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. A set of five genomic DNA samples containing different numbers of X chromosomes (1X to 5X sample set, including NA15510 and NA10851) were hybridized to Nsp copy number (CN) arrays in triplicate to evaluate detection of copy number variation using high density, non-polymorphic oligonucleotide probes. 6 Hapmap samples were hybridized to Nsp CN arrays to evaluate Mendelian inheritance of CNVs.

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

Project description:Advances in genomic technologies are rapidly filling the gap in genomic information available from non-model species that are economically and ecologically important. Reduction in costs and higher throughput of data acquisition will progressively increase the application of genomics in population and quantitative genetics. In molecular breeding, the ability to rapidly develop large numbers of genetic markers and generate high-density genetic maps at low cost is critical because they provide the framework for identification of elements that regulate trait variation, connecting genetics and genomics to phenotype. To generate the first high-density, gene-based genetic map for Eucalyptus, we genotyped a hybrid segregating population with microarray-based markers. The genus Eucalyptus includes the most economically important species used for bioenergy pulp and paper production worldwide. A custom 25-mers oligonucleotide array was designed based on 20,726 expressed sequence tags consensus, and RNA from 28 biologically-replicated individuals allowed clear-cut detection of putative single feature polymorphisms (SFPs) segregating 1:1 and 3:1. A genotyping array confirmed the segregation in a larger portion of the family and a genetic map with 1064 gene-related markers is made available with an average of one marker every 1.2 cM. Interestingly, reanalyzing the data from the 28 genotypes using a mixed-model approach resulted in most of the mapped genes among the significant probesets. We also demonstrate that designing more probes per gene increases the chance of mapping those genes. Finally, in silico validatation shows that 87% of the markers map to expected location on the draft genome, an important characteristic of SFP markers. Simultaneously detecting and genotyping SFP markers in a subset of the mapping population instead of only the genitors was more efficient for mapping genes in outcrossing species than previously reported approaches. Mapping SFP markers require low genomic resources and can be done at relatively low cost. We demonstrate the possibility of mapping hundreds to thousands of genes that can ultimately be used in generating further genomic resources, such as genome assembly, or for more direct applications, such as QTL analysis. Two biological replication of 28 genotypes were hybridized to the custom microarray, labeled with Cy3 and Cy5. Genotypes are fullsib progenies of the cross E. urophylla X E. grandis. A loop design was employed for the hybridization using xylem tissue. In total the microarray comprised 103,000 probes representing 20,726 unigenes with an average of five probes per unigene. Twenty-six negative control probes were also included in the microarray.

Project description:Advances in genomic technologies are rapidly filling the gap in genomic information available from non-model species that are economically and ecologically important. Reduction in costs and higher throughput of data acquisition will progressively increase the application of genomics in population and quantitative genetics. In molecular breeding, the ability to rapidly develop large numbers of genetic markers and generate high-density genetic maps at low cost is critical because they provide the framework for identification of elements that regulate trait variation, connecting genetics and genomics to phenotype. To generate the first high-density, gene-based genetic map for Eucalyptus, we genotyped a hybrid segregating population with microarray-based markers. The genus Eucalyptus includes the most economically important species used for bioenergy pulp and paper production worldwide. A custom 25-mers oligonucleotide array was designed based on 20,726 expressed sequence tags consensus, and RNA from 28 biologically-replicated individuals allowed clear-cut detection of putative single feature polymorphisms (SFPs) segregating 1:1 and 3:1. A genotyping array confirmed the segregation in a larger portion of the family and a genetic map with 1064 gene-related markers is made available with an average of one marker every 1.2 cM. Interestingly, reanalyzing the data from the 28 genotypes using a mixed-model approach resulted in most of the mapped genes among the significant probesets. We also demonstrate that designing more probes per gene increases the chance of mapping those genes. Finally, in silico validatation shows that 87% of the markers map to expected location on the draft genome, an important characteristic of SFP markers. Simultaneously detecting and genotyping SFP markers in a subset of the mapping population instead of only the genitors was more efficient for mapping genes in outcrossing species than previously reported approaches. Mapping SFP markers require low genomic resources and can be done at relatively low cost. We demonstrate the possibility of mapping hundreds to thousands of genes that can ultimately be used in generating further genomic resources, such as genome assembly, or for more direct applications, such as QTL analysis. Two technical replication of 68 individuals were hybridized to the custom microarray, labeled with Cy3 and Cy5. Individuals are fullsib progenies of the cross E. urophylla X E. grandis. A loop design was employed for the hybridization using xylem tissue. In total the microarray comprised 43,803 probes representing 15,698 unigenes. These probes were pre-selected in a screening array based on their mendelian segregation and bimodal signal separation. Twenty-six negative control probes were also included in the microarray.

Dataset Information

RAD methods paper - Threespine Stickleback Lateral Plate Mapping

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure