Identification and functional characterization of copy number variations in diverse chicken breeds

Background

The detection and functional characterization of genomic structural variations are important for understanding the landscape of genetic variation in the chicken. A recently recognized aspect of genomic structural variation, called copy number variation (CNV), is gaining interest in chicken genomic studies. The aim of the present study was to investigate the pattern and functional characterization of CNVs in five characteristic chicken breeds, which will be important for future studies associating phenotype with chicken genome architecture.

Results

Using a commercial 385 K array-based comparative genomic hybridization (aCGH) genome array, we performed CNV discovery using 10 chicken samples from four local Chinese breeds and the French breed Houdan chicken. The female Anka broiler was used as a reference. A total of 281 copy number variation regions (CNVR) were identified, covering 12.8 Mb of polymorphic sequences or 1.07% of the entire chicken genome. The functional annotation of CNVRs indicated that these regions completely or partially overlapped with 231 genes and 1032 quantitative traits loci, suggesting these CNVs have important functions and might be promising resources for exploring differences among various breeds. In addition, we employed quantitative PCR (qPCR) to further validate several copy number variable genes, such as prolactin receptor, endothelin 3 (EDN3), suppressor of cytokine signaling 2, CD8a molecule, with important functions, and the results suggested that EDN3 might be a molecular marker for the selection of dark skin color in poultry production. Moreover, we also identified a new CNVR (chr24: 3484617–3512275), encoding the sortilin-related receptor gene, with copy number changes in only black-bone chicken.

Conclusions

Here, we report a genome-wide analysis of the CNVs in five chicken breeds using aCGH. The association between EDN3 and melanoblast proliferation was further confirmed using qPCR. These results provide additional information for understanding genomic variation and related phenotypic characteristics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-934) contains supplementary material, which is available to authorized users.     

A high-resolution map of segmental DNA copy number variation in the mouse genome

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.     

Short Copy Number Variations Potentially Associated with Tonic Immobility Responses in Newly Hatched Chicks

Introduction

Tonic immobility (TI) is fear-induced freezing that animals may undergo when confronted by a threat. It is principally observed in prey species as defence mechanisms. In our preliminary research, we detected large inter-individual variations in the frequency and duration of freezing behavior among newly hatched domestic chicks (Gallus gallus). In this study we aim to identify the copy number variations (CNVs) in the genome of chicks as genetic candidates that underlie the behavioral plasticity to fearful stimuli.

Methods

A total of 110 domestic chicks were used for an association study between TI responses and copy number polymorphisms. Array comparative genomic hybridization (aCGH) was conducted between chicks with high and low TI scores using an Agilent 4×180 custom microarray. We specifically focused on 3 genomic regions (>60 Mb) of chromosome 1 where previous quantitative trait loci (QTL) analysis showed significant F-values for fearful responses.

Results

ACGH successfully detected short CNVs within the regions overlapping 3 QTL peaks. Eleven of these identified loci were validated by real-time quantitative polymerase chain reaction (qPCR) as copy number polymorphisms. Although there wkas no significant p value in the correlation analysis between TI scores and the relative copy number within each breed, several CNV loci showed significant differences in the relative copy number between 2 breeds of chicken (White Leghorn and Nagoya) which had different quantitative characteristics of fear-induced responses.

Conclusion

Our data shows the potential CNVs that may be responsible for innate fear response in domestic chicks.     

Allelic genome structural variations in maize detected by array comparative genome hybridization

DNA polymorphisms such as insertion/deletions and duplications affecting genome segments larger than 1 kb are known as copy-number variations (CNVs) or structural variations (SVs). They have been recently studied in animals and humans by using array-comparative genome hybridization (aCGH), and have been associated with several human diseases. Their presence and phenotypic effects in plants have not been investigated on a genomic scale, although individual structural variations affecting traits have been described. We used aCGH to investigate the presence of CNVs in maize by comparing the genome of 13 maize inbred lines to B73. Analysis of hybridization signal ratios of 60,472 60-mer oligonucleotide probes between inbreds in relation to their location in the reference genome (B73) allowed us to identify clusters of probes that deviated from the ratio expected for equal copy-numbers. We found CNVs distributed along the maize genome in all chromosome arms. They occur with appreciable frequency in different germplasm subgroups, suggesting ancient origin. Validation of several CNV regions showed both insertion/deletions and copy-number differences. The nature of CNVs detected suggests CNVs might have a considerable impact on plant phenotypes, including disease response and heterosis.     

Haplotype Phasing and Inheritance of Copy Number Variants in Nuclear Families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.     

A Statistical Change Point Model Approach for the Detection of DNA Copy Number Variations in Array CGH Data

Array comparative genomic hybridization (aCGH) provides a high-resolution and high-throughput technique for screening of copy number variations (CNVs) within the entire genome. This technique, compared to the conventional CGH, significantly improves the identification of chromosomal abnormalities. However, due to the random noise inherited in the imaging and hybridization process, identifying statistically significant DNA copy number changes in aCGH data is challenging. We propose a novel approach that uses the mean and variance change point model (MVCM) to detect CNVs or breakpoints in aCGH data sets. We derive an approximate p-value for the test statistic and also give the estimate of the locus of the DNA copy number change. We carry out simulation studies to evaluate the accuracy of the estimate and the p-value formulation. These simulation results show that the approach is effective in identifying copy number changes. The approach is also tested on fibroblast cancer cell line data, breast tumor cell line data, and breast cancer cell line aCGH data sets that are publicly available. Changes that have not been identified by the circular binary segmentation (CBS) method but are biologically verified are detected by our approach on these cell lines with higher sensitivity and specificity than CBS.     

Gene copy number variations in adaptive evolution: The genomic distribution of gene copy number variations revealed by genetic mapping and their adaptive role in an undomesticated species,white spruce (Picea glauca)

Gene copy number variation (CNV) has been associated with phenotypic variability in animals and plants, but a genomewide understanding of their impacts on phenotypes is largely restricted to human and agricultural systems. As such, CNVs have rarely been considered in investigations of the genomic architecture of adaptation in wild species. Here, we report on the genetic mapping of gene CNVs in white spruce, which lacks a contiguous assembly of its large genome (~20 Gb), and their relationships with adaptive phenotypic variation. We detected 3,911 gene CNVs including de novo structural variations using comparative genome hybridization on arrays (aCGH) in a large progeny set. We inferred the heterozygosity at CNV loci within parents by comparing haploid and diploid tissues and genetically mapped 82 gene CNVs. Our analysis showed that CNVs were distributed over 10 linkage groups and identified four CNV hotspots that we predict to occur in other species of the Pinaceae. Significant relationships were found between 29 of the gene CNVs and adaptive traits based on regression analyses with timings of bud set and bud flush, and height growth, suggesting a role for CNVs in climate adaptation. The importance of CNVs in adaptive evolution of white spruce was also indicated by functional gene annotations and the clustering of 31% of the mapped adaptive gene CNVs in CNV hotspots. Taken together, these results illustrate the feasibility of studying CNVs in undomesticated species and represent a major step towards a better understanding of the roles of CNVs in adaptive evolution.     

Elusive Copy Number Variation in the Mouse Genome

Background

Array comparative genomic hybridization (aCGH) to detect copy number variants (CNVs) in mammalian genomes has led to a growing awareness of the potential importance of this category of sequence variation as a cause of phenotypic variation. Yet there are large discrepancies between studies, so that the extent of the genome affected by CNVs is unknown. We combined molecular and aCGH analyses of CNVs in inbred mouse strains to investigate this question.

Principal Findings

Using a 2.1 million probe array we identified 1,477 deletions and 499 gains in 7 inbred mouse strains. Molecular characterization indicated that approximately one third of the CNVs detected by the array were false positives and we estimate the false negative rate to be more than 50%. We show that low concordance between studies is largely due to the molecular nature of CNVs, many of which consist of a series of smaller deletions and gains interspersed by regions where the DNA copy number is normal.

Conclusions

Our results indicate that CNVs detected by arrays may be the coincidental co-localization of smaller CNVs, whose presence is more likely to perturb an aCGH hybridization profile than the effect of an isolated, small, copy number alteration. Our findings help explain the hitherto unexplored discrepancies between array-based studies of copy number variation in the mouse genome.     

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.     

Epigenetic silencing of genomic structural variations

A great amount of copy number variations (CNVs) are identified in the human genome. Most of them are neutral; nevertheless, the role of CNVs in the pathogenesis of hereditary diseases is still significant. Especially, this is important for neuropsychiatric disorders, such as intellectual disability and autism. When analyzing the CNV-associated diseases, the controversial question is to distinguish the pathogenic CNVs among common polymorphic variants and to predict the disease risk in other children of the family. Unfortunately, the mechanisms of phenotypic expression and incomplete penetrance of CNVs remain largely unknown. Currently, incomplete penetrance and variable expressivity of CNVs are attributed mainly to allelic interaction of different genetic variations. However, epigenetic mechanisms of gene expression regulation in the context of structural variation of the genome are poorly explored. It is possible that epigenetic modifications of the genome regions with CNVs may underlie the understanding of ways of phenotypic manifestations of structural variations in the human genome.     

Breaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization

Background

Large-scale high throughput studies using microarray technology have established that copy number variation (CNV) throughout the genome is more frequent than previously thought. Such variation is known to play an important role in the presence and development of phenotypes such as HIV-1 infection and Alzheimer's disease. However, methods for analyzing the complex data produced and identifying regions of CNV are still being refined.

Results

We describe the presence of a genome-wide technical artifact, spatial autocorrelation or 'wave', which occurs in a large dataset used to determine the location of CNV across the genome. By removing this artifact we are able to obtain both a more biologically meaningful clustering of the data and an increase in the number of CNVs identified by current calling methods without a major increase in the number of false positives detected. Moreover, removing this artifact is critical for the development of a novel model-based CNV calling algorithm - CNVmix - that uses cross-sample information to identify regions of the genome where CNVs occur. For regions of CNV that are identified by both CNVmix and current methods, we demonstrate that CNVmix is better able to categorize samples into groups that represent copy number gains or losses.

Conclusion

Removing artifactual 'waves' (which appear to be a general feature of array comparative genomic hybridization (aCGH) datasets) and using cross-sample information when identifying CNVs enables more biological information to be extracted from aCGH experiments designed to investigate copy number variation in normal individuals.     

Effects of gene regulatory reprogramming on gene expression in human and mouse developing hearts

Lineage-specific regulatory elements underlie adaptation of species and play a role in disease susceptibility. We compared functionally conserved and lineage-specific enhancers by cross-mapping 5042 human and 6564 mouse heart enhancers. Of these, 79 per cent are lineage-specific, lacking a functional orthologue. Heart enhancers tend to cluster and, commonly, there are multiple heart enhancers in a heart locus providing a regulatory stability to the locus. We observed little cross-clustering, however, between lineage-specific and functionally conserved heart enhancers suggesting regulatory function acquisition and development in loci previously lacking heart activity. We also identified 862 human-specific heart enhancers: 417 featuring sequence conservation with mouse (class II) and 445 with neither sequence nor function conservation (class III). Ninety-eight per cent of class III enhancers were deleted from the mouse genome, and we estimated a similar-sized enhancer gain in the human lineage. Human-specific enhancers display no detectable decrease in the negative selection pressure and are strongly associated with genes partaking in the heart regulatory programmes. The loss of a heart enhancer could be compensated by activity of a redundant heart enhancer; however, we observed redundancy in only 15 per cent of class II and III enhancer loci indicating a large-scale reprogramming of the heart regulatory programme in mammals.     

The fine-scale and complex architecture of human copy-number variation

Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.     

Abnormal Dosage of Ultraconserved Elements Is Highly Disfavored in Healthy Cells but Not Cancer Cells

Ultraconserved elements (UCEs) are strongly depleted from segmental duplications and copy number variations (CNVs) in the human genome, suggesting that deletion or duplication of a UCE can be deleterious to the mammalian cell. Here we address the process by which CNVs become depleted of UCEs. We begin by showing that depletion for UCEs characterizes the most recent large-scale human CNV datasets and then find that even newly formed de novo CNVs, which have passed through meiosis at most once, are significantly depleted for UCEs. In striking contrast, CNVs arising specifically in cancer cells are, as a rule, not depleted for UCEs and can even become significantly enriched. This observation raises the possibility that CNVs that arise somatically and are relatively newly formed are less likely to have established a CNV profile that is depleted for UCEs. Alternatively, lack of depletion for UCEs from cancer CNVs may reflect the diseased state. In support of this latter explanation, somatic CNVs that are not associated with disease are depleted for UCEs. Finally, we show that it is possible to observe the CNVs of induced pluripotent stem (iPS) cells become depleted of UCEs over time, suggesting that depletion may be established through selection against UCE-disrupting CNVs without the requirement for meiotic divisions.     

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.     

A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process

To study chromosomal aberrations that may lead to cancer formation or genetic diseases, the array-based Comparative Genomic Hybridization (aCGH) technique is often used for detecting DNA copy number variants (CNVs). Various methods have been developed for gaining CNVs information based on aCGH data. However, most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe (e.g., biomarker) positions/distances contained in the data. Motivated by the specific features of aCGH data, we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of multiple CNVs in the data, a sliding window process combined with our derived Bayesian posterior probability was proposed. To evaluate the performance of the method in the estimation of the CNV locus, we first performed simulation studies. Finally, we applied our approach to real data from aCGH experiments, demonstrating its applicability.     

Genomic hypomethylation in the human germline associates with selective structural mutability in the human genome

The hotspots of structural polymorphisms and structural mutability in the human genome remain to be explained mechanistically. We examine associations of structural mutability with germline DNA methylation and with non-allelic homologous recombination (NAHR) mediated by low-copy repeats (LCRs). Combined evidence from four human sperm methylome maps, human genome evolution, structural polymorphisms in the human population, and previous genomic and disease studies consistently points to a strong association of germline hypomethylation and genomic instability. Specifically, methylation deserts, the ~1% fraction of the human genome with the lowest methylation in the germline, show a tenfold enrichment for structural rearrangements that occurred in the human genome since the branching of chimpanzee and are highly enriched for fast-evolving loci that regulate tissue-specific gene expression. Analysis of copy number variants (CNVs) from 400 human samples identified using a custom-designed array comparative genomic hybridization (aCGH) chip, combined with publicly available structural variation data, indicates that association of structural mutability with germline hypomethylation is comparable in magnitude to the association of structural mutability with LCR-mediated NAHR. Moreover, rare CNVs occurring in the genomes of individuals diagnosed with schizophrenia, bipolar disorder, and developmental delay and de novo CNVs occurring in those diagnosed with autism are significantly more concentrated within hypomethylated regions. These findings suggest a new connection between the epigenome, selective mutability, evolution, and human disease.     

A Genome-Wide Analysis of Array-Based Comparative Genomic Hybridization (CGH) Data to Detect Intra-Species Variations and Evolutionary Relationships

Array-based comparative genomics hybridization (aCGH) has gained prevalence as an effective technique for measuring structural variations in the genome. Copy-number variations (CNVs) form a large source of genomic structural variation, but it is not known whether phenotypic differences between intra-species groups, such as divergent human populations, or breeds of a domestic animal, can be attributed to CNVs. Several computational methods have been proposed to improve the detection of CNVs from array CGH data, but few population studies have used CGH data for identification of intra-species differences. In this paper we propose a novel method of genome-wide comparison and classification using CGH data that condenses whole genome information, aimed at quantification of intra-species variations and discovery of shared ancestry. Our strategy included smoothing CGH data using an appropriate denoising algorithm, extracting features via wavelets, quantifying the information via wavelet power spectrum and hierarchical clustering of the resultant profile. To evaluate the classification efficiency of our method, we used simulated data sets. We applied it to aCGH data from human and bovine individuals and showed that it successfully detects existing intra-specific variations with additional evolutionary implications.     

Whole Genome Distribution and Ethnic Differentiation of Copy Number Variation in Caucasian and Asian Populations

Although copy number variation (CNV) has recently received much attention as a form of structure variation within the human genome, knowledge is still inadequate on fundamental CNV characteristics such as occurrence rate, genomic distribution and ethnic differentiation. In the present study, we used the Affymetrix GeneChip® Mapping 500K Array to discover and characterize CNVs in the human genome and to study ethnic differences of CNVs between Caucasians and Asians. Three thousand and nineteen CNVs, including 2381 CNVs in autosomes and 638 CNVs in X chromosome, from 985 Caucasian and 692 Asian individuals were identified, with a mean length of 296 kb. Among these CNVs, 190 had frequencies greater than 1% in at least one ethnic group, and 109 showed significant ethnic differences in frequencies (p<0.01). After merging overlapping CNVs, 1135 copy number variation regions (CNVRs), covering approximately 439 Mb (14.3%) of the human genome, were obtained. Our findings of ethnic differentiation of CNVs, along with the newly constructed CNV genomic map, extend our knowledge on the structural variation in the human genome and may furnish a basis for understanding the genomic differentiation of complex traits across ethnic groups.