Project description:BACKGROUND: Gene expression profiles of non-model mammals may provide valuable data for biomedical and evolutionary studies. However, due to lack of sequence information of other species, DNA microarrays are currently restricted to humans and a few model species. This limitation may be overcome by using arrays developed for a given species to analyse gene expression in a related one, an approach known as "cross-species analysis". In spite of its potential usefulness, the accuracy and reproducibility of the gene expression measures obtained in this way are still open to doubt. The present study examines whether or not hybridization values from cross-species analyses are as reproducible as those from same-species analyses when using Affymetrix oligonucleotide microarrays. RESULTS: The reproducibility of the probe data obtained hybridizing deer, Old-World primates, and human RNA samples to Affymetrix human GeneChip U133 Plus 2.0 was compared. The results show that cross-species hybridization affected neither the distribution of the hybridization reproducibility among different categories, nor the reproducibility values of the individual probes. Our analyses also show that a 0.5% of the probes analysed in the U133 plus 2.0 GeneChip are significantly associated to un-reproducible hybridizations. Such probes-called in the text un-reproducible probe sequences- do not increase in number in cross-species analyses. CONCLUSION: Our study demonstrates that cross-species analyses do not significantly affect hybridization reproducibility of GeneChips, at least within the range of the mammal species analysed here. The differences in reproducibility between same-species and cross-species analyses observed in previous studies were probably caused by the analytical methods used to calculate the gene expression measures. Together with previous observations on the accuracy of GeneChips for cross-species analysis, our analyses demonstrate that cross-species hybridizations may provide useful gene expression data. However, the reproducibility and accuracy of these measures largely depends on the use of appropriated algorithms to derive the gene expression data from the probe data. Also, the identification of probes associated to un-reproducible hybridizations-useless for gene expression analyses- in the studied GeneChip, stress the need of a re-evaluation of the probes' performance.

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.

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Identical probes on different high-density oligonucleotide microarrays can produce different measurements of gene expression.

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Identical probes on different high-density oligonucleotide microarrays can produce different measurements of gene expression.

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