337 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 paper develops and validates a new analytical framework based on effective migration rates to predict how polygenic divergent selection shapes genomic patterns of differentiation and reproductive isolation in mainland-island models, offering improved tools for inferring the genetic architecture of barriers to gene flow.
The paper introduces antiGen, a machine learning model that leverages phylogenetic trees to accurately forecast future viral mutations across multiple pathogens, including SARS-CoV-2, influenza, and dengue, thereby enhancing pandemic preparedness and therapeutic development.
This study evaluates SNaQ's performance on non-level-1 phylogenetic networks, revealing that while it cannot recover exact topologies of overlapping reticulations, it reliably infers circular taxon orders and compatible tree-of-blobs structures, effectively acting as a conservative regularizer that prioritizes strong reticulation signals over complex, overlapping evolutionary histories.
This study presents a large-scale evaluation of 54 phylogenetic tree shape indices on over 45 million empirical trees using the new Python library "treeshapy," revealing critical pitfalls such as root sensitivity, size dependency, and index redundancy to guide more cautious and effective future tree shape analyses.
This study demonstrates that despite the potential of variational autoencoders to model epistatic interactions, their inherent information loss during the decoding process prevents them from accurately reconstructing ancestral sequences, as they are consistently outperformed by standard likelihood-based and parsimony methods.
The authors introduce TimeFIG, a Bayesian phylogenetic framework that integrates genetic, range, and paleogeographic data to simultaneously infer divergence times, ancestral ranges, and diversification rates without fossils, revealing that island isolation and age drive the evolutionary dynamics of the Hawaiian *Kadua* radiation.
This study proposes the establishment of a new viral order, Ariadnavirales, within the class Megaviricetes, based on the discovery of Sicyoidochytrium minutum DNA virus and related sequences that exhibit a unique evolutionary transition toward host-nucleus-dependent replication and transcription due to the loss of their own replication and transcription machinery.
This study demonstrates that nuclear-encoded plastid DNA (NUPTs) can effectively identify specific donor species of grass-to-grass lateral gene transfer, revealing that *Eremochloa attenuata* co-transferred a DNA fragment containing both a previously known LGT and a newly identified NUPT into *Alloteropsis semialata*.
This paper demonstrates that the evolution of family-based reputation creates a positive feedback loop between kin selection and indirect reciprocity, thereby expanding the conditions under which cooperation can be sustained, particularly when interactions are infrequent or individual behavior is difficult to observe.
This study demonstrates that Lusitanian wall lizards resolve the trade-off between conspecific communication and predator avoidance through distance-dependent colour-pattern perceptibility, a strategy that is maintained in females and smaller individuals but sacrificed by larger males to prioritize intraspecific signaling.