Identification of Genome-Wide Copy Number Variations among Diverse Pig Breeds Using SNP Genotyping Arrays

Copy number variations (CNVs) are important forms of genetic variation complementary to SNPs, and can be considered as promising markers for some phenotypic and economically important traits or diseases susceptibility in domestic animals. In the present study, we performed a genome-wide CNV identification in 14 individuals selected from diverse populations, including six types of Chinese indigenous breeds, one Asian wild boar population, as well as three modern commercial foreign breeds. We identified 63 CNVRs in total, which covered 9.98 Mb of polymorphic sequence and corresponded to 0.36% of the genome sequence. The length of these CNVRs ranged from 3.20 to 827.21 kb, with an average of 158.37 kb and a median of 97.85 kb. Functional annotation revealed these identified CNVR have important molecular function, and may play an important role in exploring the genetic basis of phenotypic variability and disease susceptibility among pigs. Additionally, to confirm these potential CNVRs, we performed qPCR for 12 randomly selected CNVRs and 8 of them (66.67%) were confirmed successfully. CNVs detected in diverse populations herein are essential complementary to the CNV map in the pig genome, which provide an important resource for studies of genomic variation and the association between various economically important traits and CNVs.     

Identification of Copy Number Variations in Xiang and Kele Pigs

Xiang and Kele pigs are two well-known local Chinese pig breeds that possess rich genetic resources and have enormous economic and scientific value. We performed a comprehensive genomic analysis of the copy number variations (CNVs) in these breeds. CNVs are one of the most important forms of genomic variation and have profound effects on phenotypic variation. In this study, PorcineSNP60 genotyping data from 98 Xiang pigs and 22 Kele pigs were used to identify CNVs. In total, 172 candidate CNV regions (CNVRs) were identified, ranging from 3.19 kb to 8175.26 kb and covering 80.41 Mb of the pig genome. Approximately 56.40% (97/172) of the CNVRs overlapped with those identified in seven previous studies, and 43.60% (75/172) of the identified CNVRs were novel. Of the identified CNVRs, 82 (47 gain, 33 loss, and two gain-loss events that covered 4.58 Mb of the pig genome) were found only in a Xiang population with a large litter size. In contrast, 13 CNVRs (8 gain and 5 loss events) were unique to a Xiang population with small litter sizes, and 30 CNVRs (14 loss and 16 gain events) were unique to Kele pigs. The CNVRs span approximately 660 annotated Sus scrofa genes that are significantly enriched for specific biological functions, such as sensory perception, cognition, reproduction, ATP biosynthetic processes, and neurological processes. Many CNVR-associated genes, particularly the genes involved in reproductive traits, differed between the Xiang populations with large and small litter sizes, and these genes warrant further investigation due to their importance in determining the reproductive performance of Xiang pigs. Our results provide meaningful information about genomic variation, which may be useful in future assessments of the associations between CNVs and important phenotypes in Xiang and Kele pigs to ultimately help protect these rare breeds.     

Genome-Wide Detection of Copy Number Variations among Diverse Horse Breeds by Array CGH

Recent studies have found that copy number variations (CNVs) are widespread in human and animal genomes. CNVs are a significant source of genetic variation, and have been shown to be associated with phenotypic diversity. However, the effect of CNVs on genetic variation in horses is not well understood. In the present study, CNVs in 6 different breeds of mare horses, Mongolia horse, Abaga horse, Hequ horse and Kazakh horse (all plateau breeds) and Debao pony and Thoroughbred, were determined using aCGH. In total, seven hundred CNVs were identified ranging in size from 6.1 Kb to 0.57 Mb across all autosomes, with an average size of 43.08 Kb and a median size of 15.11 Kb. By merging overlapping CNVs, we found a total of three hundred and fifty-three CNV regions (CNVRs). The length of the CNVRs ranged from 6.1 Kb to 1.45 Mb with average and median sizes of 38.49 Kb and 13.1 Kb. Collectively, 13.59 Mb of copy number variation was identified among the horses investigated and accounted for approximately 0.61% of the horse genome sequence. Five hundred and eighteen annotated genes were affected by CNVs, which corresponded to about 2.26% of all horse genes. Through the gene ontology (GO), genetic pathway analysis and comparison of CNV genes among different breeds, we found evidence that CNVs involving 7 genes may be related to the adaptation to severe environment of these plateau horses. This study is the first report of copy number variations in Chinese horses, which indicates that CNVs are ubiquitous in the horse genome and influence many biological processes of the horse. These results will be helpful not only in mapping the horse whole-genome CNVs, but also to further research for the adaption to the high altitude severe environment for plateau horses.     

Analysis of Genome-Wide Copy Number Variations in Chinese Indigenous and Western Pig Breeds by 60 K SNP Genotyping Arrays

Copy number variations (CNVs) represent a substantial source of structural variants in mammals and contribute to both normal phenotypic variability and disease susceptibility. Although low-resolution CNV maps are produced in many domestic animals, and several reports have been published about the CNVs of porcine genome, the differences between Chinese and western pigs still remain to be elucidated. In this study, we used Porcine SNP60 BeadChip and PennCNV algorithm to perform a genome-wide CNV detection in 302 individuals from six Chinese indigenous breeds (Tongcheng, Laiwu, Luchuan, Bama, Wuzhishan and Ningxiang pigs), three western breeds (Yorkshire, Landrace and Duroc) and one hybrid (Tongcheng×Duroc). A total of 348 CNV Regions (CNVRs) across genome were identified, covering 150.49 Mb of the pig genome or 6.14% of the autosomal genome sequence. In these CNVRs, 213 CNVRs were found to exist only in the six Chinese indigenous breeds, and 60 CNVRs only in the three western breeds. The characters of CNVs in four Chinese normal size breeds (Luchuan, Tongcheng and Laiwu pigs) and two minipig breeds (Bama and Wuzhishan pigs) were also analyzed in this study. Functional annotation suggested that these CNVRs possess a great variety of molecular function and may play important roles in phenotypic and production traits between Chinese and western breeds. Our results are important complementary to the CNV map in pig genome, which provide new information about the diversity of Chinese and western pig breeds, and facilitate further research on porcine genome CNVs.     

Copy Number Variations in Tilapia Genomes

Discovering the nature and pattern of genome variation is fundamental in understanding phenotypic diversity among populations. Although several millions of single nucleotide polymorphisms (SNPs) have been discovered in tilapia, the genome-wide characterization of larger structural variants, such as copy number variation (CNV) regions has not been carried out yet. We conducted a genome-wide scan for CNVs in 47 individuals from three tilapia populations. Based on 254 Gb of high-quality paired-end sequencing reads, we identified 4642 distinct high-confidence CNVs. These CNVs account for 1.9% (12.411 Mb) of the used Nile tilapia reference genome. A total of 1100 predicted CNVs were found overlapping with exon regions of protein genes. Further association analysis based on linear model regression found 85 CNVs ranging between 300 and 27,000 base pairs significantly associated to population types (R ² > 0.9 and P > 0.001). Our study sheds first insights on genome-wide CNVs in tilapia. These CNVs among and within tilapia populations may have functional effects on phenotypes and specific adaptation to particular environments.     

Genome-Wide Mapping of Structural Variations Reveals a Copy Number Variant That Determines Reproductive Morphology in Cucumber

Structural variations (SVs) represent a major source of genetic diversity. However, the functional impact and formation mechanisms of SVs in plant genomes remain largely unexplored. Here, we report a nucleotide-resolution SV map of cucumber (Cucumis sativas) that comprises 26,788 SVs based on deep resequencing of 115 diverse accessions. The largest proportion of cucumber SVs was formed through nonhomologous end-joining rearrangements, and the occurrence of SVs is closely associated with regions of high nucleotide diversity. These SVs affect the coding regions of 1676 genes, some of which are associated with cucumber domestication. Based on the map, we discovered a copy number variation (CNV) involving four genes that defines the Female (F) locus and gives rise to gynoecious cucumber plants, which bear only female flowers and set fruit at almost every node. The CNV arose from a recent 30.2-kb duplication at a meiotically unstable region, likely via microhomology-mediated break-induced replication. The SV set provides a snapshot of structural variations in plants and will serve as an important resource for exploring genes underlying key traits and for facilitating practical breeding in cucumber.     

A Genome-Wide Copy Number Variant Study of Suicidal Behavior

Suicide and suicide attempts are complex behaviors that result from the interaction of different factors, including genetic variants that increase the predisposition to suicidal behaviors. Copy number variations (CNVs) are deletions or duplications of a segment of DNA usually larger than one kilobase. These structural genetic changes, although quite rare, have been associated with genetic liability to mental disorders, such as autism, schizophrenia, and bipolar disorder. No genome-wide level studies have been published investigating the potential role of CNVs in suicidal behaviors. Based on single-nucleotide polymorphism array data, we followed the Penn-CNV standards to detect CNVs in 1,608 subjects, comprising 475 suicide and suicide attempt cases and 1,133 controls. Although the initial algorithms determined the presence of CNVs on chromosomes 6 and 12 in seven and eight cases, respectively, compared with none of the controls, visual inspection of the raw data did not support this finding. Furthermore we were unable to validate these findings by CNV-specific real-time polymerase chain reaction. Additionally, rare CNV burden analysis did not find an association between the frequency or length of rare CNVs and suicidal behavior in our sample population. Although our findings suggest CNVs do not play an important role in the etiology of suicidal behaviors, they are not inconsistent with the strong evidence from the literature suggesting that other genetic variants account for a portion of the total phenotypic variability in suicidal behavior.     

基因组拷贝数变异研究进展

基因组结构变异分为两个层次:显微水平(microscopic)和亚显微水平(submicroscopic)。显微水平的基因组结构变异主要是指显微镜下可见的染色体畸变,包括整倍体或非整倍体、缺失、插入、倒位、易位、脆性位点等结构变异。亚显微水平的基因组结构变异是指DNA片段长度在1Kb-3Mb的基因组结构变异,包括缺失、插入、重复、重排、倒位、DNA拷贝数目变化(copy numbervariation,CNV),这些统称为CNV或者CNP(copy number polymorphisms,CNP)。对CNV的研究能够帮助研究者建立遗传检测假说,进而发现疾病易感基因,同时加深对表型变异的理解,为今后研究人类生物功能、进化、疾病奠定基础。本文主要从CNV的研究历史、分子机制、研究方法、研究意义等四个方面进行综述.。     

基因拷贝数异常的研究进展

基因拷贝数异常(copy number variations,CNVs)是广泛存在于人体基因组的一种结构变异现象,主要包括拷贝数的缺失、插入、重组以及多位点的复杂变异等。最初是在病人的基因组中发现,后来的研究表明在正常人体中也普遍存在。有关CNVs的研究将随机个体之间的基因组差异估计值大大提高,极大的改变了人们的认识。目前,关于CNVs的研究多处在初步探索阶段,CNVs如何导致疾病,以及如何引起基因等的改变而诱发疾病的机理也需更进一步的研究加以验证和证实。该文主要就近年来关于CNVs的研究进展作一综述。     

Genome-Wide Copy Number Variations Inferred from SNP Genotyping Arrays Using a Large White and Minzhu Intercross Population

Copy number variations (CNVs) are one of the main contributors to genetic diversity in animals and are broadly distributed in the genomes of swine. Investigating the performance and evolutionary impacts of pig CNVs requires comprehensive knowledge of their structure and function within and between breeds. In the current study, 4 different programs (i.e., GADA, PennCNV, QuantiSNP, and cnvPartition) were used to analyze Porcine SNP60 genotyping data of 585 pigs from one Large White × Minzhu intercross population to detect copy number variant regions (CNVRs). Overlapping CNVRs recalled by at least 2 programs were used to construct a powerful and comprehensive CNVR map, which contained249 CNVRs (i.e., 70 gains, 43 losses, and 136 gains/losses) and covered 26.22% of the regions in the swine genome. Ten CNVRs, representing different predicted statuses, were selected for validation via quantitative real-time PCR (QPCR); 9/10 CNVRs (i.e., 90%) were validated. When being traced back to the F0 generation, 58 events were identified in only Minzhu F0 parents and 2 events were identified in only Large White F0 parents. A series of CNVR function analyses were performed. Some of the CNVRs functions were predicted, and several interesting CNVRs for meat quality traits and hematological parameters were obtained. A comprehensive and lower false rate genome-wide CNV map was constructed for Large White and Minzhu pig genomes in this study. Our results may provide an important basis for determining the relationship between CNVRs and important qualitative and quantitative traits. In addition, it can help to further understand genetic processes in pigs.     

Identification of Networks of Co-Occurring,Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.     

Genome-Wide Detection of Selective Signature in Chinese Holstein

Selective signatures in whole genome can help us understand the mechanisms of selection and target causal variants for breeding program. In present study, we performed Extended Haplotype Homozygosity (EHH) tests to identify significant core regions harboring such signals in Chinese Holstein, and then verified the biological significance of these identified regions based on commonly-used bioinformatics analyses. Results showed a total of 125 significant regions in entire genome containing some of important functional genes such as LEP, ABCG2, CSN1S1, CSN3 and TNF based on the Gene Ontology database. Some of these annotated genes involved in the core regions overlapped with those identified in our previous GWAS as well as those involved in a recently constructed candidate gene database for cattle, further indicating these genes under positive selection maybe underlie milk production traits and other important traits in Chinese Holstein. Furthermore, in the enrichment analyses for the second level GO terms and pathways, we observed some significant terms over represented in these identified regions as compared to the entire bovine genome. This indicates that some functional genes associated with milk production traits, as reflected by GO terms, could be clustered in core regions, which provided promising evidence for the exploitability of the core regions identified by EHH tests. Findings in our study could help detect functional candidate genes under positive selection for further genetic and breeding research in Chinese Holstein.     

Enhancing Genome-Wide Copy Number Variation Identification by High Density Array CGH Using Diverse Resources of Pig Breeds

Copy number variations (CNVs) are important forms of genomic variation, and have attracted extensive attentions in humans as well as domestic animals. In the study, using a custom-designed 2.1 M array comparative genomic hybridization (aCGH), genome-wide CNVs were identified among 12 individuals from diverse pig breeds, including one Asian wild population, six Chinese indigenous breeds and two modern commercial breeds (Yorkshire and Landrace), with one individual of the other modern commercial breed, Duroc, as the reference. A total of 1,344 CNV regions (CNVRs) were identified, covering 47.79 Mb (∼1.70%) of the pig genome. The length of these CNVRs ranged from 3.37 Kb to 1,319.0 Kb with a mean of 35.56 Kb and a median of 11.11 Kb. Compared with similar studies reported, most of the CNVRs (74.18%) were firstly identified in present study. In order to confirm these CNVRs, 21 CNVRs were randomly chosen to be validated by quantitative real time PCR (qPCR) and a high rate (85.71%) of confirmation was obtained. Functional annotation of CNVRs suggested that the identified CNVRs have important function, and may play an important role in phenotypic and production traits difference among various breeds. Our results are essential complementary to the CNV map in the pig genome, which will provide abundant genetic markers to investigate association studies between various phenotypes and CNVs in pigs.     

Enhancer Chip: Detecting Human Copy Number Variations in Regulatory Elements

Critical functional properties are embedded in the non-coding portion of the human genome. Recent successful studies have shown that variations in distant-acting gene enhancer sequences can contribute to disease. In fact, various disorders, such as thalassaemias, preaxial polydactyly or susceptibility to Hirschsprung’s disease, may be the result of rearrangements of enhancer elements. We have analyzed the distribution of enhancer loci in the genome and compared their localization to that of previously described copy-number variations (CNVs). These data suggest a negative selection of copy number variable enhancers. To identify CNVs covering enhancer elements, we have developed a simple and cost-effective test. Here we describe the gene selection, design strategy and experimental validation of a customized oligonucleotide Array-Based Comparative Genomic Hybridization (aCGH), designated Enhancer Chip. It has been designed to investigate CNVs, allowing the analysis of all the genome with a 300 Kb resolution and specific disease regions (telomeres, centromeres and selected disease loci) at a tenfold higher resolution. Moreover, this is the first aCGH able to test over 1,250 enhancers, in order to investigate their potential pathogenic role. Validation experiments have demonstrated that Enhancer Chip efficiently detects duplications and deletions covering enhancer loci, demonstrating that it is a powerful instrument to detect and characterize copy number variable enhancers.     

Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells

Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts.     

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.     

Outlier-Based Identification of Copy Number Variations Using Targeted Resequencing in a Small Cohort of Patients with Tetralogy of Fallot

Copy number variations (CNVs) are one of the main sources of variability in the human genome. Many CNVs are associated with various diseases including cardiovascular disease. In addition to hybridization-based methods, next-generation sequencing (NGS) technologies are increasingly used for CNV discovery. However, respective computational methods applicable to NGS data are still limited. We developed a novel CNV calling method based on outlier detection applicable to small cohorts, which is of particular interest for the discovery of individual CNVs within families, de novo CNVs in trios and/or small cohorts of specific phenotypes like rare diseases. Approximately 7,000 rare diseases are currently known, which collectively affect ∼6% of the population. For our method, we applied the Dixon’s Q test to detect outliers and used a Hidden Markov Model for their assessment. The method can be used for data obtained by exome and targeted resequencing. We evaluated our outlier- based method in comparison to the CNV calling tool CoNIFER using eight HapMap exome samples and subsequently applied both methods to targeted resequencing data of patients with Tetralogy of Fallot (TOF), the most common cyanotic congenital heart disease. In both the HapMap samples and the TOF cases, our method is superior to CoNIFER, such that it identifies more true positive CNVs. Called CNVs in TOF cases were validated by qPCR and HapMap CNVs were confirmed with available array-CGH data. In the TOF patients, we found four copy number gains affecting three genes, of which two are important regulators of heart development (NOTCH1, ISL1) and one is located in a region associated with cardiac malformations (PRODH at 22q11). In summary, we present a novel CNV calling method based on outlier detection, which will be of particular interest for the analysis of de novo or individual CNVs in trios or cohorts up to 30 individuals, respectively.     

A Genome-Wide Assessment of the Role of Untagged Copy Number Variants in Type 1 Diabetes

Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability.