Utilizing museomics to trace the complex history and species boundaries in an avian-study system of conservation concern.
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Ernst M, Jønsson KA, Ericson PGP, Blom MPK, Irestedt M
Heredity (Edinb) 128 (3) 159-168 [2022-03-00; online 2022-01-26]
A taxonomic classification that accurately captures evolutionary history is essential for conservation. Genomics provides powerful tools for delimiting species and understanding their evolutionary relationships. This allows for a more accurate and detailed view on conservation status compared with other, traditionally used, methods. However, from a practical and ethical perspective, gathering sufficient samples for endangered taxa may be difficult. Here, we use museum specimens to trace the evolutionary history and species boundaries in an Asian oriole clade. The endangered silver oriole has long been recognized as a distinct species based on its unique coloration, but a recent study suggested that it might be nested within the maroon oriole-species complex. To evaluate species designation, population connectivity, and the corresponding conservation implications, we assembled a de novo genome and used whole-genome resequencing of historical specimens. Our results show that the silver orioles form a monophyletic lineage within the maroon oriole complex and that maroon and silver forms continued to interbreed after initial divergence, but do not show signs of recent gene flow. Using a genome scan, we identified genes that may form the basis for color divergence and act as reproductive barriers. Taken together, our results confirm the species status of the silver oriole and highlight that taxonomic revision of the maroon forms is urgently needed. Our study demonstrates how genomics and Natural History Collections (NHC) can be utilized to shed light on the taxonomy and evolutionary history of natural populations and how such insights can directly benefit conservation practitioners when assessing wild populations.
Bioinformatics Support for Computational Resources [Service]
NGI Stockholm (Genomics Applications) [Service]
NGI Stockholm (Genomics Production) [Service]
National Genomics Infrastructure [Service]
PubMed 35082388
DOI 10.1038/s41437-022-00499-0
Crossref 10.1038/s41437-022-00499-0
pii: 10.1038/s41437-022-00499-0
pmc: PMC8897408