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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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Download Supplemental Table 1: Top 700 seed abundant gene expression patterns in distinct seed compartments of Arabidopsis (XLS)
Download all other Supplemental Material as a PDF. Includes:
Supplemental Figure 1: Monitoring compartment specific expression pattern (a) and coexpression gene
network (b) of AT5G07200 (YAP169-AtGA20ox)
Monitoring seed compartment specific expression patterns, specific sets of coexpressed genes
preferentially expressed in endosperm fraction (representative e.g. AT5G07200, AT5G07260,
AT4G25000) during linear cotyledon stage have been identified. Among them, At5g07260 (homeobox
protein-related) eFP expression map confirmed seed specificity. The coexpression gene network around
AT5G07200 (YAP169-AtGA20ox3) is closely connected with At5g07260 (homeobox protein-related)
and several other lipases, potentially involved in the PCD pathway. Its protein interaction predictions
show close connections to GA metabolism. The AMY1 coexpression gene network is also surrounded
by several senescence related markers suggesting key connections between nutrient mobilization and the
likely triggering of PCD events.
Supplemental Figure 2: Gene co-expression network of seed maturation regulators (LEC1/AFL and
ABI5) and protein-protein interaction network of the FUS3
(a) Gene co-expression network of LEC1/AFL (ABI3, FUS3 & LEC2) and ABI5, is derived from Plant
Network-AraNET (82) using Heuristic Cluster Chiseling Algorithm. Meta-network containing genes of
LEC1/AFL cluster are enriched for fatty acid and lipid metabolism, TAG synthesis, storage proteins,
development related proteins, ABA signal transduction and other transcription factors. Available mutant
phenotypic data (gametophytic and embryo lethal encoding genes) are highlighted in the interactive
network of the LEC1/AFL cluster. (b) Further details of mutant phenotypes are listed. (c) The proteinprotein interaction network of the FUS3 master regulators involved in seed maturation events has been
derived using STRING database (124).