scholarly journals Quantifying how constraints limit the diversity of viable routes to adaptation

2018 ◽  
Author(s):  
Sam Yeaman ◽  
Aleeza C. Gerstein ◽  
Kathryn A. Hodgins ◽  
Michael C. Whitlock
Keyword(s):  
Adaptive Evolution ◽  
Null Hypothesis ◽  
Hypergeometric Distribution ◽  
Simultaneous Analysis ◽  
Selection Pressures ◽  
Wide Range ◽  
Genetic Responses ◽  
Genome Scale ◽  
Pairwise Contrasts

AbstractConvergent adaptation can occur at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures. These patterns provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution. A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis. Here, we formulate a novel metric to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution, and then generalize this for simultaneous analysis of multiple lineages. This metric is explicitly based on the probability of observing a given amount of repeatability by chance under an arbitrary null hypothesis, and is readily compared among different species and types of trait. We also formulate a metric to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation. As an example of how these metrics can be used to draw inferences, we assess the amount of repeatability observed in existing datasets on adaptation to antibiotics in yeast and climate in conifers. This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution.

scholarly journals Assessing evidence for adaptive evolution in two hearing-related genes important for high-frequency hearing in echolocating mammals

2021 ◽  
Author(s):  
Hui Wang ◽  
Hanbo Zhao ◽  
Yujia Chu ◽  
Jiang Feng ◽  
Keping Sun
Keyword(s):  
Adaptive Evolution ◽  
Hair Cells ◽  
High Frequency ◽  
Phylogenetic Trees ◽  
Outer Hair Cells ◽  
Functional Domain ◽  
Coding Region ◽  
Selective Pressures ◽  
Wide Range ◽  
Different Parts

Abstract High-frequency hearing is particularly important for echolocating bats and toothed whales. Previously, studies of the hearing-related genes Prestin, KCNQ4, and TMC1 documented that adaptive evolution of high-frequency hearing has taken place in echolocating bats and toothed whales. In this study, we present two additional candidate hearing-related genes, Shh and SK2, that may also have contributed to the evolution of echolocation in mammals. Shh is a member of the vertebrate Hedgehog gene family and is required in the specification of the mammalian cochlea. SK2 is expressed in both inner and outer hair cells, and it plays an important role in the auditory system. The coding region sequences of Shh and SK2 were obtained from a wide range of mammals with and without echolocating ability. The topologies of phylogenetic trees constructed using Shh and SK2 were different; however, multiple molecular evolutionary analyses showed that those two genes experienced different selective pressures in echolocating bats and toothed whales compared to non-echolocating mammals. In addition, several nominally significant positively selected sites were detected in the non-functional domain of the SK2 gene, indicating that different selective pressures were acting on different parts of the SK2 gene. This study has expanded our knowledge of the adaptive evolution of high-frequency hearing in echolocating mammals.

scholarly journals A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Omid Oftadeh ◽  
Pierre Salvy ◽  
Maria Masid ◽  
Maxime Curvat ◽  
Ljubisa Miskovic ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Expression System ◽  
Biomass Composition ◽  
Industrial Biotechnology ◽  
Overflow Metabolism ◽  
Cellular Expression ◽  
A Genome ◽  
Wide Range ◽  
Eukaryotic Organisms ◽  
Genome Scale

AbstractEukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.

The null-hypothesis significance-test procedure is still warranted

1998 ◽  
Vol 21 (2) ◽  
pp. 228-235 ◽  
Author(s):  
Siu L. Chow
Keyword(s):  
Null Hypothesis ◽  
Statistical Power ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Test Procedure ◽  
Significance Test ◽  
Null Hypothesis Significance Test ◽  
Wide Range ◽  
Statistical Hypotheses ◽  
Alternative Hypotheses

Entertaining diverse assumptions about empirical research, commentators give a wide range of verdicts on the NHSTP defence in Statistical significance. The null-hypothesis significance-test procedure (NHSTP) is defended in a framework in which deductive and inductive rules are deployed in theory corroboration in the spirit of Popper's Conjectures and refutations (1968b). The defensible hypothetico-deductive structure of the framework is used to make explicit the distinctions between (1) substantive and statistical hypotheses, (2) statistical alternative and conceptual alternative hypotheses, and (3) making statistical decisions and drawing theoretical conclusions. These distinctions make it easier to show that (1) H0 can be true, (2) the effect size is irrelevant to theory corroboration, and (3) “strong” hypotheses make no difference to NHSTP. Reservations about statistical power, meta-analysis, and the Bayesian approach are still warranted.

scholarly journals Genome-scale data resolve ancestral rock-inhabiting lifestyle in Dothideomycetes (Ascomycota)

IMA Fungus ◽  
2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Claudio G. Ametrano ◽  
Felix Grewe ◽  
Pedro W. Crous ◽  
Stephen B. Goodwin ◽  
Chen Liang ◽  
...  
Keyword(s):  
Character State ◽  
Ancestral Character State ◽  
Wide Range ◽  
Tree Inference ◽  
Ancestral Character State Reconstruction ◽  
Inference Methods ◽  
Genome Scale ◽  
The Impact ◽  
Rock Inhabiting Fungi ◽  
Scale Data

Abstract Dothideomycetes is the most diverse fungal class in Ascomycota and includes species with a wide range of lifestyles. Previous multilocus studies have investigated the taxonomic and evolutionary relationships of these taxa but often failed to resolve early diverging nodes and frequently generated inconsistent placements of some clades. Here, we use a phylogenomic approach to resolve relationships in Dothideomycetes, focusing on two genera of melanized, extremotolerant rock-inhabiting fungi, Lichenothelia and Saxomyces, that have been suggested to be early diverging lineages. We assembled phylogenomic datasets from newly sequenced (4) and previously available genomes (238) of 242 taxa. We explored the influence of tree inference methods, supermatrix vs. coalescent-based species tree, and the impact of varying amounts of genomic data. Overall, our phylogenetic reconstructions provide consistent and well-supported topologies for Dothideomycetes, recovering Lichenothelia and Saxomyces among the earliest diverging lineages in the class. In addition, many of the major lineages within Dothideomycetes are recovered as monophyletic, and the phylogenomic approach implemented strongly supports their relationships. Ancestral character state reconstruction suggest that the rock-inhabiting lifestyle is ancestral within the class.

scholarly journals Genome-scale metabolic modelling underscores the potential of Cutaneotrichosporon oleaginosus ATCC 20509 as a cell factory for biofuel production

2020 ◽  
Author(s):  
Nhung TT Pham ◽  
Maarten Reijnders ◽  
Maria Suarez-Diez ◽  
Bart Nijsse ◽  
Jan Springer ◽  
...  
Keyword(s):  
Carbon Source ◽  
Lipid Accumulation ◽  
Crude Glycerol ◽  
Unsaturated Fatty Acids ◽  
Biodiesel Production ◽  
Biofuel Production ◽  
Cell Factory ◽  
A Genome ◽  
Wide Range ◽  
Genome Scale

Abstract Background: Cutaneotrichosporon oleaginosus ATCC 20509 is a fast growing oleaginous basidiomycete yeast that is able to grow in a wide range of low-cost carbon sources including crude glycerol, a byproduct of biodiesel production. When glycerol is used as a carbon source, this yeast can accumulate more than 50% lipids (w/w) with high concentrations of mono-unsaturated fatty acids. Results: To increase our understanding of this yeast and to provide a knowledge base for further industrial use, a FAIR re-annotated genome was used to build a genome-scale, constraint-based metabolic model containing 1553 reactions involving 1373 metabolites in 11 compartments. A new description of the biomass synthesis reaction was introduced to account for massive lipid accumulation in conditions with high carbon to nitrogen (C/N) ratio in the media. This condition-specific biomass objective function is shown to better predict conditions with high lipid accumulation using glucose, fructose, sucrose, xylose, ethanol and glycerol as sole carbon source. Conclusion: Contributing to the economic viability of biodiesel as renewable fuel, C. oleaginosus ATCC 20509 can effectively convert crude glycerol waste streams in lipids as a potential bioenergy source. Performance simulations are essential to identify optimal production conditions and to develop and fine tune a cost-effective production process. Our model suggests ATP-citrate lyase as a target for overexpression to further improve lipid production.

scholarly journals Genome-scale metabolic modelling underscores the potential of Cutaneotrichosporon oleaginosus ATCC 20509 as a cell factory for biofuel production

2020 ◽  
Author(s):  
Nhung TT Pham ◽  
Maarten Reijnders ◽  
Maria Suarez-Diez ◽  
Bart Nijsse ◽  
Jan Springer ◽  
...  
Keyword(s):  
Lipid Accumulation ◽  
Crude Glycerol ◽  
Lipid Production ◽  
Biodiesel Production ◽  
Biofuel Production ◽  
Cell Factory ◽  
Atp Citrate Lyase ◽  
A Genome ◽  
Wide Range ◽  
Genome Scale

Abstract Background: Cutaneotrichosporon oleaginosus ATCC 20509 is a fast growing oleaginous basidiomycete yeast that is able to grow in a wide range of low-cost carbon sources including crude glycerol, a byproduct of biodiesel production. When glycerol is used as a carbon source, this yeast can accumulate more than 50% lipids (w/w) with high concentrations of mono-unsaturated fatty acids.Results: To increase our understanding of this yeast and to provide a knowledge base for further industrial use, a FAIR re-annotated genome was used to build a genome-scale, constraint-based metabolic model containing 1553 reactions involving 1373 metabolites in 11 compartments. A new description of the biomass synthesis reaction was introduced to account for massive lipid accumulation in conditions with high carbon to nitrogen (C/N) ratio in the media. This condition-specific biomass objective function is shown to better predict conditions with high lipid accumulation using glucose, fructose, sucrose, xylose, and glycerol as sole carbon source.Conclusion: Contributing to the economic viability of biodiesel as renewable fuel, C. oleaginosus ATCC 20509 can effectively convert crude glycerol waste streams in lipids as a potential bioenergy source. Performance simulations are essential to identify optimal production conditions and to develop and fine tune a cost-effective production process. Our model suggests ATP-citrate lyase as a possible target to further improve lipid production.

scholarly journals Adaptive evolution in DNMT2 supports its role in the dipteran immune response

2020 ◽  
Author(s):  
Tamanash Bhattacharya ◽  
Danny W. Rice ◽  
Richard W. Hardy ◽  
Irene L.G. Newton
Keyword(s):  
Immune Response ◽  
Positive Selection ◽  
Adaptive Evolution ◽  
Fruit Fly ◽  
Fruit Flies ◽  
Host Protein ◽  
Specific Host ◽  
Wide Range ◽  
Specific Factors

AbstractEukaryotic nucleic acid methyltransferase (MTase) proteins are essential mediators of epigenetic and epitranscriptomic regulation. DNMT2 belongs to a large, conserved family of DNA MTases found in many organisms, including holometabolous insects like fruit flies and mosquitoes, where it is the lone MTase. Interestingly, despite its nomenclature, DNMT2 is not a DNA MTase, but instead targets and methylates RNA species. A growing body of literature suggest DNMT2 mediates the host immune response against a wide range of pathogens, including RNA viruses. Evidence of adaptive evolution, in the form of positive selection, can often be found in genes that are engaged in conflict with pathogens like viruses. Here we identify and describe evidence of positive selection that has occurred at different times over the course of DNMT2 evolution within dipteran insects. We identify specific codons within each ortholog that are under positive selection, and find they are restricted to four distinct domains of the protein and likely influence substrate binding, target recognition, and adaptation of unique intermolecular interactions. Additionally, we describe the role of the Drosophila-specific host protein IPOD, in regulating the expression and/or function of fruit fly DNMT2. Finally, heterologous expression of these orthologs suggest that DNMT2’s role as an antiviral is host dependent, indicating a requirement for additional host-specific factors. Collectively, our findings highlight the adaptive evolution of DNMT2 in Dipteran insects, underscoring its role as an important, albeit non-canonical, regulator of host-pathogen interactions in mosquitoes and fruit flies.

scholarly journals Modeling the Differences in Biochemical Capabilities ofPseudomonasSpecies by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Parizad Babaei ◽  
Tahereh Ghasemi-Kahrizsangi ◽  
Sayed-Amir Marashi
Keyword(s):  
In Silico ◽  
Metabolic Networks ◽  
Closely Related Species ◽  
Systematic Analysis ◽  
Reconstruction Process ◽  
Flux Balance ◽  
Wide Range ◽  
Balance Analysis ◽  
Metabolic Models ◽  
Genome Scale

To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of threePseudomonasmetabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related toP. aeruginosaPAO1,P. putidaKT2440, andP. fluorescensSBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable forin silicosimulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare thein silicoresults to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

scholarly journals 0062 Improved Circadian Data Ordering in the Presence of Biological and Technical Confounds

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A24-A26
Author(s):  
J Hammarlund ◽  
R Anafi
Keyword(s):  
Machine Learning ◽  
Network Architecture ◽  
Large Data ◽  
Data Sets ◽  
Sample Collection ◽  
Circadian Phase ◽  
Confounding Variables ◽  
Wide Range ◽  
Fully Connected ◽  
Genome Scale

Abstract Introduction We recently used unsupervised machine learning to order genome scale data along a circadian cycle. CYCLOPS (Anafi et al PNAS 2017) encodes high dimensional genomic data onto an ellipse and offers the potential to identify circadian patterns in large data-sets. This approach requires many samples from a wide range of circadian phases. Individual data-sets often lack sufficient samples. Composite expression repositories vastly increase the available data. However, these agglomerated datasets also introduce technical (e.g. processing site) and biological (e.g. age or disease) confounders that may hamper circadian ordering. Methods Using the FLUX machine learning library we expanded the CYCLOPS network. We incorporated additional encoding and decoding layers that model the influence of labeled confounding variables. These layers feed into a fully connected autoencoder with a circular bottleneck, encoding the estimated phase of each sample. The expanded network simultaneously estimates the influence of confounding variables along with circadian phase. We compared the performance of the original and expanded networks using both real and simulated expression data. In a first test, we used time-labeled data from a single-center describing human cortical samples obtained at autopsy. To generate a second, idealized processing center, we introduced gene specific biases in expression along with a bias in sample collection time. In a second test, we combined human lung biopsy data from two medical centers. Results The performance of the original CYCLOPS network degraded with the introduction of increasing, non-circadian confounds. The expanded network was able to more accurately assess circadian phase over a wider range of confounding influences. Conclusion The addition of labeled confounding variables into the network architecture improves circadian data ordering. The use of the expanded network should facilitate the application of CYCLOPS to multi-center data and expand the data available for circadian analysis. Support This work was supported by the National Cancer Institute (1R01CA227485-01)

scholarly journals A heuristic model on the role of plasticity in adaptive evolution: plasticity increases adaptation, population viability and genetic variation

2013 ◽  
Vol 280 (1771) ◽  
pp. 20131869 ◽  
Author(s):  
Ivan Gomez-Mestre ◽  
Roger Jovani
Keyword(s):  
Genetic Variation ◽  
Adaptive Evolution ◽  
Environmental Changes ◽  
Adaptive Dynamics ◽  
Adaptive Plasticity ◽  
High Plasticity ◽  
Heuristic Model ◽  
Heritable Variation ◽  
Ample Evidence ◽  
Wide Range

An ongoing new synthesis in evolutionary theory is expanding our view of the sources of heritable variation beyond point mutations of fixed phenotypic effects to include environmentally sensitive changes in gene regulation. This expansion of the paradigm is necessary given ample evidence for a heritable ability to alter gene expression in response to environmental cues. In consequence, single genotypes are often capable of adaptively expressing different phenotypes in different environments, i.e. are adaptively plastic. We present an individual-based heuristic model to compare the adaptive dynamics of populations composed of plastic or non-plastic genotypes under a wide range of scenarios where we modify environmental variation, mutation rate and costs of plasticity. The model shows that adaptive plasticity contributes to the maintenance of genetic variation within populations, reduces bottlenecks when facing rapid environmental changes and confers an overall faster rate of adaptation. In fluctuating environments, plasticity is favoured by selection and maintained in the population. However, if the environment stabilizes and costs of plasticity are high, plasticity is reduced by selection, leading to genetic assimilation, which could result in species diversification. More broadly, our model shows that adaptive plasticity is a common consequence of selection under environmental heterogeneity, and hence a potentially common phenomenon in nature. Thus, taking adaptive plasticity into account substantially extends our view of adaptive evolution.

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