NPC genome-wide human SNP array data access commitee
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ABSTRACT:
PROVIDER: EGAC00001002560 | EGA |
REPOSITORIES: EGA
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Project description:Data Access Committee EGAC00001002581
| EGAC00001002581 | EGA
Project description:nasopharyngeal carcinoma genome-wide human SNP array data for 4083 NPC cases and 4811 controls
| EGAD00010002296 | EGA
Project description:nasopharyngeal carcinoma genome-wide human SNP array data for 423 NPC cases and 573 controls
| EGAD00010002298 | EGA
Project description:As high-throughput genetic marker screening systems are essential for a range of genetics studies and plant breeding applications, the International RosBREED SNP Consortium (IRSC) has utilized the Illumina Infinium® II system to develop a medium- to high-throughput SNP screening tool for genome-wide evaluation of allelic variation in apple (Malus×domestica) breeding germplasm. For genome-wide SNP discovery, 27 apple cultivars were chosen to represent worldwide breeding germplasm and re-sequenced at low coverage with the Illumina Genome Analyzer II. Following alignment of these sequences to the whole genome sequence of 'Golden Delicious', SNPs were identified using SoapSNP. A total of 2,113,120 SNPs were detected, corresponding to one SNP to every 288 bp of the genome. The Illumina GoldenGate® assay was then used to validate a subset of 144 SNPs with a range of characteristics, using a set of 160 apple accessions. This validation assay enabled fine-tuning of the final subset of SNPs for the Illumina Infinium® II system. The set of stringent filtering criteria developed allowed choice of a set of SNPs that not only exhibited an even distribution across the apple genome and a range of minor allele frequencies to ensure utility across germplasm, but also were located in putative exonic regions to maximize genotyping success rate. A total of 7867 apple SNPs was established for the IRSC apple 8K SNP array v1, of which 5554 were polymorphic after evaluation in segregating families and a germplasm collection. This publicly available genomics resource will provide an unprecedented resolution of SNP haplotypes, which will enable marker-locus-trait association discovery, description of the genetic architecture of quantitative traits, investigation of genetic variation (neutral and functional), and genomic selection in apple.
| S-EPMC3283661 | biostudies-literature
Project description:The multispecies coalescent has provided important progress for evolutionary inferences, including increasing the statistical rigor and objectivity of comparisons among competing species delimitation models. However, Bayesian species delimitation methods typically require brute force integration over gene trees via Markov chain Monte Carlo (MCMC), which introduces a large computation burden and precludes their application to genomic-scale data. Here we combine a recently introduced dynamic programming algorithm for estimating species trees that bypasses MCMC integration over gene trees with sophisticated methods for estimating marginal likelihoods, needed for Bayesian model selection, to provide a rigorous and computationally tractable technique for genome-wide species delimitation. We provide a critical yet simple correction that brings the likelihoods of different species trees, and more importantly their corresponding marginal likelihoods, to the same common denominator, which enables direct and accurate comparisons of competing species delimitation models using Bayes factors. We test this approach, which we call Bayes factor delimitation (*with genomic data; BFD*), using common species delimitation scenarios with computer simulations. Varying the numbers of loci and the number of samples suggest that the approach can distinguish the true model even with few loci and limited samples per species. Misspecification of the prior for population size ? has little impact on support for the true model. We apply the approach to West African forest geckos (Hemidactylus fasciatus complex) using genome-wide SNP data. This new Bayesian method for species delimitation builds on a growing trend for objective species delimitation methods with explicit model assumptions that are easily tested. [Bayes factor; model testing; phylogeography; RADseq; simulation; speciation.].
| S-EPMC4072903 | biostudies-literature
Project description:BACKGROUND: The recent advent of genome-wide molecular platforms has facilitated our understanding of the human genome and disease, particularly copy number aberrations. We performed genome-wide single nucleotide polymorphism-array in hereditary coagulopathy to delineate the extent of copy number mutations and to assess its diagnostic utility. DESIGN AND METHODS: The study subjects were 17 patients with hereditary coagulopathy from copy number mutations in coagulation genes detected by multiple ligation-dependent probe amplification. Eleven had hemophilia (7 hemophilia A and 4 hemophilia B) and 6 had thrombophilia (4 protein S deficiency and 2 antithrombin deficiency). Single nucleotide polymorphism-array experiments were performed using Affymetrix Genome-Wide Human SNP arrays 6.0. RESULTS: Copy number mutations were identified by single nucleotide polymorphism-array in 9 patients, which ranged in length from 51 Kb to 6,288 Kb harboring 2 to ~160 genes. Single nucleotide polymorphism-array showed a neutral copy number status in 8 patients including 7 with either a single-exon copy number mutation or duplication mutations of PROS1. CONCLUSIONS: This study revealed unexpectedly heterogeneous lengths of copy number mutations underlying human coagulopathy. Single nucleotide polymorphism-array had limitations in detecting copy number mutations involving a single exon or those of a gene with homologous sequences such as a pseudogene.
| S-EPMC3269493 | biostudies-literature
Project description:Vibrio vulnificus is an aquatic bacterium and an important human pathogen. Strains of V. vulnificus are classified into three different biotypes. The newly emerged biotype 3 has been found to be clonal and restricted to Israel. In the family Vibrionaceae, horizontal gene transfer is the main mechanism responsible for the emergence of new pathogen groups. To better understand the evolution of the bacterium, and in particular to trace the evolution of biotype 3, we performed genome-wide SNP genotyping of 254 clinical and environmental V. vulnificus isolates with worldwide distribution recovered over a 30-year period, representing all phylogeny groups. A custom single-nucleotide polymorphism (SNP) array implemented on the Illumina GoldenGate platform was developed based on 570 SNPs randomly distributed throughout the genome. In general, the genotyping results divided the V. vulnificus species into three main phylogenetic lineages and an additional subgroup, clade B, consisting of environmental and clinical isolates from Israel. Data analysis suggested that 69% of biotype 3 SNPs are similar to SNPs from clade B, indicating that biotype 3 and clade B have a common ancestor. The rest of the biotype 3 SNPs were scattered along the biotype 3 genome, probably representing multiple chromosomal segments that may have been horizontally inserted into the clade B recipient core genome from other phylogroups or bacterial species sharing the same ecological niche. Results emphasize the continuous evolution of V. vulnificus and support the emergence of new pathogenic groups within this species as a recurrent phenomenon. Our findings contribute to a broader understanding of the evolution of this human pathogen.
| S-EPMC4272304 | biostudies-literature
Project description:Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels (Affymetrix) and 1.3 million genome-wide SNP markers (Illumina) were assayed for all 277 human LCLs. MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. 27 loci, each containing at least 2 SNPs within 50kb with p-values <10-4, were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC with p<10-3. The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes that were also associated with radiation AUC (p<10-3). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52 and DEPDC1B each significantly altered radiation sensitivity in at least 2 cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.
2010-09-25 | GSE24260 | GEO
Project description:Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels (Affymetrix) and 1.3 million genome-wide SNP markers (Illumina) were assayed for all 277 human LCLs. MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. 27 loci, each containing at least 2 SNPs within 50kb with p-values <10-4, were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC with p<10-3. The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes that were also associated with radiation AUC (p<10-3). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52 and DEPDC1B each significantly altered radiation sensitivity in at least 2 cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.
2010-09-25 | GSE24245 | GEO
Project description:Radiation therapy is used to treat half of all cancer patients. Response to radiation therapy varies widely among patients. Therefore, we performed a genome-wide association study (GWAS) to identify biomarkers to help predict radiation response using 277 ethnically defined human lymphoblastoid cell lines (LCLs). Basal gene expression levels (Affymetrix) and 1.3 million genome-wide SNP markers (Illumina) were assayed for all 277 human LCLs. MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assays for radiation cytotoxicity were also performed to obtain area under the curve (AUC) as a radiation response phenotype for use in the association studies. Functional validation of candidate genes, selected from an integrated analysis that used SNP, expression and AUC data, was performed with multiple cancer cell lines using specific siRNA knockdown, followed by MTS and colony-forming assays. 27 loci, each containing at least 2 SNPs within 50kb with p-values <10-4, were associated with radiation AUC. 270 expression probe sets were associated with radiation AUC with p<10-3. The integrated analysis identified 50 SNPs in 14 of the 27 loci that were associated with both AUC and the expression of 39 genes that were also associated with radiation AUC (p<10-3). Functional validation using siRNA knockdown in multiple tumor cell lines showed that C13orf34, MAD2L1, PLK4, TPD52 and DEPDC1B each significantly altered radiation sensitivity in at least 2 cancer cell lines. Studies performed with LCLs can help to identify novel biomarkers that might contribute to variation in response to radiation therapy and enhance our understanding of mechanisms underlying that variation.
2010-09-25 | GSE24274 | GEO