Characteristics of Highly Polymorphic Segmental Copy-Number Variations Observed in Japanese by BAC-Array-CGH

Segmental copy-number variations (CNVs) may contribute to genetic variation in humans. Reports of the existence and characteristics of CNVs in a large Japanese cohort are quite limited. We report the data from a large Japanese population. We conducted population screening for 213 unrelated Japanese individuals using comparative genomic hybridization based on a bacterial artificial chromosome microarray (BAC-aCGH). We summarize the data by focusing on highly polymorphic CNVs in ≥5.0% of the individual, since they may be informative for demonstrating the relationships between genotypes and their phenotypes. We found a total of 680 CNVs at 16 different BAC-regions in the genome. The majority of the polymorphic CNVs presented on BAC-clones that overlapped with regions of segmental duplication, and the majority of the polymorphic CNVs observed in this population had been previously reported in other publications. Some of the CNVs contained genes which might be related to phenotypic heterogeneity among individuals.

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Copy-Number Variations Observed in a Japanese Population by BAC Array CGH: Summary of Relatively Rare CNVs

Journal of Biomedicine and Biotechnology ◽

10.1155/2012/789024 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10

Author(s):

Yasunari Satoh ◽

Keiko Sasaki ◽

Yuko Shimoichi ◽

Keiko Sugita ◽

Hiroaki Katayama ◽

...

Keyword(s):

Copy Number ◽

Rare Variants ◽

Artificial Chromosome ◽

Copy Number Variations ◽

Unrelated Individual ◽

Comparative Genomic ◽

Common Disease ◽

Rare Cnvs ◽

Japanese Cohort ◽

Study Population

Copy-number variations (CNVs) may contribute to genetic variation in humans. Reports regarding existence and characteristics of CNVs in a large apparently healthy Japanese cohort are quite limited. We report the data from a screening of 213 unrelated Japanese individuals using comparative genomic hybridization based on a bacterial artificial chromosome microarray (BAC aCGH). In a previous paper, we summarized the data by focusing on highly polymorphic CNVs (in ≥5.0 % of the individuals). However, rare variations have recently received attention from scientists who espouse a hypothesis called “common disease and rare variants.” Here, we report CNVs identified in fewer than 10 individuals in our study population. We found a total of 126 CNVs at 52 different BAC regions in the genome. The CNVs observed at 27 of the 52 BAC-regions were found in only one unrelated individual. The majority of CNVs found in this study were not identified in the Japanese who were examined in the other studies. Family studies were conducted, and the results demonstrated that the CNVs were inherited from one parent in the families.

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Identification of Copy Number Variation by Array-CGH in Portuguese Children and Adolescents Diagnosed with Autism Spectrum Disorders

Neuropediatrics ◽

10.1055/s-0039-1694797 ◽

2019 ◽

Vol 50 (06) ◽

pp. 367-377

Author(s):

S. Monteiro ◽

J. Pinto ◽

A. Mira Coelho ◽

M. Leão ◽

S. Dória

Keyword(s):

Autism Spectrum Disorders ◽

Copy Number ◽

Array Cgh ◽

Chromosomal Abnormalities ◽

Daily Practice ◽

Autism Spectrum ◽

Copy Number Variations ◽

Comparative Genomic ◽

Uncertain Significance ◽

Spectrum Disorders

Background Autism spectrum disorders (ASD) affect many children with an estimated prevalence of 1%. Array-comparative genomic hybridization (CGH) offers significant sensitivity for the identification of submicroscopic chromosomal abnormalities and it is one of the most used techniques in daily practice. The main objective of this study was to describe the usefulness of array-CGH in the etiologic diagnosis of ASD. Methods Two-hundred fifty-three patients admitted to a neurogenetic outpatient clinic and diagnosed with ASD were selected for array-CGH (4 × 180K microarrays). Public databases were used for classification in accordance with the American College of Medical Genetics Standards and Guidelines. Results About 3.56% (9/253) of copy number variations (CNVs) were classified as pathogenic. When likely pathogenic CNVs were considered, the rate increased to 11.46% (29/253). Some CNVs apparently not correlated to the ASD were also found. Considering a phenotype–genotype correlation, the patients were divided in two groups. One group according to previous literature includes all the CNVs related to ASDs (23 CNVs present in 22 children) and another with those apparently not related to ASD (10 CNVs present in 7 children). In 18 patients, a next-generation sequencing (NGS) panel were performed. From these, one pathogenic and 16 uncertain significance variants were identified. Conclusion The results of our study are in accordance with the literature, highlighting the relevance of array-CGH in the genetic of diagnosis of ASD population, namely when associated with other features. Our study also reinforces the need for complementarity between array-CGH and NGS panels or whole exome sequencing in the etiological diagnosis of ASD.

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DETECTING AND ANALYZING COPY NUMBER ALTERNATIONS IN ARRAY-BASED CGH DATA

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237216500447 ◽

2016 ◽

Vol 28 (06) ◽

pp. 1650044 ◽

Cited By ~ 2

Author(s):

Mariam A. Sheha ◽

Mai S. Mabrouk ◽

Mahmoud Elhefnawi

Keyword(s):

Copy Number ◽

Genomic Dna ◽

Array Cgh ◽

Artificial Chromosome ◽

Gaussian Mixture ◽

Comparative Genomic ◽

Intensity Ratios ◽

Dna Copy Number Alterations ◽

Copy Number Changes ◽

Tissue Specimens

Copy number changes or alterations are a form of genetic variation in the human genome. Genomic DNA copy number alterations (CNAs) are associated with the development and progression of cancers. Array-based comparative genomic hybridization (a-CGH) is a technique used to identify copy number changes in genomic DNA. It yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of automated statistics algorithms for learning about the genomic alterations from array CGH data. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. For this purpose the proposed study introduces three different approaches; Circular binary segmentation, Bayesian approach, relying on the hidden Markov model and effective Gaussian mixture (GM) clustering for the analysis of array CGH profiles. Publicly available data on pancreatic adenocarcinoma and Coriell cell line bacterial artificial chromosome (BAC) array were used for the analysis to illustrate the reliability and success of the techniques.

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Genomic imbalances detected through array CGH in fetuses with holoprosencephaly

Arquivos de Neuro-Psiquiatria ◽

10.1590/s0004-282x2011000100002 ◽

2011 ◽

Vol 69 (1) ◽

pp. 3-8 ◽

Cited By ~ 2

Author(s):

Isabela Nelly Machado ◽

Juliana Karina Heinrich ◽

Ricardo Barini

Keyword(s):

Copy Number ◽

Array Cgh ◽

Copy Number Variations ◽

Comparative Genomic ◽

Molecular Technique ◽

Whole Genome ◽

Genomic Imbalances ◽

Whole Genome Microarray ◽

Gains And Losses

OBJECTIVE: Holoprosencephaly (HPE) is heterogeneous in pathogenesis, integrating genetic susceptibility with the influence of environmental factors. Submicroscopic aberrations may contribute to the etiology of HPE. Our aim was to report the molecular analysis of 4 fetuses with HPE and normal metaphase karyotype. METHOD: A whole genome BAC-array based Comparative Genomic Hybridization (array CGH) was carried out in fetal blood samples. All potential cytogenetic alterations detected on the arrays were matched against the known copy number variations databases. RESULTS: The array CGH analysis showed copy number gains and losses in all cases. We found a recurrent deletion in 15q14 (clone RP11-23J11) and in 15q22 (clone RP11-537k8) in 2 out 4 cases analyzed. We also observed submicroscopic gain in 6p21 in 3 out of 4 fetuses in nearby clones. All these regions were tested in known databases and no copy number variations have been described for them. CONCLUSION: This is the first report of molecular characterization through a whole genome microarray CGH of fetuses with HPE. Our results may contribute to verify the effectiveness and applicability of the molecular technique of array CGH for prenatal diagnosis purposes, and contributing to the knowledge of the submicroscopic genomic instability characterization of HPE fetuses.

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Array-based comparative genomic hybridization (ARRAY-CGH) in analysis of chromosomalaberrations and CNV in blighted ovum pregnancies

Journal of obstetrics and women s diseases ◽

10.17816/jowd622117-125 ◽

2013 ◽

Vol 62 (2) ◽

pp. 117-125 ◽

Cited By ~ 2

Author(s):

Igor Nikolayevich Lebedev ◽

Anna Aleksandrovna Kashevarova ◽

Nikolay Alekseyevich Skryabin ◽

Tatyana Vladimirovna Nikitina ◽

Mariya Yevgenyevna Lopatkina ◽

...

Keyword(s):

Clinical Practice ◽

Copy Number ◽

Array Cgh ◽

Copy Number Variations ◽

Molecular Karyotyping ◽

Comparative Genomic ◽

Comparative Genomic Hybridization Array ◽

Molecular Cytogenetic ◽

Clinical Cytogenetics ◽

Blighted Ovum

Application of modern molecular cytogenetic technologies in research and clinical practice provides unprecedented possibilities for high resolution molecular karyotyping in different areas of clinical cytogenetics. In this study the oligonucleotide-based array-CGH data about unbalanced chromosomal aberrations and copy number variations (CNV) in blighted ovum pregnancies are presented. Analysis of genes content of involved chromosomal regions was done. Scopes, perspectives and limitations of aCGH application into analysis of early pregnancy losses are discussed.

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High-resolution genome-wide array-CGH reveals copy number variations associated with premature ovarian failure

Placenta ◽

10.1016/j.placenta.2011.07.029 ◽

2011 ◽

Vol 32 ◽

pp. S282

Author(s):

Paola Scaruffi ◽

Sara Stigliani ◽

Annamaria Jane Nicoletti ◽

Pier Luigi Venturini ◽

Gian Paolo Tonini ◽

...

Keyword(s):

High Resolution ◽

Premature Ovarian Failure ◽

Copy Number ◽

Array Cgh ◽

Copy Number Variations ◽

Ovarian Failure ◽

Genome Wide

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PATH-39. INTEGRATED MOLECULAR-MORPHOLOGICAL MENINGIOMA CLASSIFICATION: A MULTICENTER RETROSPECTIVE ANALYSIS, RETRO- AND PROSPECTIVELY VALIDATED

Neuro-Oncology ◽

10.1093/neuonc/noab196.491 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi123-vi124

Author(s):

Sybren Maas ◽

Damian Stichel ◽

Thomas Hielscher ◽

Philipp Sievers ◽

Anna Berghoff ◽

...

Keyword(s):

Dna Methylation ◽

Copy Number ◽

Retrospective Cohort ◽

Clinical Decision Making ◽

Clinical Decision ◽

Molecular Data ◽

Copy Number Variations ◽

Who Grade ◽

Risk Of Progression ◽

The Individual

Abstract PURPOSE Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from cases with benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for the individual patient is of pivotal importance in clinical management. However, only biomarkers for highly aggressive tumors are established at present (CDKN2A/B and TERT), while no molecularly-based stratification exists for the broad spectrum of low- and intermediate-risk meningioma patients. PATIENTS AND METHODS DNA methylation data and copy-number information were generated for 3,031 meningiomas of 2,868 individual patients, with mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNV), mutations and WHO grading were comparatively analyzed. Prediction power for outcome of these parameters was assessed in an initial retrospective cohort of 514 patients, and validated on a retrospective cohort of 184, and on a prospective cohort of 287 multi-center cases, respectively. RESULTS Both CNV and methylation family- (MF)-based subgrouping independently resulted in an increase in prediction accuracy of risk of recurrence compared to the WHO classification (c-indexes WHO 2016, CNV, and MF 0.699, 0.706 and 0.721, respectively). Merging all independently powerful risk stratification approaches into an integrated molecular-morphological score resulted in a further, substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference p=0.005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (HR 4.56 [2.97;7.00], 4.34 [2.48;7.57] and 3.34 [1.28; 8.72] for discovery, retrospective, and prospective validation cohort, respectively). CONCLUSIONS Merging these layers of histological and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision-making for meningioma patients on the basis of robust outcome prediction.

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Multiplex ligation-dependent probe amplification – a short overview

Revista Romana de Medicina de Laborator ◽

10.2478/rrlm-2020-0016 ◽

2020 ◽

Vol 28 (2) ◽

pp. 123-131

Author(s):

Valeriu Moldovan ◽

Elena Moldovan

Keyword(s):

Copy Number ◽

Genetic Disorders ◽

Cost Effective ◽

Copy Number Variations ◽

Comparative Genomic ◽

Gene Deletions ◽

Conventional Cytogenetic Analysis ◽

Main Technique ◽

Cost Effective Technique ◽

Dependent Probe

AbstractMultiplex Ligation-dependent Probe Amplification is a technique proposed for the detection of deletions or duplications that may lead to copy number variations in genomic DNA, mainly due to its higher resolution, and shorter overall diagnosis time, when compared with techniques traditionally used, namely karyotyping, fluorescence in situ hybridization, and array comparative genomic hybridization. Multiplex Ligation-dependent Probe Amplification is a fast (about 2 days), useful and cost-effective technique, being suitable for the diagnosis of hereditary conditions caused by complete or partial gene deletions or duplications, as these conditions are either more difficult or impossible to be diagnosed by other techniques, such as PCR, Real-Time PCR, or sequencing (Sanger or Next Generation). Due to its numerous advantages over conventional cytogenetic analysis techniques, Multiplex Ligation-dependent Probe Amplification could be used in the near future as the main technique for the molecular investigation of genetic conditions caused by copy number variations, in both rare and complex genetic disorders.

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Construction and characterization of bacterial artificial chromosome library of black-handed spider monkey (Ateles geoffroyi)

Genome ◽

10.1139/g03-122 ◽

2004 ◽

Vol 47 (2) ◽

pp. 239-245 ◽

Cited By ~ 4

Author(s):

Yaping Qian ◽

Li Jin ◽

Bing Su

Keyword(s):

Bacterial Artificial Chromosome ◽

Large Scale ◽

Bac Library ◽

Artificial Chromosome ◽

Spider Monkey ◽

Ateles Geoffroyi ◽

Comparative Genomic ◽

Average Insert Size ◽

Bac Clones ◽

Genomic Study

The large-insert genomic DNA library is a critical resource for genome-wide genetic dissection of target species. We constructed a high-redundancy bacterial artificial chromosome (BAC) library of a New World monkey species, the black-handed spider monkey (Ateles geoffroyi). A total of 193 152 BAC clones were generated in this library. The average insert size of the BAC clones was estimated to be 184.6 kb with the small inserts (50-100 kb) accounting for less than 3% and the non-recombinant clones only 1.2%. Assuming a similar genome size with humans, the spider monkey BAC library has about 11× genome coverage. In addition, by end sequencing of randomly selected BAC clones, we generated 367 sequence tags for the library. When blasted against human genome, they showed a good correlation between the number of hit clones and the size of the chromosomes, an indication of unbiased chromosomal distribution of the library. This black-handed spider monkey BAC library would serve as a valuable resource in comparative genomic study and large-scale genome sequencing of nonhuman primates.Key words: black-handed spider monkeys, Ateles geoffroyi, BAC library.

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Bayesian Disease Classification Using Copy Number Data

Cancer Informatics ◽

10.4137/cin.s13785 ◽

2014 ◽

Vol 13s2 ◽

pp. CIN.S13785 ◽

Cited By ~ 1

Author(s):

Subharup Guha ◽

Yuan Ji ◽

Veerabhadran Baladandayuthapani

Keyword(s):

Copy Number ◽

Copy Number Variations ◽

Disease Classification ◽

Classification Model ◽

Basic Knowledge ◽

Comparative Genomic ◽

Breast Cancer Dataset ◽

Disease Category ◽

Cancer Dataset ◽

Disease States

DNA copy number variations (CNVs) have been shown to be associated with cancer development and progression. The detection of these CNVs has the potential to impact the basic knowledge and treatment of many types of cancers, and can play a role in the discovery and development of molecular-based personalized cancer therapies. One of the most common types of high-resolution chromosomal microarrays is array-based comparative genomic hybridization (aCGH) methods that assay DNA CNVs across the whole genomic landscape in a single experiment. In this article we propose methods to use aCGH profiles to predict disease states. We employ a Bayesian classification model and treat disease states as outcome, and aCGH profiles as covariates in order to identify significant regions of the genome associated with disease subclasses. We propose a principled two-stage method where we first make inferences on the underlying copy number states associated with the aCGH emissions based on hidden Markov model (HMM) formulations to account for serial dependencies in neighboring probes. Subsequently, we infer associations with disease outcomes, conditional on the copy number states, using Bayesian linear variable selection procedures. The selected probes and their effects are parameters that are useful for predicting the disease categories of any additional individuals on the basis of their aCGH profiles. Using simulated datasets, we investigate the method's accuracy in detecting disease category. Our methodology is motivated by and applied to a breast cancer dataset consisting of aCGH profiles assayed on patients from multiple disease subtypes.

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