Project description:Genomic DNA was extracted from human islets using Dneasy Blood & Tissue Kit (QIAGEN) with RNase A treatment. 200-500ng DNA was genotyped using InfiniumOmni2-5-8v Genotyping BeadChips (Illumina).DNA was isolated from human islet cells from various donors. DNA was genotyped using Illumina Infinium whole-genome genotyping array. Genotypes were called with GenomeStudio (v.2.0.4) using default settings. Genotypes that passed quality filters (missing<0.05, minor allele frequency (MAF>0.01), non-ambiguous alleles defined by AT/GC variants with MAF>40%) were exported.
Project description:Data from the VLA lyssavirus genotyping microarray. The array platform for this data is GEO accession GPL8066, and consists of 624 oligos representing two viral families. The data set itself consists of 14 arrays, 7 hybridised with RNA from mice brains infected with 7 genotypes of lyssaviruses, 1 hybridised with RNA from normal mouse brain, and 6 hybridised with RNA from coded samples consisting of infected mouse brains or control mouse brains. Keywords: Lyssavirus genotyping microarray
Project description:High density genotyping of 7 affected and 3 unaffected family members was performed using the Illumina Omni2.5-8 v1.3 BeadChip SNP.
Project description:Genome-wide SNP genotyping array can genotyped SNP highthroughly. It can be used in many aspects, such as phylogeny relationships, genome-wide association studies, copy number identification.
Project description:Genotyping arrays are tools for high throughput genotyping, which is required in genome-wide association studies (GWAS). Since the first cucumber genome draft was reported, genetic maps were constructed mainly based on simple-sequence repeats (SSRs) or on combinations of SSRs and other sequence-related amplified polymorphism (SRAP). In this study we developed the first cucumber genotyping array which consisted of 32,864 single nucleotide polymorphisms (SNPs). These markers cover the cucumber genome every 2.1Kb and have parents/F1 hybridizations as a training set. The training set was validated with Fludigm technology and had 98% concordance. The application of the genotyping array was illustrated by constructed a genetic map of 600 cM in length based on recombinant inbred lines (RIL) population of a 9930XGy14 cross of which compromise of 11564 SNPs. The markers collinearity between the genetic map and genome references of the two parents estimated as R2=0.97. Moreover, this comparison supports a translocation in the beginning of chromosome 5 that occurred in the lineage of 9930 and Gy14 as well as local variation in the recombination rate. We also used the array to investigate the local allele frequencies along the cucumber genome and found specific region with segregation distortions. We believe that the genotyping array together with the training set would be a powerful tool in applications such as quantitative-trait loci (QTL) analysis and GWAS.
Project description:Low-pass sequencing (sequencing a genome to an average depth less than 1× coverage) combined with genotype imputation has been proposed as an alternative to genotyping arrays for trait mapping and calculation of polygenic scores. To empirically assess the relative performance of these technologies for different applications, we performed low-pass sequencing (targeting coverage levels of 0.5× and 1×) and array genotyping (using the Illumina Global Screening Array (GSA)) on 120 DNA samples derived from African and European-ancestry individuals that are part of the 1000 Genomes Project. We then imputed both the sequencing data and the genotyping array data to the 1000 Genomes Phase 3 haplotype reference panel using a leave- one-out design. We evaluated overall imputation accuracy from these different assays as well as overall power for GWAS from imputed data, and computed polygenic risk scores for coronary artery disease and breast cancer using previously derived weights. We conclude that low-pass sequencing plus imputation, in addition to providing a substantial increase in statistical power for genome wide association studies, provides increased accuracy for polygenic risk prediction at effective coverages of ∼ 0.5× and higher compared to the Illumina GSA.
Project description:Porcine 60K BeadChip genotyping arrays (Illumina) are increasingly being applied in pig genomics to validate SNPs identified by re-sequencing or assembly-versus-assembly method. Here we report that more than 98% SNPs identified from the porcine 60K BeadChip genotyping array (Illumina) were consistent with the SNPs identified from the assembly-based method. This result demonstrates that whole-genome de novo assembly is a reliable approach to deriving accurate maps of SNPs.
