Modelling metabolic evolution on phenotypic fitness landscapes: a case study on C4 photosynthesis

2015 ◽  
Vol 43 (6) ◽  
pp. 1172-1176 ◽  
Author(s):  
David Heckmann
Keyword(s):  
Structural Changes ◽  
Crop Yields ◽  
C4 Photosynthesis ◽  
Fitness Landscape ◽  
Fitness Landscapes ◽  
C3 Plants ◽  
Metabolic Systems ◽  
C4 Pathway ◽  
Evolutionary Trajectories ◽  
Phenotypic Fitness

How did the complex metabolic systems we observe today evolve through adaptive evolution? The fitness landscape is the theoretical framework to answer this question. Since experimental data on natural fitness landscapes is scarce, computational models are a valuable tool to predict landscape topologies and evolutionary trajectories. Careful assumptions about the genetic and phenotypic features of the system under study can simplify the design of such models significantly. The analysis of C4 photosynthesis evolution provides an example for accurate predictions based on the phenotypic fitness landscape of a complex metabolic trait. The C4 pathway evolved multiple times from the ancestral C3 pathway and models predict a smooth ‘Mount Fuji’ landscape accordingly. The modelled phenotypic landscape implies evolutionary trajectories that agree with data on modern intermediate species, indicating that evolution can be predicted based on the phenotypic fitness landscape. Future directions will have to include structural changes of metabolic fitness landscape structure with changing environments. This will not only answer important evolutionary questions about reversibility of metabolic traits, but also suggest strategies to increase crop yields by engineering the C4 pathway into C3 plants.

scholarly journals LEAF ANATOMY CHARACTERIZATION OF FOUR Apochloa SPECIES: A C3 GENUS RELATED TO EVOLUTION OF C4 PATHWAY IN GRASSES

2020 ◽  
Vol 26 (1) ◽  
pp. 12-18
Author(s):  
Ane Marcela das Chagas Mendonça ◽  
Pedro Lage Viana ◽  
João Paulo Rodrigues Alves Delfino Barbosa
Keyword(s):  
Leaf Anatomy ◽  
C4 Photosynthesis ◽  
Water Status ◽  
Bundle Sheath ◽  
C3 Plants ◽  
Plant Water ◽  
Kranz Anatomy ◽  
C4 Pathway ◽  
Photosynthesis Pathway

Leaf anatomy characteristics provide important evidences about the transition between C3 and C4 pathways. The C4 photosynthesis pathway allowed to reduce the C3 photorespiratory rate, concentrating CO2 around the Rubisco site and using structures and machinery already presented in C3 plants. In monocots, it is observed a high number of C4 lineages, most of them phylogenetically related to C3 groups. The genus Apochloa (C3), subtribe Arthropogoninae, is related to two C4 genera Coleataenia and Cyphonanthus. The aim of this study was to evaluate four Apochloa species in order to establish anatomical characteristics related to the evolution of C4 pathway in this group. By means of transverse sections fully expanded leaves of A. euprepes, A. lorea, A. molinioides, and A. poliophylla were collected and the characteristics of the mesophyll (M) and bundle sheath (BS) cells were determined. These species showed a rustic Kranz anatomy with enlarged and radial arranged BS cells, which have few organelles organized in a centrifugal position. Although the modifications of BS cells are probably related to the maintenance of plant water status, we also discuss the evolution for the establishment of C4 photosynthesis in the related C4 genera.

scholarly journals On the deformability of an empirical fitness landscape by microbial evolution

2018 ◽  
Vol 115 (44) ◽  
pp. 11286-11291 ◽  
Author(s):  
Djordje Bajić ◽  
Jean C. C. Vila ◽  
Zachary D. Blount ◽  
Alvaro Sánchez
Keyword(s):  
Environmental Effects ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Adaptive Dynamics ◽  
Microbial Evolution ◽  
Fitness Landscapes ◽  
Complex Genetics ◽  
Evolutionary Innovation ◽  
Genotype Space ◽  
Evolutionary Trajectories

A fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be deformed by mutations that produce substantial changes to the environment. Despite its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium Escherichia coli. Deformability is quantified by the noncommutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short range. However, mutations with large environmental effects produce long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our results therefore suggest that, even in situations in which mutations have strong environmental effects, fitness landscapes may retain their power to forecast evolution over small mutational distances despite the potential attenuation of that power over longer evolutionary trajectories. Our methods and results provide an avenue for integrating adaptive and eco-evolutionary dynamics with complex genetics and genomics.

scholarly journals Estimating the predictability of cancer evolution

2019 ◽  
Vol 35 (14) ◽  
pp. i389-i397 ◽  
Author(s):  
Sayed-Rzgar Hosseini ◽  
Ramon Diaz-Uriarte ◽  
Florian Markowetz ◽  
Niko Beerenwinkel
Keyword(s):  
Cancer Progression ◽  
Fitness Landscape ◽  
Simulated Data ◽  
Fitness Landscapes ◽  
Computational Method ◽  
Supplementary Information ◽  
Cancer Evolution ◽  
Statistical Framework ◽  
Evolutionary Trajectories

Abstract Motivation How predictable is the evolution of cancer? This fundamental question is of immense relevance for the diagnosis, prognosis and treatment of cancer. Evolutionary biologists have approached the question of predictability based on the underlying fitness landscape. However, empirical fitness landscapes of tumor cells are impossible to determine in vivo. Thus, in order to quantify the predictability of cancer evolution, alternative approaches are required that circumvent the need for fitness landscapes. Results We developed a computational method based on conjunctive Bayesian networks (CBNs) to quantify the predictability of cancer evolution directly from mutational data, without the need for measuring or estimating fitness. Using simulated data derived from >200 different fitness landscapes, we show that our CBN-based notion of evolutionary predictability strongly correlates with the classical notion of predictability based on fitness landscapes under the strong selection weak mutation assumption. The statistical framework enables robust and scalable quantification of evolutionary predictability. We applied our approach to driver mutation data from the TCGA and the MSK-IMPACT clinical cohorts to systematically compare the predictability of 15 different cancer types. We found that cancer evolution is remarkably predictable as only a small fraction of evolutionary trajectories are feasible during cancer progression. Availability and implementation https://github.com/cbg-ethz/predictability\_of\_cancer\_evolution Supplementary information Supplementary data are available at Bioinformatics online.

C4 rice: a challenge for plant phenomics

2009 ◽  
Vol 36 (11) ◽  
pp. 845 ◽  
Author(s):  
Robert T. Furbank ◽  
Susanne von Caemmerer ◽  
John Sheehy ◽  
Gerry Edwards
Keyword(s):  
C4 Photosynthesis ◽  
Oryza Sativa L ◽  
Yield Potential ◽  
C3 Plants ◽  
Or Efficiency ◽  
C4 Pathway ◽  
Large Populations ◽  
Plant Phenomics ◽  
Research Consortium ◽  
Sorghum Bicolor L

There is now strong evidence that yield potential in rice (Oryza sativa L.) is becoming limited by ‘source’ capacity, i.e. photosynthetic capacity or efficiency, and hence the ability to fill the large number of grain ‘sinks’ produced in modern varieties. One solution to this problem is to introduce a more efficient, higher capacity photosynthetic mechanism to rice, the C4 pathway. A major challenge is identifying and engineering the genes necessary to install C4 photosynthesis in rice. Recently, an international research consortium was established to achieve this aim. Central to the aims of this project is phenotyping large populations of rice and sorghum (Sorghum bicolor L.) mutants for ‘C4-ness’ to identify C3 plants that have acquired C4 characteristics or revertant C4 plants that have lost them. This paper describes a variety of plant phenomics approaches to identify these plants and the genes responsible, based on our detailed physiological knowledge of C4 photosynthesis. Strategies to asses the physiological effects of the installation of components of the C4 pathway in rice are also presented.

Evolutionary transition from C3 to C4 photosynthesis and the route to C4 rice

Biologia ◽  
2013 ◽  
Vol 68 (4) ◽  
Author(s):  
Zheng Liu ◽  
Ning Sun ◽  
Shangjun Yang ◽  
Yanhong Zhao ◽  
Xiaoqin Wang ◽  
...  
Keyword(s):  
C4 Photosynthesis ◽  
C3 Plants ◽  
Hydraulic Systems ◽  
Leaf Architecture ◽  
Evolutionary Trajectory ◽  
Bisphosphate Carboxylase ◽  
Bundle Sheath Cells ◽  
C4 Pathway ◽  
C4 Evolution ◽  
C4 Enzymes

AbstractCompared with C3 plants, C4 plants possess a mechanism to concentrate CO2 around the ribulose-1,5-bisphosphate carboxylase/oxygenase in chloroplasts of bundle sheath cells so that the carboxylation reaction work at a much more efficient rate, thereby substantially eliminate the oxygenation reaction and the resulting photorespiration. It is observed that C4 photosynthesis is more efficient than C3 photosynthesis under conditions of low atmospheric CO2, heat, drought and salinity, suggesting that these factors are the important drivers to promote C4 evolution. Although C4 evolution took over 66 times independently, it is hypothesized that it shared the following evolutionary trajectory: 1) gene duplication followed by neofunctionalization; 2) anatomical and ultrastructral changes of leaf architecture to improve the hydraulic systems; 3) establishment of two-celled photorespiratory pump; 4) addition of transport system; 5) co-option of the duplicated genes into C4 pathway and adaptive changes of C4 enzymes. Based on our current understanding on C4 evolution, several strategies for engineering C4 rice have been proposed to increase both photosynthetic efficiency and yield significantly in order to avoid international food crisis in the future, especially in the developing countries. Here we summarize the latest progresses on the studies of C4 evolution and discuss the strategies to introduce two-celled C4 pathway into rice.

Physiological, anatomical and biochemical characterisation of photosynthetic types in genus Cleome (Cleomaceae)

2007 ◽  
Vol 34 (4) ◽  
pp. 247 ◽  
Author(s):  
Elena V. Voznesenskaya ◽  
Nuria K. Koteyeva ◽  
Simon D. X. Chuong ◽  
Alexandra N. Ivanova ◽  
João Barroca ◽  
...  
Keyword(s):  
Leaf Anatomy ◽  
C4 Photosynthesis ◽  
C3 Plants ◽  
Intermediate Species ◽  
Δ13c Values ◽  
C4 Species ◽  
Cleome Gynandra ◽  
The Family ◽  
C3 Species ◽  
C4 Pathway

C4 photosynthesis has evolved many times in 18 different families of land plants with great variation in leaf anatomy, ranging from various forms of Kranz anatomy to C4 photosynthesis occurring within a single type of photosynthetic cell. There has been little research on photosynthetic typing in the family Cleomaceae, in which only one C4 species has been identified, Cleome gynandra L. There is recent interest in selecting and developing a C4 species from the family Cleomaceae as a model C4 system, since it is the most closely related to Arabidopsis, a C3 model system (Brown et al. 2005). From screening more than 230 samples of Cleomaceae species, based on a measure of the carbon isotope composition (δ13C) in leaves, we have identified two additional C4 species, C. angustifolia Forssk. (Africa) and C. oxalidea F.Muell. (Australia). Several other species have δ13C values around –17‰ to –19‰, suggesting they are C4-like or intermediate species. Eight species of Cleome were selected for physiological, anatomical and biochemical analyses. These included C. gynandra, a NAD–malic enzyme (NAD–ME) type C4 species, C. paradoxa R.Br., a C3–C4 intermediate species, and 6 others which were characterised as C3 species. Cleome gynandra has C4 features based on low CO2 compensation point (Γ), C4 type δ13C values, Kranz-type leaf anatomy and bundle sheath (BS) ultrastructure, presence of C4 pathway enzymes, and selective immunolocalisation of Rubisco and phosphoenolpyruvate carboxylase. Cleome paradoxa was identified as a C3–C4 intermediate based on its intermediate Γ (27.5 μmol mol–1), ultrastructural features and selective localisation of glycine decarboxylase of the photorespiratory pathway in mitochondria of BS cells. The other six species are C3 plants based on Γ, δ13C values, non-Kranz leaf anatomy, and levels of C4 pathway enzymes (very low or absent) typical of C3 plants. The results indicate that this is an interesting family for studying the genetic basis for C4 photosynthesis and its evolution from C3 species.

scholarly journals Effective potential reveals evolutionary trajectories in complex fitness landscapes

2019 ◽  
Author(s):  
Matteo Smerlak
Keyword(s):  
Effective Potential ◽  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Coarse Graining ◽  
Fitness Landscapes ◽  
Coarse Grained ◽  
Mutational Robustness ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Evolutionary Trajectories

AbstractGrowing efforts to measure fitness landscapes in molecular and microbial systems are premised on a tight relationship between landscape topography and evolutionary trajectories. This relationship, however, is far from being straightforward: depending on their mutation rate, Darwinian populations can climb the closest fitness peak (survival of the fittest), settle in lower regions with higher mutational robustness (survival of the flattest), or fail to adapt altogether (error catastrophes). These bifurcations highlight that evolution does not necessarily drive populations “from lower peak to higher peak”, as Wright imagined. The problem therefore remains: how exactly does a complex landscape topography constrain evolution, and can we predict where it will go next? Here I introduce a generalization of quasispecies theory which identifies metastable evolutionary states as minima of an effective potential. From this representation I derive a coarse-grained, Markov state model of evolution, which in turn forms a basis for evolutionary predictions across a wide range of mutation rates. Because the effective potential is related to the ground state of a quantum Hamiltonian, my approach could stimulate fruitful interactions between evolutionary dynamics and quantum many-body theory.SIGNIFICANCE STATEMENTThe course of evolution is determined by the relationship between heritable types and their adaptive values, the fitness landscape. Thanks to the explosive development of sequencing technologies, fitness landscapes have now been measured in a diversity of systems from molecules to micro-organisms. How can we turn these data into evolutionary predictions? I show that preferred evolutionary trajectories are revealed when the effects of selection and mutations are blended in a single effective evolutionary force. With this reformulation, the dynamics of selection and mutation becomes Markovian, bringing a wealth of classical visualization and analysis tools to bear on evolutionary dynamics. Among these is a coarse-graining of evolutionary dynamics along its metastable states which greatly reduces the complexity of the prediction problem.

scholarly journals Genetic Algorithms as a method to study adaptive walks in biological landscapes

2020 ◽  
Author(s):  
Edith Invernizzi ◽  
Graeme D Ruxton
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Biology ◽  
Fitness Landscape ◽  
Evolutionary Process ◽  
Simulation Modelling ◽  
Fitness Landscapes ◽  
Mathematical Methods ◽  
Reproductive Process ◽  
Modelling Framework ◽  
Phenotypic Fitness

AbstractThe metaphor of fitness landscapes is common in evolutionary biology, as a way to visualise the change in allele or phenotypic frequencies of a population under selection. Understanding how different factors in the evolutionary process affect the trajectory of the population across the landscape is of interest to both theoretical and empirical evolutionary biologists. However, fitness landscape studies often have to rely heavily on mathematical methods that are not easy to access by biologically trained researchers. Here, we used a method borrowed from engineering - genetic algorithms - to simulate the evolutionary process and study how different components affect the path taken through a phenotypic fitness landscape. In a simple study, we compare five selection models that reflect different degrees of dependency of fitness on trait quality: this includes strengths of selection, trait-quality dependent reproductive hierarchy and the amount of stochasticity in the reproductive process. We include an analysis of other evolutionary variables such as population size and mutation rate. We analyse a game theory problem, as a test landscape, that lends itself to analysis through a deterministic mathematical simulation, which we use for comparison. Our results show that there are differences in the speed with which different models of selection lead to the fitness optimum.Author summaryEvolution and adaptation in biology occurs in fitness landscapes, multidimensional spaces representing all possible genotypic or phenotypic combinations, where population adapt by following the cline of the fitness dimension. The study of adaptation on complex fitness landscapes has so far been limited by the need for mathematically heavy methods. Here, we present a simulation modelling framework, genetic algorithms, that can be used for evolutionary simulations of a population on a fitness landscape of chosen features and with custom evolutionary parameters.

scholarly journals On the deformability of an empirical fitness landscape by microbial evolution

2018 ◽  
Author(s):  
Djordje Bajić ◽  
Jean C.C. Vila ◽  
Zachary D. Blount ◽  
Alvaro Sánchez
Keyword(s):  
Evolutionary Dynamics ◽  
Fitness Landscape ◽  
Adaptive Dynamics ◽  
Microbial Evolution ◽  
Fitness Landscapes ◽  
Complex Genetics ◽  
Evolutionary Innovation ◽  
Genome Wide ◽  
Genotype Space ◽  
Evolutionary Trajectories

AbstractA fitness landscape is a map between the genotype and its reproductive success in a given environment. The topography of fitness landscapes largely governs adaptive dynamics, constraining evolutionary trajectories and the predictability of evolution. Theory suggests that this topography can be “deformed” by mutations that produce substantial changes to the environment. In spite of its importance, the deformability of fitness landscapes has not been systematically studied beyond abstract models, and little is known about its reach and consequences in empirical systems. Here we have systematically characterized the deformability of the genome-wide metabolic fitness landscape of the bacterium E. coli. Deformability is quantified by the non-commutativity of epistatic interactions, which we experimentally demonstrate in mutant strains on the path to an evolutionary innovation. Our analysis shows that the deformation of fitness landscapes by metabolic mutations rarely affects evolutionary trajectories in the short-range. However, mutations with large environmental effects leave these as a “legacy”, producing long-range landscape deformations in distant regions of the genotype space that affect the fitness of later descendants. Our methods and results provide the basis for an integration between adaptive and eco-evolutionary dynamics with complex genetics and genomics.

SOIL CONDITIONERS—THEIR EFFECT ON COARSE-TEXTURED SOILS, CROP YIELDS AND COMPOSITION

1957 ◽  
Vol 37 (2) ◽  
pp. 102-112
Author(s):  
R. M. Holmes ◽  
S. J. Toth
Keyword(s):  
Structural Changes ◽  
Crop Yields ◽  
Cultural Practices ◽  
Sandy Soils ◽  
Growing Season ◽  
Soil Aggregate ◽  
Crop Response ◽  
The Third ◽  
Soil Conditioners ◽  
The Stability

Crop response to soil structural changes caused by soil conditioner amendments was studied in several different sandy soils of New Jersey. The response varied with the crop and treatment. Those chemicals that were slightly hydrophobic were most effective and generally crop response was greatest on these treatments. Cations such as Na may be added in large amounts as part of some conditioners, and this may result in reduced uptake of other nutrients such as Mg. and K. Except for this effect, conditioners did not reduce nutrient uptake by plants. When elements such as Na and N are added in large amounts as part of some conditioners, there may be an increased uptake of these nutrients.Catalin and VAMA conditioners produced a dry surface mulch which appeared to reduce evaporation. Moisture reserves were, therefore, preserved through a drought and this resulted in increased growth of crops over those grown on other treatments. Cultural practices destroyed the stability of the conditioned aggregates, since in most cases the effect had largely disappeared by the third growing season. Chemicals which were effective in soil aggregate stabilization were also effective as anti-crustants when crusting was a problem.

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