%0 Journal Article %1 Lakshmanan2015Unraveling %A Lakshmanan, Meiyappan %A Lim, Sun-Hyung H. %A Mohanty, Bijayalaxmi %A Kim, Jae Kwang K. %A Ha, Sun-Hwa H. %A Lee, Dong-Yup Y. %D 2015 %J Plant physiology %K metabolic-networks rice %T Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis. %U http://view.ncbi.nlm.nih.gov/pubmed/26453433 %X Light quality is an important signaling component upon which plants orchestrate various morphological processes including the seed germination and seedling photomorphogenesis. However, it is still unclear how plants, especially food crops, sense various light qualities, and modulates their cellular growth and other developmental processes. Therefore, in this work, we initially profiled the transcripts of model crop, rice, under four different light treatments, blue (B), green (G), red (R) and white (W), as well as in dark (D). Concurrently, we reconstructed a fully compartmentalized genome-scale metabolic model (GEM) of rice cells, iOS2164, containing 2164 unique genes, 2284 reactions and 1999 metabolites. We then combined the model with transcriptome profiles to elucidate the light-specific transcriptional signatures of rice metabolism. Clearly, light signals mediated rice gene expressions, differentially regulating numerous metabolic pathways: photosynthesis and secondary metabolism was upregulated in B whereas reserve carbohydrates degradation was pronounced in D. The topological analysis of gene expression data with rice GEM further uncovered that phytohormones such as abscisate, ethylene, gibberellin and jasmonate are the key biomarkers of light-mediated regulation and the subsequent analysis of the associated genes' promoter regions identified several light-specific transcription factors. Finally, the transcriptional control of rice metabolism by red- and blue-light signals was assessed by integrating the transcriptome and metabolome data with constraint-based modeling. The biological insights gained from current integrative systems biology approach offer several potential applications such as improving the agronomic traits of food crops and the designing of light-specific synthetic gene circuits in microbial and mammalian systems. Copyright \copyright 2015, Plant Physiology.

@article{Lakshmanan2015Unraveling, abstract = {Light quality is an important signaling component upon which plants orchestrate various morphological processes including the seed germination and seedling photomorphogenesis. However, it is still unclear how plants, especially food crops, sense various light qualities, and modulates their cellular growth and other developmental processes. Therefore, in this work, we initially profiled the transcripts of model crop, rice, under four different light treatments, blue (B), green (G), red (R) and white (W), as well as in dark (D). Concurrently, we reconstructed a fully compartmentalized genome-scale metabolic model ({GEM}) of rice cells, {iOS2164}, containing 2164 unique genes, 2284 reactions and 1999 metabolites. We then combined the model with transcriptome profiles to elucidate the light-specific transcriptional signatures of rice metabolism. Clearly, light signals mediated rice gene expressions, differentially regulating numerous metabolic pathways: photosynthesis and secondary metabolism was upregulated in B whereas reserve carbohydrates degradation was pronounced in D. The topological analysis of gene expression data with rice {GEM} further uncovered that phytohormones such as abscisate, ethylene, gibberellin and jasmonate are the key biomarkers of light-mediated regulation and the subsequent analysis of the associated genes' promoter regions identified several light-specific transcription factors. Finally, the transcriptional control of rice metabolism by red- and blue-light signals was assessed by integrating the transcriptome and metabolome data with constraint-based modeling. The biological insights gained from current integrative systems biology approach offer several potential applications such as improving the agronomic traits of food crops and the designing of light-specific synthetic gene circuits in microbial and mammalian systems. Copyright {\copyright} 2015, Plant Physiology.}, added-at = {2018-12-02T16:09:07.000+0100}, author = {Lakshmanan, Meiyappan and Lim, Sun-Hyung H. and Mohanty, Bijayalaxmi and Kim, Jae Kwang K. and Ha, Sun-Hwa H. and Lee, Dong-Yup Y.}, biburl = {https://www.bibsonomy.org/bibtex/23595ca577fc5e991ac5d86a5e7410a38/karthikraman}, citeulike-article-id = {13827481}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/26453433}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=26453433}, day = 9, interhash = {de519c7d9e412bb567dde57caa4746e4}, intrahash = {3595ca577fc5e991ac5d86a5e7410a38}, issn = {1532-2548}, journal = {Plant physiology}, keywords = {metabolic-networks rice}, month = oct, pmid = {26453433}, posted-at = {2015-11-04 06:25:38}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Unraveling the light-specific metabolic and regulatory signatures of rice through combined in silico modeling and multi-omics analysis.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/26453433}, year = 2015 }