A general comparison of relaxed molecular clock models

Several models have been proposed to relax the molecular clock in order to estimate divergence times. However, it is unclear which model has the best fit to real data and should therefore be used to perform molecular dating. In particular, we do not know whether rate autocorrelation should be considered or which prior on divergence times should be used. In this work, we propose a general bench mark of alternative relaxed clock models. We have reimplemented most of the already existing models, including the popular lognormal model, as well as various prior choices for divergence times (birth-death, Dirichlet, uniform), in a common Bayesian statistical framework. We also propose a new autocorrelated model, called the "CIR" process, with well-defined stationary properties. We assess the relative fitness of these models and priors, when applied to 3 different protein data sets from eukaryotes, vertebrates, and mammals, by computing Bayes factors using a numerical method called thermodynamic integration. We find that the 2 autocorrelated models, CIR and lognormal, have a similar fit and clearly outperform uncorrelated models on all 3 data sets. In contrast, the optimal choice for the divergence time prior is more dependent on the data investigated. Altogether, our results provide useful guidelines for model choice in the field of molecular dating while opening the way to more extensive model comparisons.     

Detecting the coevolution of biosequences--an example of RNA interaction prediction

A probabilistic graphical model is proposed in order to detect the coevolution between different sites in biological sequences. The model extends the continuous-time Markov process of sequence substitution for single nucleic or amino acids and imposes general constraints regarding simultaneous changes on the substitution rate matrix. Given a multiple sequence alignment for each molecule of interest and a phylogenetic tree, the model can predict potential interactions within or between nucleic acids and proteins. Initial validation of the model is carried out using tRNA and 16S rRNA sequence data. The model accurately identifies the secondary interactions of tRNA as well as several known tertiary interactions. In addition, results on 16S rRNA data indicate this general and simple coevolutionary model outperforms several other parametric and nonparametric methods in predicting secondary interactions. Furthermore, the majority of the putative predictions exhibit either direct contact or proximity of the nucleotide pairs in the 3-dimensional structure of the Thermus thermophilus ribosomal small subunit. The results on RNA data suggest a general model of coevolution might be applied to other types of interactions between protein, DNA, and RNA molecules.     

Performance of a new invariants method on homogeneous and nonhomogeneous quartet trees

An attempt to use phylogenetic invariants for tree reconstruction was made at the end of the 80s and the beginning of the 90s by several researchers (the initial idea due to Lake [1987] and Cavender and Felsenstein [1987]). However, the efficiency of methods based on invariants is still in doubt (Huelsenbeck 1995; Jin and Nei 1990). Probably because these methods only used few generators of the set of phylogenetic invariants. The method studied in this paper was first introduced in Casanellas et al. (2005) and it is the first method based on invariants that uses the "whole" set of generators for DNA data. The simulation studies performed in this paper prove that it is a very competitive and highly efficient phylogenetic reconstruction method, especially for nonhomogeneous models on phylogenetic trees.     

The location and characterisation of the O-linked glycans of the human insulin receptor

O-linked glycosylation is a post-translational and post-folding event involving exposed S/T residues at beta-turns or in regions with extended conformation. O-linked sites are difficult to predict from sequence analyses compared to N-linked sites. Here we compare the results of chemical analyses of isolated glycopeptides with the prediction using the neural network prediction method NetOGlyc3.1, a procedure that has been reported to correctly predict 76% of O-glycosylated residues in proteins. Using the heavily glycosylated human insulin receptor as the test protein six sites of mucin-type O-glycosylation were found at residues T744, T749, S757, S758, T759, and T763 compared to the three sites (T759 and T763- correctly, T756- incorrectly) predicted by the neural network method. These six sites occur in a 20 residue segment that begins nine residues downstream from the start of the insulin receptor beta-chain. This region which also includes N-linked glycosylation sites at N742 and N755, is predicted to lack secondary structure and is followed by residues 765-770, the known linear epitope for the monoclonal antibody 18-44.     

Quantile regression for longitudinal data using the asymmetric Laplace distribution

In longitudinal studies, measurements of the same individuals are taken repeatedly through time. Often, the primary goal is to characterize the change in response over time and the factors that influence change. Factors can affect not only the location but also more generally the shape of the distribution of the response over time. To make inference about the shape of a population distribution, the widely popular mixed-effects regression, for example, would be inadequate, if the distribution is not approximately Gaussian. We propose a novel linear model for quantile regression (QR) that includes random effects in order to account for the dependence between serial observations on the same subject. The notion of QR is synonymous with robust analysis of the conditional distribution of the response variable. We present a likelihood-based approach to the estimation of the regression quantiles that uses the asymmetric Laplace density. In a simulation study, the proposed method had an advantage in terms of mean squared error of the QR estimator, when compared with the approach that considers penalized fixed effects. Following our strategy, a nearly optimal degree of shrinkage of the individual effects is automatically selected by the data and their likelihood. Also, our model appears to be a robust alternative to the mean regression with random effects when the location parameter of the conditional distribution of the response is of interest. We apply our model to a real data set which consists of self-reported amount of labor pain measurements taken on women repeatedly over time, whose distribution is characterized by skewness, and the significance of the parameters is evaluated by the likelihood ratio statistic.     

Species richness of migratory birds is influenced by global climate change

Aim  Global climate change is increasingly influencing ecosystems. Long-term effects on the species richness and composition of ecological communities have been predicted using modelling approaches but, so far, hardly demonstrated in the field. Here, we test whether changes in the composition of bird communities have been influenced by recent climate change.
Location  Europe.
Methods  We focus on the proportion of migratory and resident bird species because these groups are expected to respond differently to climatic change. We used the spatial relationship between climatic factors and bird communities in Europe to predict changes in 21 European bird communities under recent climate change.
Results  Observed changes corresponded significantly to predicted changes and could not be explained by the effects of spatial autocorrelation. Alternative factors such as changes in land use were tested in a first approximation as well but no effects were found.
Main conclusions  This study demonstrates that global climate change has already influenced the species richness and composition of European bird communities.     

Statistical software for gene mapping by admixture linkage disequilibrium

Admixture mapping is a statistical methodology that detects genetic variants in recently admixed populations that are responsible for ethnic differences in disease risk. Three software packages are now available for admixture mapping and we provide a brief overview of the statistical methods and other principal features they implement.     

基于马尔科夫链模型的长江源区土地覆盖格局变化特征

利用长江源区1986、2000与2014年3期的遥感影像,结合实地野外考察获得该地区在这3个时间点的土地覆盖类型图。根据各时期之间的土地覆盖格局的变化确定土地类型之间的转移概率,进一步完成对该地区马尔科夫链模型的构建、检验与预测。结果表明:1986—2014年,长江源区的土地覆盖格局的变化特征符合马尔科夫过程,通过马尔科夫链模型能够对该地区的覆盖格局变化过程进行有效的模拟;长江源区的土地覆被退化趋势明显,湿地、中高覆盖草地等面积不断下降,裸地、沙地以及低覆盖草地等面积则一直在增加;2000年以后,由于三江源区自然保护区的建立以及降水量的增加等因素影响,长江源区的植被退化状况得到明显改善。     

Inferring demographic structure with moccasin size data from the Promontory Caves,Utah

The moccasin assemblage Julian Steward recovered from the Promontory caves in 1930–31 provides a novel example in which material culture can be used to understand the structure of an AD thirteenth century population. Several studies shed light on the relationship between shoe size, foot size, and stature. We develop an anthropometric model for understanding the composition of the Promontory Cave population by using moccasin size as a proxy for foot size. We then predict the stature of the individual who would have worn a moccasin. Stature is closely related to age for children, subadults and adult males. Although there are predictable sex and age factors biasing moccasin discard practices, moccasin dimensions suggest a relatively large proportion of children and subadults occupied the Promontory caves. This bison and antelope hunting population appears to have thrived during its stay on Promontory Point. Am J Phys Anthropol 156:76–89, 2015 © 2014 Wiley Periodicals, Inc.