What has changed in the outbreaking populations of the severe crop pest whitefly species in cassava in two decades?

Abstract

High populations of African cassava whitefly (Bemisia tabaci) have been associated with epidemics of two viral diseases in Eastern Africa. We investigated population dynamics and genetic patterns by comparing whiteflies collected on cassava in 1997, during the first whitefly upsurges in Uganda, with collections made in 2017 from the same locations. Nuclear markers and mtCOI barcoding sequences were used on 662 samples. The composition of the SSA1 population changed significantly over the 20-year period with the SSA1-SG2 percentage increasing from 0.9 to 48.6%. SSA1-SG1 and SSA1-SG2 clearly interbreed, confirming that they are a single biological species called SSA1. The whitefly species composition changed: in 1997, SSA1, SSA2 and B. afer were present; in 2017, no SSA2 was found. These data and those of other publications do not support the ‘invader’ hypothesis. Our evidence shows that no new species or new population were found in 20 years, instead, the distribution of already present genetic clusters composing SSA1 species have changed over time and that this may be in response to several factors including the introduction of new cassava varieties or climate changes. The practical implications are that cassava genotypes possessing both whitefly and disease resistances are needed urgently.

Genetic Diversity of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) Colonizing Sweet Potato and Cassava in South Sudan

“…Improvements in molecular tools led to the application of sequencing of 16S rRNA, cytochrome oxidase I gene portions in the mitochondrial genome, and the nuclear ribosomal intergenic spacer 1 (ITS1) [55,56,67,68]. Microsatellite markers have also been developed and used to study B. tabaci populations [69,70]. Recent advances have utilized SNP genotyping and nuclear genes [71][72][73].…”

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.…”

Whole‐genome single nucleotide polymorphism and mating compatibility studies reveal the presence of distinct species in sub‐Saharan Africa Bemisia tabaci whiteflies

“…Among the identified SSA1 subgroups, only SG1 to SG3 are the prevalent whiteflies in East and Central Africa (ECA) (Wosula et al, 2017;Ally et al, 2019). Various studies (Sseruwagi et al, 2005;Mugerwa et al, 2012;Legg et al, 2014;Ghosh et al, 2015;Ally et al, 2019) have shown that SSA1-SG1 gradually became the predominant whitefly on cassava and extended its geographical range within ECA, whilst displacing SSA2 whiteflies from early 2000s to the present. The displacement of SSA2 whitefly by whiteflies of SSA1 subgroups was attributed to the possible interbreeding between these two whiteflies, as reported by Maruthi et al (2004), resulting in genotypes with SSA1 subgroups mitochondrial genomes, but with fecundity traits of SSA2 (Mugerwa et al, 2012).…”