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BATOseq-PE: A public batoid DNA library with the first molecular insights into the cryptic diversity, genetic health, and management of Peruvian marine rays

Preprint Created on 22 Sep 2026 bioRxiv

Batoids (rays, skates, and relatives) are among the most threatened cartilaginous fishes globally, yet the molecular diversity of Peruvian taxa remains poorly evaluated. Furthermore, regional barcode sequences for high-conservation-priority taxa, such as sawfish, manta, and devil rays, are often restricted to private records, hindering essential phylogeographic and population structure assessments. To bridge this gap, we developed BATOseq-PE, the first public genetic reference library for Peruvian marine batoids, covering 14 species sequenced in vitro from local specimens, complemented by a novel in silico assembled mitogenome for Notoraja martinezi. This open-access repository contributes 73 novel COI barcodes, providing robust taxonomic resolution across 15 molecular operational taxonomic units (MOTUs) and Barcode Index Numbers (BINs). Notably, we provide the first Peruvian public records for high-priority species such as Mobula munkiana, Mobula thurstoni, Myliobatis peruviana, Rostroraja velezi, and the first global public barcodes for N. martinezi and Zapteryx xyster. By coupling BATOseq-PE with global datasets, we conducted the first multi-taxa screening for delimitation and phylogeographic assessments on Peruvian batoids, revealing a cryptic lineage within R. velezi and genetic connectivity patterns suggesting female philopatry in Mobula mobular. Finally, by integrating nucleotide diversity into a Genetic Diversity Risk Indicator (GDRI) alongside ecological and fishery data, we identified an alarming trend where heavy fishing pressure overlaps with extinction risk and depleted genetic diversity, allowing us to suggest data-driven, tailored management strategies. BATOseq-PE represents a valuable resource to accelerate taxonomic and population assessments, ultimately fostering ray conservation through the integration of genetic frameworks into fishery management.

Marin, A., Santos-Rojas, L. E., Gozzer-Wuest, R., Yon-Utrilla, A., Vigo-Lopez, S., Rojas-Perea, S., Villegas-Llerena, C., Paredes-Moscosso, S. R., Lopez-Landavery, E. A., Reyes-Flores, L. E., Zelada-Mazmela, E.

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