High-Resolution Temporal Profiling of Transcripts during Arabidopsis Leaf Senescence Reveals a Distinct Chronology of Processes and Regulation

Author:

Breeze Emily1,Harrison Elizabeth1,McHattie Stuart12,Hughes Linda1,Hickman Richard12,Hill Claire1,Kiddle Steven12,Kim Youn-sung1,Penfold Christopher A.2,Jenkins Dafyd2,Zhang Cunjin1,Morris Karl1,Jenner Carol1,Jackson Stephen1,Thomas Brian1,Tabrett Alexandra1,Legaie Roxane2,Moore Jonathan D.2,Wild David L.2,Ott Sascha2,Rand David2,Beynon Jim12,Denby Katherine12,Mead Andrew1,Buchanan-Wollaston Vicky12

Affiliation:

1. School of Life Sciences, University of Warwick, Wellesbourne, Warwick CV35 9EF, United Kingdom

2. Warwick Systems Biology, University of Warwick, Coventry CV4 7AL, United Kingdom

Abstract

Abstract Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a high-resolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence.

Publisher

Oxford University Press (OUP)

Subject

Cell Biology,Plant Science

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