Bayesian classifiers for detecting HGT using fixed and variable order markov models of genomic signatures

MOTIVATION: Analyses of genomic signatures are gaining attention as they allow studies of species-specific relationships without involving alignments of homologous sequences. A na?ve Bayesian classifier was built to discriminate between different bacterial compositions of short oligomers, also known as DNA words. The classifier has proven successful in identifying foreign genes in Neisseria meningitis. In this study we extend the classifier approach using either a fixed higher order Markov model (Mk) or a variable length Markov model (VLMk). RESULTS: We propose a simple algorithm to lock a variable length Markov model to a certain number of parameters and show that the use of Markov models greatly increases the flexibility and accuracy in prediction to that of a na?ve model. We also test the integrity of classifiers in terms of false-negatives and give estimates of the minimal sizes of training data. We end the report by proposing a method to reject a false hypothesis of horizontal gene transfer. AVAILABILITY: Software and Supplementary information available at www.cs.chalmers.se/~dalevi/genetic_sign_classifiers/.     

Greenhouse Gas Profile of a Plastic Material Derived from a Genetically Modified Plant

Abstract: This article reports an assessment of the global warming potential associated with the life cycle of a biopolymer (poly(hydroxyalkanoate) or PHA) produced in genetically engineered corn developed by Monsanto. The grain corn is harvested in a conventional manner, and the polymer is extracted from the corn stover (i.e., residues such as stalks, leaves and cobs), which would be otherwise left on the field. While corn farming was assessed based on current practice, four different hypothetical PHA production scenarios were tested for the extraction process. Each scenario differed in the energy source used for polymer extraction and compounding, and the results were compared to polyethylene (PE). The first scenario involved burning of the residual biomass (primarily cellulose) remaining after the polymer was extracted from the stover. In the three other scenarios, the use of conventional energy sources of coal, oil, and natural gas were investigated. This study indicates that an integrated system, wherein biomass energy from corn stover provides energy for polymer processing, would result in a better greenhouse gas profile for PHA than for PE. However, plant-based PHA production using fossil fuel sources provides no greenhouse gas advantage over PE, in fact scoring worse than PE. These results are based on a "cradle-to-pellet" modeling as the PHA end-of-life was not quantitatively studied due to complex issues surrounding the actual fate of postconsumer PHA.