The locus of sexual selection: moving sexual selection studies into the post‐genomics era

Sexual selection drives fundamental evolutionary processes such as trait elaboration and speciation. Despite this importance, there are surprisingly few examples of genes unequivocally responsible for variation in sexually selected phenotypes. This lack of information inhibits our ability to predict phenotypic change due to universal behaviours, such as fighting over mates and mate choice. Here, we discuss reasons for this apparent gap and provide recommendations for how it can be overcome by adopting contemporary genomic methods, exploiting underutilized taxa that may be ideal for detecting the effects of sexual selection and adopting appropriate experimental paradigms. Identifying genes that determine variation in sexually selected traits has the potential to improve theoretical models and reveal whether the genetic changes underlying phenotypic novelty utilize common or unique molecular mechanisms. Such a genomic approach to sexual selection will help answer questions in the evolution of sexually selected phenotypes that were first asked by Darwin and can furthermore serve as a model for the application of genomics in all areas of evolutionary biology.     

Molecular evolution study in China: progress and future promise

China has a large land area with highly diverse topography, climate and vegetation, and animal resources and is ranked eighth in the world and first in the Northern Hemisphere on richness of biodiversity. Even though little work on molecular evolution had been reported a decade ago, studies on both the evolution of macromolecules and the molecular phylogeny have become active in China in recent years. This review highlights some of the interesting and important developments in molecular evolution study in China. Chinese scientists have made significant contribution on the methods inferring phylogeny and biogeography of animals and plants in East Asia using molecular data. Studies on population and conservation genetics of animals and plants, such as Golden monkey and Chinese sturgeon, provided useful information for conserving the endangered species. East and South Asia has been demonstrated to be one of the centres of domestication. Origin and evolution of genes and gene families have been explored, which shed new insight on the genetic mechanism of adaptation. In the genomic era, Chinese researchers also made a transition from single-gene to a genomic investigation approach. Considering the fact that amazing progress has been made in the past few years, and more and more talented young scientists are entering field, the future of molecular evolution study in China holds much promise.     

Evolutionary and ecological genomics of non‐model plants

Abstract Dissecting evolutionary dynamics of ecologically important traits is a long‐term challenge for biologists. Attempts to understand natural variation and molecular mechanisms have motivated a move from laboratory model systems to non‐model systems in diverse natural environments. Next generation sequencing methods, along with an expansion of genomic resources and tools, have fostered new links between diverse disciplines, including molecular biology, evolution, ecology, and genomics. Great progress has been made in a few non‐model wild plants, such as Arabidopsis relatives, monkey flowers, and wild sunflowers. Until recently, the lack of comprehensive genomic information has limited evolutionary and ecological studies to larger QTL (quantitative trait locus) regions rather than single gene resolution, and has hindered recognition of general patterns of natural variation and local adaptation. Further efforts in accumulating genomic data and developing bioinformatic and biostatistical tools are now poised to move this field forward. Integrative national and international collaborations and research communities are needed to facilitate development in the field of evolutionary and ecological genomics.     

Statistical methods for detecting natural selection from genomic data

In the study of molecular and phenotypic evolution, understanding the relative importance of random genetic drift and positive selection as the mechanisms for driving divergences between populations and maintaining polymorphisms within populations has been a central issue. A variety of statistical methods has been developed for detecting natural selection operating at the amino acid and nucleotide sequence levels. These methods may be largely classified into those aimed at detecting recurrent and/or recent/ongoing natural selection by utilizing the divergence and/or polymorphism data. Using these methods, pervasive positive selection has been identified for protein-coding and non-coding sequences in the genomic analysis of some organisms. However, many of these methods have been criticized by using computer simulation and real data analysis to produce excessive false-positives and to be sensitive to various disturbing factors. Importantly, some of these methods have been invalidated experimentally. These facts indicate that many of the statistical methods for detecting natural selection are unreliable. In addition, the signals that have been believed as the evidence for fixations of advantageous mutations due to positive selection may also be interpreted as the evidence for fixations of deleterious mutations due to random genetic drift. The genomic diversity data are rapidly accumulating in various organisms, and detection of natural selection may play a critical role for clarifying the relative role of random genetic drift and positive selection in molecular and phenotypic evolution. It is therefore important to develop reliable statistical methods that are unbiased as well as robust against various disturbing factors, for inferring natural selection.     

Controlling for P‐value inflation in allele frequency change in experimental evolution and artificial selection experiments

Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to P‐value inflation and hence be anticonservative. One factor known from genomewide association (GWA) studies to cause P‐value inflation is population stratification, such as relatedness among individuals. Here, we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false‐positives in tests for allele frequency change in simulated data with varying levels of population structure. However, once relatedness has been accounted for, the power to detect causal loci under selection is low. Finally, we demonstrate the presence of P‐value inflation in allele frequency change in empirical data spanning multiple generations from an artificial selection experiment on tarsus length in two free‐living populations of house sparrow and correct for this using genomic control. Our results indicate that since allele frequencies in large parts of the genome may change when selection acts on a heritable trait, such selection is likely to have considerable and immediate consequences for the eco‐evolutionary dynamics of the affected populations.     

Complex principal component and correlation structure of 16 yeast genomic variables

A quickly growing number of characteristics reflecting various aspects of gene function and evolution can be either measured experimentally or computed from DNA and protein sequences. The study of pairwise correlations between such quantitative genomic variables as well as collective analysis of their interrelations by multidimensional methods have delivered crucial insights into the processes of molecular evolution. Here, we present a principal component analysis (PCA) of 16 genomic variables from Saccharomyces cerevisiae, the largest data set analyzed so far. Because many missing values and potential outliers hinder the direct calculation of principal components, we introduce the application of Bayesian PCA. We confirm some of the previously established correlations, such as evolutionary rate versus protein expression, and reveal new correlations such as those between translational efficiency, phosphorylation density, and protein age. Although the first principal component primarily contrasts genomic change and protein expression, the second component separates variables related to gene existence and expressed protein functions. Enrichment analysis on genes affecting variable correlations unveils classes of influential genes. For example, although ribosomal and nuclear transport genes make important contributions to the correlation between protein isoelectric point and molecular weight, protein synthesis and amino acid metabolism genes help cause the lack of significant correlation between propensity for gene loss and protein age. We present the novel Quagmire database (Quantitative Genomics Resource) which allows exploring relationships between more genomic variables in three model organisms-Escherichia coli, S. cerevisiae, and Homo sapiens (http://webclu.bio.wzw.tum.de:18080/quagmire).     

Spliceosomal introns as tools for genomic and evolutionary analysis

Over the past 5 years, the availability of dozens of whole genomic sequences from a wide variety of eukaryotic lineages has revealed a very large amount of information about the dynamics of intron loss and gain through eukaryotic history, as well as the evolution of intron sequences. Implicit in these advances is a great deal of information about the structure and evolution of surrounding sequences. Here, we review the wealth of ways in which structures of spliceosomal introns as well as their conservation and change through evolution may be harnessed for evolutionary and genomic analysis. First, we discuss uses of intron length distributions and positions in sequence assembly and annotation, and for improving alignment of homologous regions. Second, we review uses of introns in evolutionary studies, including the utility of introns as indicators of rates of sequence evolution, for inferences about molecular evolution, as signatures of orthology and paralogy, and for estimating rates of nucleotide substitution. We conclude with a discussion of phylogenetic methods utilizing intron sequences and positions.     

Theoretical and Applied Aspects of Comparative Genomics of Vertebrates

The Human Genome Project stimulated the development of efficient strategies and relevant hardware for complete genome sequencing. The comparative genomic approach extends the possibilities of using the sequencing data to identify new genes or conserved regulatory regions by means of nucleotide sequence alignment of the particular regions of the mouse and human genomes, or to trace the evolutionary events resulting in the genome structure of modern mammals. The review focuses on the use of new molecular cytogenetic methods along with computer-aided analysis of the genomes in vertebrates. Several factors hindering data analysis are considered. The currently available information on gene evolution rate inferred from comparative genomic data is presented. The origin and evolution of the genomes of several species are discussed.     

Fundamental and applied aspects of comparative genomics of vertebrates

The Human Genome Project stimulated the development of efficient strategies and relevant hardware for complete genome sequencing. The comparative genomic approach extends the possibilities of using the sequencing data to identify new genes or conserved regulatory regions by means of nucleotide sequence alignment of the particular regions of the mouse and human genomes, or to trace the evolutionary events resulting in the genome structure of modern mammals. The review focuses on the use of new molecular cytogenetic methods along with computer-aided analysis of the genomes in vertebrates. Several factors hindering data analysis are considered. The currently available information on gene evolution rate inferred from comparative genomic data is presented. The origin and evolution of the genomes of several species are discussed.     

Understanding phylogenetic incongruence: lessons from phyllostomid bats

All characters and trait systems in an organism share a common evolutionary history that can be estimated using phylogenetic methods. However, differential rates of change and the evolutionary mechanisms driving those rates result in pervasive phylogenetic conflict. These drivers need to be uncovered because mismatches between evolutionary processes and phylogenetic models can lead to high confidence in incorrect hypotheses. Incongruence between phylogenies derived from morphological versus molecular analyses, and between trees based on different subsets of molecular sequences has become pervasive as datasets have expanded rapidly in both characters and species. For more than a decade, evolutionary relationships among members of the New World bat family Phyllostomidae inferred from morphological and molecular data have been in conflict. Here, we develop and apply methods to minimize systematic biases, uncover the biological mechanisms underlying phylogenetic conflict, and outline data requirements for future phylogenomic and morphological data collection. We introduce new morphological data for phyllostomids and outgroups and expand previous molecular analyses to eliminate methodological sources of phylogenetic conflict such as taxonomic sampling, sparse character sampling, or use of different algorithms to estimate the phylogeny. We also evaluate the impact of biological sources of conflict: saturation in morphological changes and molecular substitutions, and other processes that result in incongruent trees, including convergent morphological and molecular evolution. Methodological sources of incongruence play some role in generating phylogenetic conflict, and are relatively easy to eliminate by matching taxa, collecting more characters, and applying the same algorithms to optimize phylogeny. The evolutionary patterns uncovered are consistent with multiple biological sources of conflict, including saturation in morphological and molecular changes, adaptive morphological convergence among nectar‐feeding lineages, and incongruent gene trees. Applying methods to account for nucleotide sequence saturation reduces, but does not completely eliminate, phylogenetic conflict. We ruled out paralogy, lateral gene transfer, and poor taxon sampling and outgroup choices among the processes leading to incongruent gene trees in phyllostomid bats. Uncovering and countering the possible effects of introgression and lineage sorting of ancestral polymorphism on gene trees will require great leaps in genomic and allelic sequencing in this species‐rich mammalian family. We also found evidence for adaptive molecular evolution leading to convergence in mitochondrial proteins among nectar‐feeding lineages. In conclusion, the biological processes that generate phylogenetic conflict are ubiquitous, and overcoming incongruence requires better models and more data than have been collected even in well‐studied organisms such as phyllostomid bats.     

Understanding Neutral Genomic Molecular Clocks

The molecular clock hypothesis is a central concept in molecular evolution and has inspired much research into why evolutionary rates vary between and within genomes. In the age of modern comparative genomics, understanding the neutral genomic molecular clock occupies a critical place. It has been demonstrated that molecular clocks run differently between closely related species, and generation time is an important determinant of lineage specific molecular clocks. Moreover, it has been repeatedly shown that regional molecular clocks vary even within a genome, which should be taken into account when measuring evolutionary constraint of specific genomic regions. With the availability of a large amount of genomic sequence data, new insights into the patterns and causes of variation in molecular clocks are emerging. In particular, factors such as nucleotide composition, molecular origins of mutations, weak selection and recombination rates are important determinants of neutral genomic molecular clocks.     

Genotyping of <Emphasis Type="Italic">Mycobacterium tuberculosis</Emphasis> using whole genome sequencing

Tuberculosis (TB) is considered one of the most serious infectious diseases worldwide. Effective control of tuberculosis infection involves multiple steps, such as reliable detection, treatment, an epidemiological control as a part of case management, and further surveillance and monitoring of TB spread in the human population. Due to the accelerating advances in molecular biology, especially in DNA sequencing, in the past decade, the application of these methods has become crucial for TB evolution studies, differentiation of Mycobacterium tuberculosis genotypes, and their distribution. Currently, several molecular genetic methods are available. The oldest typing methods (e.g., IS6110-RFLP, spoligotyping, and MIRU-VNTR) can discover the chain of transmission to the patient. Currently, whole genome sequencing facilitates is furthermore able to identify the source of infection, the transmission trays among individuals sharing the same isolate, as well as determination of the TB evolution and its resistance to antituberculotic agents. It is obvious that this technique will become a new gold standard in genotyping methods in tuberculosis molecular epidemiological studies. In this article, molecular genetic typing methods with a special focus on whole genome sequencing and data management are reviewed.     

Early vertebrate evolution

Debate over the origin and evolution of vertebrates has occupied biologists and palaeontologists alike for centuries. This debate has been refined by molecular phylogenetics, which has resolved the place of vertebrates among their invertebrate chordate relatives, and that of chordates among their deuterostome relatives. The origin of vertebrates is characterized by wide‐ranging genomic, embryologic and phenotypic evolutionary change. Analyses based on living lineages suggest dramatic shifts in the tempo of evolutionary change at the origin of vertebrates and gnathostomes, coincident with whole‐genome duplication events. However, the enriched perspective provided by the fossil record demonstrates that these apparent bursts of anatomical evolution and taxic richness are an artefact of the extinction of phylogenetic intermediates whose fossil remains evidence the gradual assembly of crown gnathostome characters in particular. A more refined understanding of the timing, tempo and mode of early vertebrate evolution rests with: (1) better genome assemblies for living cyclostomes; (2) a better understanding of the anatomical characteristics of key fossil groups, especially the anaspids, thelodonts, galeaspids and pituriaspids; (3) tests of the monophyly of traditional groups; and (4) the application of divergence time methods that integrate not just molecular data from living species, but also morphological data and extinct species. The resulting framework will provide for rigorous tests of rates of character evolution and diversification, and of hypotheses of long‐term trends in ecological evolution that themselves suffer for lack of quantitative functional tests. The fossil record has been silent on the nature of the transition from jawless vertebrates to the jawed vertebrates that have dominated communities since the middle Palaeozoic. Elucidation of this most formative of episodes likely rests with the overhaul of early vertebrate systematics that we propose, but perhaps more fundamentally with fossil grades that await discovery.     

Data mining on DNA sequences of hepatitis B virus

Extraction of meaningful information from large experimental data sets is a key element in bioinformatics research. One of the challenges is to identify genomic markers in Hepatitis B Virus (HBV) that are associated with HCC (liver cancer) development by comparing the complete genomic sequences of HBV among patients with HCC and those without HCC. In this study, a data mining framework, which includes molecular evolution analysis, clustering, feature selection, classifier learning, and classification, is introduced. Our research group has collected HBV DNA sequences, either genotype B or C, from over 200 patients specifically for this project. In the molecular evolution analysis and clustering, three subgroups have been identified in genotype C and a clustering method has been developed to separate the subgroups. In the feature selection process, potential markers are selected based on Information Gain for further classifier learning. Then, meaningful rules are learned by our algorithm called the Rule Learning, which is based on Evolutionary Algorithm. Also, a new classification method by Nonlinear Integral has been developed. Good performance of this method comes from the use of the fuzzy measure and the relevant nonlinear integral. The nonadditivity of the fuzzy measure reflects the importance of the feature attributes as well as their interactions. These two classifiers give explicit information on the importance of the individual mutated sites and their interactions toward the classification (potential causes of liver cancer in our case). A thorough comparison study of these two methods with existing methods is detailed. For genotype B, genotype C subgroups C1, C2, and C3, important mutation markers (sites) have been found, respectively. These two classification methods have been applied to classify never-seen-before examples for validation. The results show that the classification methods have more than 70 percent accuracy and 80 percent sensitivity for most data sets, which are considered high as an initial scanning method for liver cancer diagnosis.     

Conceptual bases for quantifying the role of the environment on gene evolution: the participation of positive selection and neutral evolution

To demonstrate that a given change in the environment has contributed to the emergence of a given genotypic and phenotypic shift during the course of evolution, one should ask to what extent such shifts would have occurred without environmental change. Of course, such tests are rarely practical but phenotypic novelties can still be correlated to genomic shifts in response to environmental changes if enough information is available. We surveyed and re-evaluated the published data in order to estimate the role of environmental changes on the course of species and genomic evolution. Only a few published examples clearly demonstrate a causal link between a given environmental change and the fixation of a genomic variant resulting in functional modification (gain, loss or alteration of function). Many others suggested a link between a given phenotypic shift and a given environmental change but failed to identify the underlying genomic determinant(s) and/or the associated functional consequence(s). The proportion of genotypic and phenotypic variation that is fixed concomitantly with environmental changes is often considered adaptive and hence, the result of positive selection, even though alternative causes, such as genetic drift, are rarely investigated. Therefore, the second aim herein is to review evidence for the mechanisms leading to fixation.     

EFFECTIVE POPULATION SIZE AND THE FASTER‐X EFFECT: EMPIRICAL RESULTS AND THEIR INTERPRETATION

The X or Z chromosome has several characteristics that distinguish it from the autosomes, namely hemizygosity in the heterogametic sex, and a potentially different effective population size, both of which may influence the rate and nature of evolution. In particular, there may be an accelerated rate of adaptive change for X‐linked compared to autosomal coding sequences, often referred to as the Faster‐X effect. Empirical studies have indicated that the strength of Faster‐X evolution varies among different species, and theoretical treatments have shown that demography and mating system can substantially affect the degree of Faster‐X evolution. Here we integrate genomic data on Faster‐X evolution from a variety of animals with the demographic factors, mating system, and sex chromosome regulatory characteristics that may influence it. Our results suggest that differences in effective population size and mechanisms of dosage compensation may influence the perceived extent of Faster‐X evolution, and help to explain several clade‐specific patterns that we observe.     

Inferences from tip‐calibrated phylogenies: a review and a practical guide

Molecular dating of phylogenetic trees is a growing discipline using sequence data to co‐estimate the timing of evolutionary events and rates of molecular evolution. All molecular‐dating methods require converting genetic divergence between sequences into absolute time. Historically, this could only be achieved by associating externally derived dates obtained from fossil or biogeographical evidence to internal nodes of the tree. In some cases, notably for fast‐evolving genomes such as viruses and some bacteria, the time span over which samples were collected may cover a significant proportion of the time since they last shared a common ancestor. This situation allows phylogenetic trees to be calibrated by associating sampling dates directly to the sequences representing the tips (terminal nodes) of the tree. The increasing availability of genomic data from ancient DNA extends the applicability of such tip‐based calibration to a variety of taxa including humans, extinct megafauna and various microorganisms which typically have a scarce fossil record. The development of statistical models accounting for heterogeneity in different aspects of the evolutionary process while accommodating very large data sets (e.g. whole genomes) has allowed using tip‐dating methods to reach inferences on divergence times, substitution rates, past demography or the age of specific mutations on a variety of spatiotemporal scales. In this review, we summarize the current state of the art of tip dating, discuss some recent applications, highlight common pitfalls and provide a ‘how to’ guide to thoroughly perform such analyses.     

Positive correlation between diversification rates and phenotypic evolvability can mimic punctuated equilibrium on molecular phylogenies

The hypothesis of punctuated equilibrium proposes that most phenotypic evolution occurs in rapid bursts associated with speciation events. Several methods have been developed that can infer punctuated equilibrium from molecular phylogenies in the absence of paleontological data. These methods essentially test whether the variance in phenotypes among extant species is better explained by evolutionary time since common ancestry or by the number of estimated speciation events separating taxa. However, apparent "punctuational" trait change can be recovered on molecular phylogenies if the rate of phenotypic evolution is correlated with the rate of speciation. Strong support for punctuational models can arise even if the underlying mode of trait evolution is strictly gradual, so long as rates of speciation and trait evolution covary across the branches of phylogenetic trees, and provided that lineages vary in their rate of speciation. Species selection for accelerated rates of ecological or phenotypic divergence can potentially lead to the perception that most trait divergence occurs in association with speciation events.     

<Emphasis Type="Italic">In silico</Emphasis>, biologically-inspired modelling of genomic variation generation in surface proteins of <Emphasis Type="Italic">Trypanosoma cruzi</Emphasis>

Background  

Protozoan parasites improve the likelihood of invading or adapting to the host through their capacity to present a large repertoire of surface molecules. The understanding of the mechanisms underlying the generation of antigenic diversity is crucial to aid in the development of therapies and the study of evolution. Despite advances driven by molecular biology and genomics, there is a need to gain a deeper understanding of key properties that may facilitate variation generation, models for explaining the role of genomic re-arrangements and the characterisation of surface protein families on the basis of their capacity to generate variation. Computer models may be implemented to explore, visualise and estimate the variation generation capacity of gene families in a dynamic fashion. In this paper we report the dynamic simulation of genomic variation using real T. cruzi coding sequences as inputs to a computational simulation system. The effects of random, multiple-point mutations and gene conversions on genomic variation generation were quantitatively estimated and visualised. Simulations were also implemented to investigate the potential role of pseudogenes as a source of antigenic variation in T. cruzi.