Seed-development programs: a systems biology-based comparison between dicots and monocots

Seeds develop differently in dicots and monocots, especially with respect to the major storage organs. High-resolution transcriptome data have provided the first insights into the molecular networks and pathway interactions that function during the development of individual seed compartments. Here,...

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Veröffentlicht in:Annual review of plant biology Jg. 64; S. 189
Hauptverfasser: Sreenivasulu, Nese, Wobus, Ulrich
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.01.2013
Schlagworte:
Magnoliopsida - classification
Magnoliopsida - genetics
Magnoliopsida - growth & development
Magnoliopsida - metabolism
Metabolic Networks and Pathways
Protein Interaction Maps
Seeds - growth & development
Seeds - metabolism
Systems Biology - methods
Transcriptome
ISSN:1545-2123, 1545-2123
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Zusammenfassung:Seeds develop differently in dicots and monocots, especially with respect to the major storage organs. High-resolution transcriptome data have provided the first insights into the molecular networks and pathway interactions that function during the development of individual seed compartments. Here, we review mainly recent data obtained by systems biology-based approaches, which have allowed researchers to construct and model complex metabolic networks and fluxes and identify key limiting steps in seed development. Comparative coexpression network analyses define evolutionarily conservative (FUS3/ABI3/LEC1) and divergent (LEC2) networks in dicots and monocots. Finally, we discuss the determination of seed size--an important yield-related characteristic--as mediated by a number of processes (maternal and epigenetic factors, fine-tuned regulation of cell death in distinct seed compartments, and endosperm growth) and underlying genes defined through mutant analyses. Altogether, systems approaches can make important contributions toward a more complete and holistic knowledge of seed biology and thus support strategies for knowledge-based molecular breeding.
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ISSN:1545-2123
1545-2123
DOI:10.1146/annurev-arplant-050312-120215