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Many deep evolutionary divergences still remain unresolved, such as those among major taxa of the Lophotrochozoa. As alternative phylogenetic markers, the intron-exon structure of eukaryotic genomes and the patterns of absence and presence of spliceosomal introns appear to be promising. However, given the potential homoplasy of intron presence, the phylogenetic analysis of this data using standard evolutionary approaches has remained a challenge. Here, we used Mutual Information (MI) to estimate the phylogeny of Protostomia using gene structure data, and we compared these results with those obtained with Dollo Parsimony. Using full genome sequences from nine Metazoa, we identified 447 groups of orthologous sequences with 21,732 introns in 4,870 unique intron positions. We determined the shared absence and presence of introns in the corresponding sequence alignments and have made this data available in "IntronBase", a web-accessible and downloadable SQLite database. Our results obtained using Dollo Parsimony are obviously misled through systematic errors that arise from multiple intron loss events, but extensive filtering of data improved the quality of the estimated phylogenies. Mutual Information, in contrast, performs better with larger datasets, but at the same time it requires a complete data set, which is difficult to obtain for orthologs from a large number of taxa. Nevertheless, Mutual Information-based distances proved to be useful in analyzing this kind of data, also because the estimation of MI-based distances is independent of evolutionary models and therefore no pre-definitions of ancestral and derived character states are necessary.
The rise of evolutionary novelties is one of the major drivers of evolutionary diversification. African weakly-electric fishes (Teleostei, Mormyridae) have undergone an outstanding adaptive radiation, putatively owing to their ability to communicate through species-specific Electric Organ Discharges (EODs) produced by a novel, muscle-derived electric organ. Indeed, such EODs might have acted as effective pre-zygotic isolation mechanisms, hence favoring ecological speciation in this group of fishes. Despite the evolutionary importance of this organ, genetic investigations regarding its origin and function have remained limited.
The ultimate aim of this study is to better understand the genetic basis of EOD production by exploring the transcriptomic profiles of the electric organ and of its ancestral counterpart, the skeletal muscle, in the genus Campylomormyrus. After having established a set of reference transcriptomes using “Next-Generation Sequencing” (NGS) technologies, I performed in silico analyses of differential expression, in order to identify sets of genes that might be responsible for the functional differences observed between these two kinds of tissues. The results of such analyses indicate that: i) the loss of contractile activity and the decoupling of the excitation-contraction processes are reflected by the down-regulation of the corresponding genes in the electric organ; ii) the metabolic activity of the electric organ might be specialized towards the production and turnover of membrane structures; iii) several ion channels are highly expressed in the electric organ in order to increase excitability, and iv) several myogenic factors might be down-regulated by transcription repressors in the EO.
A secondary task of this study is to improve the genus level phylogeny of Campylomormyrus by applying new methods of inference based on the multispecies coalescent model, in order to reduce the conflict among gene trees and to reconstruct a phylogenetic tree as closest as possible to the actual species-tree. By using 1 mitochondrial and 4 nuclear markers, I was able to resolve the phylogenetic relationships among most of the currently described Campylomormyrus species. Additionally, I applied several coalescent-based species delimitation methods, in order to test the hypothesis that putatively cryptic species, which are distinguishable only from their EOD, belong to independently evolving lineages. The results of this analysis were additionally validated by investigating patterns of diversification at 16 microsatellite loci. The results suggest the presence of a new, yet undescribed species of Campylomormyrus.
Thermal stress response is an essential physiological trait that determines occurrence and temporal succession in nature, including response to climate change. We compared temperature-related demography in closely related heat-tolerant and heat-sensitive Brachionus rotifer species. We found significant differences in heat response, with the heat-sensitive species adopting a strategy of long survival and low population growth, while the heat-tolerant followed the opposite strategy. In both species, we examined the genetic basis of physiological variation by comparing gene expression across increasing temperatures. Comparative transcriptomic analyses identified shared and opposing responses to heat. Interestingly, expression of heat shock proteins (hsps) was strikingly different in the two species and mirrored differences in population growth rates, showing that hsp genes are likely a key component of a species’ adaptation to different temperatures. Temperature induction caused opposing patterns of expression in further functional categories including energy, carbohydrate and lipid metabolism, and in genes related to ribosomal proteins. In the heat-sensitive species, elevated temperatures caused up-regulation of genes related to meiosis induction and post-translational histone modifications. This work demonstrates the sweeping reorganizations of biological functions that accompany temperature adaptation in these two species and reveals potential molecular mechanisms that might be activated for adaptation to global warming.
Thermal stress response is an essential physiological trait that determines occurrence and temporal succession in nature, including response to climate change. We compared temperature-related demography in closely related heat-tolerant and heat-sensitive Brachionus rotifer species. We found significant differences in heat response, with the heat-sensitive species adopting a strategy of long survival and low population growth, while the heat-tolerant followed the opposite strategy. In both species, we examined the genetic basis of physiological variation by comparing gene expression across increasing temperatures. Comparative transcriptomic analyses identified shared and opposing responses to heat. Interestingly, expression of heat shock proteins (hsps) was strikingly different in the two species and mirrored differences in population growth rates, showing that hsp genes are likely a key component of a species’ adaptation to different temperatures. Temperature induction caused opposing patterns of expression in further functional categories including energy, carbohydrate and lipid metabolism, and in genes related to ribosomal proteins. In the heat-sensitive species, elevated temperatures caused up-regulation of genes related to meiosis induction and post-translational histone modifications. This work demonstrates the sweeping reorganizations of biological functions that accompany temperature adaptation in these two species and reveals potential molecular mechanisms that might be activated for adaptation to global warming.
In order to function properly, organisms have a complex control mechanism, in which a given gene is expressed at a particular time and place. One way to achieve this control is to regulate the initiation of transcription. This step requires the assembly of several components, i.e., a basal/general machinery common to all expressed genes, and a specific/regulatory machinery, which differs among genes and is the responsible for proper gene expression in response to environmental or developmental signals. This specific machinery is composed of transcription factors (TFs), which can be grouped into evolutionarily related gene families that possess characteristic protein domains. In this work we have exploited the presence of protein domains to create rules that serve for the identification and classification of TFs. We have modelled such rules as a bipartite graph, where families and protein domains are represented as nodes. Connections between nodes represent that a protein domain should (required rule) or should not (forbidden rule) be present in a protein to be assigned into a TF family. Following this approach we have identified putative complete sets of TFs in plant species, whose genome is completely sequenced: Cyanidioschyzon merolae (red algae), Chlamydomonas reinhardtii (green alga), Ostreococcus tauri (green alga), Physcomitrella patens (moss), Arabidopsis thaliana (thale cress), Populus trichocarpa (black cottonwood) and Oryza sativa (rice). The identification of the complete sets of TFs in the above-mentioned species, as well as additional information and reference literature are available at http://plntfdb.bio.uni-potsdam.de/. The availability of such sets allowed us performing detailed evolutionary studies at different levels, from a single family to all TF families in different organisms in a comparative genomics context. Notably, we uncovered preferential expansions in different lineages, paving the way to discover the specific biological roles of these proteins under different conditions. For the basic leucine zipper (bZIP) family of TFs we were able to infer that in the most recent common ancestor (MRCA) of all green plants there were at least four bZIP genes functionally involved in oxidative stress and unfolded protein responses that are bZIP-mediated processes in all eukaryotes, but also in light-dependent regulations. The four founder genes amplified and diverged significantly, generating traits that benefited the colonization of new environments. Currently, following the approach described above, up to 57 TF and 11 TR families can be identified, which are among the most numerous transcription regulatory families in plants. Three families of putative TFs predate the split between rhodophyta (red algae) and chlorophyta (green algae), i.e., G2-like, PLATZ, and RWPRK, and may have been of particular importance for the evolution of eukaryotic photosynthetic organisms. Nine additional families, i.e., ABI3/VP1, AP2-EREBP, ARR-B, C2C2-CO-like, C2C2-Dof, PBF-2-like/Whirly, Pseudo ARR-B, SBP, and WRKY, predate the split between green algae and streptophytes. The identification of putative complete list of TFs has also allowed the delineation of lineage-specific regulatory families. The families SBP, bHLH, SNF2, MADS, WRKY, HMG, AP2-EREBP and FHA significantly differ in size between algae and land plants. The SBP family of TFs is significantly larger in C. reinhardtii, compared to land plants, and appears to have been lost in the prasinophyte O. tauri. The families bHLH, SNF2, MADS, WRKY, HMG, AP2-EREBP and FHA preferentially expanded with the colonisation of land, and might have played an important role in this great moment in evolution. Later, after the split of bryophytes and tracheophytes, the families MADS, AP2-EREBP, NAC, AUX/IAA, PHD and HRT have significantly larger numbers in the lineage leading to seed plants. We identified 23 families that are restricted to land plants and that might have played an important role in the colonization of this new habitat. Based on the list of TFs in different species we have started to develop high-throughput experimental platforms (in rice and C. reinhardtii) to monitor gene expression changes of TF genes under different genetic, developmental or environmental conditions. In this work we present the monitoring of Arabidopsis thaliana TFs during the onset of senescence, a process that leads to cell and tissue disintegration in order to redistribute nutrients (e.g. nitrogen) from leaves to reproductive organs. We show that the expression of 185 TF genes changes when leaves develop from half to fully expanded leaves and finally enter partial senescence. 76% of these TFs are down-regulated during senescence, the remaining are up-regulated. The identification of TFs in plants in a comparative genomics setup has proven fruitful for the understanding of evolutionary processes and contributes to the elucidation of complex developmental programs.
A contemporary challenge in Ecology and Evolutionary Biology is to anticipate the fate of populations of organisms in the context of a changing world. Climate change and landscape changes due to anthropic activities have been of major concern in the contemporary history. Organisms facing these threats are expected to respond by local adaptation (i.e., genetic changes or phenotypic plasticity) or by shifting their distributional range (migration). However, there are limits to their responses. For example, isolated populations will have more difficulties in developing adaptive innovations by means of genetic changes than interconnected metapopulations. Similarly, the topography of the environment can limit dispersal opportunities for crawling organisms as compared to those that rely on wind. Thus, populations of species with different life history strategy may differ in their ability to cope with changing environmental conditions. However, depending on the taxon, empirical studies investigating organisms’ responses to environmental change may become too complex, long and expensive; plus, complications arising from dealing with endangered species. In consequence, eco-evolutionary modeling offers an opportunity to overcome these limitations and complement empirical studies, understand the action and limitations of underlying mechanisms, and project into possible future scenarios. In this work I take a modeling approach and investigate the effect and relative importance of evolutionary mechanisms (including phenotypic plasticity) on the ability for local adaptation of populations with different life strategy experiencing climate change scenarios. For this, I performed a review on the state of the art of eco-evolutionary Individual-Based Models (IBMs) and identify gaps for future research. Then, I used the results from the review to develop an eco-evolutionary individual-based modeling tool to study the role of genetic and plastic mechanisms in promoting local adaption of populations of organisms with different life strategies experiencing scenarios of climate change and environmental stochasticity. The environment was simulated through a climate variable (e.g., temperature) defining a phenotypic optimum moving at a given rate of change. The rate of change was changed to simulate different scenarios of climate change (no change, slow, medium, rapid climate change). Several scenarios of stochastic noise color resembling different climatic conditions were explored. Results show that populations of sexual species will rely mainly on standing genetic variation and phenotypic plasticity for local adaptation. Population of species with relatively slow growth rate (e.g., large mammals) – especially those of small size – are the most vulnerable, particularly if their plasticity is limited (i.e., specialist species). In addition, whenever organisms from these populations are capable of adaptive plasticity, they can buffer fitness losses in reddish climatic conditions. Likewise, whenever they can adjust their plastic response (e.g., bed-hedging strategy) they will cope with bluish environmental conditions as well. In contrast, life strategies of high fecundity can rely on non-adaptive plasticity for their local adaptation to novel environmental conditions, unless the rate of change is too rapid. A recommended management measure is to guarantee interconnection of isolated populations into metapopulations, such that the supply of useful genetic variation can be increased, and, at the same time, provide them with movement opportunities to follow their preferred niche, when local adaptation becomes problematic. This is particularly important for bluish and reddish climatic conditions, when the rate of change is slow, or for any climatic condition when the level of stress (rate of change) is relatively high.
A challenge for eco-evolutionary research is to better understand the effect of climate and landscape changes on species and their distribution. Populations of species can respond to changes in their environment through local genetic adaptation or plasticity, dispersal, or local extinction. The individual-based modeling (IBM) approach has been repeatedly applied to assess organismic responses to environmental changes. IBMs simulate emerging adaptive behaviors from the basic entities upon which both ecological and evolutionary mechanisms act. The objective of this review is to summarize the state of the art of eco-evolutionary IBMs and to explore to what degree they already address the key responses of organisms to environmental change. In this, we identify promising approaches and potential knowledge gaps in the implementation of eco-evolutionary mechanisms to motivate future research. Using mainly the ISI Web of Science, we reveal that most of the progress in eco-evolutionary IBMs in the last decades was achieved for genetic adaptation to novel local environmental conditions. There is, however, not a single eco-evolutionary IBM addressing the three potential adaptive responses simultaneously. Additionally, IBMs implementing adaptive phenotypic plasticity are rare. Most commonly, plasticity was implemented as random noise or reaction norms. Our review further identifies a current lack of models where plasticity is an evolving trait. Future eco-evolutionary models should consider dispersal and plasticity as evolving traits with their associated costs and benefits. Such an integrated approach could help to identify conditions promoting population persistence depending on the life history strategy of organisms and the environment they experience.
The balance between cellular proliferation and differentiation is a key aspect of development in multicellular organisms. Recent studies on Arabidopsis roots revealed distinct roles for different reactive oxygen species (ROS) in these processes. Modulation of the balance between ROS in proliferating cells and elongating cells is controlled at least in part at the transcriptional level. The effect of ROS on proliferation and differentiation is not specific for plants but appears to be conserved between prokaryotic and eukaryotic life forms. The ways in which ROS is received and how it affects cellular functioning is discussed from an evolutionary point of view. The different redox-sensing mechanisms that evolved ultimately result in the activation of gene regulatory networks that control cellular fate and decision-making. This review highlights the potential common origin of ROS sensing, indicating that organisms evolved similar strategies for utilizing ROS during development, and discusses ROS as an ancient universal developmental regulator.
Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.
Background In angiosperm evolution, autogamously selfing lineages have been derived from outbreeding ancestors multiple times, and this transition is regarded as one of the most common evolutionary tendencies in flowering plants. In most cases, it is accompanied by a characteristic set of morphological and functional changes to the flowers, together termed the selfing syndrome. Two major areas that have changed during evolution of the selfing syndrome are sex allocation to male vs. female function and flower morphology, in particular flower (mainly petal) size and the distance between anthers and stigma.
Scope A rich body of theoretical, taxonomic, ecological and genetic studies have addressed the evolutionary modification of these two trait complexes during or after the transition to selfing. Here, we review our current knowledge about the genetics and evolution of the selfing syndrome.
Conclusions We argue that because of its frequent parallel evolution, the selfing syndrome represents an ideal model for addressing basic questions about morphological evolution and adaptation in flowering plants, but that realizing this potential will require the molecular identification of more of the causal genes underlying relevant trait variation.