Copy number variants, diseases and gene expression

Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation likely to play a role in phenotypic diversity and evolution. Much effort has been put into the identification and mapping of regions that vary in copy number among seemingly normal individuals in humans and a number of model organisms, using bioinformatics or hybridization-based methods. These have allowed uncovering associations between copy number changes and complex diseases in whole-genome association studies, as well as identify new genomic disorders. At the genome-wide scale, however, the functional impact of CNV remains poorly studied. Here we review the current catalogs of CNVs, their association with diseases and how they link genotype and phenotype. We describe initial evidence which revealed that genes in CNV regions are expressed at lower and more variable levels than genes mapping elsewhere, and also that CNV not only affects the expression of genes varying in copy number, but also have a global influence on the transcriptome. Further studies are warranted for complete cataloguing and fine mapping of CNVs, as well as to elucidate the different mechanisms by which they influence gene expressio

Schizophrenia copy number variants and associative learning

Large-scale genomic studies have made major progress in identifying genetic risk variants for schizophrenia. A key finding from these studies is that there is an increased burden of genomic copy number variants (CNVs) in schizophrenia cases compared with controls. The mechanism through which these CNVs confer risk for the symptoms of schizophrenia, however, remains unclear. One possibility is that schizophrenia risk CNVs impact basic associative learning processes, abnormalities of which have long been associated with the disorder. To investigate whether genes in schizophrenia CNVs impact on specific phases of associative learning we combined human genetics with experimental gene expression studies in animals. In a sample of 11 917 schizophrenia cases and 16 416 controls, we investigated whether CNVs from patients with schizophrenia are enriched for genes expressed during the consolidation, retrieval or extinction of associative memories. We show that CNVs from cases are enriched for genes expressed during fear extinction in the hippocampus, but not genes expressed following consolidation or retrieval. These results suggest that CNVs act to impair inhibitory learning in schizophrenia, potentially contributing to the development of core symptoms of the disorder

Assessment of copy number variants in three Brazilian locally adapted cattle breeds using whole-genome re-sequencing data.

Further characterization of genetic structural variations should strongly focus on small and endangered local breeds given their role in unraveling genes and structural variants underlying selective pressures and phenotype variation. A comprehensive genome-wide assessment of copy number variations (CNVs) based on whole-genome re-sequencing data was performed on three Brazilian locally adapted cattle breeds (Caracu Caldeano, Crioulo Lageano, and Pantaneiro) using the ARS-UCD1.2 genome assembly. Data from 36 individuals with an average coverage depth of 14.07× per individual was used. A total of 24?945 CNVs were identified distributed among the breeds (Caracu Caldeano = 7285, Crioulo Lageano = 7297, and Pantaneiro = 10 363). Deletion events were 1.75?2.07-fold higher than duplications, and the total length of CNVs is composed mostly of a high number of segments between 10 and 30?kb. CNV regions (CNVRs) are not uniformly scattered throughout the genomes (n = 463), and 105 CNVRs were found overlapping among the studied breeds. Functional annotation of the CNVRs revealed variants with high consequence on protein sequence harboring relevant genes, in which we highlighted the BOLA-DQB, BOLA-DQA5, CD1A, ?-defensins, PRG3, and ULBP21 genes. Enrichment analysis based on the gene list retrieved from the CNVRs disclosed over-represented terms (p?<?0.01) strongly associated with immunity and cattle resilience to harsh environments. Additionally, QTL associated with body conformation and dairy-related traits were also unveiled within the CNVRs. These results provide better understanding of the selective forces shaping the genome of such cattle breeds and identify traces of natural selection pressures by which these populations have been exposed to challenging environmental conditions.First online

Copy number variants in locally raised Chinese chicken genomes determined using array comparative genomic hybridization

BACKGROUND: Copy number variants contribute to genetic variation in birds. Analyses of copy number variants in chicken breeds had focused primarily on those from commercial varieties with nothing known about the occurrence and diversity of copy number variants in locally raised Chinese chicken breeds. To address this deficiency, we characterized copy number variants in 11 chicken breeds and compared the variation among these breeds. RESULTS: We presented a detailed analysis of the copy number variants in locally raised Chinese chicken breeds identified using a customized comparative genomic hybridization array. We identified 833 copy number variants contained within 308 copy number variant regions. The median and mean sizes of the copy number variant regions were 14.6 kb and 35.1 kb, respectively. Of the copy number variant regions, 138 (45%) involved gain of DNA, 159 (52%) involved loss of DNA, and 11 (3%) involved both gain and loss of DNA. Principal component analysis and agglomerative hierarchical clustering revealed the close relatedness of the four locally raised chicken breeds, Shek-Ki, Langshan, Qingyuan partridge, and Wenchang. Biological process enrichment analysis of the copy number variant regions confirmed the greater variation among the four aforementioned varieties than among the seven other breeds studied. CONCLUSION: Our description of the distribution of the copy number variants and comparison of the differences among the copy number variant regions of the 11 chicken breeds supplemented the information available concerning the copy number variants of other Chinese chicken breeds. In addition to its relevance for functional analysis, our results provided the first insight into how chicken breeds can be clustered on the basis of their genomic copy number variation

Using GWAS Data to Identify Copy Number Variants Contributing to Common Complex Diseases

Copy number variants (CNVs) account for more polymorphic base pairs in the human genome than do single nucleotide polymorphisms (SNPs). CNVs encompass genes as well as noncoding DNA, making these polymorphisms good candidates for functional variation. Consequently, most modern genome-wide association studies test CNVs along with SNPs, after inferring copy number status from the data generated by high-throughput genotyping platforms. Here we give an overview of CNV genomics in humans, highlighting patterns that inform methods for identifying CNVs. We describe how genotyping signals are used to identify CNVs and provide an overview of existing statistical models and methods used to infer location and carrier status from such data, especially the most commonly used methods exploring hybridization intensity. We compare the power of such methods with the alternative method of using tag SNPs to identify CNV carriers. As such methods are only powerful when applied to common CNVs, we describe two alternative approaches that can be informative for identifying rare CNVs contributing to disease risk. We focus particularly on methods identifying de novo CNVs and show that such methods can be more powerful than case-control designs. Finally we present some recommendations for identifying CNVs contributing to common complex disorders.Comment: Published in at http://dx.doi.org/10.1214/09-STS304 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Detection of copy number variants in sequencing data.

In this work a program for detection of CNVs in sequencing data based on depth of coverage was implemented in C++ (copyDOC). Single steps in the pipeline, the acquisition of DOC signals in windows, the event calling and merging are implemented using generic programming techniques that enable the future integration of other algorithms in the pipeline. Furthermore, a testing environment was implemented, the copySim platform, which is very useful for testing and evaluation of different algorithms. CopyDOC was successfully applied to synthetic and real data using constant sized windows. Dynamic windows, that adapt according to the local mappability of the sequence, are implemented in the pipeline, but could not be tested in this work. They might be advantageous in datasets that contain uniquely mapped reads. However, CNVs have been shown to be overrepresented in segmental duplications (Nguyen et al. 2006; Cooper et al. 2007) and by a general exclusion of multireads those CNVs might be difficult to ascertain. In the application of copyDOC to a 1000 genomes dataset the overlap of predicted variants was considerable higer using multireads compared to uniquely mapped reads. Thus there is a requirement for tools that can handle multireads. Futher improvements of copyDOC might be done for the CNV calling algorithm and the merging step. For example the program workflow could be tested with a direct comparison of the DOC signals in two datasets via log ratios instead of appling a t-test on DOC signals in the two datasets. CopyDOC and copySim could be used as platform for the implementation and evaluation of futher CNV detection algorithms

Bias of Selection on Human Copy-Number Variants

Although large-scale copy-number variation is an important contributor to conspecific genomic diversity, whether these variants frequently contribute to human phenotype differences remains unknown. If they have few functional consequences, then copy-number variants (CNVs) might be expected both to be distributed uniformly throughout the human genome and to encode genes that are characteristic of the genome as a whole. We find that human CNVs are significantly overrepresented close to telomeres and centromeres and in simple tandem repeat sequences. Additionally, human CNVs were observed to be unusually enriched in those protein-coding genes that have experienced significantly elevated synonymous and nonsynonymous nucleotide substitution rates, estimated between single human and mouse orthologues. CNV genes encode disproportionately large numbers of secreted, olfactory, and immunity proteins, although they contain fewer than expected genes associated with Mendelian disease. Despite mouse CNVs also exhibiting a significant elevation in synonymous substitution rates, in most other respects they do not differ significantly from the genomic background. Nevertheless, they encode proteins that are depleted in olfactory function, and they exhibit significantly decreased amino acid sequence divergence. Natural selection appears to have acted discriminately among human CNV genes. The significant overabundance, within human CNVs, of genes associated with olfaction, immunity, protein secretion, and elevated coding sequence divergence, indicates that a subset may have been retained in the human population due to the adaptive benefit of increased gene dosage. By contrast, the functional characteristics of mouse CNVs either suggest that advantageous gene copies have been depleted during recent selective breeding of laboratory mouse strains or suggest that they were preferentially fixed as a consequence of the larger effective population size of wild mice. It thus appears that CNV differences among mouse strains do not provide an appropriate model for large-scale sequence variations in the human population