Genomic Variation: Lessons Learned from Whole-Genome CNV Analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Riggs ER
PROVIDER: S-EPMC4129219 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The treatment of major birth defects are key concerns for child health. Hitherto, for the majority of birth defects, the underlying cause remains unknown, likely to be heterogeneous. The implicated mortality and/or reduced fecundity in major birth defects suggest a significant fraction of mutational de novo events among the affected individuals. With the advent of systematic array-based molecular karyotyping, larger cohorts of affected individuals have been screened over the past decade. This review discusses the identification of disease-causing copy-number variations (CNVs) among individuals with different congenital malformations. It highlights the differences in findings depending on the respective congenital malformation. It looks at the differences in findings of CNV analysis in non-isolated complex congenital malformations, associated with central nervous system malformations or intellectual disabilities, compared to isolated single organ-system malformations. We propose that the more complex an organ system is, and the more genes involved during embryonic development, the more likely it is that mutational de novo events, comprising CNVs, will confer to the expression of birth defects of this organ system.
| S-EPMC7663563 | biostudies-literature
Project description:Genetic Analysis Workshop 17 (GAW17) focused on the transition from genome-wide association study designs and methods to the study designs and statistical genetic methods that will be required for the analysis of next-generation sequence data including both common and rare sequence variants. In the 166 contributions to GAW17, a wide variety of statistical methods were applied to simulated traits in population- and family-based samples, and results from these analyses were compared to the known generating model. In general, many of the statistical genetic methods used in the population-based sample identified causal sequence variants (SVs) when the estimated locus-specific heritability, as measured in the population-based sample, was greater than about 0.08. However, SVs with locus-specific heritabilities less than 0.03 were rarely identified consistently. In the family-based samples, many of the methods detected SVs that were rarer than those detected in the population-based sample, but the estimated locus-specific heritabilities for these rare SVs, as measured in the family-based samples, were substantially higher (>0.2) than their corresponding heritabilities in the population-based samples. Substantial inflation of the type I error rate was observed across a wide variety of statistical methods. Although many of the contributions found little inflation in type I error for Q4, a trait with no causal SVs, type I error rates for Q1 and Q2 were well above their nominal levels with the inflation for Q1 being higher than that for Q2. It seems likely that this inflation in type I error is due to correlations among SVs.
| S-EPMC3277851 | biostudies-literature
Project description:Infectious diseases outbreaks are a cause of significant morbidity and mortality among hospitalized patients. Infants admitted to the neonatal intensive care unit (NICU) are particularly vulnerable to infectious complications during hospitalization. Thus, rapid recognition of and response to outbreaks in the NICU is essential. At Rush University Medical Center, whole-genome sequencing (WGS) has been utilized since early 2016 as an adjunctive method for outbreak investigations. The use of WGS and potential lessons learned are illustrated for 3 different NICU outbreak investigations involving methicillin-resistant Staphylococcus aureus (MRSA), group B Streptococcus (GBS), and Serratia marcescens. WGS has contributed to the understanding of the epidemiology of outbreaks in our NICU, and it has also provided further insight in settings of unusual diseases or when lower-resolution typing methods have been inadequate. WGS has emerged as the new gold standard for evaluating strain relatedness. As barriers to implementation are overcome, WGS has the potential to transform outbreak investigation in healthcare settings.
| S-EPMC9495531 | biostudies-literature
Project description:The advent of next-generation sequencing has dramatically decreased the cost for whole-genome sequencing and increased the viability for its application in research and clinical care. The Personal Genome Project (PGP) provides unrestricted access to genomes of individuals and their associated phenotypes. This resource enabled the Critical Assessment of Genome Interpretation (CAGI) to create a community challenge to assess the bioinformatics community's ability to predict traits from whole genomes. In the CAGI PGP challenge, researchers were asked to predict whether an individual had a particular trait or profile based on their whole genome. Several approaches were used to assess submissions, including ROC AUC (area under receiver operating characteristic curve), probability rankings, the number of correct predictions, and statistical significance simulations. Overall, we found that prediction of individual traits is difficult, relying on a strong knowledge of trait frequency within the general population, whereas matching genomes to trait profiles relies heavily upon a small number of common traits including ancestry, blood type, and eye color. When a rare genetic disorder is present, profiles can be matched when one or more pathogenic variants are identified. Prediction accuracy has improved substantially over the last 6 years due to improved methodology and a better understanding of features.
| S-EPMC5645203 | biostudies-literature
Project description:Current genetic studies of monogenic and complex bone diseases have broadened our understanding of disease pathophysiology, highlighting the need for medical interventions and treatments tailored to the characteristics of patients. As genomic research progresses, novel insights into the molecular mechanisms are starting to provide support to clinical decision-making; now offering ample opportunities for disease screening, diagnosis, prognosis and treatment. Drug targets holding mechanisms with genetic support are more likely to be successful. Therefore, implementing genetic information to the drug development process and a molecular redefinition of skeletal disease can help overcoming current shortcomings in pharmaceutical research, including failed attempts and appalling costs. This review summarizes the achievements of genetic studies in the bone field and their application to clinical care, illustrating the imminent advent of the genomic medicine era.
| S-EPMC7581702 | biostudies-literature
Project description:Models of thoracic irradiation have been developed as clinicians and scientists have attempted to decipher the events that led up to the pulmonary toxicity seen in human subjects following radiation treatment. The most common model is that of whole thorax irradiation (WTI), applied in a single dose. Mice, particularly the C57BL/6J strain, has been frequently used in these investigations, and has greatly informed our current understanding of the initiation and progression of radiation-induced lung injury (RILI). In this review, we highlight the sequential progression and dynamic nature of RILI, focusing primarily on the vast array of information that has been gleaned from the murine model. Ample evidence indicates a wide array of biological responses that can be seen following irradiation, including DNA damage, oxidative stress, cellular senescence and inflammation, all triggered by the initial exposure to ionizing radiation (IR) and heterogeneously maintained throughout the temporal progression of injury, which manifests as acute pneumonitis and later fibrosis. It appears that the early responses of specific cell types may promote further injury, disrupting the microenvironment and preventing a return to homeostasis, although the exact mechanisms driving these responses remains somewhat unclear. Attempts to either prevent or treat RILI in preclinical models have shown some success by targeting these disparate radiobiological processes. As our understanding of the dynamic cellular responses to radiation improves through the use of such models, so does the likelihood of preventing or treating RILI.
| S-EPMC6483900 | biostudies-literature
Project description:OBJECTIVE:To summarize lessons learned while analyzing the costs of integrating whole genome sequencing into the care of cardiology and primary care patients in the MedSeq Project by conducting the first randomized controlled trial of whole genome sequencing in general and specialty medicine. METHODS:Case study that describes key methodological and data challenges that were encountered or are likely to emerge in future work, describes the pros and cons of approaches considered by the study team, and summarizes the solutions that were implemented. RESULTS:Major methodological challenges included defining whole genome sequencing, structuring an appropriate comparator, measuring downstream costs, and examining clinical outcomes. Discussions about solutions addressed conceptual and practical issues that arose because of definitions and analyses around the cost of genomic sequencing in trial-based studies. CONCLUSIONS:The MedSeq Project provides an instructive example of how to conduct a cost analysis of whole genome sequencing that feasibly incorporates best practices while being sensitive to the varied applications and diversity of results it may produce. Findings provide guidance for researchers to consider when conducting or analyzing economic analyses of whole genome sequencing and other next-generation sequencing tests, particularly regarding costs.
| S-EPMC6444358 | biostudies-literature
Project description: Not available
| S-EPMC9246459 | biostudies-literature
Project description:Copy number variants (CNVs) constitute an important class of genetic variants in human genome and are shown to be associated with complex diseases. Whole-genome sequencing provides an unbiased way of identifying all the CNVs that an individual carries. In this paper, we consider parametric modeling of the read depth (RD) data from whole-genome sequencing with the aim of identifying the CNVs, including both Poisson and negative-binomial modeling of such count data. We propose a unified approach of using a mean-matching variance stabilizing transformation to turn the relatively complicated problem of sparse segment identification for count data into a sparse segment identification problem for a sequence of Gaussian data. We apply the optimal sparse segment identification procedure to the transformed data in order to identify the CNV segments. This provides a computationally efficient approach for RD-based CNV identification. Simulation results show that this approach often results in a small number of false identifications of the CNVs and has similar or better performances in identifying the true CNVs when compared with other RD-based approaches. We demonstrate the methods using the trio data from the 1000 Genomes Project.
| S-EPMC4059462 | biostudies-literature
Project description:BACKGROUND: Hereditary non-polyposis colorectal cancer (HNPCC)/Lynch syndrome (LS) is a cancer syndrome characterised by early-onset epithelial cancers, especially colorectal cancer (CRC) and endometrial cancer. The aim of the current study was to use SNP-array technology to identify genomic aberrations which could contribute to the increased risk of cancer in HNPCC/LS patients. METHODS: Individuals diagnosed with HNPCC/LS (100) and healthy controls (384) were genotyped using the Illumina Human610-Quad SNP-arrays. Copy number variation (CNV) calling and association analyses were performed using Nexus software, with significant results validated using QuantiSNP. TaqMan Copy-Number assays were used for verification of CNVs showing significant association with HNPCC/LS identified by both software programs. RESULTS: We detected copy number (CN) gains associated with HNPCC/LS status on chromosome 7q11.21 (28% cases and 0% controls, Nexus; p =3.60E-20 and QuantiSNP; p < 1.00E-16) and 16p11.2 (46% in cases, while a CN loss was observed in 23% of controls, Nexus; p = 4.93E-21 and QuantiSNP; p = 5.00E-06) via in silico analyses. TaqMan Copy-Number assay was used for validation of CNVs showing significant association with HNPCC/LS. In addition, CNV burden (total CNV length, average CNV length and number of observed CNV events) was significantly greater in cases compared to controls. CONCLUSION: A greater CNV burden was identified in HNPCC/LS cases compared to controls supporting the notion of higher genomic instability in these patients. One intergenic locus on chromosome 7q11.21 is possibly associated with HNPCC/LS and deserves further investigation. The results from this study highlight the complexities of fluorescent based CNV analyses. The inefficiency of both CNV detection methods to reproducibly detect observed CNVs demonstrates the need for sequence data to be considered alongside intensity data to avoid false positive results.
| S-EPMC3626775 | biostudies-literature