Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.

Phylogenetic mixture models can reduce node-density artifacts

We investigate the performance of phylogenetic mixture models in reducing a well-known and pervasive artifact of phylogenetic inference known as the node-density effect, comparing them to partitioned analyses of the same data. The node-density effect refers to the tendency for the amount of evolutionary change in longer branches of phylogenies to be underestimated compared to that in regions of the tree where there are more nodes and thus branches are typically shorter. Mixture models allow more than one model of sequence evolution to describe the sites in an alignment without prior knowledge of the evolutionary processes that characterize the data or how they correspond to different sites. If multiple evolutionary patterns are common in sequence evolution, mixture models may be capable of reducing node-density effects by characterizing the evolutionary processes more accurately. In gene-sequence alignments simulated to have heterogeneous patterns of evolution, we find that mixture models can reduce node-density effects to negligible levels or remove them altogether, performing as well as partitioned analyses based on the known simulated patterns. The mixture models achieve this without knowledge of the patterns that generated the data and even in some cases without specifying the full or true model of sequence evolution known to underlie the data. The latter result is especially important in real applications, as the true model of evolution is seldom known. We find the same patterns of results for two real data sets with evidence of complex patterns of sequence evolution: mixture models substantially reduced node-density effects and returned better likelihoods compared to partitioning models specifically fitted to these data. We suggest that the presence of more than one pattern of evolution in the data is a common source of error in phylogenetic inference and that mixture models can often detect these patterns even without prior knowledge of their presence in the data. Routine use of mixture models alongside other approaches to phylogenetic inference may often reveal hidden or unexpected patterns of sequence evolution and can improve phylogenetic inference.

Intercontinental dispersal prior to human translocation revealed in a cryptogenic invasive tree

In this study, complementary species-level and intraspecific phylogenies were used to better circumscribe the original native range and history of translocation of the invasive tree Parkinsonia aculeata. Species-level phylogenies were reconstructed using three chloroplast gene regions, and amplified fragment length polymorphism (AFLP) markers were used to reconstruct the intraspecific phylogeny. Together, these phylogenies revealed the timescale of transcontinental lineage divergence and the likely source of recent introductions of the invasive. The sequence data showed that divergence between North American and Argentinean P. aculeata occurred at least 5.7 million years ago, refuting previous hypotheses of recent dispersal between North and South America. AFLP phylogenies revealed the most likely sources of naturalized populations. The AFLP data also identified putatively introgressed plants, underlining the importance of wide sampling of AFLPs and of comparison with uniparentally inherited marker data when investigating hybridizing groups. Although P. aculeata has generally been considered North American, these data show that the original native range of P. aculeata included South America; recent introductions to Africa and Australia are most likely to have occurred from South American populations.

Genetic evidence of frequent long-distance recruitment in a vertebrate-dispersed tree

The importance of dispersal for the maintenance of biodiversity, while long-recognized, has remained unresolved. We used molecular markers to measure effective dispersal in a natural population of the vertebrate-dispersed Neotropical tree, Simarouba amara (Simaroubaceae) by comparing the distances between maternal parents and their offspring and comparing gene movement via seed and pollen in the 50 ha plot of the Barro Colorado Island forest, Central Panama. In all cases (parent-pair, mother-offspring, father-offspring, sib-sib) distances between related pairs were significantly greater than distances to nearest possible neighbours within each category. Long-distance seedling establishment was frequent: 74% of assigned seedlings established > 100 m from the maternal parent [mean = 392 +/- 234.6 m (SD), range = 9.3-1000.5 m] and pollen-mediated gene flow was comparable to that of seed [mean = 345.0 +/- 157.7 m (SD), range 57.6-739.7 m]. For S. amara we found approximately a 10-fold difference between distances estimated by inverse modelling and mean seedling recruitment distances (39 m vs. 392 m). Our findings have important implications for future studies in forest demography and regeneration, with most seedlings establishing at distances far exceeding those demonstrated by negative density-dependent effects.

Wormlike micelle formation and flow alignment of a pluronic block copolymer in aqueous solution

The self-assembly into wormlike micelles of a poly(ethylene oxide)-b-poly(propylene oxide)-b-poly(ethylene oxide) triblock copolymer Pluronic P84 in aqueous salt solution (2 M NaCl) has been studied by rheology, small-angle X-ray and neutron scattering (SAXS/SANS), and light scattering. Measurements of the flow curves by controlled stress rheometry indicated phase separation under flow. SAXS on solutions subjected to capillary flow showed alignment of micelles at intermediate shear rates, although loss of alignment was observed for high shear rates. For dilute solutions, SAXS and static light scattering data on unaligned samples could be superposed over three decades in scattering vector, providing unique information on the wormlike micelle structure over several length scales. SANS data provided information on even shorter length scales, in particular, concerning "blob" scattering from the micelle corona. The data could be modeled based on a system of semiflexible self-avoiding cylinders with a circular cross-section, as described by the wormlike chain model with excluded volume interactions. The micelle structure was compared at two temperatures close to the cloud point (47 degrees C). The micellar radius was found not to vary with temperature in this region, although the contour length increased with increasing temperature, whereas the Kuhn length decreased. These variations result in an increase of the low-concentration radius of gyration with increasing temperature. This was consistent with dynamic light scattering results, and, applying theoretical results from the literature, this is in agreement with an increase in endcap energy due to changes in hydration of the poly(ethylene oxide) blocks as the temperature is increased.

A SAXS study of flow alignment of thermotropic liquid crystal mixtures

We report on the capillary flow behaviour of thermotropic liquid crystal mixtures containing 4-n-octyl-4'-cyanobiphenyl (8CB) and 4-n-pentyl-4'-cyanobiphenyl (5CB). The liquid crystal mixtures are studied in the Nematic (N) and Smectic (SA) phases at room temperature. Polarised optical microscopy (POM), rheology and simultaneous X-ray diffraction (XRD)/capillary flow experiments are performed to characterise the system. Polarised optical microscopy reveals a dramatic change in optical texture when the 5CB content is increased from 20 to 30% in the mixtures. X-ray diffraction results show that the system goes through a SA-N phase transition, such that the mixtures are smectic for 10-20% 5CB and nematic for 30-90% 5CB. Smectic mixtures flow with the layers aligned along the flow direction (mesogens perpendicular to flow) while nematic mixtures flow with the mesogens aligned in the flow direction. Simultaneous XRD/shear flow experiments show that the SA-N transition is independent of the flow rate in the range 1-6 ml min-1. The correlation length of the liquid crystal order decreases with increasing 5CB content. Rheology is used to prove that the correlation length behaviour is related to a reduction in the viscosity of the mixture.

Formation of a one-dimensional helical alignment of water molecules within a water-mediated supramolecular helix using molecular self-assembly of a water-soluble short pseudopeptide

The reported pseudopeptide 1 adopts a double turn molecular conformation consisting of an intramolecular 9-membered turn together with a water-mediated 11-atom turn and this pseudopeptide 1 self-assembles to form a water-mediated supramolecular helical structure with internal water molecules, which are aligned in a ID helical array. (c) 2006 Elsevier Ltd. All rights reserved.

Structure, rheology and shear alignment of Pluronic block copolymer mixtures

The structure and flow behaviour of binary mixtures of Pluronic block copolymers P85 and P123 is investigated by small-angle scattering, rheometry and mobility tests. Micelle dimensions are probed by dynamic light scattering. The micelle hydrodynamic radius for the 50/50 mixture is larger than that for either P85 or P123 alone, Clue to the formation of mixed micelles with a higher association number. The phase diagram for 50/50 mixtures contains regions Of Cubic and hexagonal phases similar to those for the parent homopolymers, however the region of stability of the cubic phase is enhanced at low temperature and concentrations above 40 wt%. This is ascribed to favourable packing of the mixed micelles containing core blocks with two different chain lengths, but similar corona chain lengths. The shear flow alignment of face-centred cubic and hexagonal phases is probed by in situ small-angle X-ray or neutron scattering with simultaneous rheology. The hexagonal phase can be aligned using steady shear in a Couette geometry, however the high modulus Cubic phase cannot be aligned well in this way. This requires the application of oscillatory shear or compression. (C) 2008 Elsevier Inc. All rights reserved.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

A hybridised evolutionary algorithm for multi-criterion minimum spanning tree problems

A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.

Alignment of a model amyloid peptide fragment in bulk and at a solid surface

The alignment of model amyloid peptide YYKLVFFC is investigated in bulk and at a solid surface using a range of spectroscopic methods employing polarized radiation. The peptide is based on a core sequence of the amyloid beta (A beta) peptide, KLVFF. The attached tyrosine and cysteine units are exploited to yield information on alignment and possible formation of disulfide or dityrosine links. Polarized Raman spectroscopy on aligned stalks provides information on tyrosine orientation, which complements data from linear dichroism (LD) on aqueous solutions subjected to shear in a Couette cell. LD provides a detailed picture of alignment of peptide strands and aromatic residues and was also used to probe the kinetics of self-assembly. This suggests initial association of phenylalanine residues, followed by subsequent registry of strands and orientation of tyrosine residues. X-ray diffraction (XRD) data from aligned stalks is used to extract orientational order parameters from the 0.48 nm reflection in the cross-beta pattern, from which an orientational distribution function is obtained. X-ray diffraction on solutions subject to capillary flow confirmed orientation in situ at the level of the cross-beta pattern. The information on fibril and tyrosine orientation from polarized Raman spectroscopy is compared with results from NEXAFS experiments on samples prepared as films on silicon. This indicates fibrils are aligned parallel to the surface, with phenyl ring normals perpendicular to the surface. Possible disulfide bridging leading to peptide dimer formation was excluded by Raman spectroscopy, whereas dityrosine formation was probed by fluorescence experiments and was found not to occur except under alkaline conditions. Congo red binding was found not to influence the cross-beta XRD pattern.

Global climate change and tree nutrition: effects of elevated CO2 and temperature

Although tree nutrition has not been the primary focus of large climate change experiments on trees, we are beginning to understand its links to elevated atmospheric CO2 and temperature changes. This review focuses on the major nutrients, namely N and P, and deals with the effects of climate change on the processes that alter their cycling and availability. Current knowledge regarding biotic and abiotic agents of weathering, mobilization and immobilization of these elements will be discussed. To date, controlled environment studies have identified possible effects of climate change on tree nutrition. Only some of these findings, however, were verified in ecosystem scale experiments. Moreover, to be able to predict future effects of climate change on tree nutrition at this scale, we need to progress from studying effects of single factors to analysing interactions between factors such as elevated CO2, temperature or water availability.