Using creation science to demonstrate evolution? Senter’s strategy revisited

Senter's strategy of arguing against creationism using their own methodology focused on demonstrating a morphological continuum between birds and nonavian dinosaurs using classical multidimensional scaling (CMDS), a method used by some creationists to assign species to assist in the detection of phylogenetic 'discontinuities.' Because creationists do not typically use CMDS in the manner Senter used it, his results were re-examined using 'distance correlation,' a method used to assign species to 'created kinds.' Distance correlation using Senter's set of taxa and characters supports his conclusion of morphological continuity, but other sets of taxa with more characters do not. These results lessen the potential impact that Senter's strategy might have on creationism; however, it is possible that future fossil discoveries will provide stronger support for morphological continuity between dinosaurs and birds.     

Can indirect selection and genetic context contribute to trait diversification? A transition‐probability study of blossom‐colour evolution in two genera

Darwin recognized that biological diversity has accumulated as a result of both adaptive and nonadaptive processes. Very few studies, however, have addressed explicitly the contribution of nonadaptive processes to evolutionary diversification, and no general procedures have been established for distinguishing between adaptive and nonadaptive processes as sources of trait diversity. I use the diversification of flower colour as a model system for attempting to identify adaptive and nonadaptive causes of trait diversification. It is widely accepted that variation in flower colour reflects direct, adaptive response to divergent selective pressures generated by different pollinators. However, diversification of flower colour may also result from the effects of nonadaptive, pleiotropic relationships with vegetative traits. Floral pigments that have pleiotropic relationships to vegetative pigments may evolve and diversify in at least two nonadaptive ways. (1) Indirect response to selection on the pleiotropically related nonfloral traits may occur (indirect selection). (2) Divergent evolution in response to parallel selective pressures (e.g. selection by pollinators for visually obvious flowers) may occur because populations are at different genetic starting points, and each population follows its own genetic `line of least resistance.' A survey of literature suggests that pleiotropic relationships between flower colour and vegetative traits are common. Phylogenetically informed analyses of comparative data from Dalechampia (Euphorbiaceae) and Acer (Aceraceae), based on trait‐transition probabilities and maximum likelihood, indicated that floral and vegetative pigments are probably pleiotropically related in these genera, and this relationship better explains the diversification of floral colour than does direct selection by pollinators. In Dalechampia pink/purple floral bract colour may have originated by indirect response to selection on stem and leaf pigments. In Acer selection by pollinators for visually obvious flowers may to have led to the evolution of red or purple flowers in lineages synthesizing and deploying red anthocyanins in leaves, and pale‐green or yellow flowers in species not deploying red anthocyanins in vegetative structures. This study illustrates the broader potential of indirect selection and parallel selection on different genetic starting points to contribute to biological diversity, and the value of testing directly for the operation of these nonadaptive diversifying processes.     

Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross‐validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland‐dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross‐validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross‐validation results were correlated with extrapolation results, the use of cross‐validation performance metrics to guide modeling choices where knowledge is limited was supported.     

Do marker‐based paternity assignments favour heterozygous and unrelated males?

Genetic marker‐based parentage analyses are widely applied to studies of natural populations in the fields of evolutionary biology, conservation biology and ecology. When the same markers used in a parentage analysis are used together with the inferred parentage in a downstream analysis, such as the analysis of mate choice in terms of heterozygosity or relatedness, a bias may be incurred because a subset of the genotypes are favoured in parentage assignments or non‐exclusions. A previous simulation study shows that exclusion‐based paternity analyses are biased in favour of heterozygous males, and males less related to the mothers than expected under random mating. In this study, I investigated the biases of genetic paternity analyses achieved by both exclusion‐ and likelihood‐based methods, using both analytical and simulation approaches. It is concluded that while both exclusion‐ and likelihood‐based methods can lead to biased paternity assignments or non‐exclusions in favour of a subset of genotypes, the bias is not consistently towards heterozygous males or males apparently less related to mothers. Both the direction and extent of the bias depend heavily on the allele frequency distribution and the number of markers, the methods used for paternity assignments, and the estimators of relatedness. There exist important differences in the patterns of the biases between exclusion‐ and likelihood‐based paternity analysis methods. It is concluded that the markers, except when they are highly informative to yield accurate paternity assignments or exclusions, should be split into two subsets which are used separately in the paternity and downstream analyses.     

Simple stochastic birth and death models of genome evolution: was there enough time for us to evolve?

MOTIVATION: The distributions of many genome-associated quantities, including the membership of paralogous gene families can be approximated with power laws. We are interested in developing mathematical models of genome evolution that adequately account for the shape of these distributions and describe the evolutionary dynamics of their formation. RESULTS: We show that simple stochastic models of genome evolution lead to power-law asymptotics of protein domain family size distribution. These models, called Birth, Death and Innovation Models (BDIM), represent a special class of balanced birth-and-death processes, in which domain duplication and deletion rates are asymptotically equal up to the second order. The simplest, linear BDIM shows an excellent fit to the observed distributions of domain family size in diverse prokaryotic and eukaryotic genomes. However, the stochastic version of the linear BDIM explored here predicts that the actual size of large paralogous families is reached on an unrealistically long timescale. We show that introduction of non-linearity, which might be interpreted as interaction of a particular order between individual family members, allows the model to achieve genome evolution rates that are much better compatible with the current estimates of the rates of individual duplication/loss events.     

Trade-offs and the evolution of virulence of microparasites: do details matter?

Models of the within-host dynamics of parasites have been used to consider the evolution of microparasites causing acute infections in vertebrate hosts. In this paper, we use these models to examine how the level of virulence to which a parasite evolves, depends on factors such as the relationship between parasite density and its rate of transmission from infected hosts, and the mechanism of parasite-induced pathogenesis. We show that changes in the terms describing transmissibility and pathogenesis may lead to dramatic differences in the level of virulence to which a parasite evolves. This suggests that no single factor is likely to be responsible for the differences in virulence of different parasites, and that understanding of the evolution of virulence of parasites will require a detailed quantitative understanding of the interaction between the parasite and its host.     

Machine learning and genome annotation: a match meant to be?

By its very nature, genomics produces large, high-dimensional datasets that are well suited to analysis by machine learning approaches. Here, we explain some key aspects of machine learning that make it useful for genome annotation, with illustrative examples from ENCODE.     

Competitive exclusion: phylogeography’s ‘elephant in the room’?

Phylogeographic and evolutionary research programmes have successfully elucidated compelling genetic signatures of earth history. Particularly influential achievements include the demonstration of postglacial recolonization patterns for high-latitude taxa and phylogenetic demonstration of the 'progression rule' along oceanic island chains such as Hawaii. While both of these major biogeographic patterns clearly rely on rapid dispersal over long distances, their phylogeographic detection also apparently relies on the competitive exclusion of secondary dispersers. Such exclusion could occur either between or within species and might reflect fitness differences between lineages or, alternatively, neutral demographic processes (e.g. 'high-density blocking'). Regardless, such spatial genetic patterns would be rapidly eroded were it not for the failure of subsequent dispersers to contribute genetically to newly colonized populations. In addition to its role in revealing colonization patterns, competitive exclusion may also explain the maintenance of historic phylogeographic disjunctions long after the original physical barriers to dispersal have ceased to exist. Additionally, some of the most persuasive evidence of competitive exclusion comes from studies of anthropogenic extinction, where surviving lineages have subsequently expanded their ranges, apparently benefitting from the demise of their prehistoric sisters. Broadly, these biogeographic paradigms are united by the 'disconnect' between dispersal and colonization success, the latter being heavily influenced by inter- and intraspecific competition. Despite its apparent importance, such exclusion (especially within species) has received virtually no attention in the phylogeographic literature. Future studies should aim to test directly for the role of competitive exclusion in constraining the biogeography of highly dispersive taxa.     

A new perspective on phylogeny and evolution of tetraodontiform fishes (Pisces: Acanthopterygii) based on whole mitochondrial genome sequences: Basal ecological diversification?

Background  

The order Tetraodontiformes consists of approximately 429 species of fishes in nine families. Members of the order exhibit striking morphological diversity and radiated into various habitats such as freshwater, brackish and coastal waters, open seas, and deep waters along continental shelves and slopes. Despite extensive studies based on both morphology and molecules, there has been no clear resolution except for monophyly of each family and sister-group relationships of Diodontidae + Tetraodontidae and Balistidae + Monacanthidae. To address phylogenetic questions of tetraodontiform fishes, we used whole mitochondrial genome (mitogenome) sequences from 27 selected species (data for 11 species were newly determined during this study) that fully represent all families and subfamilies of Tetraodontiformes (except for Hollardinae of the Triacanthodidae). Partitioned maximum likelihood (ML) and Bayesian analyses were performed on two data sets comprising concatenated nucleotide sequences from 13 protein-coding genes (all positions included; third codon positions converted into purine [R] and pyrimidine [Y]), 22 transfer RNA and two ribosomal RNA genes (total positions = 15,084).     

Dispersal and divergence across the greatest ocean region: Do larvae matter?

For marine, benthic animals, duration of planktonic larval stagesis expected to correlate with dispersal ability, and thus speciesranges, at least where planktonic dispersal is necessary toreach habitats. Yet past analyses of larval duration and speciesranges across the insular Pacific show at most a weak correlation.So, do larvae matter in determining species ranges in such anisland setting? We analyze an extensive dataset on cowries andfind, again, that estimated larval duration does not correlatewith species ranges. Several factors can obscure a real correlation,however, including estimation error, intraspecific variation,other factors affecting dispersal, poor taxonomy, and remoteendemics. We show that taking these into consideration greatlyimproves correlation. Further evidence for the importance oflarval duration comes from diversity and speciation patterns.Diversity of poor dispersers drops more rapidly eastward acrossthe Pacific and leads to taxonomic differences in communitycomposition across the basin. Geographic scale of differentiationis strongly influenced by larval duration and leads to the mostrapid diversification at intermediate dispersal capacities.A major lesson from the phylogenetically corrected cowrie datasetis that without accurate and appropriate taxonomy, clear andimportant distributional and diversity patterns can become obscured.Inappropriate taxonomic scale can also obscure macroecologicalpatterns: cowrie tribes/subfamilies show substantial variationin the steepness of their diversity cline across the Pacificand in their proportional local abundance, showing the importanceof ecological traits in controlling distributions. In contrastsuch variation was not evident in a study focused at the familylevel in corals and fishes.     

The variability of the mitochondrial genome in human aging: a key for life and death?

The impressive performance of the research in mitochondrial genetics and human aging in the last decade outlines a new scenery in which the inherited variation of the mitochondrial genome (mtDNA) may play a role in rate and quality of aging. This variation in humans was initially looked at as nearly neutral, and useful just for the reconstruction of human population history. However, recent data suggest that different mtDNA molecules are qualitatively different from each other. The aim of this paper is to discuss current ideas on the relationships among mitochondrial function, mtDNA inherited variation, and aging. The main processes where the mitochondrion is involved and the importance these processes have on aging and death of individuals will be described. A possible connection between programmed death phenomena (mitoptosis, apoptosis, phenoptosis) and rate and quality of aging will be discussed. Finally, the possible role played in these processes by the mtDNA germline variation will be explored.     

Modelling the evolution of common cuckoo host‐races: speciation or genetic swamping?

Co‐evolutionary arms races have provided clear evidence for evolutionary change, especially in host–parasite systems. The evolution of host‐specific races in the common cuckoo (Cuculus canorus), however, is also an example where sexual conflict influences the outcome. Cuckoo females benefit from better adaptation to overcome host defences, whereas cuckoo males face a trade‐off between the benefits of better adaptation to a host and the benefits of multiple mating with females from other host‐races. The outcome of this trade‐off might be genetic differentiation or prevention of it by genetic swamping. We use a simulation model to test which outcome is more likely with three sympatric cuckoo host‐races. We assume a cost for cuckoo chicks that express a host adaptation allele not suited to their foster host species and that cuckoo males that switch to another host‐race experience either a fitness benefit or cost. Over most of the parameter space, cuckoo male host‐race fidelity increases significantly with time, and gene flow between host‐races ceases within a few thousand to a hundred thousand generations. Our results hence support the idea that common cuckoo host‐races might be in the incipient stages of speciation.     

Hosts’ Responses to Parasitic Eggs: Which Cues Elicit Hosts’ Egg Discrimination?

Many hosts of the common cuckoo (Cuculus canorus) exhibit egg recognition, and reject parasitic eggs. How do hosts discriminate cuckoo eggs from their own? Hosts might be able to recognize their own eggs using the specific pigment pattern on the outer eggshell surface, which may serve as a cue for recognition. We tested if patterns of egg pigments (spottedness) contain this information by manipulating spot density of great reed warbler eggs (Acrocephalus arundinaceus). We also manipulated the colour of eggs when the original spot pattern remained the same. Spot density (approximately 15–75%) did not significantly affect rejection rate (8–20% rejection), but when spots fully covered the eggs, i.e. the eggshell was plain dark brown, rejection rate increased abruptly to 100%. A loglinear model revealed the significant influence of colour on rejection rates, although there was no interactive effect between spottedness and colour. Our results strongly support the differential use of egg markers in host’s egg discrimination, suggesting that spot density has limited importance compared to eggshell colour.