Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Defining reference genes in Oryza sativa using organ, development, biotic and abiotic transcriptome datasets | Narsai et al. BMC Plant Biology 2010 10 56 http 1471-2229 10 56 BMC Plant Biology METHODOLOGY ARTICLE _ Open Access Defining reference genes in Oryza sativa using organ development biotic and abiotic transcriptome datasets Reena Narsai Aneta Ivanova Sophia Ng and James Whelan Abstract 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. Background The analysis of gene expression or more correctly transcript abundance is widely carried out in a variety of laboratories in various disciplines. Northern blotting quantitative RT-PCR QRT-PCR and microarray approaches are commonly used to assess transcript abundance. All
