Photoperiod sensors allow physiological adaptation to the changing seasons. The prevalent hypothesis is that day length perception is mediated through coupling of an endogenous rhythm with an external light signal. Sufficient molecular data are available to test this quantitatively in plants, though not yet in mammals. In Arabidopsis, the clock-regulated genes CONSTANS (CO) and FLAVIN, KELCH, F-BOX (FKF1) and their light-sensitive proteins are thought to form an external coincidence sensor. Here, we model the integration of light and timing information by CO, its target gene FLOWERING LOCUS T (FT), and the circadian clock. Among other predictions, our models show that FKF1 activates FT. We demonstrate experimentally that this effect is independent of the known activation of CO by FKF1, thus we locate a major, novel controller of photoperiodism. External coincidence is part of a complex photoperiod sensor: modeling makes this complexity explicit and may thus contribute to crop improvement.

BackgroundCassava is a well-known starchy root crop utilized for food, feed and biofuel production. However, the comprehension underlying the process of starch production in cassava is not yet available.ResultsIn this work, we exploited the recently released genome information and utilized the post-genomic approaches to reconstruct the metabolic pathway of starch biosynthesis in cassava using multiple plant templates. The quality of pathway reconstruction was assured by the employed parsimonious reconstruction framework and the collective validation steps. Our reconstructed pathway is presented in the form of an informative map, which describes all important information of the pathway, and an interactive map, which facilitates the integration of omics data into the metabolic pathway. Additionally, to demonstrate the advantage of the reconstructed pathways beyond just the schematic presentation, the pathway could be used for incorporating the gene expression data obtained from various developmental stages of cassava roots. Our results exhibited the distinct activities of the starch biosynthesis pathway in different stages of root development at the transcriptional level whereby the activity of the pathway is higher toward the development of mature storage roots.ConclusionsTo expand its applications, the interactive map of the reconstructed starch biosynthesis pathway is available for download at the SBI group’s website (http://sbi.pdti.kmutt.ac.th/?page_id=33). This work is considered a big step in the quantitative modeling pipeline aiming to investigate the dynamic regulation of starch biosynthesis in cassava roots.

Development of storage roots is a process associated with a phase change from cell division and elongation to radial growth and accumulation of massive amounts of reserve substances such as starch. Knowledge of the regulation of cassava storage root formation has accumulated over time; however, gene regulation during the initiation and early stage of storage root development is still poorly understood. In this study, transcription profiling of fibrous, intermediate and storage roots at eight weeks old were investigated using a 60-mer-oligo microarray. Transcription and gene expression were found to be the key regulating processes during the transition stage from fibrous to intermediate roots, while homeostasis and signal transduction influenced regulation from intermediate roots to storage roots. Clustering analysis of significant genes and transcription factors (TF) indicated that a number of phytohormone-related TF were differentially expressed; therefore, phytohormone-related genes were assembled into a network of correlative nodes. We propose a model showing the relationship between KNOX1 and phytohormones during storage root initiation. Exogeneous treatment of phytohormones N (6) -benzylaminopurine and 1-Naphthaleneacetic acid were used to induce the storage root initiation stage and to investigate expression patterns of the genes involved in storage root initiation. The results support the hypothesis that phytohormones are acting in concert to regulate the onset of cassava storage root development. Moreover, MeAGL20 is a factor that might play an important role at the onset of storage root initiation when the root tip becomes swollen.

Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava.

Analysis of metabolic flux was used for system level assessment of carbon partitioning in Kasetsart 50 (KU50) and Hanatee (HN) cassava cultivars to understand the metabolic routes for their distinct phenotypes. First, the c onstraint- b ased metabolic m odel of cassava storage r oots, rMeCBM, was developed based on the carbon assimilation pathway of cassava. Following the subcellular compartmentalization and curation to ensure full network connectivity and reflect the complexity of eukaryotic cells, cultivar specific data on sucrose uptake and biomass synthesis were input, and rMeCBM model was used to simulate storage root growth in KU50 and HN. Results showed that rMeCBM-KU50 and rMeCBM-HN models well imitated the storage root growth. The flux-sum analysis revealed that both cultivars utilized different metabolic precursors to produce energy in plastid. More carbon flux was invested in the syntheses of carbohydrates and amino acids in KU50 than in HN. Also, KU50 utilized less flux for respiration and less energy to synthesize one gram of dry storage root. These results may disclose metabolic potential of KU50 underlying its higher storage root and starch yield over HN. Moreover, sensitivity analysis indicated the robustness of rMeCBM model. The knowledge gained might be useful for identifying engineering targets for cassava yield improvement.

BackgroundSensitivity and robustness are essential properties of circadian clock systems, enabling them to respond to the environment but resist noisy variations. These properties should be recapitulated in computational models of the circadian clock. Highly nonlinear kinetics and multiple loops are often incorporated into models to match experimental time-series data, but these also impact on model properties for clock models.Methodology/Principal FindingsHere, we study the consequences of complicated structure and nonlinearity using simple Goodwin-type oscillators and the complex Arabidopsis circadian clock models. Sensitivity analysis of the simple oscillators implies that an interlocked multi-loop structure reinforces sensitivity/robustness properties, enhancing the response to external and internal variations. Furthermore, we found that reducing the degree of nonlinearity could sometimes enhance the robustness of models, implying that ad hoc incorporation of nonlinearity could be detrimental to a model's perceived credibility.ConclusionThe correct multi-loop structure and degree of nonlinearity are therefore critical in contributing to the desired properties of a model as well as its capacity to match experimental data.

BackgroundA number of studies have previously demonstrated that “goodness of fit” is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain.ResultsHere, we propose a novel robustness analysis that aims to determine the “common robustness” of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network.ConclusionsConsistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

Cassava is a crop of hope for the 21st century. Great advantages of cassava over other crops are not only the capacity of carbohydrates, but it is also an easily grown crop with fast development. As a plant which is highly tolerant to a poor environment, cassava has been believed to own an effective acclimation process, an intelligent mechanism behind its survival and sustainability in a wide range of climates. Herein, we aimed to investigate the transcriptional regulation underlying the adaptive development of a cassava root to different seasonal cultivation climates. Gene co-expression analysis suggests that AP2-EREBP transcription factor (ERF1) orthologue (D142) played a pivotal role in regulating the cellular response to exposing to wet and dry seasons. The ERF shows crosstalk with gibberellin, via ent-Kaurene synthase (D106), in the transcriptional regulatory network that was proposed to modulate the downstream regulatory system through a distinct signaling mechanism. While sulfur assimilation is likely to be a signaling regulation for dry crop growth response, calmodulin-binding protein is responsible for regulation in the wet crop. With our initiative study, we hope that our findings will pave the way towards sustainability of cassava production under various kinds of stress considering the future global climate change.