Back

Discovery of two potential new species and two novel bat-coronavirus subgenera (Phyllacovirus and Phyllobecovirus) in the Neotropics

Correa, L.; Dezordi, F.; da Silva, A. c.; Melo, J.; Dias, Y.; Resende, P. C.; Appolinario, L.; Siqueira, M.; Ogrzewalska, M.; Wallau, G. d. L.

2026-09-24 genomics
10.64898/2026.09.23.753618 bioRxiv
Show abstract

Bats are major natural reservoirs for coronaviruses, yet complete viral genomes from South America remain scarce, limiting evolutionary and taxonomic understanding. Here, we conducted metatranscriptomic sequencing of coronavirus-positive bat samples collected across two ecologically distinct Brazilian biomes: the Atlantic Forest and the semi-arid Caatinga. We recovered seven complete or near-complete genomes belonging to Alphacoronavirus and Betacoronavirus. Phylogenetic and comparative similarity analyses of conserved replicase domains (3CLpro, NiRAN, RdRp, ZBD, HEL1), following International Committee on Taxonomy of Viruses (ICTV) demarcation criteria, revealed significant viral diversity. Within Alphacoronavirus, two genomes from Atlantic Forest phyllostomid bats (Artibeus lituratus and Carollia perspicillata) formed a deeply divergent sister lineage to Amalacovirus, exhibiting a mean amino acid similarity of 76.7% with the reference genome. Within Betacoronavirus, one genome from a Caatinga phyllostomid bat (Artibeus planirostris) clustered within the recently described Ambecovirus clade, displaying 75.9% mean amino acid similarity with mormoopid-associated reference sequences. Based on these divergence levels and non-recombinant genomic architectures, we propose two novel candidate subgenera, Phyllacovirus and Phyllobecovirus, alongside potential novel viral species. Furthermore, our findings demonstrate strong host-associated structuring and biogeographical partitioning of viral lineages across Neotropical biomes. Overall, this study expands the genomic landscape of South American bat coronaviruses and underscores the importance of continuous genomic surveillance at human-wildlife interfaces.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.