question whether buccal brush samples provide enough high-quality DNA for this purpose.

Methods

To demonstrate the quality of CNV calls generated from DNA extracted from buccal samples, compared to calls generated from blood samples, we evaluated the concordance of calls from individuals who provided both sample types. The Illumina Human660W-Quad BeadChip was used to determine SNPs and CNVs of 39 Arkansas participants in the National Birth Defects Prevention Study (NBDPS), including 16 mother-infant dyads, who provided both whole blood and buccal brush DNA samples.

Results

We observed a 99.9% concordance rate of SNP calls in the 39 blood–buccal pairs. From the same dataset, we performed a similar analysis of CNVs. Each of the 78 samples was independently segmented into regions of like copy number using the Optimal Segmentation algorithm of Golden Helix SNP & Variation Suite 7.

Across 640,663 loci on 22 autosomal chromosomes, segment-mean log R ratios had an average correlation of 0.899 between blood-buccal pairs of samples from the same individual, while the average correlation between all possible blood-buccal pairs of samples from unrelated individuals was 0.318. An independent analysis using the QuantiSNP algorithm produced average correlations of 0.943 between blood-buccal pairs from the same individual versus 0.332 between samples from unrelated individuals.

Segment-mean log R ratios had an average correlation of 0.539 between mother-offspring dyads of buccal samples, which was not statistically significantly different than the average correlation of 0.526 between mother-offspring dyads of blood samples (p=0.302).

Conclusions

We observed performance from the subject-collected mail-in buccal brush samples comparable to that of blood. These results show that such DNA samples can be used for genome-wide scans of both SNPs and CNVs, and that high rates of CNV concordance were achieved whether using a change-point-based algorithm or one based on a hidden Markov model (HMM).

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases.

Genetic association studies of copy-number variation: should assignment of copy number states precede testing?

Recently, structural variation in the genome has been implicated in many complex diseases. Using genomewide single nucleotide polymorphism (SNP) arrays, researchers are able to investigate the impact not only of SNP variation, but also of copy-number variants (CNVs) on the phenotype. The most common analytic approach involves estimating, at the level of the individual genome, the underlying number of copies present at each location. Once this is completed, tests are performed to determine the association between copy number state and phenotype. An alternative approach is to carry out association testing first, between phenotype and raw intensities from the SNP array at the level of the individual marker, and then aggregate neighboring test results to identify CNVs associated with the phenotype. Here, we explore the strengths and weaknesses of these two approaches using both simulations and real data from a pharmacogenomic study of the chemotherapeutic agent gemcitabine. Our results indicate that pooled marker-level testing is capable of offering a dramatic increase in power (> 12-fold) over CNV-level testing, particularly for small CNVs. However, CNV-level testing is superior when CNVs are large and rare; understanding these tradeoffs is an important consideration in conducting association studies of structural variation.

Visualization of genomic changes by segmented smoothing using an L0 penalty

Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the L(0) norm of differences of neighboring values. Visualization is our main goal, but we compare classification performance to that of VEGA.