High-Resolution Temporal Profiling of Transcripts during Arabidopsis Leaf Senescence Reveals a Distinct Chronology of Processes and Regulation[C][W][OA]

By E. Breeze, E. Harrison, Stuart McHattie, L. Hughes, Richard Hickman, Claire Hill, S. Kiddle, Youn-sung Kim, Christopher A. Penfold, Dafyd J. Jenkins and 15 more. The Plant Cell, 2011

820 citations recorded by the source corpus.

This work presents a high-resolution time-course analysis of gene expression during development of a leaf from expansion through senescence. Enrichment in ontologies, sequence motifs, and transcription factor families within genes showing altered expression over time identified both metabolic pathways and potential regulators active at different stages of leaf development and senescence. 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.

Subfields: Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/58e42c8fe27fa292c93ad41d8130da8ed88ccd8d

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In Molecular Biology

  1. Kazuo Shinozaki
  2. K. Nakashima
  3. Kazuko Yamaguchi-Shinozaki
  4. Jen Sheen
  5. J. Mizoi
  6. Ildoo Hwang
  7. Bruno Müller
  8. A. Fischer

In Plant Science

  1. K. Nakashima
  2. Kazuko Yamaguchi-Shinozaki
  3. Kazuo Shinozaki
  4. Jen Sheen
  5. J. Mizoi
  6. Ildoo Hwang
  7. Bruno Müller
  8. A. Fischer

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