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Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice.

ABSTRACT: BACKGROUND:We report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features. RESULTS:We have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP) elements derived from insertions/deletions identified by aligning genomic sequences of the japonica cultivar Nipponbare and the indica cultivar 93-11. The SFPs were experimentally verified by hybridization with labeled genomic DNA prepared from the two cultivars. Using the genotyping microarrays, we found high levels of polymorphism across diverse rice accessions, and were able to classify all five subpopulations of rice with high bootstrap support. The microarrays were used for mapping of a gene conferring resistance to Magnaporthe grisea, the causative organism of rice blast disease, by quantitative genotyping of samples from a recombinant inbred line population pooled by phenotype. CONCLUSION:We anticipate this microarray-based genotyping platform, based on its low cost-per-sample, to be particularly useful in applications requiring whole-genome molecular marker coverage across large numbers of individuals.

SUBMITTER: Edwards JD

PROVIDER: S-EPMC2435114 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice.

Edwards Jeremy D JD Janda Jaroslav J Sweeney Megan T MT Gaikwad Ambika B AB Liu Bin B Leung Hei H Galbraith David W DW

Plant methods 20080529

<h4>Background</h4>We report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features.<h4>Results</h4>We have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP) elements derived from insertions/delet ...[more]

PMID: 18510771

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Project description:BACKGROUND: The induction of genomic deletions by physical- or chemical- agents is an easy and inexpensive means to generate a genome-saturating collection of mutations. Different mutagens can be selected to ensure a mutant collection with a range of deletion sizes. This would allow identification of mutations in single genes or, alternatively, a deleted group of genes that might collectively govern a trait (e.g., quantitative trait loci, QTL). However, deletion mutants have not been widely used in functional genomics, because the mutated genes are not tagged and therefore, difficult to identify. Here, we present a microarray-based approach to identify deleted genomic regions in rice mutants selected from a large collection generated by gamma ray or fast neutron treatment. Our study focuses not only on the utility of this method for forward genetics, but also its potential as a reverse genetics tool through accumulation of hybridization data for a collection of deletion mutants harboring multiple genetic lesions. RESULTS: We demonstrate that hybridization of labeled genomic DNA directly onto the Affymetrix Rice GeneChip allows rapid localization of deleted regions in rice mutants. Deletions ranged in size from one gene model to approximately 500 kb and were predicted on all 12 rice chromosomes. The utility of the technique as a tool in forward genetics was demonstrated in combination with an allelic series of mutants to rapidly narrow the genomic region, and eventually identify a candidate gene responsible for a lesion mimic phenotype. Finally, the positions of mutations in 14 mutants were aligned onto the rice pseudomolecules in a user-friendly genome browser to allow for rapid identification of untagged mutations http://irfgc.irri.org/cgi-bin/gbrowse/IR64_deletion_mutants/. CONCLUSION: We demonstrate the utility of oligonucleotide arrays to discover deleted genes in rice. The density and distribution of deletions suggests the feasibility of a database saturated with deletions across the rice genome. This community resource can continue to grow with further hybridizations, allowing researchers to quickly identify mutants that harbor deletions in candidate genomic regions, for example, regions containing QTL of interest.

Project description:BackgroundDespite the widespread use of microarrays, much ambiguity regarding data analysis, interpretation and correlation of the different technologies exists. There is a considerable amount of interest in correlating results obtained between different microarray platforms. To date, only a few cross-platform evaluations have been published and unfortunately, no guidelines have been established on the best methods of making such correlations. To address this issue we conducted a thorough evaluation of two commercial microarray platforms to determine an appropriate methodology for making cross-platform correlations.ResultsIn this study, expression measurements for 10,763 genes uniquely represented on Affymetrix U133A/B GeneChips and Amersham CodeLink UniSet Human 20 K microarrays were compared. For each microarray platform, five technical replicates, derived from the same total RNA samples, were labeled, hybridized, and quantified according to each manufacturers' standard protocols. The correlation coefficient (r) of differential expression ratios for the entire set of 10,763 overlapping genes was 0.62 between platforms. However, the correlation improved significantly (r = 0.79) when genes within noise were excluded. In addition to levels of inter-platform correlation, we evaluated precision, statistical-significance profiles, power, and noise levels for each microarray platform. Accuracy of differential expression was measured against real-time PCR for 25 genes and both platforms correlated well with r values of 0.92 and 0.79 for CodeLink and GeneChip, respectively.ConclusionsAs a result of this study, we recommend using only genes called 'present' in cross-platform correlations. However, as in this study, a large number of genes may be lost from the correlation due to differing levels of noise between platforms. This is an important consideration given the apparent difference in sensitivity of the two platforms. Data from microarray analysis need to be interpreted cautiously and therefore, we provide guidelines for making cross-platform correlations. In all, this study represents the most comprehensive and specifically designed comparison of short-oligonucleotide microarray platforms to date using the largest set of overlapping genes.

Dataset Information

Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice.

Publications

Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice.

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