The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

Timothy A Whitehead - One of the best experts on this subject based on the ideXlab platform.

  • impact of in vivo protein folding probability on local fitness landscapes
    Molecular Biology and Evolution, 2019
    Co-Authors: Matthew S Faber, Emily E Wrenbeck, Laura R Azouz, Paul J Steiner, Timothy A Whitehead
    Abstract:

    It is incompletely understood how biophysical properties like protein stability impact molecular evolution and Epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. In contrast, nonspecific Epistasis results when a mutation is influenced by a large number of nonlocal mutations. As most mutations are pleiotropic, the in vivo folding probability-governed by basal protein stability-is thought to determine activity-enhancing mutational tolerance, implying that nonspecific Epistasis is dominant. However, evidence exists for both specific and nonspecific Epistasis as the prevalent factor, with limited comprehensive data sets to support either claim. Here, we use deep mutational scanning to probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE with statistically indistinguishable catalytic efficiencies but lower probabilities of folding in vivo compared with wild-type. Local fitness landscapes show slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific Epistasis was predominant for the subset of mutations exhibiting positive sign Epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes and suggest that transcriptional-translational effects are as important as stability in determining evolutionary outcomes.

  • impact of in vivo protein folding probability on local fitness landscapes
    bioRxiv, 2019
    Co-Authors: Matthew S Faber, Emily E Wrenbeck, Laura R Azouz, Paul J Steiner, Timothy A Whitehead
    Abstract:

    Abstract It is incompletely understood how biophysical properties like protein stability impact molecular evolution and Epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. By contrast, nonspecific Epistasis results when a mutation is influenced by a large number of non-local mutations. As most mutations are pleiotropic, the in vivo folding probability – governed by basal protein stability – is thought to determine activity-enhancing mutational tolerance, which implies that nonspecific Epistasis is dominant. However, evidence exists for both specific and nonspecific Epistasis as the prevalent factor, with limited comprehensive datasets to validate either claim. Using deep mutational scanning we probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE in which catalytic efficiencies are statistically indistinguishable but the enzyme variants have lower probabilities of folding in vivo. Local fitness landscapes show only slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific Epistasis was predominant for the subset of mutations exhibiting positive sign Epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon-dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes, and suggest that transcriptional-translational effects are an equally important determinant as stability in determining evolutionary outcomes.

Jason H Moore - One of the best experts on this subject based on the ideXlab platform.

  • Why Epistasis is important for tackling complex human disease genetics
    Genome Medicine, 2014
    Co-Authors: Trudy F C Mackay, Jason H Moore
    Abstract:

    Epistasis has been dismissed by some as having little role in the genetic architecture of complex human disease. The authors argue that this view is the result of a misconception and explain why exploring Epistasis is likely to be crucial to understanding and predicting complex disease.

  • an information gain approach to detecting three way epistatic interactions in genetic association studies
    Journal of the American Medical Informatics Association, 2013
    Co-Authors: Ting Hu, Scott M Williams, Yuanzhu Peter Chen, Jeff Kiralis, R Collins, Christian Wejse, Giorgio Sirugo, Jason H Moore
    Abstract:

    Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying Epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way Epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way Epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies.

  • traversing the conceptual divide between biological and statistical Epistasis systems biology and a more modern synthesis
    BioEssays, 2005
    Co-Authors: Jason H Moore, Scott M Williams
    Abstract:

    Epistasis plays an important role in the genetic architecture of common human diseases and can be viewed from two perspectives, biological and statistical, each derived from and leading to different assumptions and research strategies. Biological Epistasis is the result of physical interactions among biomolecules within gene regulatory networks and biochemical pathways in an individual such that the effect of a gene on a phenotype is dependent on one or more other genes. In contrast, statistical Epistasis is defined as deviation from additivity in a mathematical model summarizing the relationship between multilocus genotypes and phenotypic variation in a population. The goal of this essay is to review definitions and examples of biological and statistical Epistasis and to explore the relationship between the two. Specifically, we present and discuss the following two questions in the context of human health and disease. First, when does statistical evidence of Epistasis in human populations imply underlying biomolecular interactions in the etiology of disease? Second, when do biomolecular interactions produce patterns of statistical Epistasis in human populations? Answers to these two reciprocal questions will provide an important framework for using genetic information to improve our ability to diagnose, prevent and treat common human diseases. We propose that systems biology will provide the necessary information for addressing these questions and that model systems such as bacteria, yeast and digital organisms will be a useful place to start.

  • a global view of Epistasis
    Nature Genetics, 2005
    Co-Authors: Jason H Moore
    Abstract:

    Epistasis is a phenomenon whereby the effects of a given gene on a biological trait are masked or enhanced by one or more other genes. A new study documents Epistasis among 890 metabolic genes in yeast, providing one of the largest data sets of its kind in any model organism.

  • the ubiquitous nature of Epistasis in determining susceptibility to common human diseases
    Human Heredity, 2003
    Co-Authors: Jason H Moore
    Abstract:

    There is increasing awareness that Epistasis or gene-gene interaction plays a role in susceptibility to common human diseases. In this paper, we formulate a working hypothesis that Epistasis is a ubiquitous component of the genetic architecture of common human diseases and that complex interactions are more important than the independent main effects of any one susceptibility gene. This working hypothesis is based on several bodies of evidence. First, the idea that Epistasis is important is not new. In fact, the recognition that deviations from Mendelian ratios are due to interactions between genes has been around for nearly 100 years. Second, the ubiquity of biomolecular interactions in gene regulation and biochemical and metabolic systems suggest that relationship between DNA sequence variations and clinical endpoints is likely to involve gene-gene interactions. Third, positive results from studies of single polymorphisms typically do not replicate across independent samples. This is true for both linkage and association studies. Fourth, gene-gene interactions are commonly found when properly investigated. We review each of these points and then review an analytical strategy called multifactor dimensionality reduction for detecting Epistasis. We end with ideas of how hypotheses about biological Epistasis can be generated from statistical evidence using biochemical systems models. If this working hypothesis is true, it suggests that we need a research strategy for identifying common disease susceptibility genes that embraces, rather than ignores, the complexity of the genotype to phenotype relationship.

Michael M. Desai - One of the best experts on this subject based on the ideXlab platform.

  • global Epistasis emerges from a generic model of a complex trait
    eLife, 2021
    Co-Authors: Gautam Reddy, Michael M. Desai
    Abstract:

    Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread 'microscopic' Epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs Epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the origin of this 'global' Epistasis remains unknown. Here, we show that diminishing-returns and increasing-costs Epistasis emerge generically as a consequence of pervasive microscopic Epistasis. Our model predicts a specific quantitative relationship between the magnitude of global Epistasis and the stochastic effects of microscopic Epistasis, which we confirm by reanalyzing existing data. We further show that the distribution of fitness effects takes on a universal form when Epistasis is widespread and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.

  • global Epistasis emerges from a generic model of a complex trait
    bioRxiv, 2020
    Co-Authors: Gautam Reddy, Michael M. Desai
    Abstract:

    Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread "microscopic" Epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increases during laboratory adaptation. Recent work has found that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs Epistasis, which make mutations systematically less beneficial (or more deleterious) on more-fit genetic backgrounds. This global "macroscopic" Epistasis is thought to make phenotypic evolution repeatable, even while the genetic basis of this evolution is highly stochastic. However, the mechanistic basis of consistent macroscopic Epistasis remains unknown. Here we show, using a generic model of a complex trait, that global diminishing-returns and increasing-costs Epistasis arise naturally as a consequence of pervasive microscopic Epistasis, emerging simply as a statistical trend due to an imbalance between positive and negative contributions to the fitness. Our model predicts a specific quantitative relationship between the magnitude of global Epistasis and the stochastic effects of microscopic Epistasis, which we confirm by re-analyzing existing data. We also describe the predictions of this model for the patterns of fitness evolution and for how the distribution of fitness effects shifts as a population adapts, and propose additional experimental tests of these results.

  • Modular Epistasis and the compensatory evolution of gene deletion mutants.
    PLoS genetics, 2019
    Co-Authors: José I. Rojas Echenique, Sergey Kryazhimskiy, Michael M. Desai
    Abstract:

    Screens for epistatic interactions have long been used to characterize functional relationships corresponding to protein complexes, metabolic pathways, and other functional modules. Although Epistasis between adaptive mutations is also common in laboratory evolution experiments, the functional basis for these interactions is less well characterized. Here, we quantify the extent to which gene function (as determined by a genome-wide screen for Epistasis among deletion mutants) influences the rate and genetic basis of compensatory adaptation in a set of 37 gene deletion mutants nested within 16 functional modules. We find that functional module has predictive power: mutants with deletions in the same module tend to adapt more similarly, on average, than those with deletions in different modules. At the same time, initial fitness also plays a role: independent of the specific functional modules involved, adaptive mutations tend to be systematically more beneficial in less-fit genetic backgrounds, consistent with a general pattern of diminishing returns Epistasis. We measured epistatic interactions between initial gene deletion mutations and the mutations that accumulate during compensatory adaptation and found a general trend towards positive Epistasis (i.e. mutations tend to be more beneficial in the background in which they arose). In two functional modules, epistatic interactions between the initial gene deletions and the mutations in their descendant lines caused evolutionary entrenchment, indicating an intimate functional relationship. Our results suggest that genotypes with similar epistatic interactions with gene deletion mutations will also have similar epistatic interactions with adaptive mutations, meaning that genome scale maps of Epistasis between gene deletion mutations can be predictive of evolutionary dynamics.

  • the impact of macroscopic Epistasis on long term evolutionary dynamics
    Genetics, 2015
    Co-Authors: Benjamin H Good, Michael M. Desai
    Abstract:

    Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of Epistasis over 50,000 generations in a well-studied laboratory evolution experiment in Escherichia coli. The extensive duration of this experiment provides a unique window into the effects of Epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of Epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with a “two-epoch” model of adaptation, in which an initial burst of diminishing-returns Epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of Epistasis that are compatible with all of the experimental data.

  • the impact of macroscopic Epistasis on long term evolutionary dynamics
    arXiv: Populations and Evolution, 2014
    Co-Authors: Benjamin H Good, Michael M. Desai
    Abstract:

    Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of Epistasis over 50,000 generations in a well-studied laboratory evolution experiment in E. coli. The extensive duration of this experiment provides a unique window into the effects of Epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of Epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with "two-epoch" model of adaptation, in which an initial burst of diminishing returns Epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of Epistasis that are compatible with all of the experimental data.

Joshua B Plotkin - One of the best experts on this subject based on the ideXlab platform.

  • inferring the shape of global Epistasis
    bioRxiv, 2018
    Co-Authors: Jakub Otwinowski, David M Mccandlish, Joshua B Plotkin
    Abstract:

    Genotype-phenotype relationships are notoriously complicated. Idiosyncratic interactions between specific combinations of mutations occur, and are difficult to predict. Yet it is increasingly clear that many interactions can be understood in terms of global Epistasis. That is, mutations may act additively on some underlying, unobserved trait, and this trait is then transformed via a nonlinear function to the observed phenotype as a result of subsequent biophysical and cellular processes. Here we infer the shape of such global Epistasis in three proteins, based on published high-throughput mutagenesis data. To do so, we develop a maximum-likelihood inference procedure using a flexible family of monotonic nonlinear functions spanned by an I-spline basis. Our analysis uncovers dramatic nonlinearities in all three proteins; in some proteins a model with global Epistasis accounts for virtually all the measured variation, whereas in others we find substantial local Epistasis as well. This method allows us to test hypotheses about the form of global Epistasis and to distinguish variance components attributable to global Epistasis, local Epistasis, and measurement error.

  • contingency and entrenchment in protein evolution under purifying selection
    Proceedings of the National Academy of Sciences of the United States of America, 2015
    Co-Authors: Premal Shah, David M Mccandlish, Joshua B Plotkin
    Abstract:

    The phenotypic effect of an allele at one genetic site may depend on alleles at other sites, a phenomenon known as Epistasis. Epistasis can profoundly influence the process of evolution in populations and shape the patterns of protein divergence across species. Whereas Epistasis between adaptive substitutions has been studied extensively, relatively little is known about Epistasis under purifying selection. Here we use computational models of thermodynamic stability in a ligand-binding protein to explore the structure of Epistasis in simulations of protein sequence evolution. Even though the predicted effects on stability of random mutations are almost completely additive, the mutations that fix under purifying selection are enriched for Epistasis. In particular, the mutations that fix are contingent on previous substitutions: Although nearly neutral at their time of fixation, these mutations would be deleterious in the absence of preceding substitutions. Conversely, substitutions under purifying selection are subsequently entrenched by Epistasis with later substitutions: They become increasingly deleterious to revert over time. Our results imply that, even under purifying selection, protein sequence evolution is often contingent on history and so it cannot be predicted by the phenotypic effects of mutations assayed in the ancestral background.

  • selection biases the prevalence and type of Epistasis along adaptive trajectories
    Evolution, 2013
    Co-Authors: Jeremy A Draghi, Joshua B Plotkin
    Abstract:

    The contribution to an organism's phenotype from one genetic locus may depend upon the status of other loci. Such epistatic interactions among loci are now recognized as fundamental to shaping the process of adaptation in evolving populations. Although little is known about the structure of Epistasis in most organisms, recent experiments with bacterial populations have concluded that antagonistic interactions abound and tend to deaccelerate the pace of adaptation over time. Here, we use the NK model of fitness landscapes to examine how natural selection biases the mutations that substitute during evolution based on their epistatic interactions. We find that, even when beneficial mutations are rare, these biases are strong and change substantially throughout the course of adaptation. In particular, Epistasis is less prevalent than the neutral expectation early in adaptation and much more prevalent later, with a concomitant shift from predominantly antagonistic interactions early in adaptation to synergistic and sign Epistasis later in adaptation. We observe the same patterns when reanalyzing data from a recent microbial evolution experiment. These results show that when the order of substitutions is not known, standard methods of analysis may suggest that Epistasis retards adaptation when in fact it accelerates it.

  • selection biases the prevalence and type of Epistasis along adaptive trajectories
    arXiv: Populations and Evolution, 2012
    Co-Authors: Jeremy A Draghi, Joshua B Plotkin
    Abstract:

    The contribution to an organism's phenotype from one genetic locus may depend upon the status of other loci. Such epistatic interactions among loci are now recognized as fundamental to shaping the process of adaptation in evolving populations. Although little is known about the structure of Epistasis in most organisms, recent experiments with bacterial populations have concluded that antagonistic interactions abound and tend to de-accelerate the pace of adaptation over time. Here, we use a broad class of mathematical fitness landscapes to examine how natural selection biases the mutations that substitute during evolution based on their epistatic interactions. We find that, even when beneficial mutations are rare, these biases are strong and change substantially throughout the course of adaptation. In particular, Epistasis is less prevalent than the neutral expectation early in adaptation and much more prevalent later, with a concomitant shift from predominantly antagonistic interactions early in adaptation to synergistic and sign Epistasis later in adaptation. We observe the same patterns when re-analyzing data from a recent microbial evolution experiment. Since these biases depend on the population size and other parameters, they must be quantified before we can hope to use experimental data to infer an organism's underlying fitness landscape or to understand the role of Epistasis in shaping its adaptation. In particular, we show that when the order of substitutions is not known to an experimentalist, then standard methods of analysis may suggest that Epistasis retards adaptation when in fact it accelerates it.

Brandon C Ogbunugafor - One of the best experts on this subject based on the ideXlab platform.

  • proteostasis environment shapes higher order Epistasis operating on antibiotic resistance
    Genetics, 2019
    Co-Authors: Rafael F Guerrero, Samuel V Scarpino, Joao V Rodrigues, Daniel L Hartl, Brandon C Ogbunugafor
    Abstract:

    Recent studies have affirmed that higher-order Epistasis is ubiquitous and can have large effects on complex traits. Yet, we lack frameworks for understanding how epistatic interactions are influenced by central features of cell physiology. In this study, we assess how protein quality control machinery-a critical component of cell physiology-affects Epistasis for different traits related to bacterial resistance to antibiotics. Specifically, we disentangle the interactions between different protein quality control genetic backgrounds and two sets of mutations: (i) SNPs associated with resistance to antibiotics in an essential bacterial enzyme (dihydrofolate reductase, or DHFR) and (ii) differing DHFR bacterial species-specific amino acid background sequences ( Escherichia coli , Listeria grayi , Chlamydia muridarum ). In doing so, we improve on generic observations that Epistasis is widespread by discussing how patterns of Epistasis can be partly explained by specific interactions between mutations in an essential enzyme and genes associated with proteostasis. These findings speak to the role of environmental and genotypic context in modulating higher-order Epistasis, with direct implications for evolutionary theory, genetic modification technology, and efforts to manage antimicrobial resistance.

  • proteostasis environment shapes higher order Epistasis operating on antibiotic resistance
    bioRxiv, 2018
    Co-Authors: Rafael F Guerrero, Samuel V Scarpino, Joao V Rodrigues, Daniel L Hartl, Brandon C Ogbunugafor
    Abstract:

    ABSTRACT Recent studies have shown that higher-order Epistasis is ubiquitous and can have large effects on complex traits. Yet, we lack frameworks for understanding how epistatic interactions are influenced by basic aspects of cell physiology. In this study, we assess how protein quality control machinery—a critical component of cell physiology—affects Epistasis for different traits related to bacterial resistance to antibiotics. Specifically, we attempt to disentangle the interactions between different protein quality control genetic backgrounds and two sets of mutations: (i) SNPs associated with resistance to antibiotics in an essential bacterial enzyme (dihydrofolate reductase, or DHFR) and (ii) differing DHFR bacterial species-specific amino acid background sequences (Escherichia coli, Listeria grayi, and Chlamydia muridarum). In doing so, we add nuance to the generic observation that non-linear genetic interactions are widespread and capricious in nature, by proposing a mechanistically-grounded analysis of how proteostasis shapes Epistasis. These findings simultaneously fortify and demystify the role of environmental context in modulating higher-order Epistasis, with direct implications for evolutionary theory, genetic modification technology, and efforts to manage antimicrobial resistance.