Panel sequencing for clinically oriented variant screening and copy number detection in 142 untreated multiple myeloma patients.
Ontology highlight
ABSTRACT:
SUBMITTER: Kortuem KM
PROVIDER: S-EPMC4771964 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: A newly recognized type of genetic variation, Copy Number Variation (CNV), is detected in mammalian genomes, e.g. the cattle genome. This form of variation can potentially cause phenotypic variation. Our objective was to determine whether dense SNP (single nucleotide polymorphisms) panels can capture the genetic variation due to a simple bi-allelic CNV, with the prospect of including the effect of such structural variations into genomic predictions. METHODS: A deletion type CNV on bovine chromosome 6 was predicted from its neighboring SNP with a multiple regression model. Our dataset consisted of CNV genotypes of 1,682 cows, along with 100 surrounding SNP genotypes. A prediction model was fitted considering 10 to 100 surrounding SNP and the accuracy obtained directly from the model was confirmed by cross-validation. RESULTS AND CONCLUSIONS: The accuracy of prediction increased with an increasing number of SNP in the model and the predicted accuracies were similar to those obtained by cross-validation. A substantial increase in accuracy was observed when the number of SNP increased from 10 to 50 but thereafter the increase was smaller, reaching the highest accuracy (0.94) with 100 surrounding SNP. Thus, we conclude that the genotype of a deletion type CNV and its putative QTL effect can be predicted with a maximum accuracy of 0.94 from surrounding SNP. This high prediction accuracy suggests that genetic variation due to simple deletion CNV is well captured by dense SNP panels. Since genomic selection relies on the availability of a dense marker panel with markers in close linkage disequilibrium to the QTL in order to predict their genetic values, we also discuss opportunities for genomic selection to predict the effects of CNV by dense SNP panels, when CNV cause variation in quantitative traits.
| S-EPMC3366870 | biostudies-other
Project description:Current high-sensitivity cancer screening methods, largely utilizing correlative biomarkers, suffer from false positive rates that lead to unnecessary medical procedures and debatable public health benefit overall. Detection of circulating tumor DNA (ctDNA), a causal biomarker, has the potential to revolutionize cancer screening. Thus far, the majority of ctDNA studies have focused on detection of tumor-specific point mutations after cancer diagnosis for the purpose of post-treatment surveillance. However, ctDNA point mutation detection methods developed to date likely lack either the scope or analytical sensitivity necessary to be useful for cancer screening, due to the low (<1%) ctDNA fraction derived from early stage tumors. On the other hand, tumor-derived copy number variant (CNV) detection is hypothetically a superior means of ctDNA-based cancer screening for many tumor types, given that, relative to point mutations, each individual tumor CNV contributes a much larger number of ctDNA fragments to the overall pool of circulating free DNA (cfDNA). A small number of studies have demonstrated the potential of ctDNA CNV-based screening in select cancer types. Here we perform an in silico assessment of the potential for ctDNA CNV-based cancer screening across many common cancers, and suggest ctDNA CNV detection shows promise as a broad cancer screening methodology.
| S-EPMC5501586 | biostudies-literature
Project description:BACKGROUND:Recent advances in molecular genetic analysis using next-generation sequencing (NGS) have drastically accelerated the identification of disease-causing gene mutations. Most next-generation sequencing analyses of inherited diseases have mainly focused on single-nucleotide variants and short indels, although, recently, structure variations including copy number variations have come to be considered an important cause of many different diseases. However, only a limited number of tools are available for multiplex PCR-based target genome enrichment. METHODS:In this paper, we reported a simple and efficient copy number variation visualization method for Ion AmpliSeq™ target resequencing data. Unlike the hybridization capture-based target genome enrichment system, Ion AmpliSeq™ reads are multiplex PCR products, and each read generated by the same amplicon is quite uniform in length and position. Based on this feature, the depth of coverage information for each amplicon included in the barcode/amplicon coverage matrix file was used for copy number detection analysis. We also performed copy number analysis to investigate the utility of this method through the use of positive controls and a large Japanese hearing loss cohort. RESULTS:Using this method, we successfully confirmed previously reported copy number loss cases involving the STRC gene and copy number gain in trisomy 21 cases. We also performed copy number analysis of a large Japanese hearing loss cohort (2,475 patients) and identified many gene copy number variants. The most prevalent copy number variation was STRC gene copy number loss, with 129 patients carrying this copy number variation. CONCLUSION:Our copy number visualization method for Ion AmpliSeq™ data can be utilized in efficient copy number analysis for the comparison of a large number of samples. This method is simple and requires only easy calculations using standard spread sheet software.
| S-EPMC6081219 | biostudies-literature
Project description:Chromosomal aberrations are a hallmark of multiple myeloma but their global prognostic impact is largely unknown.We performed a genome-wide analysis of malignant plasma cells from 192 newly diagnosed patients with myeloma using high-density, single-nucleotide polymorphism (SNP) arrays to identify genetic lesions associated with prognosis.Our analyses revealed deletions and amplifications in 98% of patients. Amplifications in 1q and deletions in 1p, 12p, 14q, 16q, and 22q were the most frequent lesions associated with adverse prognosis, whereas recurrent amplifications of chromosomes 5, 9, 11, 15, and 19 conferred a favorable prognosis. Multivariate analysis retained three independent lesions: amp(1q23.3), amp(5q31.3), and del(12p13.31). When adjusted to the established prognostic variables (ie, t(4;14), del(17p), and serum beta(2)-microglobulin [Sbeta(2)M]), del(12p13.31) remained the most powerful independent adverse marker (P < .0001; hazard ratio [HR], 3.17) followed by Sbeta(2)M (P < .0001; HR, 2.78) and the favorable marker amp(5q31.3) (P = .0005; HR, 0.37). Patients with amp(5q31.3) alone and low Sbeta(2)M had an excellent prognosis (5-year overall survival, 87%); conversely, patients with del(12p13.31) alone or amp(5q31.3) and del(12p13.31) and high Sbeta(2)M had a very poor outcome (5-year overall survival, 20%). This prognostic model was validated in an independent validation cohort of 273 patients with myeloma.These findings demonstrate the power and accessibility of molecular karyotyping to predict outcome in myeloma. In addition, integration of expression of genes residing in the lesions of interest revealed putative features of the disease driving short survival.
| S-EPMC2754906 | biostudies-other
Project description:Cerebral palsy (CP) represents a group of non-progressive clinically heterogeneous disorders that are characterized by motor impairment and early age of onset, frequently accompanied by co-morbidities. The cause of CP has historically been attributed to environmental stressors resulting in brain damage. While genetic risk factors are also implicated, guidelines for diagnostic assessment of CP do not recommend for routine genetic testing. Given numerous reports of aetiologic copy number variations (CNVs) in other neurodevelopmental disorders, we used microarrays to genotype a population-based prospective cohort of children with CP and their parents. Here we identify de novo CNVs in 8/115 (7.0%) CP patients (?1% rate in controls). In four children, large chromosomal abnormalities deemed likely pathogenic were found, and they were significantly more likely to have severe neuromotor impairments than those CP subjects without such alterations. Overall, the CNV data would have impacted our diagnosis or classification of CP in 11/115 (9.6%) families.
| S-EPMC4532872 | biostudies-literature
Project description:Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Previous genome-wide association studies had identified single-nucleotide polymorphisms in several genomic regions to be associated with AF. In human genome, copy number variations (CNVs) are known to contribute to disease susceptibility. Using a genome-wide multistage approach to identify AF susceptibility CNVs, we here show a common 4,470-bp diallelic CNV in the first intron of potassium interacting channel 1 gene (KCNIP1) is strongly associated with AF in Taiwanese populations (odds ratio=2.27 for insertion allele; P=6.23 × 10(-24)). KCNIP1 insertion is associated with higher KCNIP1 mRNA expression. KCNIP1-encoded protein potassium interacting channel 1 (KCHIP1) is physically associated with potassium Kv channels and modulates atrial transient outward current in cardiac myocytes. Overexpression of KCNIP1 results in inducible AF in zebrafish. In conclusions, a common CNV in KCNIP1 gene is a genetic predictor of AF risk possibly pointing to a functional pathway.
| S-EPMC4740744 | biostudies-literature
Project description:Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.
| S-EPMC6586881 | biostudies-literature
Project description:Copy number variants (CNVs) are the gain or loss of DNA segments in the genome that can vary in dosage and length. CNVs comprise a large proportion of variation in human genomes and impact health conditions. To detect rare CNV associations, kernel-based methods have been shown to be a powerful tool due to their flexibility in modeling the aggregate CNV effects, their ability to capture effects from different CNV features, and their accommodation of effect heterogeneity. To perform a kernel association test, a CNV locus needs to be defined so that locus-specific effects can be retained during aggregation. However, CNV loci are arbitrarily defined and different locus definitions can lead to different performance depending on the underlying effect patterns. In this work, we develop a new kernel-based test called CONCUR (i.e., copy number profile curve-based association test) that is free from a definition of locus and evaluates CNV-phenotype associations by comparing individuals' copy number profiles across the genomic regions. CONCUR is built on the proposed concepts of "copy number profile curves" to describe the CNV profile of an individual, and the "common area under the curve (cAUC) kernel" to model the multi-feature CNV effects. The proposed method captures the effects of CNV dosage and length, accounts for the numerical nature of copy numbers, and accommodates between- and within-locus etiological heterogeneity without the need to define artificial CNV loci as required in current kernel methods. In a variety of simulation settings, CONCUR shows comparable or improved power over existing approaches. Real data analyses suggest that CONCUR is well powered to detect CNV effects in the Swedish Schizophrenia Study and the Taiwan Biobank.
| S-EPMC7224564 | biostudies-literature
Project description:BACKGROUND:1q21.1 Copy Number Variant (CNV) is associated with a highly variable phenotype ranging from congenital anomalies, learning deficits/intellectual disability (ID), to a normal phenotype. Hence, the clinical significance of this CNV can be difficult to evaluate. Here we described the consequences of the 1q21.1 CNV on genome-wide gene expression and function of selected candidate genes within 1q21.1 using cell lines from clinically well described subjects. METHODS AND RESULTS:Eight subjects from 3 families were included in the study: six with a 1q21.1 deletion and two with a 1q21.1 duplication. High resolution Affymetrix 2.7M array was used to refine the 1q21.1 CNV breakpoints and exclude the presence of secondary CNVs of pathogenic relevance. Whole genome expression profiling, studied in lymphoblast cell lines (LBCs) from 5 subjects, showed enrichment of genes from 1q21.1 in the top 100 genes ranked based on correlation of expression with 1q21.1 copy number. The function of two top genes from 1q21.1, CHD1L/ALC1 and PRKAB2, was studied in detail in LBCs from a deletion and a duplication carrier. CHD1L/ALC1 is an enzyme with a role in chromatin modification and DNA damage response while PRKAB2 is a member of the AMP kinase complex, which senses and maintains systemic and cellular energy balance. The protein levels for CHD1L/ALC1 and PRKAB2 were changed in concordance with their copy number in both LBCs. A defect in chromatin remodeling was documented based on impaired decatenation (chromatid untangling) checkpoint (DCC) in both LBCs. This defect, reproduced by CHD1L/ALC1 siRNA, identifies a new role of CHD1L/ALC1 in DCC. Both LBCs also showed elevated levels of micronuclei following treatment with a Topoisomerase II inhibitor suggesting increased DNA breaks. AMP kinase function, specifically in the deletion containing LBCs, was attenuated. CONCLUSION:Our studies are unique as they show for the first time that the 1q21.1 CNV not only causes changes in the expression of its key integral genes, associated with changes at the protein level, but also results in changes in their known function, in the case of AMPK, and newly identified function such as DCC activation in the case of CHD1L/ALC1. Our results support the use of patient lymphoblasts for dissecting the functional sequelae of genes integral to CNVs in carrier cell lines, ultimately enhancing understanding of biological processes which may contribute to the clinical phenotype.
| S-EPMC3180300 | biostudies-literature
Project description:To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single-base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation-dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT-RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi-ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.
| S-EPMC7877843 | biostudies-literature