A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Rotunno M
PROVIDER: S-EPMC8279039 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:As whole-exome sequencing (WES) and whole-genome sequencing (WGS) move into routine clinical practice, it is timely to review data that might inform the debate regarding secondary findings (SF) and the development of policies that maximize participant benefit.We systematically searched for qualitative and quantitative studies that explored stakeholder views on SF in WES/WGS. Framework analysis was undertaken to identify major themes.Forty-four articles reporting the views of 11,566 stakeholders were included. Stakeholders were broadly supportive of returning "actionable" findings, but definitions of actionability varied. Stakeholder views on SF disclosure exist along a spectrum: potential WES/WGS recipients' views were largely influenced by a sense of rights, whereas views of genomics professionals were informed by a sense of professional responsibility. Experience with genetic illness and testing resulted in greater caution about SF, suggesting that truly informed decisions require an understanding of the implications and limitations of WES/WGS and possible findings.This review suggests that bidirectional interaction during consent might best facilitate informed decision making about SF and that dynamic forms of consent, allowing for changing preferences, should be considered. Research exploring views from wider perspectives and from recipients who have received SF is critical if evidence-based policies are to be achieved.Genet Med 19 3, 283-293.
| S-EPMC5447864 | biostudies-other
Project description:BACKGROUND:Understanding the underlying genetic structure of human populations is of fundamental interest to both biological and social sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation. The most widely used methods for collecting variant information at the DNA-level include whole genome sequencing, which remains costly, and the more economical solution of array-based techniques, as these are capable of simultaneously genotyping a pre-selected set of variable DNA sites in the human genome. The largest publicly accessible set of human genomic sequence data available today originates from exome sequencing that comprises around 1.2% of the whole genome (approximately 30 million base pairs). RESULTS:To unbiasedly compare the effect of SNP selection strategies in population genetic analysis we subsampled the variants of the same highly curated 1 K Genome dataset to mimic genome, exome sequencing and array data in order to eliminate the effect of different chemistry and error profiles of these different approaches. Next we compared the application of the exome dataset to the array-based dataset and to the gold standard whole genome dataset using the same population genetic analysis methods. CONCLUSIONS:Our results draw attention to some of the inherent problems that arise from using pre-selected SNP sets for population genetic analysis. Additionally, we demonstrate that exome sequencing provides a better alternative to the array-based methods for population genetic analysis. In this study, we propose a strategy for unbiased variant collection from exome data and offer a bioinformatics protocol for proper data processing.
| S-EPMC6206721 | biostudies-literature
Project description:Most tumor samples are a heterogeneous mixture of cells, including admixture by normal (non-cancerous) cells and subpopulations of cancerous cells with different complements of somatic aberrations. This intra-tumor heterogeneity complicates the analysis of somatic aberrations in DNA sequencing data from tumor samples.We describe an algorithm called THetA2 that infers the composition of a tumor sample-including not only tumor purity but also the number and content of tumor subpopulations-directly from both whole-genome (WGS) and whole-exome (WXS) high-throughput DNA sequencing data. This algorithm builds on our earlier Tumor Heterogeneity Analysis (THetA) algorithm in several important directions. These include improved ability to analyze highly rearranged genomes using a variety of data types: both WGS sequencing (including low ?7× coverage) and WXS sequencing. We apply our improved THetA2 algorithm to WGS (including low-pass) and WXS sequence data from 18 samples from The Cancer Genome Atlas (TCGA). We find that the improved algorithm is substantially faster and identifies numerous tumor samples containing subclonal populations in the TCGA data, including in one highly rearranged sample for which other tumor purity estimation algorithms were unable to estimate tumor purity.
| S-EPMC4253833 | biostudies-other
Project description:Congenital Zika Syndrome (CZS) is a critical illness with a wide range of severity caused by Zika virus (ZIKV) infection during pregnancy. Life-threatening neurodevelopmental dysfunctions are among the most common phenotypes observed in affected newborns. Risk factors that contribute to susceptibility and response to ZIKV infection may be related to the virus itself, the environment, and maternal genetic background. Nevertheless, the newborn's genetic contribution to the critical illness is still not elucidated. Here, we aimed to identify possible genetic variants as well as relevant biological pathways that might be associated with CZS phenotypes. For this purpose, we performed a whole-exome sequencing in 40 children born to women with confirmed exposure to ZIKV during pregnancy. We investigated the occurrence of rare harmful single-nucleotide variants (SNVs) possibly associated with inborn errors in genes ontologically related to CZS phenotypes. Moreover, an exome-wide association analysis was also performed using a case-control design (29 CZS cases and 11 controls), for both common and rare variants. Five out of the 29 CZS patients harbored known pathogenic variants likely to contribute to mild to severe manifestations observed. Approximately, 30% of affected individuals carried at least one pathogenic or likely pathogenic SNV in genes candidates to play a role in CZS. Our common variant association analysis detected a suggestive protective effect of the rs2076469 in DISP3 gene (p-value: 1.39 x 10-5). The IL12RB2 gene (p-value: 2.18x10-11) also showed an unusual distribution of nonsynonymous rare SNVs in control samples. Finally, genes harboring harmful variants are involved in processes related to CZS phenotypes such as neurological development and immunity. Therefore, both rare and common variations may be likely to contribute as the underlying genetic cause of CZS susceptibility. The variations and pathways identified in this study may also have implications for the development of therapeutic strategies in the future.
| S-EPMC8224898 | biostudies-literature
Project description:As the cost of DNA sequencing decreases, association studies based on whole genome sequencing are now becoming feasible. It is still unclear, however, how much more we could gain from whole genome sequencing compared to exome sequencing, which has been widely used to study a variety of diseases. In this project, we performed a comparison between whole genome sequencing and exome sequencing for family-based association analysis using data from Genetic Analysis Workshop 18. Whole genome sequencing was able to identify several significant hits within intergenic regions. However, the increased cost of multiple testing counteracted the benefits and resulted in a higher false discovery rate. Our results suggest that exome sequencing is a cost-effective way to identify disease-related variants. With the decreasing sequencing cost and accumulating knowledge of the human genome, whole genome sequencing has the potential to identify important variants in regulatory regions typically inaccessible for exome sequencing.
| S-EPMC4143706 | biostudies-literature
Project description:Multiple factors, including host genetics, environmental factors, and Epstein-Barr virus (EBV) infection, contribute to nasopharyngeal carcinoma (NPC) development. To identify genetic susceptibility genes for NPC, a whole-exome sequencing (WES) study was performed in 161 NPC cases and 895 controls of Southern Chinese descent. The gene-based burden test discovered an association between macrophage-stimulating 1 receptor (MST1R) and NPC. We identified 13 independent cases carrying the MST1R pathogenic heterozygous germ-line variants, and 53.8% of these cases were diagnosed with NPC aged at or even younger than 20 y, indicating that MST1R germline variants are relevant to disease early-age onset (EAO) (age of ≤20 y). In total, five MST1R missense variants were found in EAO cases but were rare in controls (EAO vs. control, 17.9% vs. 1.2%, P = 7.94 × 10(-12)). The validation study, including 2,160 cases and 2,433 controls, showed that the MST1R variant c.G917A:p.R306H is highly associated with NPC (odds ratio of 9.0). MST1R is predominantly expressed in the tissue-resident macrophages and is critical for innate immunity that protects organs from tissue damage and inflammation. Importantly, MST1R expression is detected in the ciliated epithelial cells in normal nasopharyngeal mucosa and plays a role in the cilia motility important for host defense. Although no somatic mutation of MST1R was identified in the sporadic NPC tumors, copy number alterations and promoter hypermethylation at MST1R were often observed. Our findings provide new insights into the pathogenesis of NPC by highlighting the involvement of the MST1R-mediated signaling pathways.
| S-EPMC4812767 | biostudies-literature
Project description:We compared whole-exome sequencing (WES) and whole-genome sequencing (WGS) in six unrelated individuals. In the regions targeted by WES capture (81.5% of the consensus coding genome), the mean numbers of single-nucleotide variants (SNVs) and small insertions/deletions (indels) detected per sample were 84,192 and 13,325, respectively, for WES, and 84,968 and 12,702, respectively, for WGS. For both SNVs and indels, the distributions of coverage depth, genotype quality, and minor read ratio were more uniform for WGS than for WES. After filtering, a mean of 74,398 (95.3%) high-quality (HQ) SNVs and 9,033 (70.6%) HQ indels were called by both platforms. A mean of 105 coding HQ SNVs and 32 indels was identified exclusively by WES whereas 692 HQ SNVs and 105 indels were identified exclusively by WGS. We Sanger-sequenced a random selection of these exclusive variants. For SNVs, the proportion of false-positive variants was higher for WES (78%) than for WGS (17%). The estimated mean number of real coding SNVs (656 variants, ?3% of all coding HQ SNVs) identified by WGS and missed by WES was greater than the number of SNVs identified by WES and missed by WGS (26 variants). For indels, the proportions of false-positive variants were similar for WES (44%) and WGS (46%). Finally, WES was not reliable for the detection of copy-number variations, almost all of which extended beyond the targeted regions. Although currently more expensive, WGS is more powerful than WES for detecting potential disease-causing mutations within WES regions, particularly those due to SNVs.
| S-EPMC4418901 | biostudies-literature
Project description:BackgroundGenotypes generated in next generation sequencing studies contain errors which can significantly impact the power to detect signals in common and rare variant association tests. These genotyping errors are not explicitly filtered by the standard GATK Variant Quality Score Recalibration (VQSR) tool and thus remain a source of errors in whole exome sequencing (WES) projects that follow GATK's recommended best practices. Therefore, additional data filtering methods are required to effectively remove these errors before performing association analyses with complex phenotypes. Here we empirically derive thresholds for genotype and variant filters that, when used in conjunction with the VQSR tool, achieve higher data quality than when using VQSR alone.ResultsThe detailed filtering strategies improve the concordance of sequenced genotypes with array genotypes from 99.33% to 99.77%; improve the percent of discordant genotypes removed from 10.5% to 69.5%; and improve the Ti/Tv ratio from 2.63 to 2.75. We also demonstrate that managing batch effects by separating samples based on different target capture and sequencing chemistry protocols results in a final data set containing 40.9% more high-quality variants. In addition, imputation is an important component of WES studies and is used to estimate common variant genotypes to generate additional markers for association analyses. As such, we demonstrate filtering methods for imputed data that improve genotype concordance from 79.3% to 99.8% while removing 99.5% of discordant genotypes.ConclusionsThe described filtering methods are advantageous for large population-based WES studies designed to identify common and rare variation associated with complex diseases. Compared to data processed through standard practices, these strategies result in substantially higher quality data for common and rare association analyses.
| S-EPMC4098776 | biostudies-literature
Project description:Although a standard genome-wide significance level has been accepted for the testing of association between common genetic variants and disease, the era of whole-genome sequencing (WGS) requires a new threshold. The allele frequency spectrum of sequence-identified variants is very different from common variants, and the identified rare genetic variation is usually jointly analyzed in a series of genomic windows or regions. In nearby or overlapping windows, these test statistics will be correlated, and the degree of correlation is likely to depend on the choice of window size, overlap, and the test statistic. Furthermore, multiple analyses may be performed using different windows or test statistics. Here we propose an empirical approach for estimating genome-wide significance thresholds for data arising from WGS studies, and we demonstrate that the empirical threshold can be efficiently estimated by extrapolating from calculations performed on a small genomic region. Because analysis of WGS may need to be repeated with different choices of test statistics or windows, this prediction approach makes it computationally feasible to estimate genome-wide significance thresholds for different analysis choices. Based on UK10K whole-genome sequence data, we derive genome-wide significance thresholds ranging between 2.5 × 10(-8) and 8 × 10(-8) for our analytic choices in window-based testing, and thresholds of 0.6 × 10(-8) -1.5 × 10(-8) for a combined analytic strategy of testing common variants using single-SNP tests together with rare variants analyzed with our sliding-window test strategy.
| S-EPMC4489336 | biostudies-other
Project description:Genomic sequence comparisons between individuals are usually restricted to the analysis of single nucleotide polymorphisms (SNPs). While the interrogation of SNPs is efficient, they are not the only form of divergence between genomes. In this report, we expand the scope of polymorphism detection by investigating the occurrence of double nucleotide polymorphisms (DNPs) and triple nucleotide polymorphisms (TNPs), in which two or three consecutive nucleotides are altered compared to the reference sequence. We have found such DNPs and TNPs throughout two complete genomes and eight exomes. Within exons, these novel polymorphisms are over-represented amongst protein-altering variants; nearly all DNPs and TNPs result in a change in amino acid sequence and, in some cases, two adjacent amino acids are changed. DNPs and TNPs represent a potentially important new source of genetic variation which may underlie human disease and they should be included in future medical genetics studies. As a confirmation of the damaging nature of xNPs, we have identified changes in the exome of a glioblastoma cell line that are important in glioblastoma pathogenesis. We have found a TNP causing a single amino acid change in LAMC2 and a TNP causing a truncation of HUWE1.
| S-EPMC2952858 | biostudies-other