Transcriptional Regulatory Network of Arabidopsis Starch Metabolism under Extensive Light Condition: A Potential Model of Transcription-modulated Starch Metabolism in Roots of Starchy Crops

Starchy root crops are a major carbohydrates source for being both human food and animal feed. The increasing demand of such crops has been a driving force of studies and research in biology of the crops. However, the related-knowledge as well as the existing information is still very few in comparison with the Arabidopsis model plant. Accordingly, the aims of this work are (1) to attempt to exploit the enormous data of Arabidopsis model plant to infer the regulation in the starchy root crops, and (2) to investigate the possibility and plausibility of the inference. Here, the transcriptional regulatory network of starch metabolism of Arabidopsis under extensive light condition was performed through the modified graphical Gaussian model (GGM) to infer the regulation of the similar process in root crops. The resulting correlation network of the significant genes includes 70 transcription factors and two starch-related genes, alpha-Glucosidase-like3 (AGL3:At3g45940) and beta-Amylase 5 (BAM5:At4g15210). Though the results provided the potential transcription factors of starch-related genes, which could be useful for further investigation, it is more likely that the selected condition of data is not appropriate to represent the starch metabolism in root crops. The results showed that greater than 70% of the significant genes were related to the starch degradation process which might reflect that the plants were under stress. This observation was supported by the Gene Ontology (GO) enrichment analysis that found many enriched GO terms relevant to the stress response. In conclusion, we believe that the data of the model plant are useful for gaining more understanding into the regulation in other plants, including root crops, but the suitable condition of data measurement in use need to be well defined.