The fall speeds of sub-100 mu m ice crystals

Estimates for the sedimentation rate of realistic ice crystals at sizes smaller than 100 µm are presented. These calculations, which exploit new results for the capacitance of ice crystals, are compared with laboratory studies and found to be in good agreement. The results highlight a weakness in contemporary ice particle fall speed parametrizations for very small crystals, which can lead to sedimentation rates being overestimated by a factor of two. The theoretical approach applied here may also be useful for calculating the sedimentation rate and mobility of non-spherical aerosol particles.

Recent oppositely directed trends in solar climate forcings and the global mean surface air temperature. II. Different reconstructions of the total solar irradiance variation and dependence on response time scale

We have previously placed the solar contribution to recent global warming in context using observations and without recourse to climate models. It was shown that all solar forcings of climate have declined since 1987. The present paper extends that analysis to include the effects of the various time constants with which the Earth’s climate system might react to solar forcing. The solar input waveform over the past 100 years is defined using observed and inferred galactic cosmic ray fluxes, valid for either a direct effect of cosmic rays on climate or an effect via their known correlation with total solar irradiance (TSI), or for a combination of the two. The implications, and the relative merits, of the various TSI composite data series are discussed and independent tests reveal that the PMOD composite used in our previous paper is the most realistic. Use of the ACRIM composite, which shows a rise in TSI over recent decades, is shown to be inconsistent with most published evidence for solar influences on pre-industrial climate. The conclusions of our previous paper, that solar forcing has declined over the past 20 years while surface air temperatures have continued to rise, are shown to apply for the full range of potential time constants for the climate response to the variations in the solar forcings.

Inbreeding depression and founder diversity among captive and free-living populations of the endangered pink pigeon Columba mayeri

The endemic pink pigeon has recovered from less than 20 birds in the mid-1970s to 355 free-living individuals in 2003. A major concern for the species' recovery has been the potential genetic problem of inbreeding. Captive pink pigeons bred for reintroduction were managed to maximise founder representation and minimise inbreeding. In this paper, we quantify the effect of inbreeding on survival and reproductive parameters in captive and wild populations and quantify DNA sequence variation in the mitochondrial d-loop region for pink pigeon founders. Inbreeding affected egg fertility, squab, juvenile and adult survival, but effects were strongest in highly inbred birds (F≥0.25). Inbreeding depression was more apparent in free-living birds where even moderate levels of inbreeding affected survival, although highly inbred birds were equally compromised in both captive and wild populations. Mitochondrial DNA haplotypic diversity in pink pigeon founders is low, suggesting that background inbreeding is contributing to low fertility and depressed productivity in this species, as well as comparable survival of some groups of non-inbred and nominally inbred birds. Management of wild populations has boosted population growth and may be required long-term to offset the negative effects of inbreeding depression and enhance the species' survival.

A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.

PopABC: a program to infer historical demographic parameters

PopABC is a computer package for inferring the pattern of demographic divergence of closely related populations and species. The software performs coalescent simulation in the framework of approximate Bayesian computation (ABC). PopABC can also be used to perform Bayesian model choice to discriminate between different demographic scenarios. The program can be used either for research or for education and teaching purposes.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.

Intrinsic disorder prediction from the analysis of multiple protein fold recognition models

Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

The ModFOLD server for the quality assessment of protein structural models

The reliable assessment of the quality of protein structural models is fundamental to the progress of structural bioinformatics. The ModFOLD server provides access to two accurate techniques for the global and local prediction of the quality of 3D models of proteins. Firstly ModFOLD, which is a fast Model Quality Assessment Program (MQAP) used for the global assessment of either single or multiple models. Secondly ModFOLDclust, which is a more intensive method that carries out clustering of multiple models and provides per-residue local quality assessment.

Constrained models of evolution lead to improved prediction of functional linkage from correlated gain and loss of genes

Motivation: We compare phylogenetic approaches for inferring functional gene links. The approaches detect independent instances of the correlated gain and loss of pairs of genes from species' genomes. We investigate the effect on results of basing evidence of correlations on two phylogenetic approaches, Dollo parsminony and maximum likelihood (ML). We further examine the effect of constraining the ML model by fixing the rate of gene gain at a low value, rather than estimating it from the data. Results: We detect correlated evolution among a test set of pairs of yeast (Saccharomyces cerevisiae) genes, with a case study of 21 eukaryotic genomes and test data derived from known yeast protein complexes. If the rate at which genes are gained is constrained to be low, ML achieves by far the best results at detecting known functional links. The model then has fewer parameters but it is more realistic by preventing genes from being gained more than once. Availability: BayesTraits by M. Pagel and A. Meade, and a script to configure and repeatedly launch it by D. Barker and M. Pagel, are available at http://www.evolution.reading.ac.uk .

Stocking may increase mitochondrial DNA diversity but fails to halt the decline of endangered Atlantic salmon populations

Over the last 50 years, Spanish Atlantic salmon (Salmo salar) populations have been in decline. In order to bolster these populations, rivers were stocked with fish of northern European origin during the period 1974-1996, probably also introducing the furunculosis-inducing pathogen, Aeromonas salmonicida. Here we assess the relative importance of processes influencing mitochondrial (mt)DNA variability in these populations from 1948 to 2002. Genetic material collected over this period from four rivers in northern Spain (Cantabria) was used to detect variability at the mtDNA ND1 gene. Before stocking, a single haplotype was found at high frequency (0.980). Following stocking, haplotype diversity (h) increased in all rivers (mean h before stocking was 0.041, and 0.245 afterwards). These increases were due principally to the dramatic increase in frequency of a previously very low frequency haplotype, reported at higher frequencies in northern European populations proximate to those used to stock Cantabrian rivers. Genetic structuring increased after stocking: among-river differentiation was low before stocking (1950s/1960s Phi(ST) = -0.00296-0.00284), increasing considerably at the height of stocking (1980s Phi(ST) = 0.18932) and decreasing post-stocking (1990s/2002 Phi(ST) = 0.04934-0.03852). Gene flow from stocked fish therefore seems to have had a substantial role in increasing mtDNA variability. Additionally, we found significant differentiation between individuals that had probably died from infectious disease and apparently healthy, angled fish, suggesting a possible role for pathogen-driven selection of mtDNA variation. Our results suggest that stocking with non-native fish may increase genetic diversity in the short term, but may not reverse population declines.

The automation of nested clade phylogeographic analysis

ANeCA is a fully automated implementation of Nested Clade Phylogeographic Analysis. This was originally developed by Templeton and colleagues, and has been used to infer, from the pattern of gene sequence polymorphisms in a geographically structured population, the historical demographic processes that have shaped its evolution. Until now it has been necessary to perform large parts of the procedure manually. We provide a program that will take data in Nexus sequential format, and directly output a set of inferences. The software also includes TCS v1.18 and GeoDis v2.2 as part of automation.

Analysing the ability to retain sidechain hydrogen-bonds in mutant proteins

Motivation: Hydrogen bonds are one of the most important inter-atomic interactions in biology. Previous experimental, theoretical and bioinformatics analyses have shown that the hydrogen bonding potential of amino acids is generally satisfied and that buried unsatisfied hydrogen-bond-capable residues are destabilizing. When studying mutant proteins, or introducing mutations to residues involved in hydrogen bonding, one needs to know whether a hydrogen bond can be maintained. Our aim, therefore, was to develop a rapid method to evaluate whether a sidechain can form a hydrogen-bond. Results: A novel knowledge-based approach was developed in which the conformations accessible to the residues involved are taken into account. Residues involved in hydrogen bonds in a set of high resolution crystal structures were analyzed and this analysis is then applied to a given protein. The program was applied to assess mutations in the tumour-suppressor protein, p53. This raised the number of distinct mutations identified as disrupting sidechain-sidechain hydrogen bonding from 181 in our previous analysis to 202 in this analysis.

An extensible automated protein annotation tool: standardizing input and output using validated XML

Motivation: There is a frequent need to apply a large range of local or remote prediction and annotation tools to one or more sequences. We have created a tool able to dispatch one or more sequences to assorted services by defining a consistent XML format for data and annotations. Results: By analyzing annotation tools, we have determined that annotations can be described using one or more of the six forms of data: numeric or textual annotation of residues, domains (residue ranges) or whole sequences. With this in mind, XML DTDs have been designed to store the input and output of any server. Plug-in wrappers to a number of services have been written which are called from a master script. The resulting APATML is then formatted for display in HTML. Alternatively further tools may be written to perform post-analysis.