Biology subjects

Stoltzfus, A.

Publications and source records attributed to Stoltzfus, A..

7 recordsLinked to original sources

bioRxiv2025

Molecular adaptation reflects taxon-specific mutational biases

A fundamental question in molecular evolution is the extent to which patterns of adaptive change are shaped by mutational biases that make some variants more likely than others to arise. Past studies provide support for important effects of mutation bias on adaptive change, but leave open the empirical question of how strongly and how broadly evolutionary patterns depend on taxon-specific mutational tendencies. To characterize this effect quantitatively, we aggregated frequency spectra of adaptive amino acid changes from 14 species, comprising over 5000 total adaptive events, primarily from adaptive laboratory evolution studies. We then paired each species-specific spectrum of adaptive changes with independent measurements of the mutation spectrum of that same species. Across the 14 species, we find considerable heterogeneity in the relative frequencies of the six possible types of single-nucleotide changes, for both the mutational and adaptive spectra. Comparing these spectra across species, we find that, for any given mutation type, the stronger the bias toward or against that type in a species mutation spectrum, the more enriched or depleted it tends to be in that species adaptive spectrum. We conclude that, for the adaptation of proteins via amino acid changes, taxon-specific evolutionary preferences are strongly responsive to taxon-specific mutational preferences over their observed range. Significance statementThe rates at which different types of mutation occur vary widely, both for different types of mutations within a single species and across species. Historically, a strong concordance between patterns of sequence evolution and mutational biases was used to support the thesis that most sequence evolution is caused by variants that do not affect fitness. However, more recent evidence shows that mutational biases can also influence adaptive evolution. Using data from 14 species, we find a strong relationship between the rate at which different kinds of nucleotide mutations emerge and their frequency among adaptive amino acid changes during protein evolution. These results suggest that processes that bias the production of variation may have a strong impact even during adaptive evolution.

evolutionary biology↗

bioRxiv2024

A fitness distribution law for amino-acid replacements

The effect of replacing the amino acid at a given site in a protein is difficult to predict. Yet, evolutionary comparisons have revealed highly regular patterns of interchangeability between pairs of amino acids, and such patterns have proved enormously useful in a range of applications in bioinformatics, evolutionary inference, and protein design. Here we reconcile these apparently contradictory observations using fitness data from over 350,000 experimental amino acid replacements. Almost one-quarter of the 20 x 19 = 380 types of replacements have broad distributions of fitness effects (DFEs) that closely resemble the background DFE for random changes, indicating an overwhelming influence of protein context in determining mutational effects. However, we also observe that the 380 pair-specific DFEs closely follow a maximum entropy distribution, specifically a truncated exponential distribution. The shape of this distribution is determined entirely by its mean, which is equivalent to the chance that a replacement of the given type is fitter than a random replacement. In this type of distribution, modest deviations in the mean correspond to much larger changes in the probability of falling in the far right tail, so that modest differences in mean exchangeability may result in much larger differences in the chance of a highly fit mutation. Indeed, we show that under the assumption that purifying selection filters out the vast majority of mutations, the maximum entropy distributions of fitness effects inferred from deep mutational scanning experiments predict the characteristic patterns of amino acid change observed in molecular evolution. These maximum entropy distributions of mutational effects not only provide a tuneable model for molecular evolution, but also have implications for mutational effect prediction and protein engineering.

evolutionary biology↗

bioRxiv2023

Mutation and selection induce correlations between selection coefficients and mutation rates

The joint distribution of selection coefficients and mutation rates is a key determinant of the genetic architecture of molecular adaptation. Three different distributions are of immediate interest: (1) the nominal distribution of possible changes, prior to mutation or selection, (2) the de novo distribution of realized mutations, and (3) the fixed distribution of selectively established mutations. Here, we formally characterize the relationships between these joint distributions under the strong selection, weak mutation (SSWM) regime. The de novo distribution is enriched relative to the nominal distribution for the highest rate mutations, and the fixed distribution is further enriched for the most highly beneficial mutations. Whereas mutation rates and selection coefficients are often assumed to be uncorrelated, we show that even with no correlation in the nominal distribution, the resulting de novo and fixed distributions can have correlations with any combination of signs. Nonetheless, we suggest that natural systems with a finite number of beneficial mutations will frequently have the kind of nominal distribution that induces negative correlations in the fixed distribution. We apply our mathematical framework, along with population simulations, to explore joint distributions of selection coefficients and mutation rates from deep mutational scanning and cancer informatics. Finally, we consider the evolutionary implications of these joint distributions together with two additional joint distributions relevant to parallelism and the rate of adaptation.

evolutionary biology↗

bioRxiv2021

Mutation bias shapes the spectrum of adaptive substitutions

Evolutionary adaptation often occurs via the fixation of beneficial point mutations, but different types of mutation may differ in their relative frequencies within the collection of substitutions contributing to adaptation in any given species. Recent studies have established that this spectrum of adaptive substitutions is enriched for classes of mutations that occur at higher rates. Yet, little is known at a quantitative level about the precise extent of this enrichment, or its dependence on other factors such as the beneficial mutation supply or demographic conditions. Here we address the extent to which the mutation spectrum shapes the spectrum of adaptive amino acid substitutions by applying a codon-based negative binomial regression model to three large data sets that include thousands of amino acid changes identified in natural and experimental adaptation in S. cerevisiae, E. coli, and M. tuberculosis. We find that the mutation spectrum has a strong and roughly proportional influence on the spectrum of adaptive substitutions in all three species. In fact, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover species-specific mutational spectra obtained via mutation accumulation experiments. We complement this empirical analysis with simulations to determine the factors that influence how closely the spectrum of adaptive substitutions mirrors the spectrum of amino acid variants introduced by mutation, and find that the predictive power of mutation depends on multiple factors including population size and the breadth of the mutational target for adaptation. SIGNIFICANCE STATEMENTHow do mutational biases influence the process of adaptation? Classical neo-Darwinian thinking assumes that selection alone determines the course of adaptation from abundant pre-existing variation. Yet, theoretical work shows that under some circumstances the mutation rate to a given variant may have a strong impact on the probability of that variant contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation, and show that the mutation spectrum has a proportional influence on the changes fixed in adaptation observed in three large data sets. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions mirrors the spectrum of variants introduced by mutation.

evolutionary biology↗

bioRxiv2019

The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function

An underexplored question in evolutionary genetics concerns the extent to which mutational bias in the production of genetic variation influences outcomes and pathways of adaptive molecular evolution. In the genomes of at least some vertebrate taxa, an important form of mutation bias involves changes at CpG dinucleotides: If the DNA nucleotide cytosine (C) is immediately 5 to guanine (G) on the same coding strand, then - depending on methylation status - point mutations at both sites occur at an elevated rate relative to mutations at non-CpG sites. Here we examine experimental data from case studies in which it has been possible to identify the causative substitutions that are responsible for adaptive changes in the functional properties of vertebrate hemoglobin (Hb). Specifically, we examine the molecular basis of convergent increases in Hb-O2 affinity in high-altitude birds. Using a data set of experimentally verified, affinity-enhancing mutations in the Hbs of highland avian taxa, we tested whether causative changes are enriched for mutations at CpG dinucleotides relative to the frequency of CpG mutations among all possible missense mutations. The tests revealed that a disproportionate number of causative amino acid replacements were attributable to CpG mutations, suggesting that mutation bias can influence outcomes of molecular adaptation.

evolutionary biology↗

bioRxiv2018

Phylotastic: improving access to tree-of-life knowledge with flexible, on-the-fly delivery of trees

(1) A comprehensive phylogeny of species, i.e., a tree of life, has potential uses in a variety of contexts in research and education. This potential is limited if accessing the tree of life requires special knowledge, complex software, or long periods of training.\n\n(2) The Phylotastic project aims to use web-services technologies to lower the barrier for accessing phylogenetic knowledge, making it as easy to get a phylogeny of species as it is to get online driving directions. In prior work, we designed an open system of web services to validate and manage species names, find phylogeny resources, extract subtrees matching a users species list, calibrate them, and mash them up with images and information from online resources.\n\n(3) Here we report a publicly accessible system for on-the-fly delivery of phylogenetic knowledge, developed with user feedback on what types of functionality are considered useful by researchers and educators. The system currently consists of a web portal that implements 3 types of workflows to obtain species phylogenies (scaled by geologic time and decorated with thumbnail images); 19 underlying web services accessible via a common registry; and toolbox code in R and Python so that others can create applications that leverage these services. These resources cover most of the use-cases identified in our analysis of user needs.\n\n(4) The Phylotastic system, accessible via http://www.phylotastic.org, provides a unique resource to access the current state of phylogenetic knowledge, useful for a variety of cases in which a tree extracted quickly from online resources (as distinct from a tree custom-made from character data) is sufficient, as it is for many casual uses of trees identified here.

bioinformatics↗

bioRxiv2017

Mutational biases influence parallel adaptation

While mutational biases strongly influence neutral molecular evolution, the role of mutational biases in shaping the course of adaptation is less clear. Here we consider the frequency of transitions relative to transversions among adaptive substitutions. Because mutation rates for transitions are higher than those for transversions, if mutational biases influence the dynamics of adaptation, then transitions should be over-represented among documented adaptive substitutions. To test this hypothesis, we assembled a dataset of putatively adaptive amino acid substitutions that have occurred in parallel during evolution in nature or in the laboratory. We find that the frequency of transitions in this dataset is much higher than would be predicted under a null model where mutation has no effect. Our results are qualitatively similar even if we restrict ourself to changes that have occurred, not merely twice, but three or more times. These results suggest that the course of adaptation is biased by mutation.

evolutionary biology↗