Biology subjects

Rose, M. R.

Publications and source records attributed to Rose, M. R..

4 recordsLinked to original sources

bioRxiv2026

Beyond Fixation: Persistent Genetic Variation Under Intense Selection

Understanding how and why genetic variation is maintained under sustained selection remains a central question in evolutionary genetics. Experimental evolution shows that adaptation in sexually reproducing populations is often highly polygenic, proceeding through coordinated, genome-wide allele frequency shifts from standing variation rather than classic hard sweeps. Recent explanations emphasize highly polygenic architectures, optimizing-selection, and genetic redundancy, which can slow fixation by distributing selection across many loci during adaptation. However, observations from long-term selection experiments reveal a pattern these frameworks do not fully explain: substantial genetic variation persists after hundreds of generations of intense directional selection in constant environments. Here, we use long-term experimental evolution in Drosophila melanogaster to test whether balancing-selection actively maintains genetic variation under strong life-history selection and preserves evolutionary reversibility. Longstanding populations selected for accelerated or delayed reproduction were shifted to the opposing regime, imposing age-structured fitness trade-offs. Notably, selection for early reproduction is associated with substantial loss of genetic variation, providing a stringent test of whether standing variation is truly depleted. Following reciprocal shifts, populations showed rapid phenotypic convergence toward the target regime. At the genomic level, allele-frequency trajectories were strongly antiparallel and highly repeatable across replicates, revealing coordinated polygenic responses. Relaxing long-standing early-life selection produced a pronounced rebound in genome-wide heterozygosity. Deep sequencing uncovered ultra-rare alleles at sites appearing fixed under standard coverage, indicating low-frequency functional variation persists below detection thresholds. These results suggest that substantial genetic variation can persist under intense directional selection and be rapidly redeployed when selection reverses, consistent with widespread balancing-selection.

evolutionary biology↗

bioRxiv2022

Building bridges from genome to physiology using machine learning and Drosophila experimental evolution

Drosophila experimental evolution, with its well-defined selection protocols, has long supplied useful genetic material for the analysis of functional physiology. While there is a long tradition of interpreting the effects of large-effect mutants physiologically, in the genomic era identifying and interpreting gene-to-phenotype relationships has been challenging, with many labs not resolving how physiological traits are affected by multiple genes throughout the genome. Drosophila experimental evolution has demonstrated that multiple phenotypes change due to the evolution of many loci across the genome, creating the scientific challenge of sifting out differentiated but noncausal loci for individual characters. The fused lasso additive model method (FLAM) allows us to infer some of the differentiated loci that have relatively greater causal effects on the differentiation of specific phenotypes. The experimental material used in the present study comes from 50 populations that have been selected for different life-histories and levels of stress resistance. Differentiation of cardiac robustness, starvation resistance, desiccation resistance, lipid content, glycogen content, water content, and body masses was assayed among 40 to 50 of these experimentally-evolved populations. Through FLAM, we combined physiological analysis from eight parameters with whole-body pooled-seq genomic data to identify potentially causally linked genomic regions. We have identified approximately 1,900 significantly differentiated 50 kb genomic windows among our 50 populations, with 161 of those identified genomic regions highly likely to have a causal effect connecting specific genome sites to specific physiological characters.

physiology↗

bioRxiv2020

Genome-Wide Architecture of Adaptation in Experimentally Evolved Drosophila

The molecular basis of adaptation remains elusive even with the current ease of sequencing the genome and transcriptome. We used experimentally evolved populations of Drosophila in conjunction with statistical learning tools to explore interactions between the genome, the transcriptome, and phenotypes. Our results indicate that transcriptomic measures from adult samples can predict phenotypic characters at many adult ages. Importantly, when comparing the genome and transcriptome in predicting phenotypic characters, we find that the two types of data are comparably useful. When using genome sites as predictors for the expression of the transcriptome, we find that gene expression is influenced by genomic regions across all large chromosome arms. Conversely, we found many genomic regions influencing the expression of numerous genes, which is consistent with widespread pleiotropy. Our results also highlight the power of the combination of experimental evolution, next-generation sequencing, and statistical learning tools in exploring the molecular basis of adaptation.

evolutionary biology↗

bioRxiv2019

How phenotypic convergence arises in experimental evolution

Evolutionary convergence is a core issue in the study of adaptive evolution, as well as a highly debated topic at present. Few studies have analyzed this issue using a \"real-time\" or evolutionary trajectory approach. Do populations that are initially differentiated converge to a similar adaptive state when experiencing a common novel environment? Drosophila subobscura populations founded from different locations and years showed initial differences and variation in evolutionary rates in several traits during short-term ([~]20 generations) laboratory adaptation. Here we extend that analysis to 40 more generations to analyze (1) how differences in evolutionary dynamics between populations change between shorter and longer time spans, and (2) whether evolutionary convergence occurs after sixty generations of evolution in a common environment. We found substantial variation in longer-term evolutionary trajectories and differences between short and longer-term evolutionary dynamics. Though we observed pervasive patterns of convergence towards the character values of long-established populations, populations still remain differentiated for several traits at the final generations analyzed. This pattern might involve transient divergence, as we report in some cases, indicating that more generations should lead to final convergence. These findings highlight the importance of longer-term studies for understanding convergent evolution.

evolutionary biology↗