Biology subjects

Perez, T. J.

Publications and source records attributed to Perez, T. J..

3 recordsLinked to original sources

bioRxiv2026

Adaptation and conservation of turtle visual opsins over a deep phylogenetic divergence

The ecological radiation of organisms in diverse light environments depends, in part, on adaptive alterations within visual systems, particularly retinal photoreceptors and their visual pigments. Evidence of visual adaptation occurs across vertebrate lineages but is notably lacking in turtles, despite their complex visual system with up to eight photoreceptor cell types and five visual pigments. This lack of knowledge is especially pronounced in side-neck turtles (Pleurodira), as nearly all information on turtle vision derives from hidden-neck turtles (Cryptodira). Here, we bridge this ~200-million-year evolutionary gap by investigating visual opsin evolution using an eye transcriptome and whole-genome sequences from 59 turtle species spanning both suborders, as well as an additional 42 representative reptile species. We estimated selective pressures using codon-based evolutionary models, testing for positive selection and long-term shifts between turtles and other reptiles, between suborders, and among major habitat types. We also analysed spectral tuning sites to assess how spectral sensitivity diverged between and within suborders. Our analyses revealed remarkably conserved turtle visual opsin sequences, with phylogeny-wide positive selection detected only in LWS. Habitat explained more shifts in selective pressure than taxonomy, with long-term shifts detected across all five opsins. Spectral tuning sites predict conserved UV sensitivity of SWS1 across cryptodirans, consistent with the few species previously characterised, whereas shared changes identified in pleurodirans predict violet sensitivity, revealing previously unrecognized divergence in short-wavelength vision between turtle suborders. This study advances our understanding of turtle visual system evolution and highlights the need for conservation strategies that account for their distinct visual capabilities.

evolutionary biology↗

bioRxiv2026

HYphlow: bringing end-to-end flow to HyPhy selection analyses, from taxon reconciliation to trait-based foreground assignment

Phylogenetic analyses of molecular evolution often require repeated manual preparation to reconcile taxa, annotate trees, execute models, and summarize results. These steps become increasingly time-consuming and difficult to standardize as the number of taxa, genes, and analytical hypotheses increases. We present HYphlow, an open-source graphical workflow developed in Python that integrates data preparation, trait-based foreground branch assignment, HyPhy execution, and structured result extraction within a single interface. HYphlow reconciles taxon labels across alignments, trees, and trait data; reconstructs ancestral states using parsimony and maximum likelihood; generates alternative foreground annotations; executes HyPhy analyses locally or through portable scripts for high-performance computing; and records analytical decisions and settings throughout the workflow. We evaluated HYphlow using simulations and two published datasets comprising cryptochrome analyses in pigeons and doves and visual opsin analyses in skinks. A name-similarity threshold of 80 reliably recovered simulated spelling variants, while consensus foreground assignment increased precision relative to parsimony or maximum likelihood alone (0.928 vs 0.891 and 0.907, respectively), with a corresponding reduction in recall (0.875 vs 0.921 and 0.918). In the empirical datasets, HYphlow reconciled taxon labels, reconstructed or reproduced foreground hypotheses derived using different approaches, and generated selection results consistent with the principal conclusions of the original studies. HYphlow therefore provides a reproducible framework for carrying comparative molecular evolutionary analyses from independently prepared sequence, phylogenetic, and trait data through branch assignment, model execution, and results summary while retaining researcher control over analytical decisions. HYphlow is freely available under the MIT licence from GitHub at: https://github.com/Schott-Lab/HYphlow.

bioinformatics↗

bioRxiv2023

Comparing Approaches to Specimen Identification using Neotropical Freshwater Fishes in the Barra del Colorado Wildlife Refuge, Costa Rica

As global biodiversity declines continue, conservation efforts are increasingly important in megadiverse areas such as the Neotropics where biodiversity is especially imperiled. The accurate identification of specimens is critical to successful conservation plans. However, in groups such as freshwater fishes, different identification methodologies have documented challenges. Using a biodiversity survey of fishes from the Barra del Colorado Wildlife Refuge in northeastern Costa Rica, we compared: (1) morphological identifications in the field, (2) morphological identifications in the lab by experts, (3) DNA barcode-based identifications, and (4) identifications based on an integrative approach. Our results suggest that both barcode-based identifications and field morphological identifications provided fewer correct species identifications than lab identifications performed by experts using morphology. We attribute shortfalls of DNA barcoding in this case to the misidentification of reference material, the use of outdated taxonomy for references sequences, and the non-uniform representation of groups in public databases across taxa. We suggest the use of an integrative approach to identify freshwater fishes in Costa Rica and other megadiverse areas of the Neotropics where similar issues with public barcode reference libraries exist. We also recommend the creation of regional curated barcode reference libraries to aid in the identification of traditionally difficult to identify species/specimens. We also provide the most up to date species list for the ichthyofauna of the Barra del Colorado Wildlife Refuge identifying 51 species from 42 genera, 21 families, and 17 orders. Generating accurate species lists for protected areas and areas of importance will provide conservation practitioners with effective tools for tracking diversity changes over time.

molecular biology↗