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 meta-analysis of 123 effect sizes from 11 studies finds limited evidence for a general relationship between epidemic size and host-parasite coevolution, revealing that evolutionary responses are highly system-specific and dependent on host taxonomy and ecological context rather than epidemic magnitude alone.
This study identifies a functional, complete mitochondrial genome integrated into the nuclear genome of the sawfly *Euura vittata*, likely resulting from recent introgression, and highlights the critical need for long-read sequencing to distinguish such NUMTs from divergent heteroplasmy.
This paper demonstrates that domain adaptation techniques can significantly improve the robustness of supervised machine learning models in population genetics by enabling accurate detection of introgression even when training data fails to account for complex, unmodelled evolutionary processes like ghost introgression.
This study establishes *Caenorhabditis becei* as a tractable gonochoristic model organism by demonstrating the conservation of key genetic features found in androdioecious species while characterizing its unique genomic architecture, including a large X chromosome and distinct GC composition shifts, through the generation of a high-quality reference genome assembly.
This paper presents a population genetic model for mutator alleles with arbitrary dominance to analyze human germline mutation rate modifiers, finding that most known variants are consistent with purifying selection while suggesting that recessive mutators are likely underrepresented in current discovery efforts due to detection biases.
Ancestree is a unified likelihood-based framework that infers ancestral alleles across diverse inputs—including plain variant data, ancestral recombination graphs, and locally sampled trees—while accommodating complex mutation scenarios and demonstrating superior accuracy and scalability compared to existing tools, particularly when leveraging outgroup information.
This paper introduces DSTAR, a new rarefaction-based method that overcomes the limitations of the traditional D statistic by enabling precise detection of local introgression in multi-lineage datasets without requiring an outgroup, as demonstrated by its successful identification of Denisovan immune-related DNA in modern Papuans.
By integrating an accounting model with an optimization framework to disentangle mechanical relationships from causal effects, this study demonstrates that while early life adversity influences life history variables, it does not support the hypothesis that such adversity accelerates reproductive trajectories to maximize fitness in wild female baboons.
By analyzing a comprehensive deep mutational scanning dataset of IGPD and other proteins, this study identifies a distinct class of "super compensatory" substitutions at solvent-exposed residues that not only restore function to nonfunctional variants but also broadly enhance mutational robustness across diverse genetic backgrounds.
This paper introduces PartitionFinder-mAIC, a new feature in IQ-TREE 3 that utilizes the marginal Akaike Information Criterion to select more efficient partitioning schemes, resulting in fewer partitions and improved phylogenetic inference accuracy compared to traditional AIC and BIC methods.