Refine
Year of publication
Document Type
- Article (12)
- Doctoral Thesis (7)
- Postprint (5)
Language
- English (24)
Is part of the Bibliography
- yes (24)
Keywords
- evolution (24) (remove)
Institute
- Institut für Biochemie und Biologie (24) (remove)
Young Genes out of the Male: An Insight from Evolutionary Age Analysis of the Pollen Transcriptome
(2015)
The birth of new genes in genomes is an important evolutionary event. Several studies reveal that new genes in animals tend to be preferentially expressed in male reproductive tissues such as testis (Betran et al., 2002; Begun et al., 2007; Dubruille et al., 2012), and thus an "out of testis' hypothesis for the emergence of new genes has been proposed (Vinckenbosch et al., 2006; Kaessmann, 2010). However, such phenomena have not been examined in plant species. Here, by employing a phylostratigraphic method, we dated the origin of protein-coding genes in rice and Arabidopsis thaliana and observed a number of young genes in both species. These young genes tend to encode short extracellular proteins, which may be involved in rapid evolving processes, such as reproductive barriers, species specification, and antimicrobial processes. Further analysis of transcriptome age indexes across different tissues revealed that male reproductive cells express a phylogenetically younger transcriptome than other plant tissues. Compared with sporophytic tissues, the young transcriptomes of the male gametophyte displayed greater complexity and diversity, which included a higher ratio of anti-sense and inter-genic transcripts, reflecting a pervasive transcription state that facilitated the emergence of new genes. Here, we propose that pollen may act as an "innovation incubator' for the birth of de novo genes. With cases of male-biased expression of young genes reported in animals, the "new genes out of the male' model revealed a common evolutionary force that drives reproductive barriers, species specification, and the upgrading of defensive mechanisms against pathogens.
Aim Growth is a multifarious phenomenon that has been studied by nutritionists, economists, paediatric endocrinologists; archaeologists, child psychologists and other experts. Yet, a unifying theory of understanding growth regulation is still lacking. Method Critical review of the literature. Results We summarise evidence linking social competition and its effect on hierarchies in social structures, with the neuronal networks of the ventromedial hypothalamus and body size. The endocrine signalling system regulating growth hormone, Insulin-like-Growth-Factor1 and skeletal growth, is well conserved in the evolution of vertebrata for some 400 million years. The link between size and status permits adaptive plasticity, competitive growth and strategic growth adjustments also in humans. Humans perceive size as a signal of dominance with tallness being favoured and particularly prevalent in the upper social classes. Conclusion Westernised societies are competitive. People are tall, and "open to change." Social values include striving for status and prestige implying socio-economic domination. We consider the transition of political and social values following revolutions and civil wars, as key elements that interact with the evolutionarily conserved neuroendocrine competence for adaptive developmental plasticity, overstimulate the hypothalamic growth regulation and finally lead to the recent historic increases in average height.
The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton
(2020)
Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.
The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton
(2020)
Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.
Nonribosomal peptides (NRP) are crucial molecular mediators in microbial ecology and provide indispensable drugs. Nevertheless, the evolution of the flexible biosynthetic machineries that correlates with the stunning structural diversity of NRPs is poorly understood. Here, we show that recombination is a key driver in the evolution of bacterial NRP synthetase (NRPS) genes across distant bacterial phyla, which has guided structural diversification in a plethora of NRP families by extensive mixing andmatching of biosynthesis genes. The systematic dissection of a large number of individual recombination events did not only unveil a striking plurality in the nature and origin of the exchange units but allowed the deduction of overarching principles that enable the efficient exchange of adenylation (A) domain substrates while keeping the functionality of the dynamic multienzyme complexes. In the majority of cases, recombination events have targeted variable portions of the A(core) domains, yet domain interfaces and the flexible A(sub) domain remained untapped. Our results strongly contradict the widespread assumption that adenylation and condensation (C) domains coevolve and significantly challenge the attributed role of C domains as stringent selectivity filter during NRP synthesis. Moreover, they teach valuable lessons on the choice of natural exchange units in the evolution of NRPS diversity, which may guide future engineering approaches.
Role of diversification rates and evolutionary history as a driver of plant naturalization success
(2020)
Human introductions of species beyond their natural ranges and their subsequent establishment are defining features of global environmental change. However, naturalized plants are not uniformly distributed across phylogenetic lineages, with some families contributing disproportionately more to the global alien species pool than others. Additionally, lineages differ in diversification rates, and high diversification rates have been associated with characteristics that increase species naturalization success. Here, we investigate the role of diversification rates in explaining the naturalization success of angiosperm plant families.
We use five global data sets that include native and alien plant species distribution, horticultural use of plants, and a time-calibrated angiosperm phylogeny. Using phylogenetic generalized linear mixed models, we analysed the effect of diversification rate, different geographical range measures, and horticultural use on the naturalization success of plant families.
We show that a family's naturalization success is positively associated with its evolutionary history, native range size, and economic use. Investigating interactive effects of these predictors shows that native range size and geographic distribution additionally affect naturalization success. High diversification rates and large ranges increase naturalization success, especially of temperate families.
We suggest this may result from lower ecological specialization in temperate families with large ranges, compared with tropical families with smaller ranges.
Role of diversification rates and evolutionary history as a driver of plant naturalization success
(2020)
Human introductions of species beyond their natural ranges and their subsequent establishment are defining features of global environmental change. However, naturalized plants are not uniformly distributed across phylogenetic lineages, with some families contributing disproportionately more to the global alien species pool than others. Additionally, lineages differ in diversification rates, and high diversification rates have been associated with characteristics that increase species naturalization success. Here, we investigate the role of diversification rates in explaining the naturalization success of angiosperm plant families.
We use five global data sets that include native and alien plant species distribution, horticultural use of plants, and a time-calibrated angiosperm phylogeny. Using phylogenetic generalized linear mixed models, we analysed the effect of diversification rate, different geographical range measures, and horticultural use on the naturalization success of plant families.
We show that a family's naturalization success is positively associated with its evolutionary history, native range size, and economic use. Investigating interactive effects of these predictors shows that native range size and geographic distribution additionally affect naturalization success. High diversification rates and large ranges increase naturalization success, especially of temperate families.
We suggest this may result from lower ecological specialization in temperate families with large ranges, compared with tropical families with smaller ranges.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
RangeShiftR
(2021)
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.