Olivia Ghosh

All Publications

• Genotype-fitness mapping of adaptive mutants reveals shifting low-dimensional structure across divergent environments. PLoS biology Ghosh, O. M., Kinsler, G., Good, B. H., Petrov, D. A. 2026; 24 (3): e3003618

  Abstract

  A central goal in evolutionary biology is to predict the effect of a genetic mutation on fitness. This is a major challenge because it requires knowledge of both the phenotypic effects of a mutation and their importance in an arbitrary environment, which are high-dimensional quantities and difficult to guess a priori. Here, we address this problem by taking a top-down, data-driven approach to infer the mapping between genotypes, latent phenotypes, and fitness. We measure the fitness effects of a large collection of adaptive yeast mutants in many lab environments, from which we build low-dimensional, linear fitness landscapes. We find that these models are highly predictive of fitness variation for thousands of adaptive mutants, both in environments similar to where they evolved and also in divergent environments. This implies that the underlying genotype-phenotype-fitness maps for these adaptive mutants tend to be broadly low-dimensional. We further demonstrate that these maps only partially overlap across divergent environments, suggesting that the phenotypic determinants of fitness shift with the environment but remain low-dimensional. These results combine to emphasize the importance of environmental context in evolution, and suggest that top-down, low-dimensional fitness landscapes pave the way for evolutionary prediction.

  View details for DOI 10.1371/journal.pbio.3003618

  View details for PubMedID 41886417

• An empirical long-term competition among natural yeast isolates reveals that short-term fitness largely but not entirely predicts long-term outcomes. bioRxiv : the preprint server for biology Khristich, A. N., Ghosh, O. M., Vila, J. C., Mathur, S., Dutta, A., Garin, M., Schacherer, J., Petrov, D. A. 2025

  Abstract

  In this study, we investigate the relative contribution of initial fitness to the long-term success of a genotype competing in a naturally diverse population. Specifically, we compete over 300 genetically barcoded S. cerevisiae isolates in a pooled setting for over 700 generations. We found that the strains that remain at detectable frequency until the end of the competition uniformly come from the top 95th percentile in the initial fitness values, making initial fitness the most significant predictor of long-term success. However, we occasionally see heterogeneity in the competition outcomes, which suggests a role of stochastic adaptation, clonal interference, and possibly frequency-dependent changes in strains' fitness. We demonstrate that the "finalists" of our competition change on the genetic level, and that the spectrum of de novo mutations depends both on the strains' genotype and environment. Finally, we show that gene targets of the novel mutations are specific to the combination of strain identity and environment, even among the genetically similar strains and environments that select for the same strains in the beginning of the competition.

  View details for DOI 10.1101/2025.10.09.681448

  View details for PubMedID 41279677

  View details for PubMedCentralID PMC12632622

• Low-dimensional genotype-fitness mapping across divergent environments suggests a limiting functions model of fitness. bioRxiv : the preprint server for biology Ghosh, O. M., Kinsler, G., Good, B. H., Petrov, D. A. 2025

  Abstract

  A central goal in evolutionary biology is to be able to predict the effect of a genetic mutation on fitness. This is a major challenge because fitness depends both on phenotypic changes due to the mutation, and how these phenotypes map onto fitness in a particular environment. Genotype, phenotype, and environment spaces are all extremely complex, rendering bottom-up prediction unlikely. Here we show, using a large collection of adaptive yeast mutants, that fitness across a set of lab environments can be well-captured by top-down, low-dimensional linear models that generate abstract genotype-phenotype-fitness maps. We find that these maps are low-dimensional not only in the environment where the adaptive mutants evolved, but also in more divergent environments. We further find that the genotype-phenotype-fitness spaces implied by these maps overlap only partially across environments. We argue that these patterns are consistent with a "limiting functions" model of fitness, whereby only a small number of limiting functions can be modified to affect fitness in any given environment. The pleiotropic side-effects on non-limiting functions are effectively hidden from natural selection locally, but can be revealed globally. These results combine to emphasize the importance of environmental context in genotype-phenotype-fitness mapping, and have implications for the predictability and trajectory of evolution in complex environments.

  View details for DOI 10.1101/2025.04.05.647371

  View details for PubMedID 40291729

• Massively parallel experimental interrogation of natural variants in ancient signaling pathways reveals both purifying selection and local adaptation. bioRxiv : the preprint server for biology Aguilar-Rodríguez, J., Vila, J., Chen, S. A., Razo-Mejia, M., Ghosh, O., Fraser, H. B., Jarosz, D. F., Petrov, D. A. 2024

  Abstract

  The nature of standing genetic variation remains a central debate in population genetics, with differing perspectives on whether common variants are mostly neutral or have functional effects. We address this question by directly mapping the fitness effects of over 9,000 natural variants in the Ras/PKA and TOR/Sch9 pathways-key regulators of cell proliferation in eukaryotes-across four conditions in Saccharomyces cerevisiae. While many variants are neutral in our assay, on the order of 3,500 exhibited significant fitness effects. These non-neutral variants tend to be missense and affect conserved, more densely packed, and less solvent-exposed protein regions. They are also typically younger, occur at lower frequencies, and more often found in heterozygous states, suggesting they are subject to purifying selection. A substantial fraction of non-neutral variants showing strong fitness effects in our experiments, however, is present at high frequencies in the population. These variants show signs of local adaptation as they tend to be found specifically in domesticated strains adapted to human-made environments. Our findings support the view that while common variants are often neutral, a significant proportion have adaptive functional consequences and are driven into the population by local positive selection. This study highlights the potential to explore the functional effects of natural genetic variation on a genome scale with quantitative fitness measurements in the laboratory, bridging the gap between population genetics and functional genomics to understand evolutionary dynamics in the wild.

  View details for DOI 10.1101/2024.10.30.621178

  View details for PubMedID 39553990

  View details for PubMedCentralID PMC11565963

• Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota. Proceedings of the National Academy of Sciences of the United States of America Ghosh, O. M., Good, B. H. 2022; 119 (28): e2114931119

  Abstract

  The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.

  View details for DOI 10.1073/pnas.2114931119

  View details for PubMedID 35787046