In sexual populations, gene-flow between niches is predicted to have differential consequences on local adaptation contingent upon the nature of trade-offs underlying local adaptation. Sex retards local adaptation if antagonistic pleiotropy underlies trade-offs, but facilitates adaptation if mutation accumulation underlies trade-offs. We evaluate the effect of sex in heterogeneous environments by manipulating gene-flow between two niches in sexual and asexual populations using steady-state microcosm experiments with yeast. We find that only sex in the presence of gene-flow promotes simultaneous local adaptation to different niches, presumably as this exposes mutations neutrally accrued in alternate niches to selection. This finding aligns with work showing mutation accumulation underlies trade-offs to local adaptation in asexual microbes, and with inferences of divergence in the presence of gene-flow in natural sexual populations. This experiment shows that sex may be of benefit in heterogeneous environments, and thus helps explain why sex has been maintained more generally.
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http://dx.doi.org/10.1111/j.1461-0248.2012.01814.x | DOI Listing |
Adv Ther
January 2025
Department of Endocrinology and Nutrition, Hospital Universitari de Bellvitge-IDIBELL, C/de la Feixa Llarga S/N, 08907, Hospitalet de Llobregat, Barcelona, Spain.
Introduction: Obesity and its complications are associated with high morbidity/mortality and a significant healthcare cost burden in Spain. It is therefore essential to know the potential clinical and economic benefits of reducing obesity. The objective of this study is to predict the decrease in rates of onset of potential complications associated with obesity and the cost savings after a weight loss of 15% over 10 years in Spain.
View Article and Find Full Text PDFMol Ecol
January 2025
Department of Environmental Toxicology, University of California Davis, Davis, California, USA.
Characterising patterns of genetic diversity including evidence of local adaptation is relevant for predicting and managing species recovering from overexploitation in the face of climate change. Red abalone (Haliotis rufescens) is a species of conservation concern due to recent declines from overharvesting, disease and climate change, resulting in the closure of commercial and recreational fisheries. Using whole-genome resequencing data from 23 populations spanning their entire range (southern Oregon, USA, to Baja California, MEX) we investigated patterns of population connectivity and genotype-environment associations that would reveal local adaptation across the mosaic of coastal environments that define the California Current System (CCS).
View Article and Find Full Text PDFMol Ecol
January 2025
Department of Biology, Colorado State University, Fort Collins, Colorado, USA.
Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity.
View Article and Find Full Text PDFGut Pathog
January 2025
Diarrheal Pathogens Research Unit (DPRU), Department of Virology, Sefako Makgatho Health Sciences University, Ga-rankuwa, Pretoria, South Africa.
Bacterial flagellin, a potent intestinal innate immune activator, prevents murine rotavirus (RV) infection independent of adaptive immunity and interferons. The flagellin-induced immunity is mediated by Toll-like receptor (TLR5) and Nod-like receptor C4 (NLRC4), which elicit the production of interleukins 22 (IL-22) and IL-18, respectively. Here, we assessed whether a high abundance of flagellin at the time of vaccination would negatively affect the oral RV vaccine take.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.
Background: Drug response prediction is critical in precision medicine to determine the most effective and safe treatments for individual patients. Traditional prediction methods relying on demographic and genetic data often fall short in accuracy and robustness. Recent graph-based models, while promising, frequently neglect the critical role of atomic interactions and fail to integrate drug fingerprints with SMILES for comprehensive molecular graph construction.
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