Coltri, P. P. | Search bioRxiv

bioRxiv2019

Software for agriculture climate risk management focused in smallholders

Taking Persimmon (Diospyros kaki L.), Fig (Ficus carica L.) and Papaya (Carica Papaya L) fruits in Sao Paulo State, southeast of Brazil, as a case of study, we present here new software that was designed to support smallholders to manage their climate risk on the production area. The main idea of this new software named \"Brazilian Mapping for Agricultural Zoning System\" (BRAMAZOS) is to transform scientific knowledge into useful information for crop climate risk management, indicating the risk of crop failure and which is the limiting meteorological element for the area unsuitability. The software was developed based on user experience design, focusing on the users facilities with a friendly interface. We simulated these fruits climate risk in current and future scenarios of climate change using ETAHadgem ES Regional Climate Models (RCM), which is a downscaling of the Global Climate Model HadGEM2-ES, based on the IPCC 5th Assessment Report (AR5). We observed changes in the climate risk zone distribution for Persimmon and Papaya cultivation, which could lose almost 30% and 9% of the suitable area respectively. On the other hand, fig did not present significant reduction in the climate risk zone. The results presented here suggested that the temperate fruit examples used here seem to be more sensible to the temperature increase and, the tropical example seems to be more precipitation decrease sensitive. We discussed the significance of BRAMAZOS software as tool to support efficient information to climate risk management, providing agroclimatic information that are efficient to assist decision making, increase food security with the intention to reduce the climate impact on smallholders development and resources management issues.

bioinformatics↗

bioRxiv2018

Interaction pathways promote spliceosome module integration and network-level robustness to cascading effects

The functionality of distinct types of protein networks depends on the patterns of protein-protein interactions. A problem to solve is understanding the fragility of protein networks to predict system malfunctioning due to mutations and other errors. Spectral graph theory provides tools to understand the structural and dynamical properties of a system based on the mathematical properties of matrices associated with the networks. We combined two of such tools to explore the fragility to cascading effects of the network describing protein interactions within a key macromolecular complex, the spliceosome. Using S. cerevisiae as a model system we show that the spliceosome network has more indirect paths connecting proteins than random networks. Such multiplicity of paths may promote routes to cascading effects to propagate across the network. However, the modular network structure concentrates paths within modules, thus constraining the propagation of such cascading effects, as indicated by analytical results from the spectral graph theory and by numerical simulations of a minimal mathematical model parameterized with the spliceosome network. We hypothesize that the concentration of paths within modules favors robustness of the spliceosome against failure, but may lead to a higher vulnerability of functional subunits which may affect the temporal assembly of the spliceosome. Our results illustrate the utility of spectral graph theory for identifying fragile spots in biological systems and predicting their implications.

molecular biology↗