Gene tree distributions under the coalescent process

Under the coalescent model for population divergence, lineage sorting can cause considerable variability in gene trees generated from any given species tree. In this paper, we derive a method for computing the distribution of gene tree topologies given a bifurcating species tree for trees with an arbitrary number of taxa in the case that there is one gene sampled per species. Applications for gene tree distributions include determining exact probabilities of topological equivalence between gene trees and species trees and inferring species trees from multiple datasets. In addition, we examine the shapes of gene tree distributions and their sensitivity to changes in branch lengths, species tree shape, and tree size. The method for computing gene tree distributions is implemented in the computer program COAL.     

Molecular dynamics studies of the full-length integrase-DNA complex

We have carried out a molecular dynamics (MD) simulation of full-length HIV-1 integrase (IN) dimer complexed with viral DNA with the aim of gaining information about the enzyme motion and investigating the movement of the catalytic flexible loop (residues 140-149) thought to be essential in the catalytic mechanism of IN. During the simulation, we observed quite a different behavior of this region in the presence or absence of the viral DNA. In particular, the MD results underline the crucial role of the residue Tyr143 in the mechanism of integration of viral DNA into the host chromosome. The present findings confirm the experimental data (e.g., site-directed mutagenesis experiments) showing that the loop is involved in the integration reactions and its mobility is correlated with the catalytic activity of HIV-1 integrase.     

Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana's national adoption of a universal test and treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy modified the preventative effects of the study intervention. To address such questions, we adopt a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on either the baseline hazard functions or the within-cluster dependence structure. We show that the resulting estimators for the regression parameters are consistent and asymptotically normal. We also propose and provide theoretical justification for the use of the profile composite likelihood function to construct a robust sandwich estimator for the variance. We characterize the finite-sample performance and robustness of these estimators through extensive simulation studies. Finally, we conclude by applying this stratified proportional hazards model to a re-analysis of the Botswana Combination Prevention Project, with the national adoption of a universal test and treat strategy now modeled as a time-dependent covariate.     

Improved semiparametric estimation of the proportional rate model with recurrent event data

Owing to its robustness properties, marginal interpretations, and ease of implementation, the pseudo-partial likelihood method proposed in the seminal papers of Pepe and Cai and Lin et al. has become the default approach for analyzing recurrent event data with Cox-type proportional rate models. However, the construction of the pseudo-partial score function ignores the dependency among recurrent events and thus can be inefficient. An attempt to investigate the asymptotic efficiency of weighted pseudo-partial likelihood estimation found that the optimal weight function involves the unknown variance–covariance process of the recurrent event process and may not have closed-form expression. Thus, instead of deriving the optimal weights, we propose to combine a system of pre-specified weighted pseudo-partial score equations via the generalized method of moments and empirical likelihood estimation. We show that a substantial efficiency gain can be easily achieved without imposing additional model assumptions. More importantly, the proposed estimation procedures can be implemented with existing software. Theoretical and numerical analyses show that the empirical likelihood estimator is more appealing than the generalized method of moments estimator when the sample size is sufficiently large. An analysis of readmission risk in colorectal cancer patients is presented to illustrate the proposed methodology.     

Assessing the reconstruction of macromolecular assemblies with toleranced models

We introduce toleranced models (TOMs), a generic and versatile framework meant to handle models of macromolecular assemblies featuring uncertainties on the shapes and the positions of proteins. A TOM being a continuum of nested shapes, the inner (resp. outer) ones representing high (low) confidence regions, we present topological and geometric statistics assessing features of this continuum at multiple scales. While the topological statistics qualify contacts between instances of protein types and complexes involving prescribed protein types, the geometric statistics scale the geometric accuracy of these complexes. We validate the TOM framework on recent average models of the entire nuclear pore complex (NPC) obtained from reconstruction by data integration, and confront our quantitative analysis against experimental findings related to complexes of the NPC, namely the Y-complex, the T-complex, and the Nsp1-Nup82-Nup159 complex. In the three cases, our analysis bridges the gap between global qualitative models of the entire NPC, and atomic resolution models or putative models of the aforementioned complexes. In a broader perspective, the quantitative assessments provided by the TOM framework should prove instrumental to implement a virtuous loop "model reconstruction-model selection", in the context of reconstruction by data integration.     

Effects of temperature on the dynamic behaviour of the HIV-1 nucleocapsid NCp7 and its DNA complex

The nucleocapsid protein NCp7 of human immunodeficiency virus type 1 (HIV-1) contains two highly conserved CCHC zinc fingers and is involved in many crucial steps of the virus life-cycle. A large number of physiological r?les of NCp7 involve its binding to single-stranded nucleic acid chains. Several solution structures of NCp7 and its complex with single-stranded RNA or DNA have been reported. We have investigated the changes in the dynamic behaviour experienced by the (12-53)NCp7 peptide upon DNA binding using (15)N heteronuclear relaxation measurements at 293 K and 308 K, and fluorescence spectroscopy. The relaxation data were interpreted using the reduced spectral density approach, which allowed the high-frequency motion, overall tumbling rates and the conformational exchange contributions to be characterized for various states of the peptide without using a specific motional model. Analysis of the temperature-dependent correlation times derived from both NMR and fluorescence data indicated a co-operative change of the molecular shape of apo (12-53)NCp7 around 303 K, leading to an increased hydrodynamic radius at higher temperatures. The binding of (12-53)NCp7 to a single-stranded d(ACGCC) pentanucleotide DNA led to a reduction of the conformational flexibility that characterized the apo peptide. Translational diffusion experiments as well as rotational correlation times indicated that the (12-53)NCp7/d(ACGCC) complex tumbles as a rigid object. The amplitudes of high-frequency motions were restrained in the complex and the occurrence of conformational exchange was displaced from the second zinc finger to the linker residue Ala30.     

Analysis of the structure of chemically synthesized HIV-1 protease complexed with a hexapeptide inhibitor. Part I: Crystallographic refinement of 2 Å data

The structure of a complex between a hexapeptide-based inhibitor, MVT-101, and the chemically synthesized (Aba 67,95,167,195; Aba: l-α-amino-n-butyric acid) protease from the human immunodeficiency virus (HIV-1), reported previously at 2.3 Å has now been refined to a crystallographic R factor of 15.4% at 2.0 Å resolution. Root mean square deviations from ideality are 0.18 Å for bond lengths and 2.4° for the angles. The inhibitor can be fitted to the difference electron density map in two alternative orientations. Drastic differences are observed for positions and interactions at P3/S3 and P3′/S3′ subsites of the two orientations due to different crystallographic environments. © 1997 Wiley-Liss, Inc.     

Integrating coalescent-based species delimitation with ecological niche modeling delimited two species within the Stewartia sinensis complex (Theaceae)

Accurate species delimitation is the key to precise estimation of species diversity and is fundamental to most branches of biology. Unclear species boundaries within species complexes could lead to the underestimation of species diversity. However, species delimitation of species complexes remains challenging due to the continuum of phenotypic variations. To robustly examine species boundaries within a species complex, integrative approaches in phylogeny, ecology, and morphology were applied to the Stewartia sinensis complex (Theaceae) endemic to China. Multispecies coalescent-based species delimitation using 572 nuclear ortholog sequences (anchored enrichment) supported reciprocal phylogenetic monophyly of the northern lineage (NL) and southern lineage (SL), which were not sister clades. Niche equivalency and similarity tests demonstrated significant climatic niche differentiation between NL and SL with observed Warren et al.'s I = 0.0073 and Schoener's D = 0.0021. Species distribution modeling also separated their potential distribution. Morphometric analyses suggested significant interlineage differentiation of multiple traits including the ratio of length and width, leaf width, and pedicel length, although overall similarity did not differ. Based on the integrative species concept, two distinct species were proposed with legitimate names of Stewartia gemmata for SL and S. sinensis for NL. Our empirical study of the S. sinensis complex highlights the importance of applying multiple species criteria, in particular the underappreciated niche differentiation, to species delimitation in species complexes pervasive in plants.     

High level HIV-1 DNA concentrations in brain tissues differentiate patients with post-HAART AIDS dementia complex or cardiovascular disease from those with AIDS

Highly active antiretroviral treatment (HAART) has had a significant impact on survival of individuals with acquired immunodeficiency syndrome (AIDS); however, with the longer life-span of patients with AIDS, there is increasing prevalence of AIDS dementia complex (ADC) and other non-AIDS-defining illness, and cardiovascular diseases (CVD) are also common. The influence of these varied disease processes on HIV-1 DNA concentration in brain tissues has not been thoroughly assessed in the post-HAART era. The purpose of the current study is to clarify the impacts of ADC and other complications of HIV disease on the viral load in the brains in AIDS patients with post-HARRT. We examined autopsy specimens from the brains of thirteen patients who died from complications of AIDS with quantitative polymerase chain reaction (QPCR). All but one patient had received HAART prior to death since 1995. Two patients died with severe CVD, multiple cerebrovascular atherosclerosis (CVA) throughout the brain and five patients died with ADC. Six patients had no ADC/CVA. A QPCR was used to measure the presence of HIV-1 DNA in six brain tissues (meninges, frontal grey matter, frontal white matter, temporal subcortex, cerebellum and basal ganglia). In the post-HARRT era, for non-ADC/CVA patients, HIV-1 DNA concentration in brain tissues was statistically higher than that in patients with ADC. In a new finding, two patients who suffered from severe CVD, especially CVA, also had high concentrations of HIV-1 in brain compartments not showing ADC related changes. To our knowledge, this is the first report of a relationship between the CVA and HIV-1 viral burden in brain. The current observations suggest that HAART-resistant HIV reservoirs may survive within ADC lesions of the brain as well as the macrophage rich atherosclerosis, which needs to be confirmed by more AIDS cases with CVA. Supported by the National Institutes of Health (Grant Nos. NIH ZMH1 BRB-S and UOI CA66259-09 TDC), National Science Foundation (Grant No. NSF DMI-0349669), abd Science & Technology Development Program of Shandong Province (Grant No. 2007GG30002003).     

A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more

The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.     

Accuracy of rate estimation using relaxed-clock models with a critical focus on the early metazoan radiation

In recent years, a number of phylogenetic methods have been developed for estimating molecular rates and divergence dates under models that relax the molecular clock constraint by allowing rate change throughout the tree. These methods are being used with increasing frequency, but there have been few studies into their accuracy. We tested the accuracy of several relaxed-clock methods (penalized likelihood and Bayesian inference using various models of rate change) using nucleotide sequences simulated on a nine-taxon tree. When the sequences evolved with a constant rate, the methods were able to infer rates accurately, but estimates were more precise when a molecular clock was assumed. When the sequences evolved under a model of auto-correlated rate change, rates were accurately estimated using penalized likelihood and by Bayesian inference using lognormal and exponential models of rate change, while other models did not perform as well. When the sequences evolved under a model of uncorrelated rate change, only Bayesian inference using an exponential rate model performed well. Collectively, the results provide a strong recommendation for using the exponential model of rate change if a conservative approach to divergence time estimation is required. A case study is presented in which we use a simulation-based approach to examine the hypothesis of elevated rates in the Cambrian period, and it is found that these high rate estimates might be an artifact of the rate estimation method. If this bias is present, then the ages of metazoan divergences would be systematically underestimated. The results of this study have implications for studies of molecular rates and divergence dates.     

Frequent false detection of positive selection by the likelihood method with branch-site models

Positive Darwinian selection promotes fixations of advantageous mutations during gene evolution and is probably responsible for most adaptations. Detecting positive selection at the DNA sequence level is of substantial interest because such information provides significant insights into possible functional alterations during gene evolution as well as important nucleotide substitutions involved in adaptation. Efficient detection of positive selection, however, has been difficult because selection often operates on only a few sites in a short period of evolutionary time. A likelihood-based method with branch-site models was recently introduced to overcome such difficulties. Here I examine the accuracy of the method using computer simulation. I find that the method detects positive selection in 20%-70% of cases when the DNA sequences are generated by computer simulation under no positive selection. Although the frequency of such false detection varies depending on, among other things, the tree topology, branch length, and selection scheme, the branch-site likelihood method generally gives misleading results. Thus, detection of positive selection by this method alone is unreliable. This unreliability may have resulted from its over-sensitivity to violations of assumptions made in the method, such as certain distributions of selective strength among sites and equal transition/transversion ratios for synonymous and nonsynonymous substitutions.     

Coordination of Recombination with Meiotic Progression in the Caenorhabditis elegans Germline by KIN-18, a TAO Kinase That Regulates the Timing of MPK-1 Signaling

Meiosis is a tightly regulated process requiring coordination of diverse events. A conserved ERK/MAPK-signaling cascade plays an essential role in the regulation of meiotic progression. The Thousand And One kinase (TAO) kinase is a MAPK kinase kinase, the meiotic role of which is unknown. We have analyzed the meiotic functions of KIN-18, the homolog of mammalian TAO kinases, in Caenorhabditis elegans. We found that KIN-18 is essential for normal meiotic progression; mutants exhibit accelerated meiotic recombination as detected both by analysis of recombination intermediates and by crossover outcome. In addition, ectopic germ-cell differentiation and enhanced levels of apoptosis were observed in kin-18 mutants. These defects correlate with ectopic activation of MPK-1 that includes premature, missing, and reoccurring MPK-1 activation. Late progression defects in kin-18 mutants are suppressed by inhibiting an upstream activator of MPK-1 signaling, KSR-2. However, the acceleration of recombination events observed in kin-18 mutants is largely MPK-1-independent. Our data suggest that KIN-18 coordinates meiotic progression by modulating the timing of MPK-1 activation and the progression of recombination events. The regulation of the timing of MPK-1 activation ensures the proper timing of apoptosis and is required for the formation of functional oocytes. Meiosis is a conserved process; thus, revealing that KIN-18 is a novel regulator of meiotic progression in C. elegans would help to elucidate TAO kinase’s role in germline development in higher eukaryotes.     

Crystal structure of the HIV-1 integrase core domain in complex with sucrose reveals details of an allosteric inhibitory binding site

HIV integrase (IN) is an essential enzyme in HIV replication and an important target for drug design. IN has been shown to interact with a number of cellular and viral proteins during the integration process. Disruption of these important interactions could provide a mechanism for allosteric inhibition of IN. We present the highest resolution crystal structure of the IN core domain to date. We also present a crystal structure of the IN core domain in complex with sucrose which is bound at the dimer interface in a region that has previously been reported to bind integrase inhibitors.

Structured summary

MINT-7713125: IN (uniprotkb:P04585) and IN (uniprotkb:P04585) bind (MI:0407) by X-ray crystallography (MI:0114)     

Bias analysis and the simulation‐extrapolation method for survival data with covariate measurement error under parametric proportional odds models

It has been well known that ignoring measurement error may result in substantially biased estimates in many contexts including linear and nonlinear regressions. For survival data with measurement error in covariates, there has been extensive discussion in the literature with the focus on proportional hazards (PH) models. Recently, research interest has extended to accelerated failure time (AFT) and additive hazards (AH) models. However, the impact of measurement error on other models, such as the proportional odds model, has received relatively little attention, although these models are important alternatives when PH, AFT, or AH models are not appropriate to fit data. In this paper, we investigate this important problem and study the bias induced by the naive approach of ignoring covariate measurement error. To adjust for the induced bias, we describe the simulation‐extrapolation method. The proposed method enjoys a number of appealing features. Its implementation is straightforward and can be accomplished with minor modifications of existing software. More importantly, the proposed method does not require modeling the covariate process, which is quite attractive in practice. As the precise values of error‐prone covariates are often not observable, any modeling assumption on such covariates has the risk of model misspecification, hence yielding invalid inferences if this happens. The proposed method is carefully assessed both theoretically and empirically. Theoretically, we establish the asymptotic normality for resulting estimators. Numerically, simulation studies are carried out to evaluate the performance of the estimators as well as the impact of ignoring measurement error, along with an application to a data set arising from the Busselton Health Study. Sensitivity of the proposed method to misspecification of the error model is studied as well.     

A statistical method for the estimation of window-period risk of transfusion-transmitted HIV in donor screening under non-steady state

Human immunodeficiency virus (HIV) can be transmitted by transfusion of blood even if the blood unit is test-negative for HIV. This is largely due to a time period following an infection, called the window period, during which antibodies against HIV are not detectable. Window-period risk refers to the probability for a test-negative blood unit to be infectious because of its donation during the window period. Estimation of window-period risk is important in public health for evaluating the safety of donated blood. The standard method for this estimation problem has been based on so-called incidence/window-period (IWP) models in which blood-donation and HIV-infection processes are assumed to be stochastically stationary and independent. Here we propose a new approach in which we relax this key assumption of the IWP models. We estimate window-period risk for each unit of donated blood using a given distribution of window-period risk. The proposed method utilizes the actual observed donation intervals including those of seroconversions, thereby relaxing the assumption that may not be met in practice. Bootstrap is used to compute confidence intervals without specifying the complex dynamics of the donation and infection processes. A simulation study illustrates the usefulness of the proposed method over the IWP method in scenarios where the IWP assumptions do not hold. A real application of the proposed method is presented using blood bank data from a province of northern Thailand. Advantages and limitations of the proposed method are discussed and compared with the IWP models.