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A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors

机译:用于2500个水稻转录因子的高通量表达谱分析的定量RT-PCR平台

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Background Quantitative reverse transcription – polymerase chain reaction (qRT-PCR) has been demonstrated to be particularly suitable for the analysis of weakly expressed genes, such as those encoding transcription factors. Rice (Oryza sativa L.) is an important crop and the most advanced model for monocotyledonous species; its nuclear genome has been sequenced and molecular tools are being developed for functional analyses. However, high-throughput methods for rice research are still limited and a large-scale qRT-PCR platform for gene expression analyses has not been reported. Results We established a qRT-PCR platform enabling the multi-parallel determination of the expression levels of more than 2500 rice transcription factor genes. Additionally, using different rice cultivars, tissues and physiological conditions, we evaluated the expression stability of seven reference genes. We demonstrate this resource allows specific and reliable detection of the expression of transcription factor genes in rice. Conclusion Multi-parallel qRT-PCR allows the versatile and sensitive transcriptome profiling of large numbers of rice transcription factor genes. The new platform complements existing microarray-based expression profiling techniques, by allowing the analysis of lowly expressed transcription factor genes to determine their involvement in developmental or physiological processes. We expect that this resource will be of broad utility to the scientific community in the further development of rice as an important model for plant science.
机译:背景技术定量逆转录聚合酶链反应(qRT-PCR)已被证明特别适用于弱表达基因的分析,例如那些编码转录因子的基因。水稻(Oryza sativa L.)是重要的农作物,也是单子叶植物最先进的模式。它的核基因组已经测序,并且正在开发分子工具进行功能分析。然而,用于水稻研究的高通量方法仍然受到限制,尚未报道用于基因表达分析的大规模qRT-PCR平台。结果我们建立了一个qRT-PCR平台,可以多重平行测定2500多个水稻转录因子基因的表达水平。此外,使用不同的水稻品种,组织和生理条件,我们评估了七个参考基因的表达稳定性。我们证明了这种资源可以特异性和可靠地检测水稻中转录因子基因的表达。结论多重平行qRT-PCR可以对大量水稻转录因子基因进行通用而敏感的转录组分析。该新平台通过允许对低表达的转录因子基因进行分析,以确定它们在发育或生理过程中的参与,对现有的基于微阵列的表达谱技术进行补充。我们希望这种资源在水稻作为植物科学的重要模型的进一步发展中将对科学界具有广泛的用途。

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