Abstract
Circadian rhythms are biological cycles with a period length of approximately 24 h that are generated by endogenous clocks. The application of microarrays for high-throughput transcriptome analysis has led to the insight that substantial portions of the transcriptomes of both humans and many model organisms are clock-regulated. In a typical circadian time course microarray experiment, samples are collected from organisms maintained in constant environmental conditions, gene expression at each time point is determined using microarrays, and finally clock-regulated transcripts are identified using statistical algorithms. Here, we describe how to design the experiment, process RNA, determine expression profiles using ATH1 microarrays, and use a nonparametric statistical algorithm named JTK_CYCLE in order to identify circadian-regulated transcripts in Arabidopsis. This basic procedure can be modified to identify clock-regulated transcripts in different organisms or using different expression analysis platforms.
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Acknowledgement
We thank Hsin-Yen Wu for reading and testing the commands in this manuscript, and Michael Hughes for helpful discussions about JTK_CYCLE. This work was supported by the National Institutes of Health (NIGMS) (http://www.nigms.nih.gov/) [GM069418] and the Taiwan Merit Scholarship (http://web1.nsc.gov.tw/) [NSC-095-SAF-I-564-014-TMS].
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Hsu, P.Y., Harmer, S.L. (2014). Global Profiling of the Circadian Transcriptome Using Microarrays. In: Staiger, D. (eds) Plant Circadian Networks. Methods in Molecular Biology, vol 1158. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0700-7_3
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DOI: https://doi.org/10.1007/978-1-4939-0700-7_3
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