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.
This study utilizes long-read and short-read sequencing to identify species-specific structural variants in North American deer, revealing that these genomic changes, particularly those affecting reproduction and sensory adaptation, likely play a significant role in adaptive divergence and reproductive isolation during speciation.
This study reveals that brain-related traits, including psychiatric disorders, exhibit distinct genetic architectures characterized by weaker GWAS associations and higher allele frequencies due to strong selective constraints acting on their large mutational target sizes, suggesting that the tissues mediating complex traits fundamentally shape their genetic underpinnings.
By developing an evolutionarily informed gene-set framework to analyze single-cell data across eleven vertebrate species, this study reveals that forebrain evolution proceeds through lineage-specific tuning of deeply conserved transcriptional programs within stable cellular architectures rather than the emergence of entirely new cell types.
By analyzing the distribution of fitness effects across 38 catarrhine primates, this study demonstrates that interspecific differences in deleterious mutations are primarily driven by variation in effective population size rather than clade-specific factors, supporting the nearly neutral theory and confirming the robustness of these findings to demographic history and dominance effects.
Ancient DNA analysis of Song Dynasty melon seeds from China reveals that these fruits were introduced from the broader Asian domestication pool rather than independently domesticated locally, and were likely consumed as fresh or culinary fruits with green flesh and jade-green aesthetics rather than as sweet dessert melons.
This study reconstructs mobility patterns among Eneolithic-Bronze Age populations in the North Pontic steppe by establishing a regional strontium isotope baseline and analyzing human remains to identify individuals who migrated from the eastern or western Caspian steppes or experienced physiological stress.
This paper introduces Genomebook, a system that encodes LLM agent behaviors into a Mendelian genetic framework to demonstrate that structured, heritable parameterization enables predictable evolutionary adaptation and trait selection, unlike non-genetic baselines which converge to static population means.
This paper presents a Bayesian approach that links cross-inoculation assay data to Fisher's geometrical model to infer a multi-host fitness landscape for endive necrotic mosaic virus, revealing host permissiveness heterogeneity and phylogenetic concordance to better understand viral adaptation and establishment barriers.
This paper proposes a kinetic proofreading model demonstrating that environmental perturbations dynamically modulate genomic error correction to balance mutational supply and viability, thereby mechanistically explaining punctuated equilibrium and the constraints on evolutionary resilience dictated by the drift-barrier principle.
This study adapts the deep learning software phyddle to perform ancestral state reconstruction for discrete characters, demonstrating that while it matches Bayesian inference on simple models and small trees, it offers a viable alternative for complex models with intractable likelihoods, as validated by its application to empirical datasets including Liolaemus lizards and the 2014 Ebola outbreak.