Unveiling Protein Functions through the Dynamics of the Interaction Network

Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes

Genetic characterization of chestnut (Castanea sativa Mill.) orchards and traditional nut varieties in El Bierzo, a glacial refuge and major cultivation site in Northwestern Spain

This paper presents a detailed genetic study of Castanea sativa in El Bierzo, a major nut production region with interesting features. It is located within a glacial refuge at one extreme of the distribution area (northwest Spain); it has a centenary tradition of chestnut management; and more importantly, it shows an unusual degree of genetic isolation. Seven nuclear microsatellite markers were selected to analyze the genetic variability and structure of 169 local trees grafted for nut production. We analyzed in the same manner 62 local nuts. The selected loci were highly discriminant for the genotypes studied, giving a combined probability of identity of 6.1 × 10−6. An unprecedented density of trees was sampled for this project over the entire region, and nuts were collected representing 18 cultivars marketed by local producers. Several instances of misclassification by local growers were detected. Fixation index estimates and analysis of molecular variance (AMOVA) data are supportive of an unexpectedly high level of genetic differentiation in El Bierzo, larger than that estimated in a previous study with broader geographical scope but based on limited local sampling (Pereira-Lorenzo et al., Tree Genet Genomes 6: 701–715, 2010a). Likewise, we have determined that clonality due to grafting had been previously overestimated. In line with these observations, no significant spatial structure was found using both a model-based Bayesian procedure and Mantel’s tests. Taken together, our results evidence the need for more fine-scale genetic studies if conservation strategies are to be efficiently improved.