Biology subjects

Petrov, D.

Publications and source records attributed to Petrov, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Intragenic epistasis in couch potato shapes life history traits and climatic adaptation in Drosophila melanogaster

Populations adapting to heterogeneous environments often harbor many alleles that covary with environmental gradients, yet how so many adaptive variants can be maintained and show signatures of local adaptation remains unclear. Epistatic non-additive interactions among alleles may concentrate fitness effects at specific allelic combinations to shape complex traits and facilitate adaptation. We evaluate compositional epistasis among three intronic SNPs in the couch potato (cpo) gene, each independently clinal along the North American latitudinal gradient, using recombinant outbred populations fixed for distinct three-locus combinations. Flies carrying all three temperate alleles (cpoTTA) or all three tropical alleles (cpoCGT) show non-additive increases in traits associated with fitness in their respective environments: dormancy, starvation resistance, and lipid storage in temperate flies and fecundity in tropical flies. Intermediate genotype combinations generally show weaker and negative deviations from additive predictions. Temperate genotypes show reduced cpo expression and independently create predicted transcription factor binding sites, suggesting a regulatory basis for the observed phenotypic effects. Consistent with selection shaping haplotype frequencies against a backdrop of ongoing recombination, the temperate and tropical genotypes are enriched above random expectation across the latitudinal cline, with directionally consistent but non-significant seasonal patterns. Our findings demonstrate that non-additive interactions among non-coding variants within a single gene can produce large, pleiotropic fitness effects and shape genotype distributions in natural populations, providing a mechanism by which a small number of regulatory variants can underlie complex climatic adaptation.

evolutionary biology↗

bioRxiv2026

Genetic Diversity and Population Structure of the Black-Footed Cat: Insights into Felis's Deadliest Predator

BackgroundBlack-footed cats (Felis nigripes) are one of Africas least studied felines. The population dynamics and demographic history of this solitary species have not been well-described. Reports of ongoing decline of present-day populations resulted in the IUCN Red List categorizing the species as vulnerable to extinction. As populations decline and become isolated from each other, they become susceptible to strong genetic drift and inbreeding, which can lead to the accumulation of deleterious alleles and increased sextinction risk. However, the IUCN cited data deficiencies across the species range as a limitation in this categorization for black-footed cats. In cases where ecological surveys are lacking, range-wide population genomic surveys can improve our understanding of population dynamics. ResultsIn the first genomic study of free-roaming individuals, we sequenced whole genomes of black-footed cats (N=44) from across their distribution. To do so, we incorporated whole genome sequences generated from both modern biological samples and century-old museum specimens. We assembled a highly contiguous reference genome using a combination of PacBio HiFi data and publicly available Hi-C data and investigated the demographic history, population structure, and genetic diversity of wild black-footed cats. We found evidence of historical effective population sizes of [~]11,500 individuals, which is lower than estimates reported in other felid species. Consistent with modest historical population sizes, we found that present-day genome-wide diversity was low ({pi} {approx} 0.0004). However, despite low genetic diversity, we find that black-footed cat genomes do not harbor long runs of homozygosity. Simulation results indicate that low present-day genetic diversity may simply result from modest historical population size. However, other analyses point to evidence of a population contraction in the last 50 generations, which could contribute to future genomic erosion. We also compared genomic variation in populations across the range to evaluate patterns of population structure, finding evidence of higher genetic similarity between individuals in closer geographic proximity. ConclusionOverall, these results provide range-wide information about the demographic history and present-day genetic diversity of an understudied species. Together with analyses of population structure, we speculate that there may be greater connectivity between populations of black-footed cats than previously assumed. Our study underscores the utility of genomic data in providing insights into population dynamics for better conservation management.

evolutionary biology↗

bioRxiv2025

An empirical long-term competition among natural yeast isolates reveals that short-term fitness largely but not entirely predicts long-term outcomes

The fitness of an organism determines its likelihood of succeeding in short-term competition, but many other factors can influence its long-term success. In this study, we investigate the relative contribution of initial fitness to a strain's long-term success in a naturally diverse population. Specifically, we compete a pool of 282 genetically barcoded S. cerevisiae isolates for up to 720 generations in six distinct environments. We find that the strains that remain at detectable frequency until the end of the competition uniformly come from the initially fittest top 5% of strains, rendering initial fitness a strong predictor of long-term success. However, small fitness differences among the top strains matter little for their long-term evolutionary fate. Indeed, we often see heterogeneity in the competition outcomes across replicates, suggesting that stochastic, large-effect adaptive mutations overwrite small differences in the initial fitness of the highest fitness strains. In addition, our results hint that evolvability differences might result in certain strains consistently over- or underperforming in the competition. We further demonstrate that the "finalists" of our competition accumulate a diverse spectrum of de novo genetic changes: single nucleotide mutations, indels, whole chromosome losses and amplifications, and widespread losses of heterozygosity that occasionally span hundreds of kilobases. Taken together, we show that for a pool of natural strains, high initial fitness is necessary, though not sufficient, to succeed long-term, and that adaptive evolution can drive unexpected outcomes in a long-term competition in a novel environment.

evolutionary biology↗

bioRxiv2025

Comparative gene annotation of 304 species of Drosophilidae

High-quality genome annotations are essential if we are to address central questions in comparative genomics, such as the origin of new genes, the drivers of genome size variation, and the evolutionary forces shaping gene content and structure. Here, we present protein-coding gene annotations for 301 species of the family Drosophilidae, generated using the Comparative Annotation Toolkit (CAT) and BRAKER3, and incorporating available RNA-seq and protein evidence. We take a comparative phylogenetic approach to annotation, with the aim of improving consistency and accuracy, and to generate a robust set of gene annotations and orthology assignments. We analyze our annotations using a phylogenetic mixed-model approach and find that gene number and CDS length exhibit moderate phylogenetic heritability (40% and 9.7%, respectively). For comparison, we also present analyses using a subset of the 215 highest quality genomes, although the findings were not markedly different. Our work suggests that while evolutionary history contributes to variation in these traits, species-specific factors--including assembly error--play a substantial role in shaping observed differences. To illustrate the utility of our annotations for comparative analyses, we investigate codon usage bias and amino acid composition across Drosophilidae. We find that codon usage is correlated with overall GC content and evolves slowly, but that it is also strongly shaped by selection--such that, in general, species with the strongest selection on synonymous codon usage show the lowest GC bias in third codon positions. This comparative annotation dataset forms part of an on-going collaborative project to sequence and annotate all species of Drosophilidae, with data and annotations being made rapidly and freely available on an on-going basis. We hope that this effort will serve as a foundation for studies in evolutionary and functional genomics and comparative biology across Drosophilidae.

genomics↗

bioRxiv2025

Low-dimensional genotype-fitness mapping across divergent environments suggests a limiting functions model of fitness

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 extremely large and complex, rendering bottom-up prediction difficult. Here we show, using a large collection of adaptive yeast mutants, that fitness across a set of lab environments can be well-captured by low-dimensional linear models of 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 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.

evolutionary biology↗

bioRxiv2025

President Roosevelt's lions reveal a century of population fragmentation in Africa's largest carnivore

Over the past century, lion (Panthera leo) populations across Africa have experienced rapid and severe declines. Despite this, East Africa is considered a modern-day lion stronghold. Here, we use whole-genome sequencing of both recent and historical lion populations, primarily collected during the Smithsonians Roosevelt East African (1909-1911) and Rainey (1911-1912) Expeditions, to investigate changes in population structure, connectivity, and diversity over the last [~]100 years in East Africa. We find a clear signal of population fragmentation when comparing historical (1896-1946) and recent (1990-present) lion populations. Our analyses reveal genetic distinctions between remaining lion populations in Kenya and Tanzania and document loss of genetic diversity over time including reduced heterozygosity and the accumulation of runs of homozygosity. We detect a severe bottleneck in both Kenya and Tanzania approximately 25 generations ago, coinciding with a severe rinderpest outbreak in the region that is known to have decimated bovid and ultimately carnivore populations in the area. Nevertheless, modern lions in East Africa still exhibit overall high levels of diversity and low levels of inbreeding. Our results provide direct evidence of the effects of increasing habitat fragmentation and the significance of temporal data for contextualizing current patterns of population connectivity and diversity.

evolutionary biology↗

bioRxiv2024

Variation in Resource Environment Drives Adaptive Divergence in Drosophila melanogaster

Natural populations often experience heterogeneity in the quality and abundance of environmentally acquired resources across both space and time, and this variation can influence population demographics and evolutionary dynamics. In this study, we directly manipulated diet in replicate populations of Drosophila melanogaster cultured in experimental mesocosms in the field. We found no significant effect of resource variation on demographic patterns. Furthermore, while resource variation altered the patterns of phenotypic and genomic evolution, this effect is secondary to population responses to seasonally fluctuating selective pressures. Seasonal adaptation was observed for all traits assayed and elicited genome-wide signatures of selection; in contrast, adaptation to the resource environment was trait-specific and exhibited an oligogenic architecture. This illustrates the capacity of populations to adapt to a specific axis of variation (the resource environment) without hindering the adaptive response to seasonal change. This in turn, suggests that resource variation may be an important force driving fluctuating selection across natural populations, ultimately contributing to the maintenance of genetic and phenotypic variation.

evolutionary biology↗

bioRxiv2024

Pervasive fitness trade-offs revealed by rapid adaption in large experimental populations of Drosophila melanogaster

Trade-offs are an inherent feature of organismal biology that are expected play a fundamental role in the evolution of natural populations. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of Drosophila melanogaster to directly measure the manifestation of trade-offs in response to fluctuating selection on ecological timescales. Specifically, we first conducted a lab-based selection experiment to quantify a genome-wide signal of antagonistic pleiotropy elicited in response to shifting population densities and associated with reproduction and stress tolerance selection. In doing so, we identified a putative role of two cosmopolitan inversions in these trade-offs. We then conducted an independent experiment to show that a simple manipulation of increasing population density under controlled lab-based conditions identified loci that are relevant to selection during population expansion and collapse in a complex, semi-natural setting. In concert, our results reveal how adaptation in complex, natural environments can be coarse-grained in such a manner to drive repeatable and predictable patterns of genomic variation, and further add credence to models positing a role of generic fitness trade-offs in the maintenance of variation in natural populations.

evolutionary biology↗

bioRxiv2024

Integrative multiomic approaches reveal ZMAT3 and p21 as conserved hubs in the p53 tumor suppression network

TP53, the most frequently mutated gene in human cancer, encodes a transcriptional activator that induces myriad downstream target genes. Despite the importance of p53 in tumor suppression, the specific p53 target genes important for tumor suppression remain unclear. Recent studies have identified the p53-inducible gene Zmat3 as a critical effector of tumor suppression, but many questions remain regarding its p53-dependence, activity across contexts, and mechanism of tumor suppression alone and in cooperation with other p53-inducible genes. To address these questions, we used Tuba-seqUltra somatic genome editing and tumor barcoding in a mouse lung adenocarcinoma model, combinatorial in vivo CRISPR/Cas9 screens, meta-analyses of gene expression and Cancer Dependency Map data, and integrative RNA-sequencing and shotgun proteomic analyses. We established Zmat3 as a core component of p53-mediated tumor suppression and identified Cdkn1a as the most potent cooperating p53-induced gene in tumor suppression. We discovered that ZMAT3/CDKN1A serve as near-universal effectors of p53-mediated tumor suppression that regulate cell division, migration, and extracellular matrix organization. Accordingly, combined Zmat3-Cdkn1a inactivation dramatically enhanced cell proliferation and migration compared to controls, akin to p53 inactivation. Together, our findings place ZMAT3 and CDKN1A as hubs of a p53-induced gene program that opposes tumorigenesis across various cellular and genetic contexts.

cancer biology↗

bioRxiv2024

EML4-ALK variant-specific genetic interactions shape lung tumorigenesis

Oncogenic fusions of EML4 and ALK occur in [~]5% of lung adenocarcinomas. More than 15 EML4-ALK variants with distinct breakpoints within EML4 have been identified, but the functional differences between these variants remain poorly understood. Here we use CRISPR/Cas9 somatic genome editing to generate autochthonous mouse models of the two most common EML4-ALK variants, V1 and V3, and show that V3 is more oncogenic than V1. By integrating these models with multiplexed genome editing, we quantify the effects of 29 putative tumor suppressor genes on V1- and V3-driven lung cancer growth in vivo and show that many tumor suppressor genes have dramatically variant-specific effects on tumorigenesis. Analysis of a novel dataset representing the largest human EML4-ALK lung cancer cohort to date identified alterations in the genomic landscape depending on the EML4-ALK variant. These findings demonstrate functional heterogeneity among EML4-ALK variants, suggesting that EML4-ALK variants behave more like distinct oncogenes than a uniform entity. More broadly, these findings highlight the dramatic impact of oncogenic fusions partner proteins on tumor biology.

cancer biology↗

bioRxiv2024

Functional mapping of epigenetic regulators uncovers coordinated tumor suppression by the HBO1 and MLL1 complexes

Epigenetic dysregulation is widespread in cancer. However, the specific epigenetic regulators and the processes they control to drive cancer phenotypes are poorly understood. Here, we employed a novel, scalable and high-throughput in vivo method to perform iterative functional screens of over 250 epigenetic regulatory genes within autochthonous oncogenic KRAS-driven lung tumors. We identified multiple novel epigenetic tumor suppressor and tumor dependency genes. We show that a specific HBO1 complex and the MLL1 complex are among the most impactful tumor suppressive epigenetic regulators in lung. The histone modifications generated by the HBO1 complex are frequently absent or reduced in human lung adenocarcinomas. The HBO1 and MLL1 complexes regulate chromatin accessibility of shared genomic regions, lineage fidelity and the expression of canonical tumor suppressor genes. The HBO1 and MLL1 complexes are epistatic during lung tumorigenesis, and their functional correlation is conserved in human cancer cell lines. Together, these results demonstrate the value of quantitative methods to generate a phenotypic roadmap of epigenetic regulatory genes in tumorigenesis in vivo.

cancer biology↗

bioRxiv2024

Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury

Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.

neuroscience↗

bioRxiv2024

Recommendations for Population and Individual Diagnostic SNP Selection in Non-Model Species

Despite substantial reductions in the cost of sequencing over the last decade, genetic panels remain relevant due to their cost-effectiveness and flexibility across a variety of sample types. In particular, single nucleotide polymorphism (SNP) panels are increasingly favored for conservation applications. SNP panels are often used because of their adaptability, effectiveness with low-quality samples, and cost-efficiency for use in population monitoring and forensics. However, the selection of diagnostic SNPs for population assignment and individual identification can be challenging. The consequences of poor SNP selection are under-powered panels, inaccurate results, and monetary loss. Here, we develop a novel user-friendly SNP selection pipeline for population assignment and individual identification, mPCRselect. mPCRselect allows any researcher, who has sufficient SNP-level data, to design a successful and cost-effective SNP panel for species of conservation concern.

evolutionary biology↗

bioRxiv2024

A shift from pleiotropic to modular adaptation revealed by a high-resolution two-step adaptive walk

Evolution by natural selection is expected to be a slow and gradual process. In particular, the mutations that drive evolution are predicted to be small and modular, incrementally improving a small number of traits. However, adaptive mutations identified early in microbial evolution experiments, cancer, and other systems often provide substantial fitness gains and pleiotropically improve multiple traits at once. We asked whether such pleiotropically adaptive mutations are common throughout adaptation or are instead a rare feature of early steps in evolution that tend to target key signaling pathways. To do so, we conducted barcoded second-step evolution experiments initiated from five first-step mutations identified from a prior yeast evolution experiment. We then isolated hundreds of second-step mutations from these evolution experiments, measured their fitness and performance in several growth phases, and conducted whole-genome sequencing of the second-step clones. Here, we found that while the vast majority of mutants isolated from the first-step of evolution in this condition show patterns of pleiotropic adaptation - improving both performance in fermentation and respiration growth phases - second-step mutations show a shift towards modular adaptation, mostly improving respiration performance and only rarely improving fermentation performance. We also identified a shift in the molecular basis of adaptation from genes in cellular signaling pathways towards genes involved in respiration and mitochondrial function. Our results suggest that the genes in cellular signaling pathways are particularly capable of providing large, adaptively pleiotropic benefits to the organism due to their ability to coherently affect many phenotypes at once. As such, these genes may serve as the source of pleiotropic adaptation in the early stages of evolution, and once these become exhausted, organisms then adapt more gradually, acquiring smaller, more modular mutations.

evolutionary biology↗

bioRxiv2024

Modeling the genomic complexity of human cancer using Cas12a mice

Somatic genome editing in mouse models has increased our understanding of the in vivo effects of genetic alterations in areas ranging from neuroscience to cancer biology and beyond. However, existing models are limited in their ability to create multiple targeted edits. Thus, our understanding of the complex genetic interactions that underlie development, homeostasis, and disease remains incomplete. Cas12a is an RNA-guided endonuclease with unique attributes that enable simple targeting of multiple genes with crRNA arrays containing tandem guides. To accelerate and expand the generation of complex genotypes in somatic cells, we generated transgenic mice with Cre-regulated and constitutive expression of enhanced Acidaminococcus sp. Cas12a (enAsCas12a). In these mice, enAsCas12a-mediated somatic genome editing robustly generated compound genotypes, as exemplified by the initiation of diverse cancer types driven by homozygous inactivation of trios of tumor suppressor genes. We further integrated these modular crRNA arrays with clonal barcoding to quantify the size and number of tumors with each array, as well as the efficiency of each crRNA. These Cas12a alleles will enable the rapid generation of disease models and broadly facilitate the high-throughput investigation of coincident genomic alterations in somatic cells in vivo.

cancer biology↗

bioRxiv2023

Extreme in Every Way: Exceedingly Low Genetic Diversity in Snow Leopards Due to Persistently Small Population Size

Snow leopards (Panthera uncia) serve as an umbrella species whose conservation benefits their high-elevation Asian habitat. Their numbers are believed to be in decline due to numerous Anthropogenic threats; however, their conservation is hindered by numerous knowledge gaps. They are the least studied genetically of all big cat species with more to learn regarding their population structure, historical population size, and current levels of genetic diversity. Here, we use whole-genome sequencing data for 41 snow leopards (37 newly sequenced) to offer new insights into these unresolved questions. Among our samples, we find evidence of a primary genetic divide between the northern and southern part of the range around the Dzungarian Basin, as previously identified, and a secondary divide south of Kyrgyzstan around the Taklamakan Desert. Most noteworthy, we find that snow leopards have the lowest genetic diversity of any big cat species, due to a persistently small population size (relative to other big cat species) throughout their evolutionary history rather than recent inbreeding. Without a large population size or ample standing genetic variation to help buffer them from any forthcoming Anthropogenic challenges, snow leopard persistence may be more tenuous than currently appreciated.

evolutionary biology↗

bioRxiv2023

Improving the accuracy of bulk fitness assays by correcting barcode processing biases

Measuring the fitnesses of genetic variants is a fundamental objective in evolutionary biology. A standard approach for measuring microbial fitnesses in bulk involves labeling a library of genetic variants with unique sequence barcodes, competing the labeled strains in batch culture, and using deep sequencing to track changes in the barcode abundances over time. However, idiosyncratic properties of barcodes (e.g., GC content) can induce non-uniform amplification or uneven sequencing coverage that cause some barcodes to be over-or under-represented in samples. This systematic bias can result in erroneous read count trajectories and misestimates of fitness. Here we develop a computational method for inferring the effects of processing bias by leveraging the structure of systematic deviations in the data. We illustrate this approach by applying it to fitness assay data collected for a large library of yeast variants, and show that this method estimates and corrects for bias more accurately than standard proxies, such as GC-based corrections. Our method mitigates bias and improves fitness estimates in high-throughput assays with-out introducing additional complexity to the experimental protocols, with potential value in a range of experimental evolution and mutation screening contexts.

evolutionary biology↗

bioRxiv2023

Bayesian inference of relative fitness on high-throughput pooled competition assays

The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.

evolutionary biology↗