Genetic structure of the whitefly Bemisia tabaci populations in Colombia following a recent invasion

Abstract

The whitefly Bemisia tabaci (Gennadius) is one of the most important pests causing economic losses in a variety of cropping systems around the world. This species was recently found in a coastal region of Colombia and has now spread inland. To investigate this invasive process, the genetic structure of B. tabaci was examined in 8 sampling locations from 2 infested regions (coastal, inland) using 9 microsatellite markers and the mitochondrial COI gene. The mitochondrial analysis indicated that only the invasive species of the B. tabaci complex Middle East-Asia Minor 1 (MEAM 1 known previously as biotype B) was present. The microsatellite data pointed to genetic differences among the regions and no isolation by distance within regions. The coastal region in the Caribbean appears to have been the initial point of invasion, while the inland region in the Southwest showed genetic variation among populations most likely reflecting founder events and ongoing changes associated with climatic and topographical heterogeneity. These findings have implications for tracking and managing B. tabaci.

Introduction of Aethina tumida (Coleoptera: Nitidulidae) in the regions of Calabria and Sicily (southern Italy)

“…The findings can also contribute to tracking future movements of this honey bee pest, particularly through migratory beekeeping and trade, considering the existing restrictions on movements within the two affected regions of Italy and between these regions and the rest of the European Union (EU 2015b). These genetic markers have already proven useful in the detection and tracing of new incursions of pests leading to economic losses in a variety of cropping systems around the world (Ehler et al 2004;Díaz et al 2015;Blacket et al 2015;Wu et al 2015;Arnemann et al 2016). mtDNA sequence analysis should also facilitate identification of the origins of any further beetle introductions to Europe within the framework of an EU surveillance program (Chauzat et al 2015).…”

The genetic basis of population fecundity prediction across multiple field populations of Nilaparvata lugens

“…Similarly, the genetic structure of whitefly Bemisia tabaci in 8 sampling locations was examined by STRUCTURE with nine microsatellite markers (Díaz et al . ).…”

What Is the Spatial Extent of a Bemisia tabaci Population?

“…The fixation index (F ST ) [76], is a commonly used measure of genetic differentiation between populations, ranging from 0 (no differentiation) to 1 (complete differentiation). Of the 15 studies reporting values of F ST among populations within cryptic species, eight (53%) include ranges of F ST that bound zero [17,41,54,58,61,[65][66][67], though upper estimates of F ST among studies sometimes exceed 0.5 [59,64,65] (Figure 2, Table S2). Differences in the geographic extent of sampling largely explain differences in the range of F ST among studies.…”

“…Differences in the geographic extent of sampling largely explain differences in the range of F ST among studies. Studies reporting relatively low genetic differentiation between populations typically cover small geographic areas within individual countries [16,17,54,56,61,66], whereas those with high or broad ranges of genetic differentiation generally compared populations spanning multiple islands [63], numerous sites distributed throughout individual countries [58,59], or sites spanning multiple countries/continents [64,67]. Analysis of Molecular Variance (AMOVA) is another common tool used for reporting levels of genetic differentiation, functionally partitioning levels of genetic variance into hierarchical levels including categories for among-individuals within a population and among-populations within a region.…”

“…These studies are global in coverage, focus largely on populations of MEAM 1 and MED, and span collections from 1991−2018 ( Figure 1, Table S1). Studies leverage a variety of genetic marker types [27,[39][40][41][42][43][44][45][46][47][48][49][50][51][52][53], but, while the majority use microsatellites [13,16,17,[54][55][56][57][58][59][60][61][62][63][64][65][66][67][68], use of single nucleotide polymorphisms is beginning to become more common [15,[69][70][71] (Figure 1). We organize our synthesis around insights gained from three common marker types (cytochrome oxidase I, microsatellites, single nucleotide polymorphisms) and associated measures of genetic diversity and differentiation, interpreting emergent patterns in light of potential underlying ecological and evolutionary processes.…”