Extensive Copy-Number Variation of Young Genes across Stickleback Populations

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Increased DNA Copy Number Variation Mosaicism in Elderly Human Brain.

Aging is a complex process strongly determined by genetics. Previous reports have shown that the genome of neuronal cells displays somatic genomic mosaicism including DNA copy number variations (CNVs). CNVs represent a significant source of genetic variation in the human genome and have been implicated in several disorders and complex traits, representing a potential mechanism that contributes to neuronal diversity and the etiology of several neurological diseases and provides new insights into the normal, complex functions of the brain. Nonetheless, the features of somatic CNV mosaicism in nondiseased elderly brains have not been investigated. In the present study, we demonstrate a highly significant increase in the number of CNVs in nondiseased elderly brains compared to the blood. In two neural tissues isolated from paired postmortem samples (same individuals), we found a significant increase in the frequency of deletions in both brain areas, namely, the frontal cortex and cerebellum. Also, deletions were found to be significantly larger when present only in the cerebellum. The sizes of the variants described here were in the 150-760 kb range, and importantly, nearly all of them were present in the Database of Genomic Variants (common variants). Nearly all evidence of genome structural variation in human brains comes from studies detecting changes in single cells which were interpreted as derived from independent, isolated mutational events. The observations based on array-CGH analysis indicate the existence of an extensive clonal mosaicism of CNVs within and between the human brains revealing a different type of variation that had not been previously characterized

Human amylase gene copy number variation as a determinant of metabolic state

Introduction Humans have multiple genes encoding amylase that are broadly divided into salivary (AMY1) and pancreatic (AMY2) genes. They exhibit some of the greatest copy numbers of any human gene, an expansion possibly driven by increased dietary starch intake. Within the population, amylase gene copy number is highly variable and there is evidence of an inverse association between AMY1 copy number and BMI. Areas covered We examine the evidence for the link between AMY1 and BMI, its potential mechanisms, and the metabolic effects of salivary and pancreatic amylase, both in the gastrointestinal tract and the blood. Expert commentary Salivary amylase may influence postprandial ‘cephalic phase’ insulin release, which improves glucose tolerance, while serum amylase may have insulin-sensitizing properties. This could explain the favorable metabolic status associated with higher AMY1 copy number. The association with BMI is harder to explain and is potentially mediated by increased flux of undigested starch into the ileum, with resultant effects on short-chain fatty acids (SCFAs), changes in gut microbiota and effects on appetite and energy expenditure in those with low copy number. Future research on the role of amylase as a determinant of metabolic health and BMI may lead to novel therapies to target obesity

DNA Copy Number Variation in Autism

Autism is a childhood neurodevelopmental and psychiatric disorder that involves the impairment of social skills and communication. The genetics behind the inheritance and susceptibility of this disorder are not well known but have recently been studied. Lately, DNA Copy number variation (CNV) in autistic individuals has been a topic of high interest, and has been shown to have an association with this disorder. CNV generally refers to differences in the germ line DNA content between individuals. CNVs span from 1-kb to multi-megabases, and represent a significant portion of genetic variation in normal humans. Significant work has been done in the field of Autism Spectrum Disorder (ASD) genetics to find CNVs implicated in the development of autism and the variation of phenotype. In order to identify new disease alterations, we are conducting CNV discovery studies on 10 autistic children and their families. We expect our findings will lead to a better understanding of pathophysiology and to new avenues of therapeutic treatment. We conducted CNV discovery in 10 autistic children using array Comparative Genome Hybridization (aCGH) on a tiling-resolution whole genome BAC microarray. This platform can detect CNVs >50-kb. From the high confidence CNV calls (based on standard deviation and signal-to-noise Ratios), we filtered out all variants that are found in 4% or more of normal individuals. We have identified over 100 high confidence candidate CNVs that have rarely or never been reported previously. In addition, we have begun to determine if any variants were created de novo in the affected child (i.e., were not inherited from parents). Some candidate de novo variants span many genes and could have functional effects. We conclude that it is worth conducting more genome-wide CNV discovery in autism, and testing suggestive CNVs for association in large numbers of autism patients.No embarg

Copy number variation in bipolar disorder.

Large (>100 kb), rare (500 kb) CNVs in BD compared with SZ, most notably for deletions >1 Mb (P=9 × 10(-4))

Copy-number-variation and copy-number-alteration region detection by cumulative plots

Background: Regions with copy number variations (in germline cells) or copy number alteration (in somatic cells) are of great interest for human disease gene mapping and cancer studies. They represent a new type of mutation and are larger-scaled than the single nucleotide polymorphisms. Using genotyping microarray for copy number variation detection has become standard, and there is a need for improving analysis methods. Results: We apply the cumulative plot to the detection of regions with copy number variation/alteration, on samples taken from a chronic lymphocytic leukemia patient. Two sets of whole-genome genotyping of 317k single nucleotide polymorphisms, one from the normal cell and another from the cancer cell, are analyzed. We demonstrate the utility of cumulative plot in detecting a 9Mb (9 x 10^6 bases) hemizygous deletion and 1Mb homozygous deletion on chromosome 13. We also show the possibility to detect smaller copy number variation/alteration regions below the 100kb range. Conclusions: As a graphic tool, the cumulative plot is an intuitive and a scale-free (window-less) way for detecting copy number variation/alteration regions, especially when such regions are small

Copy number variation in African Americans

<p>Abstract</p> <p>Background</p> <p>Copy number variants (CNVs) have been identified in several studies to be associated with complex diseases. It is important, therefore, to understand the distribution of CNVs within and among populations. This study is the first report of a CNV map in African Americans.</p> <p>Results</p> <p>Employing a SNP platform with greater than 500,000 SNPs, a first-generation CNV map of the African American genome was generated using DNA from 385 healthy African American individuals, and compared to a sample of 435 healthy White individuals. A total of 1362 CNVs were identified within African Americans, which included two CNV regions that were significantly different in frequency between African Americans and Whites (17q21 and 15q11). In addition, a duplication was identified in 74% of DNAs derived from cell lines that was not present in any of the whole blood derived DNAs.</p> <p>Conclusion</p> <p>The Affymetrix 500 K array provides reliable CNV mapping information. However, using cell lines as a source of DNA may introduce artifacts. The duplication identified in high frequency in Whites and low frequency in African Americans on chromosome 17q21 reflects haplotype specific frequency differences between ancestral groups. The generation of the CNV map will be a valuable tool for identifying disease associated CNVs in African Americans.</p

Automated copy number variation concordance analysis

Rapid growth and advancement of next generation sequencing (NGS) technologies have changed the landscape of genomic medicine. Today, clinical laboratories perform DNA sequencing on a regular basis, which is an error prone process. Erroneous data affects downstream analysis and produces fallacious result. Therefore, external quality assessment (EQA) of laboratories working with NGS data is crucial. Validation of variations such as single nucleotide polymor- phism (SNP) and InDels (<50 bp) is fairly accurate these days. However, detection and quality assessment of large changes such as the copy number variation (CNV) continues to be a concern. In this work, we aimed to study the feasibility of an automated CNV concordance analysis for the laboratory EQA services. We benchmarked variants reported by 25 laboratories against the highly curated gold standard for the son (HG002/NA24385) of the askenazim trio from the Personal Genome Project published by the Genome in a Bottle Consortium (GIAB). We employed two methods to conduct concordance of CNVs, the sequence based comparison with Truvari and the in-house exome-based comparison. For deletion calls of two whole genome sequencing (WGS) submissions, Truvari gained a value greater than 88% and 68% for precision and recall respectively. Conversely, the in-house method’s precision and recall score peaked at 39% and 7.9% respectively for one WGS submission for both deletion and duplication calls. The results indicate that automated CNV concordance analysis of the deletion calls for the WGS-based callset might be feasible with Truvari. On the other hand, results for panel-based targeted sequencing for the deletion calls showed precision and recall rates ranging from 0-80% and 0-5.6% respectively with Truvari. The result suggests that automated concordance analysis of CNVs for targeted sequencing remains a challenge. In conclusion, CNV concordance analysis depends on how the sequence data is generated

Copy Number Variation across European Populations

Genome analysis provides a powerful approach to test for evidence of genetic variation within and between geographical regions and local populations. Copy number variants which comprise insertions, deletions and duplications of genomic sequence provide one such convenient and informative source. Here, we investigate copy number variants from genome wide scans of single nucleotide polymorphisms in three European population isolates, the island of Vis in Croatia, the islands of Orkney in Scotland and the South Tyrol in Italy. We show that whereas the overall copy number variant frequencies are similar between populations, their distribution is highly specific to the population of origin, a finding which is supported by evidence for increased kinship correlation for specific copy number variants within populations

Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data