Eric P Palkovacs | Search PubMed

PubMed2026

Bycatch in a bottle: what taxa are recoverable from metabarcoding DNA in historical invertebrate collection preservative fluid?

Natural history museum collections are invaluable repositories of biodiversity, offering insights into life on Earth. Genomic approaches provide powerful tools to characterize biodiversity in these collections. However using these collections for genomics without damaging specimens is a challenge. Here, we develop and test non-destructive DNA metabarcoding methods to capture biodiversity from the preservative fluids of archived insect collections ('Bycatch'). We optimized workflows for extracting and amplifying the partial CO1 locus (CO1) and fungal ITS1 locus from ethanol-based preservative fluids, validating ethanol preparation methods, comparing DNA extraction kits, and refining PCR protocols. Our results demonstrate that from museum collections with low DNA yields, CO1 and fungal ITS1 loci can often be recovered from preservative fluids, and we present detailed methodology and workflows. We test metabarcoding success to recover taxa in several museum collections ranging in age and storage condition. This is to support the State of California's effort to catalog and sequence all insects and fungi, building baselines of California biodiversity with help from museum collections. Lastly, we investigate the complementarity of metabarcoding water versus ethanol and morphological identifications aimed to capture benthic macroinvertebrate biodiversity in streams. Our findings highlight that DNA metabarcoding of the preservative fluid is a non-destructive tool for capturing biodiversity in historical specimens, but there are limitations on the overlaps between DNA results and physical contents, where morphological identification still reigns in taxon counts, but metabarcoding sometimes provides more taxonomic resolution, and can be used to track DNA from other organisms such as fungi beyond the directly surveyed specimens.

Animals↗

PubMed2026

The Spatial and Temporal Repeatability of Genomic Responses to Natural Selection as Demonstrated in Stickleback Populations Experiencing Highly Dynamic Environments.

The evolution of genotypic parallelism under shared environmental conditions provides strong evidence for the role of natural selection. However, analyses typically examine genomic signatures of selection long after the putative selection event and only assess the repeatability of responses across spatial population replicates. This impedes our ability to attribute a particular response to a given selection pressure and to distinguish non-parallel responses caused by stochastic processes from those caused by local selection. As such, the consistency of natural selection over space and time is unknown, and the role of persistent local selection pressures is unclear. Here, we leveraged the natural bar-built estuary system of Santa Cruz, California, to examine the repeatability of seasonal genomic change in threespine stickleback (Gasterosteus aculeatus) over space and time. By comparing allele-frequency shifts that are shared across locations (spatial repeatability) with those that are shared across years within locations (temporal repeatability), we identified both spatially shared and local components of putative selection. We found that repeated seasonal outlier responses occurred more often than expected under a neutral null model. Although repeatability declined as the number of estuaries sharing an outlier increased, enrichment above neutral expectations increased with broader spatial sharing, particularly for outliers repeated across both years. While the precise outlier SNPs varied across years, estuary-specific patterns of responses were broadly consistent, suggesting an important role for local conditions. Together, our findings show that temporal sampling can reveal components of putative selection that would be missed from spatial comparisons alone. More broadly, they highlight the importance of examining repeatability over both space and time to understand the parallel and non-parallel components of adaptive genomic change.

Animals↗