Evolutionary Analysis of a Parrot Bornavirus 2 Detected in a Sulphur-Crested Cockatoo (Cacatua galerita) Suggests a South American Ancestor

Animals (Basel). 2023 Dec 22;14(1):47. doi: 10.3390/ani14010047.

Abstract

Parrot bornavirus (PaBV) is an RNA virus that causes Proventricular Dilatation Disease (PDD), neurological disorders, and death in Psittaciformes. Its diversity in South America is poorly known. We examined a Cacatua galerita presenting neuropathies, PDD, and oculopathies as the main signs. We detected PaBV through reverse transcription polymerase chain reaction (RT-PCR) and partial sequencing of the nucleoprotein (N) and matrix (M) genes. Maximum likelihood and Bayesian phylogenetic inferences classified it as PaBV-2. The nucleotide identity of the sequenced strain ranged from 88.3% to 90.3% against genotype PaBV-2 and from 80.2% to 84.4% against other genotypes. Selective pressure analysis detected signs of episodic diversifying selection in both the N and M genes. No recombination events were detected. Phylodynamic analysis estimated the time to the most recent common ancestor (TMRCA) as the year 1758 for genotype PaBV-2 and the year 1049 for the Orthobornavirus alphapsittaciforme species. Substitution rates were estimated at 2.73 × 10-4 and 4.08 × 10-4 substitutions per year per site for N and M, respectively. The analysis of population dynamics showed a progressive decline in the effective population size during the last century. Timescale phylogeographic analysis revealed a potential South American ancestor as the origin of genotypes 1, 2, and 8. These results contribute to our knowledge of the evolutionary origin, diversity, and dynamics of PaBVs in South America and the world. Additionally, it highlights the importance of further studies in captive Psittaciformes and the potential impact on endangered wild birds.

Keywords: Orthobornavirus; Proventricular Dilatation Disease; matrix; nucleoprotein; phylodynamics; phylogeography; selective pressure.

Grants and funding

This research was partly funded by the Conselho Nacional de Pesquisa e Desenvolvimento Tecnológico (CNPq), grant number 301084/2019-0.