bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.04.27.721231

The genome of the Pacific acorn barnacle provides insights into the evolution of extremely large populations

Rivera-Colon, A. G.·Small, S. T.·Jezuit, E.·Wares, J. P.·Kern, A. D.
View original source ↗Export metadata ↓

Abstract

Population size is a key factor underlying the mode and tempo of evolution, particularly as it relates to the strength of selection and drift. While the mechanisms underlying the interactions between population size and selection have been studied in population genetics for over a century, empirical knowledge of these dynamics has been limited to species with small-to-moderate historical population sizes. This gap in knowledge highlights the need for empirical studies in systems with historically large population sizes and elevated diversity. The Pacific acorn barnacle (Balanus glandula) presents an exceptional model to study evolution in extremely large populations, exhibiting census sizes often exceeding the tens of thousands of individuals per square meter. We generated a new chromosome-level genome assembly for this species, which we leverage in one of the first large-scale genomic analyses in this system. This assembly reveals a highly polymorphic genome with over 3% heterozygosity. At a population level, B. glandula exhibits extreme levels of polymorphism, with nucleotide diversity surpassing 5% genome-wide in just a small collection of individuals. Across the genome, nucleotide diversity predictably decreases at functional elements, including both coding and non-coding sequences, likely reflecting strong purifying selection along the genome. At the same time, McDonald-Kreitman tests reveal that the majority of non-synonymous substitutions between barnacle species were driven by positive selection, consistent with the expected increase in the efficacy of selection in large populations. These remarkable levels of diversity set B. glandula as a unique model for the study of evolution at extreme demographic scales and highlights the importance of testing evolutionary theory across a wide variety of empirical systems.

Explore related subjects

evolutionary biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rivera-Colon, A. G., Small, S. T., Jezuit, E., Wares, J. P., Kern, A. D.. 2026-04-28. The genome of the Pacific acorn barnacle provides insights into the evolution of extremely large populations. https://doi.org/10.64898/2026.04.27.721231

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Ocean current models predict spatial structure for coastal biodiversity

Genomic diversity provides the raw material through which all evolutionary processes occur. Accurately describing how environmental features affect patterns of diversity shows promise in predicting the resilience of populations and entire communities to dynamic environments and novel stressors. Identifying the contribution of purely neutral responses to environmental effects can be difficult, especially across large spatial ranges with many covarying environmental features. Using an individual-based model of larvae carried by ocean currents, we predict patterns of neutral genomic diversity in a passively dispersed coastal species, suggesting large geographic regions of relative homogeneity with ancestry determined by the nearest "upstream" population with limited larval input. The genomic identity that dominates each region sharply transitions at the next such interruption, generating hierarchical structure and violating assumptions of isolation-by-distance. We call these upstream populations "lineage source regions" (LSRs), and we find strong concordance between LSR model predictions and an empirical population genomic survey of a keystone salt marsh mussel (Geukensia demissa). We quantitatively validate model performance and goodness-of-fit, updating baseline predictions of genomic diversity patterns from the classic isolation-by-distance model to this LSR framework. This spatially explicit coastal ancestry model has potential for generalization across passive dispersing species.

evolutionary biology↗
bioRxiv2026

TaxaAudit: A statistical model of consensus in phylogenetics identifies non-monophyletic taxa

Interpreting variation in genes and traits across species requires understanding their evolutionary relationships. Taxonomic hierarchies provide a practical approximation of the tree of life, with the NCBI taxonomy linking this framework directly to public sequence data. Some named groups, however, are not evolutionary clades, and recognizing these exceptions requires knowledge scattered across the phylogenetics literature. Here we introduce TaxaAudit, a statistical model that identifies taxonomic groups whose monophyly is repeatedly contradicted by published phylogenies. The model accounts for background taxonomic conflict and the ability of each study's species sampling to expose non-monophyly. Applied to 5,865 molecular phylogenies from TimeTree, TaxaAudit flagged 516 NCBI taxa at family rank and below for significant recurrent contradiction of monophyly. Excluding these taxa's monophyly requirements improved the taxonomy's agreement with independent phylogenomic reference trees and phylogenies withheld from discovery. Flagged taxa were also 3.61 times as likely as matched controls to have their monophyly challenged in publications outside the discovery set. In tree-inference experiments, excluding these monophyly constraints improved agreement with reference phylogenies relative to enforcing the unmodified taxonomy. By identifying groups whose monophyly should not be assumed, TaxaAudit lets researchers draw on published phylogenetic knowledge without reviewing the specialist literature for every taxon. This supports broader use of the NCBI taxonomy as an evolutionary framework for biological comparisons.

evolutionary biology↗
bioRxiv2026

Shared landscape, divergent genomes: Comparative population genomics of co-occurring flora in an isolated Australian mountain range

Understanding how landscape heterogeneity shapes genomic variation is key to conserving biodiversity and evolutionary potential. Yet conservation genomics is typically conducted at the single species level, limiting our ability to identify shared genomic patterns or understand how co-occurring taxa differ in their response to common environmental gradients. We assessed spatial patterns of genomic variation and their associations with geographic and environmental features among populations of nine co-existing plant species with contrasting life-histories and ecological traits across Gariwerd, a threatened biodiversity hotspot in south-eastern Australia. All species exhibited weak overall genetic structure, although the magnitude and spatial distribution of differentiation varied among species. Despite this variation, broadly consistent spatial trends were apparent, with higher genomic divergence largely concentrated in central zones and higher genomic diversity localised in southern regions of the landscape. Significant associations between genetic differentiation and geographic distance were observed in three species, while another species showed associations with environmental distance. These findings demonstrate that coexisting species can show overlapping spatial patterns in genomic variation while differing markedly in their associations with geographic and environmental variation across the same landscape. This comparative approach provides a basis for spatial prioritisation and conservation planning, while highlighting the complex eco-evolutionary processes operating across heterogeneous landscapes.

evolutionary biology↗