Pospiviroids detection
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REPOSITORIES: ENA
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Project description:Meiotic DNA double stranded breaks (DSBs) initiate genetic recombination in discrete areas of the genome called recombination hotspots. Although DSBs can be directly mapped using ChIP-Seq and antibody against ssDNA-associated proteins, genome-wide mapping of recombination hotspots in mammals is still a challenge due to the low frequency of recombination, high heterogeneity of the germ cell population and the relatively low efficiency of ChIP. To overcome these limitations we have developed a novel method, single-stranded DNA (ssDNA) sequencing (SSDS), that specifically detects protein-bound single-stranded DNA at DSB ends. SSDS consists of a computational framework for the specific detection of ssDNA-derived reads in a sequencing library and a new library preparation procedure for the enrichment of fragments originating from ssDNA. When applied to mapping meiotic DSBs, the use of SSDS reduces the non-specific dsDNA background more than ten-fold. Our method can be extended to other systems where the identification of ssDNA or DSBs is desired. Development and validation of the method, SSDS, for the specific detection of ssDNA-derived and dsDNA-derived fragments in sequencing libraries and enrichment of ssDNA-derived fragments. SSDS was used to detect meiotic DSBs in 9R/13R mice.
2012-02-21 | E-GEOD-34592 | biostudies-arrayexpress
Project description:A CHG microarray for detection and identification of bacteria and viruses pathogenic on maize
2016-07-01 | GSE69895 | GEO
Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples.
2011-04-14 | GSE28597 | GEO
Project description:Goal: To identify copy number variation in normal individuals using high density, non-polymorphic oligonucleotide probes Background DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1kb to over 3Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay. Results In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3M independent NspI restriction enzyme fragments in the 200bp to 1100bp size range, which is a several fold increase in marker density as compared to the 500K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries. Conclusions Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization. Keywords: Copy number variation (CNV) detection
2008-04-24 | GSE9053 | GEO
Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples. 19 clinical samples were analyzed for presence of virus using the MDA microarray. One of the samples is a negative control (water). One HCV-positive serum sample is included twice (HCV+1 and HCV+2).
2011-04-14 | E-GEOD-28597 | biostudies-arrayexpress
Project description:Meiotic DNA double stranded breaks (DSBs) initiate genetic recombination in discrete areas of the genome called recombination hotspots. Although DSBs can be directly mapped using ChIP-Seq and antibody against ssDNA-associated proteins, genome-wide mapping of recombination hotspots in mammals is still a challenge due to the low frequency of recombination, high heterogeneity of the germ cell population and the relatively low efficiency of ChIP. To overcome these limitations we have developed a novel method, single-stranded DNA (ssDNA) sequencing (SSDS), that specifically detects protein-bound single-stranded DNA at DSB ends. SSDS consists of a computational framework for the specific detection of ssDNA-derived reads in a sequencing library and a new library preparation procedure for the enrichment of fragments originating from ssDNA. When applied to mapping meiotic DSBs, the use of SSDS reduces the non-specific dsDNA background more than ten-fold. Our method can be extended to other systems where the identification of ssDNA or DSBs is desired.
2012-02-21 | GSE34592 | GEO
Project description:We developed a new approach called antibody detection of translocations (ADOT) which combines a transcriptional microarray-based approach with a novel antibody-based detection method to detect translocations in cancer. ADOT allows for the accurate and sensitive identification of translocations and provides exon-level information about the fusion transcript. ADOT can detect translocations in poor quality unprocessed total RNA. We demonstrate the feasibility of ADOT by examples in which both known and unknown Ewing sarcoma translocations are identified from cell lines, tumor xenografts, and FFPE primary tumors. These results demonstrate that ADOT may be an effective approach for translocation analysis in clinical specimens with significant RNA degradation and may offer a novel diagnostic tool for translocation-based cancers.
2012-01-31 | GSE35450 | GEO
Project description:PCR based detection of Y-chromosome compared against results obtained by CGH microarrrays in Preimplantation Genetic Screening
2017-04-05 | GSE97386 | GEO
Project description:In order to evaluate the performance of CNV detection in next-generation sequencing platform in varied sample types, we employed chromosomal microarray analysis (CMA) for validation of the samples with NGS-based detection results (NCBI Sequence Read Archive with accession number SRA296708). Besides snp-array, we used a customized array Comparative Genomics Hybridization (aCGH, Agilent) approach for a cohort of clinical samples including early abortus, induced termination, prenatal samples and postnatal samples. CMA results were compared with NGS-based detection results. 100% consistency was obtained between NGS-based approach and CMA in pathogenic or likely pathogenic CNVs detection.
2015-10-01 | GSE72891 | GEO