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: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:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested. 10 chronic lymphocytic leukemia (CLL) samples was analyzed using four different high-resolution platforms: 32K BAC arrays, 185K Agilent oligonucleotide arrays, 250K Affymetrix SNP arrays and 317K Illumina SNP arrays.
Project description:Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1,000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385,000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH, and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM’s performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of less than 10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2-5 kb, and 1 kb, respectively. Keywords: CNV detection algorithm development and assessment
Project description:We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data. Keywords: genomic DNA, CGH, Copy Number Variation