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1.  Common and distinct organ and stress responsive transcriptomic patterns in Oryza sativa and Arabidopsis thaliana 
BMC Plant Biology  2010;10:262.
Background
Arabidopsis thaliana is clearly established as the model plant species. Given the ever-growing demand for food, there is a need to translate the knowledge learned in Arabidopsis to agronomically important species, such as rice (Oryza sativa). To gain a comparative insight into the similarities and differences into how organs are built and how plants respond to stress, the transcriptomes of Arabidopsis and rice were compared at the level of gene orthology and functional categorisation.
Results
Organ specific transcripts in rice and Arabidopsis display less overlap in terms of gene orthology compared to the orthology observed between both genomes. Although greater overlap in terms of functional classification was observed between root specific transcripts in rice and Arabidopsis, this did not extend to flower, leaf or seed specific transcripts. In contrast, the overall abiotic stress response transcriptome displayed a significantly greater overlap in terms of gene orthology compared to the orthology observed between both genomes. However, ~50% or less of these orthologues responded in a similar manner in both species. In fact, under cold and heat treatments as many or more orthologous genes responded in an opposite manner or were unchanged in one species compared to the other. Examples of transcripts that responded oppositely include several genes encoding proteins involved in stress and redox responses and non-symbiotic hemoglobins that play central roles in stress signalling pathways. The differences observed in the abiotic transcriptomes were mirrored in the presence of cis-acting regulatory elements in the promoter regions of stress responsive genes and the transcription factors that potentially bind these regulatory elements. Thus, both the abiotic transcriptome and its regulation differ between rice and Arabidopsis.
Conclusions
These results reveal significant divergence between Arabidopsis and rice, in terms of the abiotic stress response and its regulation. Both plants are shown to employ unique combinations of genes to achieve growth and stress responses. Comparison of these networks provides a more rational approach to translational studies that is based on the response observed in these two diverse plant models.
doi:10.1186/1471-2229-10-262
PMCID: PMC3095337  PMID: 21106056
2.  Defining reference genes in Oryza sativa using organ, development, biotic and abiotic transcriptome datasets 
BMC Plant Biology  2010;10:56.
Background
Reference genes are widely used to normalise transcript abundance data determined by quantitative RT-PCR and microarrays. However, the approaches taken to define reference genes can be variable. Although Oryza sativa (rice) is a widely used model plant and important crop specie, there has been no comprehensive analysis carried out to define superior reference genes.
Results
Analysis of 136 Affymetrix transcriptome datasets comprising of 373 genome microarrays from studies in rice that encompass tissue, developmental, abiotic, biotic and hormonal transcriptome datasets identified 151 genes whose expression was considered relatively stable under all conditions. A sub-set of 12 of these genes were validated by quantitative RT-PCR and were seen to be stable under a number of conditions. All except one gene that has been previously proposed as a stably expressed gene for rice, were observed to change significantly under some treatment.
Conclusion
A new set of reference genes that are stable across tissue, development, stress and hormonal treatments have been identified in rice. This provides a superior set of reference genes for future studies in rice. It confirms the approach of mining large scale datasets as a robust method to define reference genes, but cautions against using gene orthology or counterparts of reference genes in other plant species as a means of defining reference genes.
doi:10.1186/1471-2229-10-56
PMCID: PMC2923530  PMID: 20353606

Results 1-2 (2)