Genome-Wide Identification of Copy Number Variations in Chinese Holstein

Recent studies of mammalian genomes have uncovered the vast extent of copy number variations (CNVs) that contribute to phenotypic diversity. Compared to SNP, a CNV can cover a wider chromosome region, which may potentially incur substantial sequence changes and induce more significant effects on phenotypes. CNV has been becoming an alternative promising genetic marker in the field of genetic analyses. Here we firstly report an account of CNV regions in the cattle genome in Chinese Holstein population. The Illumina Bovine SNP50K Beadchips were used for screening 2047 Holstein individuals. Three different programes (PennCNV, cnvPartition and GADA) were implemented to detect potential CNVs. After a strict CNV calling pipeline, a total of 99 CNV regions were identified in cattle genome. These CNV regions cover 23.24 Mb in total with an average size of 151.69 Kb. 52 out of these CNV regions have frequencies of above 1%. 51 out of these CNV regions completely or partially overlap with 138 cattle genes, which are significantly enriched for specific biological functions, such as signaling pathway, sensory perception response and cellular processes. The results provide valuable information for constructing a more comprehensive CNV map in the cattle genome and offer an important resource for investigation of genome structure and genomic variation underlying traits of interest in cattle.     

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.     

Genome‐wide copy number profiling using high‐density SNP array in chickens

Phenotypic diversity is a direct consequence resulting mainly from the impact of underlying genetic variation, and recent studies have shown that copy number variation (CNV) is emerging as an important contributor to both phenotypic variability and disease susceptibility. Herein, we performed a genome‐wide CNV scan in 96 chickens from 12 diversified breeds, benefiting from the high‐density Affymetrix 600 K SNP arrays. We identified a total of 231 autosomal CNV regions (CNVRs) encompassing 5.41 Mb of the chicken genome and corresponding to 0.59% of the autosomal sequence. The length of these CNVRs ranged from 2.6 to 586.2 kb with an average of 23.4 kb, including 130 gain, 93 loss and eight both gain and loss events. These CNVRs, especially deletions, had lower GC content and were located particularly in gene deserts. In particular, 102 CNVRs harbored 128 chicken genes, most of which were enriched in immune responses. We obtained 221 autosomal CNVRs after converting probe coordinates to Galgal3, and comparative analysis with previous studies illustrated that 153 of these CNVRs were regarded as novel events. Furthermore, qPCR assays were designed for 11 novel CNVRs, and eight (72.73%) were validated successfully. In this study, we demonstrated that the high‐density 600 K SNP array can capture CNVs with higher efficiency and accuracy and highlighted the necessity of integrating multiple technologies and algorithms. Our findings provide a pioneering exploration of chicken CNVs based on a high‐density SNP array, which contributes to a more comprehensive understanding of genetic variation in the chicken genome and is beneficial to unearthing potential CNVs underlying important traits of chickens.     

Genomic regions showing copy number variations associate with resistance or susceptibility to gastrointestinal nematodes in Angus cattle

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. We previously reported an initial analysis of copy number variations (CNVs) in Angus cattle selected for resistance or susceptibility to gastrointestinal nematodes. In this study, we performed a large-scale analysis of CNVs using SNP genotyping data from 472 animals of the same population. We detected 811 candidate CNV regions, which represent 141.8 Mb (~4.7%) of the genome. To investigate the functional impacts of CNVs, we created 2 groups of 100 individual animals with extremely low or high estimated breeding values of eggs per gram of feces and referred to these groups as parasite resistant (PR) or parasite susceptible (PS), respectively. We identified 297 (~51 Mb) and 282 (~48 Mb) CNV regions from PR and PS groups, respectively. Approximately 60% of the CNV regions were specific to the PS group or PR group of animals. Selected PR- or PS-specific CNVs were further experimentally validated by quantitative PCR. A total of 297 PR CNV regions overlapped with 437 Ensembl genes enriched in immunity and defense, like WC1 gene which uniquely expresses on gamma/delta T cells in cattle. Network analyses indicated that the PR-specific genes were predominantly involved in gastrointestinal disease, immunological disease, inflammatory response, cell-to-cell signaling and interaction, lymphoid tissue development, and cell death. By contrast, the 282 PS CNV regions contained 473 Ensembl genes which are overrepresented in environmental interactions. Network analyses indicated that the PS-specific genes were particularly enriched for inflammatory response, immune cell trafficking, metabolic disease, cell cycle, and cellular organization and movement.     

Copy number variations identified in the chicken using a 60K SNP BeadChip

Copy number variation (CNV) is considered an important genetic variation, contributing to many economically important traits in the chicken. Although CNVs can be detected using a comparative genomic hybridization array, the high‐density SNP array has provided an alternative way to identify CNVs in the chicken. In the current study, a chicken 60K SNP BeadChip was used to identify CNVs in two distinct chicken genetic lines (White Leghorn and dwarf) using the penncnv program. A total of 209 CNV regions were identified, distributing on chromosomes 1–22 and 24–28 and encompassing 13.55 Mb (1.42%) of chicken autosomal genome area. Three of seven selected CNVs (73.2% individuals) were completely validated by quantitative PCR. To our knowledge, this is the first report in the chicken identifying CNVs using a SNP array. Identification of 190 new identified CNVs illustrates the feasibility of the chicken 60K SNP BeadChip to detect CNVs in the chicken, which lays a solid foundation for future analyses of associations of CNVs with economically important phenotypes in chickens.     

Precision-mapping and statistical validation of quantitative trait loci by machine learning

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.     

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.     

A map of copy number variations in Chinese populations

It has been shown that the human genome contains extensive copy number variations (CNVs). Investigating the medical and evolutionary impacts of CNVs requires the knowledge of locations, sizes and frequency distribution of them within and between populations. However, CNV study of Chinese minorities, which harbor the majority of genetic diversity of Chinese populations, has been underrepresented considering the same efforts in other populations. Here we constructed, to our knowledge, a first CNV map in seven Chinese populations representing the major linguistic groups in China with 1,440 CNV regions identified using Affymetrix SNP 6.0 Array. Considerable differences in distributions of CNV regions between populations and substantial population structures were observed. We showed that ～35% of CNV regions identified in minority ethnic groups are not shared by Han Chinese population, indicating that the contribution of the minorities to genetic architecture of Chinese population could not be ignored. We further identified highly differentiated CNV regions between populations. For example, a common deletion in Dong and Zhuang (44.4% and 50%), which overlaps two keratin-associated protein genes contributing to the structure of hair fibers, was not observed in Han Chinese. Interestingly, the most differentiated CNV deletion between HapMap CEU and YRI containing CCL3L1 gene reported in previous studies was also the highest differentiated regions between Tibetan and other populations. Besides, by jointly analyzing CNVs and SNPs, we found a CNV region containing gene CTDSPL were in almost perfect linkage disequilibrium between flanking SNPs in Tibetan while not in other populations except HapMap CHD. Furthermore, we found the SNP taggability of CNVs in Chinese populations was much lower than that in European populations. Our results suggest the necessity of a full characterization of CNVs in Chinese populations, and the CNV map we constructed serves as a useful resource in further evolutionary and medical studies.     

Analysis of copy number variations in Holstein cows identify potential mechanisms contributing to differences in residual feed intake

Genomic structural variation is an important and abundant source of genetic and phenotypic variation. In this study, we performed an initial analysis of copy number variations (CNVs) using BovineHD SNP genotyping data from 147 Holstein cows identified as having high or low feed efficiency as estimated by residual feed intake (RFI). We detected 443 candidate CNV regions (CNVRs) that represent 18.4?Mb (0.6?%) of the genome. To investigate the functional impacts of CNVs, we created two groups of 30 individual animals with extremely low or high estimated breeding values (EBVs) for RFI, and referred to these groups as low intake (LI; more efficient) or high intake (HI; less efficient), respectively. We identified 240 (~9.0?Mb) and 274 (~10.2?Mb) CNVRs from LI and HI groups, respectively. Approximately 30–40?% of the CNVRs were specific to the LI group or HI group of animals. The 240 LI CNVRs overlapped with 137 Ensembl genes. Network analyses indicated that the LI-specific genes were predominantly enriched for those functioning in the inflammatory response and immunity. By contrast, the 274 HI CNVRs contained 177 Ensembl genes. Network analyses indicated that the HI-specific genes were particularly involved in the cell cycle, and organ and bone development. These results relate CNVs to two key variables, namely immune response and organ and bone development. The data indicate that greater feed efficiency relates more closely to immune response, whereas cattle with reduced feed efficiency may have a greater capacity for organ and bone development.     

Diversity of copy number variation in a worldwide population of sheep

Copy number variation (CNV) represents a major source of genomic variation. We investigated the diversity of CNV distribution using SNP array data collected from a comprehensive collection of geographically dispersed sheep breeds. We identified 24,558 putative CNVs, which can be merged into 619 CNV regions, spanning 197 Mb of total length and corresponding to ~ 6.9% of the sheep genome. Our results reveal a population differentiation in CNV between different geographical areas, including Africa, America, Asia, Southwestern Asia, Central Europe, Northern Europe and Southwestern Europe. We observed clear distinctions in CNV prevalence between diverse groups, possibly reflecting the population history of different sheep breeds. We sought to determine the gene content of CNV, and found several important CNV-overlapping genes (BTG3, PTGS1 and PSPH) which were involved in fetal muscle development, prostaglandin (PG) synthesis, and bone color. Our study generates a comprehensive CNV map, which may contribute to genome annotation in sheep.     

Detection of copy number variants in the horse genome and examination of their association with recurrent laryngeal neuropathy

We used the data from a recently performed genome‐wide association study using the Illumina Equine SNP50 beadchip for the detection of copy number variants (CNVs) and examined their association with recurrent laryngeal neuropathy (RLN), an important equine upper airway disease compromising performance. A total of 2797 CNVs were detected for 477 horses, covering 229 kb and seven SNPs on average. Overlapping CNVs were merged to define 478 CNV regions (CNVRs). CNVRs, particularly deletions, were shown to be significantly depleted in genes. Fifty‐two of the 67 common CNVRs (frequency ≥ 1%) were validated by association mapping, Mendelian inheritance, and/or Mendelian inconsistencies. None of the 67 common CNVRs were significantly associated with RLN when accounting for multiple testing. However, a duplication on chromosome 10 was detected in 10 cases (representing three breeds) and two unphenotyped parents but in none of the controls. The duplication was embedded in an 8‐Mb haplotype shared across breeds.     

Copy number variants in a highly inbred Iberian porcine strain

We carried out a comprehensive genomic analysis of porcine copy number variants (CNVs) based on whole‐genome SNP genotyping data and provided new measures of genomic diversity (number, length and distribution of CNV events) for a highly inbred strain (the Guadyerbas strain). This strain represents one of the most ancient surviving populations of the Iberian breed, and it is currently in serious danger of extinction. CNV detection was conducted on the complete Guadyerbas population, adjusted for genomic waves, and used strict quality criteria, pedigree information and the latest porcine genome annotation. The analysis led to the detection of 65 CNV regions (CNVRs). These regions cover 0.33% of the autosomal genome of this particular strain. Twenty‐nine of these CNVRs were identified here for the first time. The relatively low number of detected CNVRs is in line with the low variability and high inbreeding estimated previously for this Iberian strain using pedigree, microsatellite or SNP data. A comparison across different porcine studies has revealed that more than half of these regions overlap with previously identified CNVRs or multicopy regions. Also, a preliminary analysis of CNV detection using whole‐genome sequence data for four Guadyerbas pigs showed overlapping for 16 of the CNVRs, supporting their reliability. Some of the identified CNVRs contain relevant functional genes (e.g., the SCD and USP15 genes), which are worth being further investigated because of their importance in determining the quality of Iberian pig products. The CNVR data generated could be useful for improving the porcine genome annotation.     

Genome-wide patterns of copy number variations in Spodoptera litura

Spodoptera litura is a polyphagous pest and can feed on more than 100 species of plants, causing great damage to agricultural production. The SNP results showed that there were gene exchanges between different regions. To explore the variations of larger segments in S. litura genome, we used genome resequencing samples from 14 regions of China, India, and Japan to study the copy number variations (CNVs). We identified 3976 CNV events and 1581 unique copy number variation regions (CNVRs) occupying the 108.5 Mb genome of S. litura. A total of 5527 genes that overlapped with CNVRs were detected. Selection signal analysis identified 19 shared CNVRs and 105 group-specific CNVRs, whose related genes were involved in various biological processes in S. litura. We constructed the first CNVs map in S. litura genome, and our findings will be valuable for understanding the genomic variations and population differences of S. litura.     

A first comparative map of copy number variations in the sheep genome

We carried out a cross species cattle-sheep array comparative genome hybridization experiment to identify copy number variations (CNVs) in the sheep genome analysing ewes of Italian dairy or dual-purpose breeds (Bagnolese, Comisana, Laticauda, Massese, Sarda, and Valle del Belice) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. We identified 135 CNV regions (CNVRs; 24 reported in more than one animal) covering ~10.5 Mb of the virtual sheep genome referred to the bovine genome (0.398%) with a mean and a median equal to 77.6 and 55.9 kb, respectively. A comparative analysis between the identified sheep CNVRs and those reported in cattle and goat genomes indicated that overlaps between sheep and both other species CNVRs are highly significant (P<0.0001), suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Many sheep CNVRs include genes with important biological functions. Further studies are needed to evaluate their functional relevance.     

GStream: Improving SNP and CNV Coverage on Genome-Wide Association Studies

We present GStream, a method that combines genome-wide SNP and CNV genotyping in the Illumina microarray platform with unprecedented accuracy. This new method outperforms previous well-established SNP genotyping software. More importantly, the CNV calling algorithm of GStream dramatically improves the results obtained by previous state-of-the-art methods and yields an accuracy that is close to that obtained by purely CNV-oriented technologies like Comparative Genomic Hybridization (CGH). We demonstrate the superior performance of GStream using microarray data generated from HapMap samples. Using the reference CNV calls generated by the 1000 Genomes Project (1KGP) and well-known studies on whole genome CNV characterization based either on CGH or genotyping microarray technologies, we show that GStream can increase the number of reliably detected variants up to 25% compared to previously developed methods. Furthermore, the increased genome coverage provided by GStream allows the discovery of CNVs in close linkage disequilibrium with SNPs, previously associated with disease risk in published Genome-Wide Association Studies (GWAS). These results could provide important insights into the biological mechanism underlying the detected disease risk association. With GStream, large-scale GWAS will not only benefit from the combined genotyping of SNPs and CNVs at an unprecedented accuracy, but will also take advantage of the computational efficiency of the method.     

Accuracy of CNV Detection from GWAS Data

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.     

Identification of copy number variations in three Chinese horse breeds using 70K single nucleotide polymorphism BeadChip array

Copy number variation (CNV), an essential form of genetic variation, has been increasingly recognized as one promising genetic marker in the analysis of animal genomes. Here, we used the Equine 70K single nucleotide polymorphism genotyping array for the genome‐wide detection of CNVs in 96 horses from three diverse Chinese breeds: Debao pony (DB), Mongolian horse (MG) and Yili horse (YL). A total of 287 CNVs were determined and merged into 122 CNV regions (CNVRs) ranging from 199 bp to 2344 kb in size and distributed in a heterogeneous manner on chromosomes. These CNVRs were integrated with seven existing reports to generate a composite genome‐wide dataset of 1558 equine CNVRs, revealing 69 (56.6%) novel CNVRs. The majority (69.7%) of the 122 CNVRs overlapped with 438 genes, whereas 30.3% were located in intergenic regions. Most of these genes were associated with common CNVRs, which were shared by divergent horse breeds. As many as 60, 42 and 91 genes overlapping with the breed‐specific ss were identified in DB, MG and YL respectively. Among these genes, FGF11, SPEM1, PPARG, CIDEB, HIVEP1 and GALR may have potential relevance to breed‐specific traits. These findings provide valuable information for understanding the equine genome and facilitating association studies of economically important traits with equine CNVRs in the future.     

Microarray-based maps of copy-number variant regions in European and sub-Saharan populations

The genetic basis of phenotypic variation can be partially explained by the presence of copy-number variations (CNVs). Currently available methods for CNV assessment include high-density single-nucleotide polymorphism (SNP) microarrays that have become an indispensable tool in genome-wide association studies (GWAS). However, insufficient concordance rates between different CNV assessment methods call for cautious interpretation of results from CNV-based genetic association studies. Here we provide a cross-population, microarray-based map of copy-number variant regions (CNVRs) to enable reliable interpretation of CNV association findings. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to scan the genomes of 1167 individuals from two ethnically distinct populations (Europe, N=717; Rwanda, N=450). Three different CNV-finding algorithms were tested and compared for sensitivity, specificity, and feasibility. Two algorithms were subsequently used to construct CNVR maps, which were also validated by processing subsamples with additional microarray platforms (Illumina 1M-Duo BeadChip, Nimblegen 385K aCGH array) and by comparing our data with publicly available information. Both algorithms detected a total of 42669 CNVs, 74% of which clustered in 385 CNVRs of a cross-population map. These CNVRs overlap with 862 annotated genes and account for approximately 3.3% of the haploid human genome.We created comprehensive cross-populational CNVR-maps. They represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.