Genetic Structure and Demographic History Reveal Migration of the Diamondback Moth <i>Plutella xylostella</i> (Lepidoptera: Plutellidae) from the Southern to Northern Regions of China

<div><p>The diamondback moth <i>Plutella xylostella</i> (Linnaeus) (Lepidoptera: Plutellidae) is one of the most destructive insect pests of cruciferous plants worldwide. Biological, ecological and genetic studies have indicated that this moth is migratory in many regions around the world. Although outbreaks of this pest occur annually in China and cause heavy damage, little is known concerning its migration. To better understand its migration pattern, we investigated the population genetic structure and demographic history of the diamondback moth by analyzing 27 geographical populations across China using four mitochondrial genes and nine microsatellite loci. The results showed that high haplotype diversity and low nucleotide diversity occurred in the diamondback moth populations, a finding that is typical for migratory species. No genetic differentiation among all populations and no correlation between genetic and geographical distance were found. However, pairwise analysis of the mitochondrial genes has indicated that populations from the southern region were more differentiated than those from the northern region. Gene flow analysis revealed that the effective number of migrants per generation into populations of the northern region is very high, whereas that into populations of the southern region is quite low. Neutrality testing, mismatch distribution and Bayesian Skyline Plot analyses based on mitochondrial genes all revealed that deviation from Hardy-Weinberg equilibrium and sudden expansion of the effective population size were present in populations from the northern region but not in those from the southern region. In conclusion, all our analyses strongly demonstrated that the diamondback moth migrates within China from the southern to northern regions with rare effective migration in the reverse direction. Our research provides a successful example of using population genetic approaches to resolve the seasonal migration of insects.</p>