Biology subjects

Gitschlag, B. L.

Publications and source records attributed to Gitschlag, B. L..

4 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↗

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↗

bioRxiv2022

Multilevel selection analysis reveals diversity in selfish mitochondrial genome dynamics

Cells possess multiple mitochondrial DNA (mtDNA) copies, which undergo semi-autonomous replication and stochastic inheritance. This enables mutant mtDNA variants to arise and selfishly compete with cooperative (wildtype) mtDNA. Selfish mitochondrial genomes are subject to selection at different levels: they compete against wildtype mtDNA directly within hosts and indirectly through organismal selection. However, determining the relative contributions of selection at different levels has proven challenging. We overcome this challenge by combining mathematical modeling with experiments designed to isolate the levels of selection. Applying this approach to many selfish mitochondrial genotypes in Caenorhabditis elegans revealed an unexpected diversity of evolutionary mechanisms. Some mutant genomes persist at high frequency for many generations, despite a host fitness cost, by aggressively outcompeting cooperative genomes within hosts. Conversely, some mutant genomes persist by evading organismal selection. Strikingly, the mutant genomes vary dramatically in their susceptibility to neutral drift. Although different mechanisms can cause high frequency of selfish mtDNA, we show how they give rise to characteristically different distributions of mutant frequency among individuals. Given that heteroplasmic frequency represents a key determinant of phenotypic severity, this work outlines an evolutionary theoretic framework for predicting the distribution of phenotypic consequences among individuals carrying a selfish mitochondrial genome.

evolutionary biology↗

bioRxiv2020

Selfish mitochondria exploit nutrient status across different levels of selection

Cooperation and cheating are widespread evolutionary strategies. Competition can simultaneously favor cheating within groups and cooperation between groups. Selfish or cheater mitochondrial DNA (mtDNA) mutants proliferate within hosts while being selected against at the level of host fitness. How does environment govern competition between cooperators and cheaters across different selection levels? Focusing on food availability, we address this question using heteroplasmic Caenorhabditis elegans. We show that by promoting germline development, nutrient status provides the niche space for mtDNA variants to compete. However, the within-host advantage of selfish mtDNA requires additional conditions, namely the FoxO transcription factor DAF-16. During food scarcity, DAF-16 mitigates the host fitness cost of the selfish mtDNA. We conclude that food availability, and resilience to food scarcity, govern selfish mtDNA dynamics across the levels of selection. Our study integrates an evolutionary framework with experimentation to identify cellular mechanisms underlying the multilevel selection that characterizes cheater dynamics.

evolutionary biology↗