Inference of the worldwide invasion routes of the pinewood nematode Bursaphelenchus xylophilus using approximate Bayesian computation analysis - Archive ouverte HAL Access content directly
Journal Articles Peer Community Journal Year : 2021

Inference of the worldwide invasion routes of the pinewood nematode Bursaphelenchus xylophilus using approximate Bayesian computation analysis

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Abstract

Population genetics have been greatly beneficial to improve knowledge about biological invasions. Model-based genetic inference methods, such as approximate Bayesian computation (ABC), have brought this improvement to a higher level and are now essential tools to decipher the invasion routes of any invasive species. In this paper, we performed ABC random forest analyses to shed light on the pinewood nematode (PWN) worldwide invasion routes and to identify the source of European populations. Originating from North America, this microscopic worm has been invading Asia since 1905 and Europe since 1999, causing tremendous damage on pine forests. Using microsatellite data, we demonstrated the existence of multiple introduction events in Japan (at least two involving individuals originating from the USA) and China (one involving individuals originating from the USA and one involving individuals originating from Japan). We also found that Portuguese samples had a Japanese origin. We observed some discrepancies between descriptive genetic methods and the ABC method, which are worth investigating and are discussed here. The ABC method helped clarify the worldwide history of the PWN invasion, even though the results still need to be considered with some caution because the features of the PWN and the genetic markers used probably push the ABC method to its very limits.

Dates and versions

hal-03707979 , version 1 (28-06-2022)

Licence

Attribution - CC BY 4.0

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Sophie Mallez, Chantal Castagnone, Eric Lombaert, Philippe Castagnone-Sereno, Thomas Guillemaud. Inference of the worldwide invasion routes of the pinewood nematode Bursaphelenchus xylophilus using approximate Bayesian computation analysis. Peer Community Journal, 2021, 1, pp.e56. ⟨10.24072/pcjournal.64⟩. ⟨hal-03707979⟩
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