Historical introgression among the American live oaks and the comparative nature of tests for introgression

Introgressive hybridization challenges the concepts we use to define species and infer phylogenetic relationships. Methods for inferring historical introgression from the genomes of extant species, such as ABBA‐BABA tests, are widely used, however, their results can be easily misinterpreted. Because these tests are inherently comparative, they are sensitive to the effects of missing data (unsampled species) and nonindependence (hierarchical relationships among species). We demonstrate this using genomic RADseq data sampled from all extant species in the American live oaks (Quercus series Virentes), a group notorious for hybridization. By considering all species and their phylogenetic relationships, we were able to distinguish true hybridizing lineages from those that falsely appear admixed. Six of seven species show evidence of admixture, often with multiple other species, but which is explained by introgression among a few related lineages occurring in close proximity. We identify the Cuban oak as the most admixed lineage and test alternative scenarios for its origin. The live oaks form a continuous ring‐like distribution around the Gulf of Mexico, connected in Cuba, across which they could effectively exchange alleles. However, introgression appears highly localized, suggesting that oak species boundaries and their geographic ranges have remained relatively stable over evolutionary time.     

Phylogeny of the Oriental Drosophila melanogaster species group: a multilocus reconstruction

The melanogaster species group of Drosophila (subgenus Sophophora) has long been a favored model for evolutionary studies because of its morphological and ecological diversity and wide geographic distribution. However, phylogenetic relationships among species and subgroups within this lineage are not well understood. We reconstructed the phylogeny of 17 species representing 7 "oriental" species subgroups, which are especially closely related to D. melanogaster. We used DNA sequences of four nuclear and two mitochondrial loci in an attempt to obtain the best possible estimate of species phylogeny and to assess the extent and sources of remaining uncertainties. Comparison of trees derived from single-gene data sets allowed us to identify several strongly supported clades, which were also consistently seen in combined analyses. The relationships among these clades are less certain. The combined data set contains data partitions that are incongruent with each other. Trees reconstructed from the combined data set and from internally homogenous data sets consisting of three or four genes each differ at several deep nodes. The total data set tree is fully resolved and strongly supported at most nodes. Statistical tests indicated that this tree is compatible with all individual and combined data sets. Therefore, we accepted this tree as the most likely model of historical relationships. We compared the new molecular phylogeny to earlier estimates based on morphology and chromosome structure and discuss its taxonomic and evolutionary implications.     

Cultural interaction and biological distance in postclassic period Mexico

Economic, political, and cultural relationships connected virtually every population throughout Mexico during Postclassic period (AD 900–1520). Much of what is known about population interaction in prehistoric Mexico is based on archaeological or ethnohistoric data. What is unclear, especially for the Postclassic period, is how these data correlate with biological population structure. We address this by assessing biological (phenotypic) distances among 28 samples based upon a comparison of dental morphology trait frequencies, which serve as a proxy for genetic variation, from 810 individuals. These distances were compared with models representing geographic and cultural relationships among the same groups. Results of Mantel and partial Mantel matrix correlation tests show that shared migration and trade are correlated with biological distances, but geographic distance is not. Trade and political interaction are also correlated with biological distance when combined in a single matrix. These results indicate that trade and political relationships affected population structure among Postclassic Mexican populations. We suggest that trade likely played a major role in shaping patterns of interaction between populations. This study also shows that the biological distance data support the migration histories described in ethnohistoric sources. Am J Phys Anthropol 157:121–133, 2015. © 2015 Wiley Periodicals, Inc.     

Improved approximations to scaling relationships for species, populations, and ecosystems across latitudinal and elevational gradients

Historically, allometric equations relate organismal traits, such as metabolic rate, individual growth rate, and lifespan, to body mass. Similarly, Boltzmann or Q(10) factors are used to relate many organismal traits to body temperature. Allometric equations and Boltzmann factors are being applied increasingly to higher levels of biological organization in an attempt to describe aggregate properties of populations and ecosystems. They have been used previously for studies that analyse scaling relationships between populations and across latitudinal gradients. For these kinds of applications, it is crucial to be aware of the "fallacy of the averages", and it is often problematic or incorrect to simply substitute the average body mass or temperature for an entire population or ecosystem into allometric equations. We derive improved approximations to allometric equations and Boltzmann factors in terms of the central moments of body size and temperature, and we provide tests for the accuracy of these approximations. This framework is necessary for interpreting the predictions of scaling theories for large-scale systems and grants insight into which characteristics of a given distribution are important. These approximations and tests are applied to data for body size for several taxonomic groups, including groups with multiple species, and to data for temperature at locations of varying latitude, corresponding to ectothermic body temperatures. Based on these results, the accuracy and utility of these approximations as applied to biological systems are assessed. We conclude that approximations to allometric equations at the species level are extremely accurate. However, for systems with a large range in body size, evaluating the skewness and kurtosis is often necessary, so it may be advantageous to calculate the exact form for the averaged scaling relationships instead. Moreover, the improved approximation for the Boltzmann factor, which uses the average and standard deviation of temperature, is quite accurate and represents a significant improvement over previous approximations.     

Matched-pairs tests of homogeneity with applications to homologous nucleotide sequences

MOTIVATION: Most phylogenetic methods assume that the sequences of nucleotides or amino acids have evolved under stationary, reversible and homogeneous conditions. When these assumptions are violated by the data, there is an increased probability of errors in the phylogenetic estimates. Methods to examine aligned sequences for these violations are available, but they are rarely used, possibly because they are not widely known or because they are poorly understood. RESULTS: We describe and compare the available tests for symmetry of k-dimensional contingency tables from homologous sequences, and develop two new tests to evaluate different aspects of the evolutionary processes. For any pair of sequences, we consider a partition of the test for symmetry into a test for marginal symmetry and a test for internal symmetry. The proposed tests can be used to identify appropriate models for estimation of evolutionary relationships under a Markovian model. Simulations under more or less complex evolutionary conditions were done to display the performance of the tests. Finally, the tests were applied to an alignment of small-subunit ribosomal RNA sequences of five species of bacteria to outline the evolutionary processes under which they evolved. AVAILABILITY: Programs written in R to do the tests on nucleotides are available from http://www.maths.usyd.edu.au/u/johnr/testsym/     

Identifying a minimal rheological configuration: a tool for effective and efficient constitutive modeling of soft tissues

We describe a modeling methodology intended as a preliminary step in the identification of appropriate constitutive frameworks for the time-dependent response of biological tissues. The modeling approach comprises a customizable rheological network of viscous and elastic elements governed by user-defined 1D constitutive relationships. The model parameters are identified by iterative nonlinear optimization, minimizing the error between experimental and model-predicted structural (load-displacement) tissue response under a specific mode of deformation. We demonstrate the use of this methodology by determining the minimal rheological arrangement, constitutive relationships, and model parameters for the structural response of various soft tissues, including ex vivo perfused porcine liver in indentation, ex vivo porcine brain cortical tissue in indentation, and ex vivo human cervical tissue in unconfined compression. Our results indicate that the identified rheological configurations provide good agreement with experimental data, including multiple constant strain rate load/unload tests and stress relaxation tests. Our experience suggests that the described modeling framework is an efficient tool for exploring a wide array of constitutive relationships and rheological arrangements, which can subsequently serve as a basis for 3D constitutive model development and finite-element implementations. The proposed approach can also be employed as a self-contained tool to obtain simplified 1D phenomenological models of the structural response of biological tissue to single-axis manipulations for applications in haptic technologies.     

A phylogenetic analysis of the allometry of diving

The oxygen store/usage hypothesis suggests that larger animals are able to dive for longer and hence deeper because oxygen storage scales isometrically with body mass, whereas oxygen usage scales allometrically with an exponent <1 (typically 0.67-0.75). Previous tests of the allometry of diving tend to reject this hypothesis, but they are based on restricted data sets or invalid statistical analyses (which assume that every species provides independent information). Here we apply information-theoretic statistical methods that are phylogenetically informed to a large data set on diving variables for birds and mammals to describe the allometry of diving. Body mass is strongly related to all dive variables except dive:pause ratio. We demonstrate that many diving variables covary strongly with body mass and that they have allometric exponents close to 0.33. Thus, our results fail to falsify the oxygen store/usage hypothesis. The allometric relationships for most diving variables are statistically indistinguishable for birds and mammals, but birds tend to dive deeper than mammals of equivalent mass. The allometric relationships for all diving variables except mean dive duration are also statistically indistinguishable for all major taxonomic groups of divers within birds and mammals, with the exception of the procellariiforms, which, strictly speaking, are not true divers.     

Maximum likelihood estimation of marginal pairwise associations with multiple source predictors

Researchers interested in the association of a predictor with an outcome will often collect information about that predictor from more than one source. Standard multiple regression methods allow estimation of the effect of each predictor on the outcome while controlling for the remaining predictors. The resulting regression coefficient for each predictor has an interpretation that is conditional on all other predictors. In settings in which interest is in comparison of the marginal pairwise relationships between each predictor and the outcome separately (e.g., studies in psychiatry with multiple informants or comparison of the predictive values of diagnostic tests), standard regression methods are not appropriate. Instead, the generalized estimating equations (GEE) approach can be used to simultaneously estimate, and make comparisons among, the separate pairwise marginal associations. In this paper, we consider maximum likelihood (ML) estimation of these marginal relationships when the outcome is binary. ML enjoys benefits over GEE methods in that it is asymptotically efficient, can accommodate missing data that are ignorable, and allows likelihood-based inferences about the pairwise marginal relationships. We also explore the asymptotic relative efficiency of ML and GEE methods in this setting.     

Nonparametric testing for DNA copy number induced differential mRNA gene expression

Summary .  The central dogma of molecular biology relates DNA with mRNA. Array CGH measures DNA copy number and gene expression microarrays measure the amount of mRNA. Methods that integrate data from these two platforms may uncover meaningful biological relationships that further our understanding of cancer. We develop nonparametric tests for the detection of copy number induced differential gene expression. The tests incorporate the uncertainty of the calling of genomic aberrations. The test is preceded by a "tuning algorithm" that discards certain genes to improve the overall power of the false discovery rate selection procedure. Moreover, the test statistics are "shrunken" to borrow information across neighboring genes that share the same array CGH signature. For each gene we also estimate its effect, its amount of differential expression due to copy number changes, and calculate the coefficient of determination. The method is illustrated on breast cancer data, in which it confirms previously reported findings, now with a more profound statistical underpinning.     

Testing threshold and hormesis in a random effects dose-response model applied to developmental toxicity data

Here we describe a random effects threshold dose-response model for clustered binary-response data from developmental toxicity studies. For our model we assume that a hormetic effect occurs in addition to a threshold effect. Therefore, the dose-response curve is based on two components: relationships below the threshold (hormetic u-shaped model) and those above the threshold (logistic model). In the absence of hormesis and threshold effects, the estimation procedure is straightforward. We introduce score tests that are derived from a random effects hormetic-threshold dose-response model. The model and tests are applied to clustered binary data from developmental toxicity studies of animals to test for hormesis and threshold effects. We also compare the score test and likelihood ratio test to test for hormesis and threshold effects in a simulated study.     

Differences among Yanomama Indian villages: Do the patterns of allele frequencies,anthropometrics and map locations correspond?

In order to determine the degree of correspondence between sets of multivariate observations based on different kinds of traits, two new methods, derived from fundamentally different notions of “correspondence,” are adopted here and compared. Using networks or trees to represent contemporary relationships, the first method tests the similarity of the cluster or hierarchic structures implicit in two sets of data. The second approach tests the departure from perfect geometric congruence or superimposability. Computer simulation was used to generate the distributions needed for significance tests under the null hypothesis. By the first technique, we find significant correspondence among the cluster structures for geographic, allele frequency, and anthropometric data on 19 Yanomama Indian villages. The results are similar and more precise for a subset consisting of seven villages. Some of these results differ from the conclusions which would be reached with the conventional correlations based upon entries in distance tables. The direct test of congruence, used only for the data on the subset of seven villages, gives results which differ substantially from those based on cluster-structure. There are, however, similarities between the measure of congruence and the simple correlations based on entries in the distance tables. The significant correspondences observed call for some explanation. Cultural and demographic features determine the particular non-random allocation of individuals to village fragments when a village splits. These social phenomena are invoked in tentative explanation of the agreement among historical, biological, and geographic relationships of villages.     

Mitochondrial DNA,morphology, and the phylogenetic relationships of Antarctic icefishes (Notothenioidei: Channichthyidae)

The Channichthyidae is a lineage of 16 species in the Notothenioidei, a clade of fishes that dominate Antarctic near-shore marine ecosystems with respect to both diversity and biomass. Among four published studies investigating channichthyid phylogeny, no two have produced the same tree topology, and no published study has investigated the degree of phylogenetic incongruence between existing molecular and morphological datasets. In this investigation we present an analysis of channichthyid phylogeny using complete gene sequences from two mitochondrial genes (ND2 and 16S) sampled from all recognized species in the clade. In addition, we have scored all 58 unique morphological characters used in three previous analyses of channichthyid phylogenetic relationships. Data partitions were analyzed separately to assess the amount of phylogenetic resolution provided by each dataset, and phylogenetic incongruence among data partitions was investigated using incongruence length difference (ILD) tests. We utilized a parsimony-based version of the Shimodaira-Hasegawa test to determine if alternative tree topologies are significantly different from trees resulting from maximum parsimony analysis of the combined partition dataset. Our results demonstrate that the greatest phylogenetic resolution is achieved when all molecular and morphological data partitions are combined into a single maximum parsimony analysis. Also, marginal to insignificant incongruence was detected among data partitions using the ILD. Maximum parsimony analysis of all data partitions combined results in a single tree, and is a unique hypothesis of phylogenetic relationships in the Channichthyidae. In particular, this hypothesis resolves the phylogenetic relationships of at least two species (Channichthys rhinoceratus and Chaenocephalus aceratus), for which there was no consensus among the previous phylogenetic hypotheses. The combined data partition dataset provides substantial statistical power to discriminate among alternative hypotheses of channichthyid relationships. These findings suggest the optimal strategy for investigating the phylogenetic relationships of channichthyids is one that uses all available phylogenetic data in analyses of combined data partitions.     

Identification of Mendelian inconsistencies between SNP and pedigree information of sibs

Background

Using SNP genotypes to apply genomic selection in breeding programs is becoming common practice. Tools to edit and check the quality of genotype data are required. Checking for Mendelian inconsistencies makes it possible to identify animals for which pedigree information and genotype information are not in agreement.

Methods

Straightforward tests to detect Mendelian inconsistencies exist that count the number of opposing homozygous marker (e.g. SNP) genotypes between parent and offspring (PAR-OFF). Here, we develop two tests to identify Mendelian inconsistencies between sibs. The first test counts SNP with opposing homozygous genotypes between sib pairs (SIBCOUNT). The second test compares pedigree and SNP-based relationships (SIBREL). All tests iteratively remove animals based on decreasing numbers of inconsistent parents and offspring or sibs. The PAR-OFF test, followed by either SIB test, was applied to a dataset comprising 2,078 genotyped cows and 211 genotyped sires. Theoretical expectations for distributions of test statistics of all three tests were calculated and compared to empirically derived values. Type I and II error rates were calculated after applying the tests to the edited data, while Mendelian inconsistencies were introduced by permuting pedigree against genotype data for various proportions of animals.

Results

Both SIB tests identified animal pairs for which pedigree and genomic relationships could be considered as inconsistent by visual inspection of a scatter plot of pairwise pedigree and SNP-based relationships. After removal of 235 animals with the PAR-OFF test, SIBCOUNT (SIBREL) identified 18 (22) additional inconsistent animals.Seventeen animals were identified by both methods. The numbers of incorrectly deleted animals (Type I error), were equally low for both methods, while the numbers of incorrectly non-deleted animals (Type II error), were considerably higher for SIBREL compared to SIBCOUNT.

Conclusions

Tests to remove Mendelian inconsistencies between sibs should be preceded by a test for parent-offspring inconsistencies. This parent-offspring test should not only consider parent-offspring pairs based on pedigree data, but also those based on SNP information. Both SIB tests could identify pairs of sibs with Mendelian inconsistencies. Based on type I and II error rates, counting opposing homozygotes between sibs (SIBCOUNT) appears slightly more precise than comparing genomic and pedigree relationships (SIBREL) to detect Mendelian inconsistencies between sibs.     

Enrichment or depletion of a GO category within a class of genes: which test?

MOTIVATION: A number of available program packages determine the significant enrichments and/or depletions of GO categories among a class of genes of interest. Whereas a correct formulation of the problem leads to a single exact null distribution, these GO tools use a large variety of statistical tests whose denominations often do not clarify the underlying P-value computations. SUMMARY: We review the different formulations of the problem and the tests they lead to: the binomial, chi2, equality of two probabilities, Fisher's exact and hypergeometric tests. We clarify the relationships existing between these tests, in particular the equivalence between the hypergeometric test and Fisher's exact test. We recall that the other tests are valid only for large samples, the test of equality of two probabilities and the chi2-test being equivalent. We discuss the appropriateness of one- and two-sided P-values, as well as some discreteness and conservatism issues. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Sensitivity of the relative-rate test to taxonomic sampling

Relative-rate tests may be used to compare substitution rates between more than two sequences, which yields two main questions: What influence does the number of sequences have on relative-rate tests and what is the influence of the sampling strategy as characterized by the phylogenetic relationships between sequences? Using both simulations and analysis of real data from murids (APRT and LCAT nuclear genes), we show that comparing large numbers of species significantly improves the power of the test. This effect is stronger if species are more distantly related. On the other hand, it appears to be less rewarding to increase outgroup sampling than to use the single nearest outgroup sequence. Rates may be compared between paraphyletic ingroups and using paraphyletic outgroups, but unbalanced taxonomic sampling can bias the test. We present a simple phylogenetic weighting scheme which takes taxonomic sampling into account and significantly improves the relative- rate test in cases of unbalanced sampling. The answers are thus: (1) large taxonomic sampling of compared groups improves relative-rate tests, (2) sampling many outgroups does not bring significant improvement, (3) the only constraint on sampling strategy is that the outgroup be valid, and (4) results are more accurate when phylogenetic relationships between the investigated sequences are taken into account. Given current limitations of the maximum-likelihood and nonparametric approaches, the relative-rate test generalized to any number of species with phylogenetic weighting appears to be the most general test available to compare rates between lineages.      

Phylogenetic resolution within the tribe Episcieae (Gesneriaceae): congruence of ITS and NDHF sequences from parsimony and maximum-likelihood analyses

Generic relationships within Episcieae were assessed using ITS and ndhF sequences. Previous analyses of this tribe have focussed only on ndhF data and have excluded two genera, Rhoogeton and Oerstedina, which are included in this analysis. Data were analyzed using both parsimony and maximum-likelihood methods. Results from partition homogeneity tests imply that the two data sets are significantly incongruent, but when Rhoogeton is removed from the analysis, the data sets are not significantly different. The combined data sets reveal greater strength of relationships within the tribe with the exception of the position of Rhoogeton. Poorly or unresolved relationships based exclusively on ndhF data are more fully resolved with ITS data. These resolved clades include the monophyly of the genera Columnea and Paradrymonia and the sister-group relationship of Nematanthus and Codonanthe. A closer affinity between Neomortonia nummularia and N. rosea than has previously been seen is apparent from these data, although these two species are not monophyletic in any tree. Lastly, Capanea appears to be a member of Gloxinieae, although C. grandiflora remains within Episcieae. Evolution of fruit type, epiphytic habit, and presence of tubers is re-examined with the new data presented here.     

Viburnum phylogeny based on combined molecular data: implications for taxonomy and biogeography

We investigated Viburnum phylogeny using separate and combined analyses of DNA sequence data from two chloroplast and three nuclear loci. Separate analyses of nuclear and chloroplast data sets resulted in gene trees that were generally congruent with one another and with trees from two previous analyses. Our gene trees do differ in the position of section Pseudotinus, as well as in species relationships within sections Pseudotinus and Lentago. However, tests for incongruence indicate that differences between the nuclear and chloroplast data are not significant. Furthermore, gene trees from combined analyses were highly similar to those found in separate analyses, suggesting that these localized differences do not affect other parts of the tree. Our analyses provide convincing support for numerous relationships, although there is still uncertainty at the base of the tree. To facilitate future study, we propose informal names for 12 well-supported species groups, as well as for several higher-level clades. We also discuss the biogeographic implications of our phylogeny, focusing on repeated, although apparently temporally incongruent, patterns of disjunction between the Old and New Worlds.     

Geometric interpretation of gene coexpression network analysis

THE MERGING OF NETWORK THEORY AND MICROARRAY DATA ANALYSIS TECHNIQUES HAS SPAWNED A NEW FIELD: gene coexpression network analysis. While network methods are increasingly used in biology, the network vocabulary of computational biologists tends to be far more limited than that of, say, social network theorists. Here we review and propose several potentially useful network concepts. We take advantage of the relationship between network theory and the field of microarray data analysis to clarify the meaning of and the relationship among network concepts in gene coexpression networks. Network theory offers a wealth of intuitive concepts for describing the pairwise relationships among genes, which are depicted in cluster trees and heat maps. Conversely, microarray data analysis techniques (singular value decomposition, tests of differential expression) can also be used to address difficult problems in network theory. We describe conditions when a close relationship exists between network analysis and microarray data analysis techniques, and provide a rough dictionary for translating between the two fields. Using the angular interpretation of correlations, we provide a geometric interpretation of network theoretic concepts and derive unexpected relationships among them. We use the singular value decomposition of module expression data to characterize approximately factorizable gene coexpression networks, i.e., adjacency matrices that factor into node specific contributions. High and low level views of coexpression networks allow us to study the relationships among modules and among module genes, respectively. We characterize coexpression networks where hub genes are significant with respect to a microarray sample trait and show that the network concept of intramodular connectivity can be interpreted as a fuzzy measure of module membership. We illustrate our results using human, mouse, and yeast microarray gene expression data. The unification of coexpression network methods with traditional data mining methods can inform the application and development of systems biologic methods.