389 papers
Evolutionary biology explores the dynamic history of life on Earth, tracing how species change, adapt, and diversify over time. This field investigates the mechanisms driving everything from the development of antibiotic resistance in bacteria to the complex social behaviors of primates, revealing the deep connections that bind all living organisms together.
On Gist.Science, we ensure these groundbreaking discoveries remain accessible by processing every new preprint uploaded to bioRxiv in this category. Our team generates both plain-language overviews and detailed technical summaries for each paper, bridging the gap between raw research and public understanding without requiring a specialized background.
Below are the latest studies in evolutionary biology, offering fresh insights into the ongoing story of life.
By combining micro-tomographic imaging with genomic analysis of cichlid hybrids, this study reveals that brain morphology evolves through largely structure-specific genetic loci rather than global factors, suggesting a modular genetic architecture that allows individual brain components to evolve independently despite their phenotypic integration.
This study uses an NKC model to demonstrate that intergenomic epistasis in coevolving species drives highly repeatable adaptation patterns that diverge from intragenomic expectations due to fitness trade-offs, often resulting in evolutionary cycling and increased fitness loads.
This paper derives a saddle-point approximation revealing that the genotypic density of additive fitness landscapes near maximal fitness follows a power law rather than a Gaussian distribution, demonstrating that the peaks of these "Mount Fuji" landscapes are significantly broader and "stubbier" than previously understood.
By analyzing the distribution of derived alleles, this study provides evidence that human ancestors interbred with two distinct superarchaic populations: an earlier-diverging group that contributed to Neanderthals and Denisovans, and a later-diverging group that contributed to early modern humans in Africa.
This study develops a mathematical model incorporating stem cell dynamics to infer somatic mutation rates and genetic drift patterns in long-lived tropical Dipterocarpaceae trees, revealing how shoot elongation and branching drive genetic mosaicism and providing more accurate mutation rate estimates than previous static approaches.
This study establishes a natural predator-prey model using *Pristionchus pacificus* and *Oscheius myriophilus* on beetle carcasses, revealing evidence of a co-evolutionary arms race where the prey's partial resistance and unique mixed reproductive strategy (including internal hatching) likely evolved as countermeasures against predation.
This study demonstrates that Quaternary climatic changes and the Central Valley barrier drove the codiversification of the California carpenter ant *Camponotus laevigatus* and its endosymbiont *Blochmaniella*, resulting in congruent phylogeographic patterns and Pleistocene divergence across three distinct genetic clusters.
By integrating comparative morphology, kinematics, and aerodynamics across 133 Dipteran species, this study reveals that insect flight diversity is shaped by the interplay of phylogenetic history, aerodynamic constraints, and scaling laws, where tiny flies prioritize force production through larger wings and higher frequencies while larger species face power limitations that drive increased muscle mass, alongside specific evolutionary trade-offs like the acoustic-muscular adaptation in mosquitoes.
This study reveals that in variationally modular organisms, evolution is constrained by a "module-selection balance" where traits improve at equal rates rather than following the fitness gradient, a phenomenon supported by theoretical models and empirical data from *E. coli* long-term evolution experiments.
This study presents a comprehensive, living database of genetic paternity across 52 primate species and uses Bayesian modeling to demonstrate that while phylogeny has a modest influence, group composition is the strongest predictor of primary male paternity success, revealing a complex relationship between social organization and reproductive outcomes that challenges simple categorical predictions.