Exploring regulatory networks in plants: transcription factors of starch metabolism

• Published in: PeerJ (San Francisco, CA) CA), 2019-07, Vol.7, p.e6841-e6841, Article e6841
• Main Authors: López-González, Cristal, Juárez-Colunga, Sheila, Morales-Elías, Norma Cecilia, Tiessen, Axel
• Format: Article
• Language: English
• Subjects: Agricultural Science; Animal genetics; Anopheles; Biochemistry; Biological networks; Crop yields; DNA binding proteins; Enzymes; Food quality; Genes; Genomes; Genomics; Hormones; Literature reviews; Metabolism; Metabolites; Metabolomics; Molecular Biology; Network hierarchies; Phosphates; Physiological aspects; Physiology; Plant genetics; Plant Science; Plant sciences; Potatoes; Proteins; Regulatory loops; Sink-source; Starch; Sucrose; Sucrose-starch; Transcription factors; Transcriptional regulation
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.6841

Biological networks are complex (non-linear), redundant (cyclic) and compartmentalized at the subcellular level. Rational manipulation of plant metabolism may have failed due to inherent difficulties of a comprehensive understanding of regulatory loops. We first need to identify key factors controlling the regulatory loops of primary metabolism. The paradigms of plant networks are revised in order to highlight the differences between metabolic and transcriptional networks. Comparison between animal and plant transcription factors (TFs) reveal some important differences. Plant transcriptional networks function at a lower hierarchy compared to animal regulatory networks. Plant genomes contain more TFs than animal genomes, but plant proteins are smaller and have less domains as animal proteins which are often multifunctional. We briefly summarize mutant analysis and co-expression results pinpointing some TFs regulating starch enzymes in plants. Detailed information is provided about biochemical reactions, TFs and cis regulatory motifs involved in sucrose-starch metabolism, in both source and sink tissues. Examples about coordinated responses to hormones and environmental cues in different tissues and species are listed. Further advancements require combined data from single-cell transcriptomic and metabolomic approaches. Cell fractionation and subcellular inspection may provide valuable insights. We propose that shuffling of promoter elements might be a promising strategy to improve in the near future starch content, crop yield or food quality.