Literature DB >> 21447789

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation.

Emily Breeze1, Elizabeth Harrison, Stuart McHattie, Linda Hughes, Richard Hickman, Claire Hill, Steven Kiddle, Youn-Sung Kim, Christopher A Penfold, Dafyd Jenkins, Cunjin Zhang, Karl Morris, Carol Jenner, Stephen Jackson, Brian Thomas, Alexandra Tabrett, Roxane Legaie, Jonathan D Moore, David L Wild, Sascha Ott, David Rand, Jim Beynon, Katherine Denby, Andrew Mead, Vicky Buchanan-Wollaston.   

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.

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Year:  2011        PMID: 21447789      PMCID: PMC3082270          DOI: 10.1105/tpc.111.083345

Source DB:  PubMed          Journal:  Plant Cell        ISSN: 1040-4651            Impact factor:   11.277


  88 in total

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  310 in total

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4.  Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize.

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5.  Characterization and RNA-seq analysis of underperformer, an activation-tagged potato mutant.

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Review 6.  Alternative splicing at the intersection of biological timing, development, and stress responses.

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9.  Time-Course Transcriptome Analysis of Arabidopsis Siliques Discloses Genes Essential for Fruit Development and Maturation.

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10.  Stitching together the Multiple Dimensions of Autophagy Using Metabolomics and Transcriptomics Reveals Impacts on Metabolism, Development, and Plant Responses to the Environment in Arabidopsis.

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