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Population Genetics and Trajectory Simulation Reveals the Invasion Process of the Fall Armyworm (Spodoptera
Pengfei Fu1, Xijie Li2,3, Zhongxiang Sun1
1State Key Laboratory of Conservation and Utilization of Biological Resources of Yunnan College of Plant Protection, Yunnan Agricultural University Kunming China.
Abstract:
As a migratory agricultural pest, the fall armyworm has been in the spotlight since it invaded Africa in 2016. Invasive populations have now colonized much of the Eastern Hemisphere, causing severe damage to a wide range of crops. However, there is still disagreement internationally on the origin and mode of invasion of fall armyworm populations, especially from the Americas to China. In this study, we provided an in-depth insight into the invasion of the fall armyworm in the Eastern hemisphere based on genome-wide data from 124 fall armyworm individuals collected from 14 sites across three continents and trajectory simulation. First, based on 770,423 high-quality SNPs, the PCA and ADMIXTURE analyses clearly distinguished the geographical populations of the Eastern and Western hemispheres. Second, the genetic diversity results revealed that the invasive populations exhibited higher heterozygosity than the native populations. Third, the results of integrated individual assignment tests and migration path simulations showed that the W1 (Florida, Texas, and Puerto Rico) population may be the potential source of the invasive populations in Africa, and a low possibility of trans-sea migration between the Americas and Africa suggested that fall armyworms may have spread through trade in goods. Fourth, our results indicate that the Indian population is a genetically admixed group derived from the E1 (Benin, Ethiopia, and South Africa) population, which subsequently migrated to the Indo-China Peninsula through natural trans-sea dispersal and to Yunnan via Myanmar. These findings not only provide new insights into the invasion of the fall armyworm in the Eastern Hemisphere but also present a method to improve the prediction accuracy of migratory pests.
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