295 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 analyzing high-quality telomere-to-telomere genome assemblies across eight primate species, this study reveals that while Y-linked ampliconic genes are primarily under purifying selection, X-linked ampliconic gene families exhibit pervasive positive selection and dynamic copy number variation, likely driven by sperm competition, meiotic drive, or dosage-dependent selection.
This paper proposes that geochemical changes around 3.9–3.8 billion years ago triggered a mass extinction of ribozymes, from which resilient "generalist" survivors like the hammerhead ribozyme expanded as disaster taxa, leaving an ecological legacy that fundamentally shaped the structure and organization of the modern genetic code.
By integrating cytogenetic and genomic mapping across a 50-million-year timeline, this study reveals that the structural evolution of the allotetraploid *Xenopus borealis* involved 17 rearrangements accumulating in three distinct temporal strata while maintaining persistent sex chromosome homomorphism, challenging the notion that polyploid structural changes occur solely in immediate bursts following whole-genome duplication.
This study reveals that intensifying drought in a dependent-lineage population of red harvester ants has driven a sharp decline in the rare J1 lineage and altered demographic patterns, suggesting that rapid environmental shifts are reshaping population dynamics faster than natural selection can act on specific phenotypic traits.
This study investigates the relationship between X-chromosomal diversity and climate, finding mixed results where initial associations with temperature and sex-biased migration were not consistently replicated across different datasets, ultimately leaving the existence of a climatic signal in X-chromosomal diversity unclear.
This paper presents a diffusion-based model demonstrating that under stabilizing selection on a polygenic trait, a persistent deviation of the trait mean from its optimum generates a pervasive, constant intensity of genic selection across loci, while providing a framework to predict macroscopic observables like genetic variance and the dynamics of the trait mean.
Through forward-time simulations, this study demonstrates that the mode of selection (hard vs. soft) fundamentally dictates the scaling relationships between population size, genetic load, and nucleotide diversity, revealing how soft selection decouples neutral diversity from mutational burden and offers a mechanistic explanation for the weak correlation between census size and genetic diversity known as Lewontin's paradox.
This study constructs an operational genotype-phenotype map for influenza hemagglutinin using predicted secondary structure to reveal that protein neutral networks are characterized by strong phenotypic bias, locally structured but globally constrained connectivity, and limited long-range evolvability compared to RNA systems.
By integrating remote homology detection, AlphaFold structural modeling, and functional genetics, this study reveals that Scm3/HJURP orthologs are universally conserved across metazoans despite rapid sequence divergence, overturning the previous belief that they were absent in insects, nematodes, and many vertebrates.
This paper introduces a novel stochastic framework based on measure-valued processes to model integrated eco-evolutionary dynamics, revealing that genetic drift fundamentally alters the orientation of the G-matrix by driving genetic correlations to extremes, a finding that challenges conventional wisdom and aligns with empirical observations.