Phylogeny of Arvicolinae (Mammalia,Cricetidae): utility of morphological and molecular data sets in a recently radiating clade

Phylogenetic relationships within the Arvicolinae are examined based on two genes (mitochondrial cytb, nuclear GHR exon 10) and 296 morphological, developmental, behavioural, ecological and cytogenetic characters. To inspect the phylogenetic ‘behaviour’ of individual taxa, basic maximum‐parsimony and Bayesian phylogenetic analyses were accompanied by experiments based on different data‐partition combinations, ‘slow–fast’ character weighting, and inclusion/exclusion of individual problematic taxa. Ellobius, Prometheomys and Lagurus are the most basal arvicolines; Dicrostonyx, Phenacomys and Arborimus form a clade (Dicrostonychini s.lat.); the ‘core arvicolines’ include three subclades: Lemmini (Synaptomys, Lemmus, Myopus), Clethrionomyini (Eothenomys, Myodes) and Arvicolini (Arvicola, Chionomys, Stenocranius and Microtus, the last with six monophyletic subgenera: Alexandromys, ‘Neodon’, Mynomes, Lasiopodomys, Terricola, and Microtus s.str.). Position of Ondatra and Dinaromys is uncertain, probably compromised by highly homoplastic morphological characters.     

Failure of the ILD to determine data combinability for slow loris phylogeny

Tests for incongruence as an indicator of among-data partition conflict have played an important role in conditional data combination. When such tests reveal significant incongruence, this has been interpreted as a rationale for not combining data into a single phylogenetic analysis. In this study of lorisiform phylogeny, we use the incongruence length difference (ILD) test to assess conflict among three independent data sets. A large morphological data set and two unlinked molecular data sets--the mitochondrial cytochrome b gene and the nuclear interphotoreceptor retinoid binding protein (exon 1)--are analyzed with various optimality criteria and weighting mechanisms to determine the phylogenetic relationships among slow lorises (Primates, Loridae). When analyzed separately, the morphological data show impressive statistical support for a monophyletic Loridae. Both molecular data sets resolve the Loridae as paraphyletic, though with different branching orders depending on the optimality criterion or character weighting used. When the three data partitions are analyzed in various combinations, an inverse relationship between congruence and phylogenetic accuracy is observed. Nearly all combined analyses that recover monophyly indicate strong data partition incongruence (P = 0.00005 in the most extreme case), whereas all analyses that recover paraphyly indicate lack of significant incongruence. Numerous lines of evidence verify that monophyly is the accurate phylogenetic result. Therefore, this study contributes to a growing body of information affirming that measures of incongruence should not be used as indicators of data set combinability.     

Phylogeny of extant and fossil Juglandaceae inferred from the integration of molecular and morphological data sets

It is widely acknowledged that integrating fossils into data sets of extant taxa is imperative for proper placement of fossils, resolution of relationships, and a better understanding of character evolution. The importance of this process has been further magnified because of the crucial role of fossils in dating divergence times. Outstanding issues remain, including appropriate methods to place fossils in phylogenetic trees, the importance of molecules versus morphology in these analyses, as well as the impact of potentially large amounts of missing data for fossil taxa. In this study we used the angiosperm clade Juglandaceae as a model for investigating methods of integrating fossils into a phylogenetic framework of extant taxa. The clade has a rich fossil record relative to low extant diversity, as well as a robust molecular phylogeny and morphological database for extant taxa. After combining fossil organ genera into composite and terminal taxa, our objectives were to (1) compare multiple methods for the integration of the fossils and extant taxa (including total evidence, molecular scaffolds, and molecular matrix representation with parsimony [MRP]); (2) explore the impact of missing data (incomplete taxa and characters) and the evidence for placing fossils on the topology; (3) simulate the phylogenetic effect of missing data by creating "artificial fossils"; and (4) place fossils and compare the impact of single and multiple fossil constraints in estimating the age of clades. Despite large and variable amounts of missing data, each of the methods provided reasonable placement of both fossils and simulated "artificial fossils" in the phylogeny previously inferred only from extant taxa. Our results clearly show that the amount of missing data in any given taxon is not by itself an operational guideline for excluding fossils from analysis. Three fossil taxa (Cruciptera simsonii, Paleoplatycarya wingii, and Platycarya americana) were placed within crown clades containing living taxa for which relationships previously had been suggested based on morphology, whereas Polyptera manningii, a mosaic taxon with equivocal affinities, was placed firmly as sister to two modern crown clades. The position of Paleooreomunnea stoneana was ambiguous with total evidence but conclusive with DNA scaffolds and MRP. There was less disturbance of relationships among extant taxa using a total evidence approach, and the DNA scaffold approach did not provide improved resolution or internal support for clades compared to total evidence, whereas weighted MRP retained comparable levels of support but lost crown clade resolution. Multiple internal minimum age constraints generally provided reasonable age estimates, but the use of single constraints provided by extinct genera tended to underestimate clade ages.     

Integrative analysis and variable selection with multiple high-dimensional data sets

In high-throughput -omics studies, markers identified from analysis of single data sets often suffer from a lack of reproducibility because of sample limitation. A cost-effective remedy is to pool data from multiple comparable studies and conduct integrative analysis. Integrative analysis of multiple -omics data sets is challenging because of the high dimensionality of data and heterogeneity among studies. In this article, for marker selection in integrative analysis of data from multiple heterogeneous studies, we propose a 2-norm group bridge penalization approach. This approach can effectively identify markers with consistent effects across multiple studies and accommodate the heterogeneity among studies. We propose an efficient computational algorithm and establish the asymptotic consistency property. Simulations and applications in cancer profiling studies show satisfactory performance of the proposed approach.     

Comparing two sets of community data: A method for testing reserve adequacy

Abstract Comparing a new set of samples to what may be considered a reference set is a common problem in ecology. The investigator may be interested in the degree of correspondence or any anomalies. For example, does a set of existing reserves adequately cover the range of communities sampled in a region? A technique for such comparisons is proposed. Being dependent solely on estimates of ecological resemblance, it is simple, efficient and robust. Significant difference is defined by means of a resemblance coefficient. A threshold value denoting significant difference can be defined either by species overlap or other attributes of the data. For presence/absence data the Czekanowski coefficient provides a suitable measure of ecological resemblance. Traditional discriminant analysis does not provide a viable alternative due to its limitations in accommodating ecological data.     

Sample size calculation for multiple testing in microarray data analysis

Microarray technology is rapidly emerging for genome-wide screening of differentially expressed genes between clinical subtypes or different conditions of human diseases. Traditional statistical testing approaches, such as the two-sample t-test or Wilcoxon test, are frequently used for evaluating statistical significance of informative expressions but require adjustment for large-scale multiplicity. Due to its simplicity, Bonferroni adjustment has been widely used to circumvent this problem. It is well known, however, that the standard Bonferroni test is often very conservative. In the present paper, we compare three multiple testing procedures in the microarray context: the original Bonferroni method, a Bonferroni-type improved single-step method and a step-down method. The latter two methods are based on nonparametric resampling, by which the null distribution can be derived with the dependency structure among gene expressions preserved and the family-wise error rate accurately controlled at the desired level. We also present a sample size calculation method for designing microarray studies. Through simulations and data analyses, we find that the proposed methods for testing and sample size calculation are computationally fast and control error and power precisely.     

Phylogenetic position of Dictyostelium inferred from multiple protein data sets

The phylogenetic position of Dictyostelium inferred from 18S rRNA data contradicts that from protein data. Protein trees always show the close affinity of Dictyostelium with animals, fungi, and plants, whereas in 18S rRNA trees the branching of Dictyostelium is placed at a position before the massive radiation of protist groups including the divergence of the three kingdoms. To settle this controversial issue and to determine the correct position of Dictyostelium, we inferred the phylogenetic relationship among Dictyostelium and the three kingdoms Animalia, Fungi, and Plantae by a maximum-likelihood method using 19 different protein data sets. It was shown at the significance level of 1 SE that the branching of Dictyostelium antedates the divergence of Animalia and Fungi, and Plantae is an outgroup of the Animalia-Fungi-Dictyostelium clade.Correspondence to: T. Miyata     

Supertree bootstrapping methods for assessing phylogenetic variation among genes in genome-scale data sets

Nonparamtric bootstrapping methods may be useful for assessing confidence in a supertree inference. We examined the performance of two supertree bootstrapping methods on four published data sets that each include sequence data from more than 100 genes. In "input tree bootstrapping," input gene trees are sampled with replacement and then combined in replicate supertree analyses; in "stratified bootstrapping," trees from each gene's separate (conventional) bootstrap tree set are sampled randomly with replacement and then combined. Generally, support values from both supertree bootstrap methods were similar or slightly lower than corresponding bootstrap values from a total evidence, or supermatrix, analysis. Yet, supertree bootstrap support also exceeded supermatrix bootstrap support for a number of clades. There was little overall difference in support scores between the input tree and stratified bootstrapping methods. Results from supertree bootstrapping methods, when compared to results from corresponding supermatrix bootstrapping, may provide insights into patterns of variation among genes in genome-scale data sets.     

The phylogeny of the austral grass subfamily Danthonioideae: Evidence from multiple data sets

The grass subfamily Danthonioideae is one of the smaller in the family. We utilize DNA sequence data from three chloroplast regions (trnL, rpoC2 and rbcL) and one nuclear region (Internal Transcribed Spacer; ITS) both singly and in combination to elucidate the relationships of the genera in the subfamily. The topology retrieved by the ITS region is not congruent with that of the plastid data, but this conflict is not strongly supported. Nine well-supported clades are retrieved by all data sets. The relationships at the base of the subfamily are clearly established, comprising a series of three clades of Merxmuellera species. The earliest diverging clade probably does not belong in Danthonioideae. The other two clades are centered in the tropical African mountains and Cape mountains respectively. A clade of predominantly North and South American Danthonia species as well as D. archboldii from New Guinea is retrieved, but the African and Asian species of Danthonia are related to African species of Merxmuellera, thus rendering Danthonia polyphyletic. The relationships of the Danthonia clade remain equivocal, as do those of the two Cortaderia clades, the Pseudopentameris and Rytidosperma clades. Paseka Mafa was tragically killed in a vehicle accident in July 2001. This paper includes information he collected during the course of his MSc in Systematics and Biodiversity Science at the University of Cape Town.     

Molecular phylogeny of the hominoids: inferences from multiple independent DNA sequence data sets

Consensus on the evolutionary relationships of humans, chimpanzees, andgorillas has not been reached, despite the existence of a number of DNAsequence data sets relating to the phylogeny, partly because not all genetrees from these data sets agree. However, given the well-known phenomenonof gene tree-species tree mismatch, agreement among gene trees is notexpected. A majority of gene trees from available DNA sequence data supportone hypothesis, but is this evidence sufficient for statistical confidencein the majority hypothesis? All available DNA sequence data sets showingphylogenetic resolution among the hominoids are grouped according togenetic linkage of their corresponding genes to form independent data sets.Of the 14 independent data sets defined in this way, 11 support a human-chimpanzee clade, 2 support a chimpanzee-gorilla clade, and one supports ahuman-gorilla clade. The hypothesis of a trichotomous speciation eventleading to Homo; Pan, and Gorilla can be firmly rejected on the basis ofthis data set distribution. The multiple-locus test (Wu 1991), whichevaluates hypotheses using gene tree-species tree mismatch probabilities ina likelihood ratio test, favors the phylogeny with a Homo-Pan clade andrejects the other alternatives with a P value of 0.002. When theprobabilities are modified to reflect effective population size differencesamong different types of genetic loci, the observed data set distributionis even more likely under the Homo-Pan clade hypothesis. Maximum-likelihoodestimates for the time between successive hominoid divergences are in therange of 300,000-2,800,000 years, based on a reasonable range of estimatesfor long-term hominoid effective population size and for generation time.The implication of the multiple-locus test is that existing DNA sequencedata sets provide overwhelming and sufficient support for ahuman-chimpanzee clade: no additional DNA data sets need to be generatedfor the purpose of estimating hominoid phylogeny. Because DNA hybridizationevidence (Caccone and Powell 1989) also supports a Homo-Pan clade, theproblem of hominoid phylogeny can be confidently considered solved.     

Combination of multiple microsatellite data sets to investigate genetic diversity and admixture of domestic cattle

Microsatellite markers are commonly used for population genetic analyses of livestock. However, up to now, combinations of microsatellite data sets or comparison of population genetic parameters from different studies and breeds has proven difficult. Often different genotyping methods have been employed, preventing standardization of microsatellite allele calling. In other cases different sets of markers have been genotyped, providing differing estimates of population genetic parameters. Here, we address these issues and illustrate a general two-step regression approach in cattle using three different sets of microsatellite data, to combine population genetics estimates of diversity and admixture. This regression-based method is independent of the loci genotyped but requires common breeds in the data sets. We show that combining microsatellite data sets can provide new insights on the origin and geographical distribution of genetic diversity and admixture in cattle, which will facilitate global management of this livestock species.     

Phylogeny and diversification patterns among vesicomyid bivalves

Vesicomyid bivalves are among the most abundant and diverse symbiotic taxa in chemosynthetic-based ecosystems: more than 100 different vesicomyid species have been described so far. In the present study, we investigated the phylogenetic positioning of recently described vesicomyid species from the Gulf of Guinea and their western Atlantic and Pacific counterparts using mitochondrial DNA sequence data. The maximum-likelihood (ML) tree provided limited support for the recent taxonomic revision of vesicomyids based on morphological criteria; nevertheless, most of the newly sequenced specimens did not cluster with their morphological conspecifics. Moreover, the observed lack of geographic clustering suggests the occurrence of independent radiations followed by worldwide dispersal. Ancestral character state reconstruction showed a significant correlation between the characters "depth" and "habitat" and the reconstructed ML phylogeny suggesting possible recurrent events of 'stepwise speciation' from shallow to deep waters in different ocean basins. This is consistent with genus or species bathymetric segregation observed from recent taxonomic studies. Altogether, our results highlight the need for ongoing re-evaluation of the morphological characters used to identify vesicomyid bivalves.     

Phylogenetic congruence and discordance among one morphological and three molecular data sets from Pontederiaceae

A morphological data set and three sources of data from the chloroplast genome (two genes and a restriction site survey) were used to reconstruct the phylogenetic history of the pickerelweed family Pontederiaceae. The chloroplast data converged towards a single tree, presumably the true chloroplast phylogeny of the family. Unrooted trees estimated from each of the three chloroplast data sets were identical or extremely similar in shape to each other and mostly robustly supported. There was no evidence of significant heterogeneity among the data sets, and the few topological differences seen among unrooted trees from each chloroplast data set are probably artifacts of sampling error on short branches. Despite well-documented differences in rates of evolution for different characters in individual data sets, equally weighted parsimony permits accurate reconstructions of chloroplast relationships in Pontederiaceae. A separate morphology-based data set yielded trees that were very different from the chloroplast trees. Although there was substantial support from the morphological evidence for several major clades supported by chloroplast trees, most of the conflicting phylogenetic structure on the morphology trees was not robust. Nonetheless, several statistical tests of incongruence indicate significant heterogeneity between molecules and morphology. The source of this apparent incongruence appears to be a low ratio of phylogenetic signal to noise in the morphological data.     

Phylogeny and distribution of the soxB gene among thiosulfate-oxidizing bacteria

A PCR protocol for the detection of sulfur-oxidizing bacteria based on soxB genes that are essential for thiosulfate oxidation by sulfur-oxidizing bacteria of various phylogenetic groups which use the 'Paracoccus sulfur oxidation' pathway was developed. Five degenerate primers were used to specifically amplify fragments of soxB genes from different sulfur-oxidizing bacteria previously shown to oxidize thiosulfate. The PCR yielded a soxB fragment of approximately 1000 bp from most of the bacteria. Amino acid and nucleotide sequences of soxB from reference strains as well as from new isolates and environmental DNA from a hydrothermal vent habitat in the North Fiji Basin were compared and used to infer relationships of soxB between sulfur-oxidizing bacteria belonging to various 16S rDNA-based phylogenetic groups. Major phylogenetic lines derived from 16S rDNA were confirmed by soxB phylogeny. Thiosulfate-oxidizing green sulfur bacteria formed a coherent group by their soxB sequences. Likewise, clearly separated branches demonstrated the distant relationship of representatives of alpha-, beta-, and gamma-Proteobacteria including representative species of the former genus Thiobacillus (now Halothiobacillus - gamma-Proteobacteria, Thiobacillus - beta-Proteobacteria and Starkeya - alpha-Proteobacteria). This general picture emerged although apparent evidence for lateral transfer of the soxB gene is indicated and comparison of soxB phylogeny and 16S rDNA phylogeny points to the significance of this gene transfer in hydrothermal vent bacterial communities of the North Fiji Basin.     

Molecular phylogeny of the Arctoidea (Carnivora): effect of missing data on supertree and supermatrix analyses of multiple gene data sets

Phylogenetic relationships of 79 caniform carnivores were addressed based on four nuclear sequence-tagged sites (STS) and one nuclear exon, IRBP, using both supertree and supermatrix analyses. We recovered the three major arctoid lineages, Ursidae, Pinnipedia, and Musteloidea, as monophyletic, with Ursidae (bears) strongly supported as the basal arctoid lineage. Within Pinnipedia, Phocidae (true seals) were sister to the Otaroidea [Otariidae (fur seals and sea lions) and Odobenidae (walrus)]. Phocid subfamily and tribal designations were supported, but the otariid subfamily split between fur seals and sea lions was not. All family designations within Musteloidea were strongly supported: Mephitidae (skunks), Ailuridae (monotypic red panda), Mustelidae (weasels, badgers, otters), and Procyonidae (raccoons). A novel hypothesis for the position of the red panda was recovered, placing it as branching after Mephitidae and before Mustelidae+Procyonidae. Within Mustelidae, subfamily taxonomic changes are considered. This study represents the most comprehensive sampling to date of the Caniformia in a molecular study and contains the most complete molecular phylogeny for the Procyonidae. Our data set was also used in an empirical examination of the effect of missing data on both supertree and supermatrix analyses. Sequence for all genes in all taxa could not be obtained, so two variants of the data set with differing amounts of missing data were examined. The amount of missing data did not have a strong effect; instead, phylogenetic resolution was more dependent on the presence of sufficient informative characters. Supertree and supermatrix methods performed equivalently with incomplete data and were highly congruent; conflicts arose only in weakly supported areas, indicating that more informative characters are required to confidently resolve close species relationships.     

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

Background  

Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms.