Quartet mapping and the extent of lateral transfer in bacterial genomes

Several recent analyses have used quartet-based methods to assess the congruence among phylogenies derived for large sets of genes from prokaryotic genomes. The principal conclusion from these studies is that lateral gene transfer (LGT) has blurred prokaryotic phylogenies to such a degree that the darwinian scheme of treelike evolution might be abandoned in favor of a net or web. Here, we focus on one of these methods, quartet mapping, and show that its application can lead to overestimation of the extent of inferred LGT in prokaryotes, particularly when applied to distantly related taxa.     

Analysis of survival data with cross-effects of survival functions

We present a model and semiparametric estimation procedures for analysis of survival data with cross-effects (CE) of survival functions. Finite sample properties of the estimators are analyzed by simulation. A goodness-of-fit test for the proportional hazards model against the CE model is proposed. The well known data concerning effects of chemotherapy and radiotherapy on the survival times of gastric cancer patients is analyzed as an example.     

Evaluating the performance of likelihood methods for detecting population structure and migration

A plethora of statistical models have recently been developed to estimate components of population genetic history. Very few of these methods, however, have been adequately evaluated for their performance in accurately estimating population genetic parameters of interest. In this paper, we continue a research program of evaluation of population genetic methods through computer simulation. Specifically, we examine the software MIGRATEE-N 1.6.8 and test the accuracy of this software to estimate genetic diversity (Theta), migration rates, and confidence intervals. We simulated nucleotide sequence data under a neutral coalescent model with lengths of 500 bp and 1000 bp, and with three different per site Theta values of (0.00025, 0.0025, 0.025) crossed with four different migration rates (0.0000025, 0.025, 0.25, 2.5) to construct 1000 evolutionary trees per-combination per-sequence-length. We found that while MIGRATEE-N 1.6.8 performs reasonably well in estimating genetic diversity (Theta), it does poorly at estimating migration rates and the confidence intervals associated with them. We recommend researchers use this software with caution under conditions similar to those used in this evaluation.     

Phylogenetic and biogeographic diversification of Rhus (Anacardiaceae) in the Northern Hemisphere

Sequences of internal transcribed spacers (ITS) of nuclear ribosomal DNA, the chloroplast ndhF gene, and chloroplast trnL-F regions (trnL intron, and trnL [UAA] 3' exon-trnF [GAA] intergenic spacer) were used for phylogenetic analyses of Rhus, a genus disjunctly distributed in Asia, Europe, Hawaii, North America, and Northern Central America. Both ITS and cpDNA data sets support the monophyly of Rhus. The monophyly of subgenus Rhus was suggested by the combined cpDNA and ITS data, and largely supported in the cpDNA data except that Rhus microphylla of subgenus Lobadium was nested within it. The monophyly of subgenus Lobadium was strongly supported in the ITS data, whereas the cpDNA data revealed two main clades within the subgenus, which formed a trichotomy with the clade of subgenus Rhus plus R. microphylla. The ITS and cpDNA trees differ in the positions of Rhus michauxii, R. microphylla, and Rhus rubifolia, and hybridization may have caused this discordance. Fossil evidence indicates that Rhus dates back to the early Eocene. The penalized likelihood method was used to estimate divergence times, with fossils of Rhus subgenus Lobadium, Pistacia and Toxicodendron used for age constraints. Rhus diverged from its closest relative at 49.1+/-2.1 million years ago (Ma), the split of subgenus Lobadium and subgenus Rhus was at 38.1+/-3.0 Ma. Rhus most likely migrated from North America into Asia via the Bering Land Bridge during the Late Eocene (33.8+/-3.1 Ma). Rhus coriaria from southern Europe and western Asia diverged from its relatives in eastern Asia at 24.4+/-3.2 Ma. The Hawaiian Rhus sandwicensis diverged from the Asian Rhus chinensis at 13.5+/-3.0 Ma. Subgenus Lobadium was inferred to be of North American origin. Taxa of subgenus Lobadium then migrated southward to Central America. Furthermore, we herein make the following three nomenclatural combinations: (1) Searsia leptodictya (Diels) T. S. Yi, A. J. Miller and J. Wen, comb. nov., (2) Searsia pyroides (A. Rich.) T. S. Yi, A. J. Miller and J. Wen, comb. nov., and (3) Searsia undulata (Jacq.) T. S. Yi, A. J. Miller and J. Wen, because our analyses support the segregation of Searsia from Rhus.     

AFLP utility for population assignment studies: analytical investigation and empirical comparison with microsatellites

Individual-based population assignment tests have thus far mainly relied on the use of microsatellite loci. However, the logistic difficulty of screening large numbers of loci required to reach sufficient statistical power hampers the usefulness of microsatellites in situations of weak population structuring. Amplified fragment length polymorphisms (AFLP) represents an alternative for overcoming this logistical issue as the technique allows the user to characterize a much larger number of loci with a comparable analytical effort. In this study, an assignment test based on maximum likelihood for dominant markers was used to investigate the potential usefulness of AFLP for population assignment. We also compared assignment success achieved with AFLP with that obtained using microsatellites in a case study of low population differentiation involving whitefish (Coregonus clupeaformis) sympatric ecotypes. The analytical investigation showed that the minimum number of AFLP loci required to reach an assignment success of 95% stood within values that are easily achievable in many situations. This also showed how assignment success varied according to the number of AFLP loci used, their absolute frequency and their frequency differential and sampling errors, as well as the number of putative source populations. The case study showed that given a comparable analytical effort in the laboratory, AFLP were much more efficient than the microsatellite loci in discriminating the source of an individual among putative populations. AFLP resulted in higher assignment success at all levels of stringency and the log-likelihood differences between populations obtained with AFLP for each individual were much larger than those obtained with microsatellites. These results indicate that research involving individual-based population assignment methods should benefit importantly from the use of AFLP markers, especially in systems characterized by weak population structuring.     

Methods of parentage analysis in natural populations

The recent proliferation of hypervariable molecular markers has ushered in a surge of techniques for the analysis of parentage in natural and experimental populations. Consequently, the potential for meaningful studies of paternity and maternity is at an all-time high. However, the details and implementation of the multifarious techniques often differ in subtle ways that can influence the results of parentage analyses. Now is a good time to reflect on the available techniques and to consider their strengths and weaknesses. Here, we review the leading techniques in parentage analysis, with a particular emphasis on those that have been implemented in readily useable software packages. Our survey leads to some important insights with respect to the utility of the different approaches. This review should serve as a useful guide to anyone who wishes to embark on the study of parentage.     

Semiparametric estimation of tag loss and reporting rates for tag-recovery experiments using exact time-at-liberty data

We present a semiparametric likelihood approach to estimating reporting rates and tag-loss rates from the tags returned from capture-recapture studies. Such studies are commonly used to estimate critical population parameters. Tag loss rates are estimated using double-tagged animals, while reporting rates are estimated using information from high-reward tags. A likelihood function is constructed based on the conditional distribution of the type of tag returned (low or high reward, single or double tag), given that a tag has been returned. This involves many sparse 5 x 1 tag-return contingency tables, and choosing a good functional form for the tag loss rate is difficult with such data. We model tag-loss rates using monotone-smoothing splines, and use these nonparametric estimates to diagnose the parametric form of the tag-loss rate. The nonparametric methods can also be used directly to model tag-loss rates.     

Bayesian latent variable models for median regression on multiple outcomes

Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions about residual densities by relying on an approximation based on quantiles. To accommodate within-subject dependency, the quantile response categories of the surrogate outcomes are related to underlying normal variables, which depend on a latent normal response. This underlying Gaussian covariance structure simplifies interpretation and model fitting, without restricting the marginal densities of the surrogate outcomes. A Markov chain Monte Carlo algorithm is proposed for posterior computation, and the methods are applied to single-cell electrophoresis (comet assay) data from a genetic toxicology study.