PartitionTest test suite
The blind use of models of nucleotide substitution in evolutionary analyses is a common practice in the viral community. Typically, a simple model of evolution like the Kimura two-parameter model is used for estimating genetic distances and phylogenies, either because other authors have used it or because it is the default in various phylogenetic packages. Using two statistical approaches to model fitting, hierarchical likelihood ratio tests and the Akaike information criterion, we show that different viral data sets are better explained by different models of evolution. We demonstrate our results with the analysis of HIV-1 sequences from a hierarchy of samples; sequences within individuals, individuals within subtypes, and subtypes within groups. We also examine results for three different gene regions: gag, pol, and env. The Kimura two-parameter model was not selected as the best-fit model for any of these data sets, despite its widespread use in phylogenetic analyses of HIV-1 sequences. Furthermore, the model complexity increased with increasing sequence divergence. Finally, the molecular-clock hypothesis was rejected in most of the data sets analyzed, throwing into question clock-based estimates of divergence times for HIV-1. The importance of models in evolutionary analyses and their repercussions on the derived conclusions are discussed.
Sample preparation is the stage of the analytical process where greenness-related issues can likely play the most important role. With the exception of direct methods for solid sample analysis, for most analytical methods it is necessary to carry out a certain number of operations to make the sample amenable to the instrument. These operations, which may include digestion, extraction, dissolution, preconcentration and clean-up, typically require the use of large amounts of acids, organic solvents, and in general, chemicals that can often be persistent, bioaccumulative and toxic (PBT) as well as operating conditions that can become unsafe and energy-consuming. Therefore, sample preparation stages should be targeted as a priority when green chemistry principles are to be adapted to analytical activities. This chapter is devoted to the discussion of most relevant sample preparation strategies that approach the fulfilment of the green chemistry principles. Thus, digestion and extraction strategies from solid samples for both inorganic and organic analysis are approached using microwaves and ultrasound, followed by a discussion of modern extraction techniques, such as microwave-assisted extraction, supercritical fluid extraction, pressurized liquid extraction and solid-phase extraction for trace organic analysis. Microextraction techniques also deserve a place here, since a high degree of greenness is achieved when they are implemented in analytical methodology. Finally, application of surfactants in techniques such as cloud point extraction or membranes that allow minimizing the use of organic solvents for analysis of liquid samples are discussed.
Summary The history of particular genes and that of the species that carry them can be different due to different reasons. In particular, gene trees and species trees can truly differ due to well-known evolutionary processes like gene duplication and loss, lateral gene transfer or incomplete lineage sorting. Different species tree reconstruction methods have been developed to take this incongruence into account, which can be divided grossly into supertree and supermatrix approaches. Here, we introduce a new Bayesian hierarchical model that we have recently developed and implemented in the program Guenomu, that considers multiple sources of gene tree/species tree disagreement. Guenomu takes as input the posterior distributions of unrooted gene tree topologies for multiple gene families, in order to estimate the posterior distribution of rooted species tree topologies.
