4,804 research outputs found

    Copy Number Variation (CNV): A New Genomic Insight in Horses

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    This study aimed to contribute to our knowledge of CNVs, a type of genomic marker in equines, by producing, for the first time, a fine-scale characterization of the CNV regions (CNVRs) in the Pura Raza Española horse breed. We found not only the existence of a unique pattern of genomic regions enriched in CNVs in the PRE in comparison with the data available from other breeds but also the incidence of CNVs across the entire genome. Since these regions could affect the structure and dose of the genes involved, we also performed a gene ontology analysis which revealed that most of the genes overlapping in CNVRs were related to the olfactory pathways and immune response.Fil: Nora Laseca. Universidad de Córdoba; EspañaFil: Antonio Molina. Universidad de Córdoba; EspañaFil: Mercedes Valera. Universidad de Sevilla; EspañaFil: Alicia Antonini. Facultad de Ciencias Veterinarias, Universidad Nacional de la Plata; ArgentinaFil: Demyda Peyrás, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Facultad de Ciencias Veterinarias, Universidad Nacional de la Plata; Argentin

    Genome wide Copy Number Variation (CNV) detection in Cinisara cattle breed

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    Copy Number Variations (CNVs) are classes of polymorphic genomic regions including deletions, duplications and insertions of DNA fragments from at least 0.5 kb up to several Mb. CNV represents an important source of genetic variability that provides genomics structural information complementary to the single nucleotide polymorphism (SNP) data. Some CNVs have been shown to be important in both normal phenotypic variability and disease susceptibility in livestock. Several approaches to identify CNVs including FISH, aCGH, SNP array or NGS, were proposed and among these SNP genotyping is relatively low cost, high-throughput and high coverage method. The aim of this study was to identify the CNVs in 71 animals of Cinisara breed using Illumina BovineSNP50 BeadChip v2. PennCNV software, which incorporates Log R ratio and B allele frequency at each SNP marker, was used to identify CNVs. Seven animals showed not shared CNVs, as well as autosomes 19, 21, 22. Chromosome 25 presented no CNVs at all. A final number of 322 CNVs were detected. The average number of CNVs was 4.5 per individual, with an average length and median size of 143.04 kb and 122.14 kb, respectively. All CNVs were grouped in CNV regions (CNVRs) and a total of 107 CNVRs, ranged from 50 to ~500 kb, were detected, which covered 4.90 Mb of polymorphic sequence and corresponded to 0.18% of the total genome length. In particular, we found 81 CNVRs with only gain (duplication), 22 with only loss (deletion), and four CNVRs with both. Furthermore, 8 CNVRs with >1%, 77 with >2.5%, and 22 with >5% frequency, were found. CNVRs having the highest frequency were located on Chr3:120501439-120647330 and Chr23:34673581-35007295, whereas the greatest number of genes was mapped in only one CNVR located on Chr 17:74123863-74393620. A total of 241 genes were included in the identified CNVRs. According to KEGG and DAVID database, most of the genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes, such as immune response, adaptability, and olfactory receptors pathway. Further studies, using different algorithms and validating the CNVs discovered, will be conducted to corroborate these preliminary results on the CNVRs detected. These results will be used for the investigation of genomic changes and features of interest in the Cinisara breed, such as for association with functional or production traits and for biodiversity studies

    Sacral agenesis: a pilot whole exome sequencing and copy number study

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    Background: Caudal regression syndrome (CRS) or sacral agenesis is a rare congenital disorder characterized by a constellation of congenital caudal anomalies affecting the caudal spine and spinal cord, the hindgut, the urogenital system, and the lower limbs. CRS is a complex condition, attributed to an abnormal development of the caudal mesoderm, likely caused by the effect of interacting genetic and environmental factors. A well-known risk factor is maternal type 1 diabetes. Method: Whole exome sequencing and copy number variation (CNV) analyses were conducted on 4 Caucasian trios to identify de novo and inherited rare mutations. Results: In this pilot study, exome sequencing and copy number variation (CNV) analyses implicate a number of candidate genes, including SPTBN5, MORN1, ZNF330, CLTCL1 and PDZD2. De novo mutations were found in SPTBN5, MORN1 and ZNF330 and inherited predicted damaging mutations in PDZD2 (homozygous) and CLTCL1 (compound heterozygous). Importantly, predicted damaging mutations in PTEN (heterozygous), in its direct regulator GLTSCR2 (compound heterozygous) and in VANGL1 (heterozygous) were identified. These genes had previously been linked with the CRS phenotype. Two CNV deletions, one de novo (chr3q13.13) and one homozygous (chr8p23.2), were detected in one of our CRS patients. These deletions overlapped with CNVs previously reported in patients with similar phenotype. Conclusion: Despite the genetic diversity and the complexity of the phenotype, this pilot study identified genetic features common across CRS patients

    Genome-wide copy number variation (CNV) in patients with autoimmune Addison's disease

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    <p>Abstract</p> <p>Background</p> <p>Addison's disease (AD) is caused by an autoimmune destruction of the adrenal cortex. The pathogenesis is multi-factorial, involving genetic components and hitherto unknown environmental factors. The aim of the present study was to investigate if gene dosage in the form of copy number variation (CNV) could add to the repertoire of genetic susceptibility to autoimmune AD.</p> <p>Methods</p> <p>A genome-wide study using the Affymetrix GeneChip<sup>® </sup>Genome-Wide Human SNP Array 6.0 was conducted in 26 patients with AD. CNVs in selected genes were further investigated in a larger material of patients with autoimmune AD (n = 352) and healthy controls (n = 353) by duplex Taqman real-time polymerase chain reaction assays.</p> <p>Results</p> <p>We found that low copy number of <it>UGT2B28 </it>was significantly more frequent in AD patients compared to controls; conversely high copy number of <it>ADAM3A </it>was associated with AD.</p> <p>Conclusions</p> <p>We have identified two novel CNV associations to <it>ADAM3A </it>and <it>UGT2B28 </it>in AD. The mechanism by which this susceptibility is conferred is at present unclear, but may involve steroid inactivation (<it>UGT2B28</it>) and T cell maturation (<it>ADAM3A</it>). Characterization of these proteins may unravel novel information on the pathogenesis of autoimmunity.</p

    CONTRA: copy number analysis for targeted resequencing

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    Motivation: In light of the increasing adoption of targeted resequencing (TR) as a cost-effective strategy to identify disease-causing variants, a robust method for copy number variation (CNV) analysis is needed to maximize the value of this promising technology

    Copy number variations in healthy subjects. Case study: iPSC line CSSi005-A (3544) production from an individual with variation in 15q13.3 chromosome duplicating gene CHRNA7

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    CHRNA7, encoding the neuronal alpha7 nicotinic acetylcholine receptor (a7nAChR), is highly expressed in the brain, particularly in the hippocampus. It is situated in the 15q13.3 chromosome region, frequently associated with a Copy Number Variation (CNV), which causes its duplication or deletion. The clinical significance of CHRNA7 duplications is unknown so far, but there are several research data suggesting that they may be pathogenic, with reduced penetrance. We have produced an iPS cell line from a single healthy donor's fibroblasts carrying a 15q13.3 CNV, including CHRNA7 in order to study the exact role of this CNV during the neurodevelopment

    Performance of four modern whole genome amplification methods for copy number variant detection in single cells

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    Whole genome amplification (WGA) has become an invaluable tool to perform copy number variation (CNV) detection in single, or a limited number of cells. Unfortunately, current WGA methods introduce representation bias that limits the detection of small CNVs. New WGA methods have been introduced that might have the potential to reduce this bias. We compared the performance of PicoPLEX DNA-Seq (Picoseq), DOPlify, REPLI-g and Ampli-1 WGA for aneuploidy screening and copy number analysis using shallow whole genome massively parallel sequencing (MPS), starting from single or a limited number of cells. Although the four WGA methods perform differently, they are all suited for this application

    Copy Number Variation in Forensic Science

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    Copy Number Variation (CNV) refers to duplication or deletion in the DNA sequence. Studying the pattern of these duplications or deletions can add value to forensic and population genetics. These can also be used for the study of genetic diseases and development of personalized medicine. Further research may improve the utilization and benefits of CNV in forensic investigations

    A backward procedure for change-point detection with applications to copy number variation detection

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    Change-point detection regains much attention recently for analyzing array or sequencing data for copy number variation (CNV) detection. In such applications, the true signals are typically very short and buried in the long data sequence, which makes it challenging to identify the variations efficiently and accurately. In this article, we propose a new change-point detection method, a backward procedure, which is not only fast and simple enough to exploit high-dimensional data but also performs very well for detecting short signals. Although motivated by CNV detection, the backward procedure is generally applicable to assorted change-point problems that arise in a variety of scientific applications. It is illustrated by both simulated and real CNV data that the backward detection has clear advantages over other competing methods especially when the true signal is short
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