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1.
PLoS One ; 3(10): e3337, 2008 Oct 06.
Article in English | MEDLINE | ID: mdl-18836531

ABSTRACT

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.


Subject(s)
Multigene Family , Oligonucleotide Array Sequence Analysis/methods , Oryza/genetics , Oryza/radiation effects , Plant Proteins/genetics , Cluster Analysis , Expressed Sequence Tags , Gene Expression Profiling , Genome, Plant , Light , Oligonucleotide Array Sequence Analysis/economics , Oryza/physiology , Plant Proteins/metabolism , Reproducibility of Results , Transcription, Genetic/radiation effects
2.
PLoS Genet ; 4(8): e1000164, 2008 Aug 22.
Article in English | MEDLINE | ID: mdl-18725934

ABSTRACT

Functional redundancy limits detailed analysis of genes in many organisms. Here, we report a method to efficiently overcome this obstacle by combining gene expression data with analysis of gene-indexed mutants. Using a rice NSF45K oligo-microarray to compare 2-week-old light- and dark-grown rice leaf tissue, we identified 365 genes that showed significant 8-fold or greater induction in the light relative to dark conditions. We then screened collections of rice T-DNA insertional mutants to identify rice lines with mutations in the strongly light-induced genes. From this analysis, we identified 74 different lines comprising two independent mutant lines for each of 37 light-induced genes. This list was further refined by mining gene expression data to exclude genes that had potential functional redundancy due to co-expressed family members (12 genes) and genes that had inconsistent light responses across other publicly available microarray datasets (five genes). We next characterized the phenotypes of rice lines carrying mutations in ten of the remaining candidate genes and then carried out co-expression analysis associated with these genes. This analysis effectively provided candidate functions for two genes of previously unknown function and for one gene not directly linked to the tested biochemical pathways. These data demonstrate the efficiency of combining gene family-based expression profiles with analyses of insertional mutants to identify novel genes and their functions, even among members of multi-gene families.


Subject(s)
Gene Expression Profiling/methods , Gene Expression/radiation effects , Oryza/genetics , Oryza/radiation effects , Plant Proteins/genetics , Arabidopsis/genetics , Arabidopsis/metabolism , Light , Molecular Sequence Data , Multigene Family , Mutagenesis, Insertional , Oligonucleotide Array Sequence Analysis , Oryza/physiology , Phenotype , Plant Proteins/metabolism , Signal Transduction , Transcription, Genetic/radiation effects
3.
BMC Bioinformatics ; 9: 314, 2008 Jul 19.
Article in English | MEDLINE | ID: mdl-18638416

ABSTRACT

BACKGROUND: A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue. RESULTS: We develop a procedure for quantifying the extent of probe-specific dye and slide bias in two-color microarrays. The primary output is a graphical diagnostic of the extent of the bias which called ECDF (Empirical Cumulative Distribution Function), though numerical results are also obtained. CONCLUSION: We show that the dye and slide biases were high for human and rice genomic arrays in two gene expression facilities, even after the standard intensity-based normalization, and describe how this diagnostic allowed the problems causing the probe-specific bias to be addressed, and resulted in important improvements in performance. The R package LMGene which contains the method described in this paper has been available to download from Bioconductor.


Subject(s)
Algorithms , DNA Probes/genetics , Fluorescent Dyes/analysis , Image Interpretation, Computer-Assisted/methods , Microscopy, Fluorescence, Multiphoton/methods , Oligonucleotide Array Sequence Analysis/methods , Observer Variation , Reproducibility of Results , Sensitivity and Specificity
4.
BMC Microbiol ; 8: 99, 2008 Jun 18.
Article in English | MEDLINE | ID: mdl-18564427

ABSTRACT

BACKGROUND: Xanthomonas oryzae pv. oryzae (Xoo) and X. oryzae pv. oryzicola (Xoc) are bacterial pathogens of the worldwide staple and grass model, rice. Xoo and Xoc are closely related but Xoo invades rice vascular tissue to cause bacterial leaf blight, a serious disease of rice in many parts of the world, and Xoc colonizes the mesophyll parenchyma to cause bacterial leaf streak, a disease of emerging importance. Both pathogens depend on hrp genes for type III secretion to infect their host. We constructed a 50-70 mer oligonucleotide microarray based on available genome data for Xoo and Xoc and compared gene expression in Xoo strains PXO99A and Xoc strain BLS256 grown in the rich medium PSB vs. XOM2, a minimal medium previously reported to induce hrp genes in Xoo strain T7174. RESULTS: Three biological replicates of the microarray experiment to compare global gene expression in representative strains of Xoo and Xoc grown in PSB vs. XOM2 were carried out. The non-specific error rate and the correlation coefficients across biological replicates and among duplicate spots revealed that the microarray data were robust. 247 genes of Xoo and 39 genes of Xoc were differentially expressed in the two media with a false discovery rate of 5% and with a minimum fold-change of 1.75. Semi-quantitative-RT-PCR assays confirmed differential expression of each of 16 genes each for Xoo and Xoc selected for validation. The differentially expressed genes represent 17 functional categories. CONCLUSION: We describe here the construction and validation of a two-genome microarray for the two pathovars of X. oryzae. Microarray analysis revealed that using representative strains, a greater number of Xoo genes than Xoc genes are differentially expressed in XOM2 relative to PSB, and that these include hrp genes and other genes important in interactions with rice. An exception was the rax genes, which are required for production of the host resistance elicitor AvrXa21, and which were expressed constitutively in both pathovars.


Subject(s)
Bacterial Proteins/metabolism , Gene Expression Profiling , Genome, Bacterial/genetics , Oligonucleotide Array Sequence Analysis/methods , Oryza/microbiology , Xanthomonas/metabolism , Bacterial Proteins/genetics , Gene Expression Regulation, Bacterial , Molecular Sequence Data , Plant Diseases/microbiology , Reverse Transcriptase Polymerase Chain Reaction , Xanthomonas/classification , Xanthomonas/genetics
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