What's in a likelihood? Simple models of protein evolution and the contribution of structurally viable reconstructions to the likelihood

Most phylogenetic models of protein evolution assume that sites are independent and identically distributed. Interactions between sites are ignored, and the likelihood can be conveniently calculated as the product of the individual site likelihoods. The calculation considers all possible transition paths (also called substitution histories or mappings) that are consistent with the observed states at the terminals, and the probability density of any particular reconstruction depends on the substitution model. The likelihood is the integral of the probability density of each substitution history taken over all possible histories that are consistent with the observed data. We investigated the extent to which transition paths that are incompatible with a protein's three-dimensional structure contribute to the likelihood. Several empirical amino acid models were tested for sequence pairs of different degrees of divergence. When simulating substitutional histories starting from a real sequence, the structural integrity of the simulated sequences quickly disintegrated. This result indicates that simple models are clearly unable to capture the constraints on sequence evolution. However, when we sampled transition paths between real sequences from the posterior probability distribution according to these same models, we found that the sampled histories were largely consistent with the tertiary structure. This suggests that simple empirical substitution models may be adequate for interpolating changes between observed sequences during phylogenetic inference despite the fact that the models cannot predict the effects of structural constraints from first principles. This study is significant because it provides a quantitative assessment of the biological realism of substitution models from the perspective of protein structure, and it provides insight on the prospects for improving models of protein sequence evolution.     

PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

Background  

The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.     

Eradication of the House Mouse (Mus musculus) from Montague Island,New South Wales,Australia

Summary Of all the introduced mammalian pests, rodents are the most common invaders of islands and have triggered numerous extinctions around the globe. They have a short gestation period and large litter size, giving them the ability to colonise new areas rapidly. The same biological traits make them difficult to eradicate. Although the biodiversity benefits of removing exotic rodents from islands are increasingly being recognised, there are few published analyses of eradication attempts that critically evaluate eradication tools. This study examined the response of House Mouse (Mus musculus) populations to an eradication operation on Montague Island, Australia. While the specific impacts of mice have not been studied on this particular island, elsewhere they have been shown to have negative impacts on a range of species including plants, invertebrates, lizards and seabirds. On Montague Island, mouse abundance across different habitats was examined using mark–recapture data collected before and after the deployment of brodifacoum baits. Data obtained before baiting showed significantly lower numbers of mice in sites dominated by exotic grass compared with those dominated by native vegetation. Mouse numbers overall were declining during winter and the population was not breeding, making this an optimal time to undertake the eradication. Trapping immediately after the initial bait drop failed to capture any survivors, and no individuals have been detected during the 3 years since the deployment of baits. This study demonstrated that both small and large baits (0.6 and 2 g pellets) were effective in eradicating the House Mouse from Montague Island. While present, mice were probably slowing the re‐establishment of native vegetation by grazing seedlings and consuming seeds. With this pest now gone, the process of natural regeneration is expected to accelerate. The eradication of the House Mouse from Montague is likely to have other positive effects on the island’s biodiversity. The operation itself contributed to enhancing local capacity to eradicate exotic rodents from larger or more complex islands.     

On the relevance of peptide sequence permutations in shotgun proteomics studies

In collision-induced dissociation (CID) of peptides, it has been observed that rearrangement processes can take place that appear to permute/scramble the original primary structure, which may in principle adversely affect peptide identification. Here, an analysis of sequence permutation in tandem mass spectra is presented for a previously published proteomics study on P. aeruginosa (Scherl et al., J. Am. Soc. Mass Spectrom.2008, 19, 891) conducted using an LTQ-orbitrap. Overall, 4878 precursor ions are matched by considering the accurate mass (i.e., <5 ppm) of the precursor ion and at least one fragment ion that confirms the sequence. The peptides are then grouped into higher- and lower-confidence data sets, using five fragment ions as a cutoff for higher-confidence identification. It is shown that the propensity for sequence permutation increases with the length of the tryptic peptide in both data sets. A higher charge state (i.e., 3+ vs 2+) also appears to correlate with a higher appearance of permuted masses for larger peptides. The ratio of these permuted sequence ions, compared to all tandem mass spectral peaks, reaches ～25% in the higher-confidence data set, compared to an estimated incidence of false positives for permuted masses (maximum ～8%), based on a null-hypothesis decoy data set.     

Changes in the phenology of the ground beetle Pterostichus madidus (Fabricius, 1775)

Abstract A growing body of evidence shows that climate change can alter the phenology of plants and animals. In this study long‐term data from the UK Environmental Change Network (ECN) were analyzed to investigate whether there has been a change in the phenology of the ground beetle Pterostichus madidus (Fabricius, 1775). Pitfall trap data were available from 12 ECN sites across the United Kingdom, most of which have been in operation for more than 15 years. Weather and vegetation datasets were also utilized. Pitfall trap lines were categorized to eight vegetation types. Trend analysis over time was carried out first using all the available dates of capture events, then the datasets grouped by vegetation type and site. Shifts in high‐activity periods were also analyzed. P. madidus appearance dates advanced significantly at seven sites and in five vegetation types. Peak activity advanced at two sites. At one site the timing of activity became significantly later. The last day of activity did not change significantly, supporting the theory that the cessation of the activity period is more likely to be controlled by photoperiod than temperature. The relationships between phenological variables and climatic factors were also investigated. However, no significant correlations were detected. These results demonstrate that between 1992 and 2008, phenology of P. madidus at seven sites from the eight analyzed has changed. Global warming may be driving these changes and future work will investigate underlying processes.