ABSTRACT
Cassava is a root crop important for global food security and the third biggest source of calories on the African continent. Cassava production is threatened by Cassava mosaic disease (CMD), which is caused by a complex of single-stranded DNA viruses (family: Geminiviridae, genus: Begomovirus) that are transmitted by the sweet potato whitefly (Bemisia tabaci). Understanding the dynamics of different cassava mosaic begomovirus (CMB) species through time is important for contextualizing disease trends. Cassava plants with CMD symptoms were sampled in Lake Victoria and coastal regions of Kenya before transfer to a greenhouse setting and regular propagation. The field-collected and greenhouse samples were sequenced using Illumina short-read sequencing and analyzed on the Galaxy platform. In the field-collected samples, African cassava mosaic virus (ACMV), East African cassava mosaic virus (EACMV), East African cassava mosaic Kenya virus (EACMKV), and East African cassava mosaic virus-Uganda variant (EACMV-Ug) were detected in samples from the Lake Victoria region, while EACMV and East African mosaic Zanzibar virus (EACMZV) were found in the coastal region. Many of the field-collected samples had mixed infections of EACMV and another begomovirus. After 3 years of regrowth in the greenhouse, only EACMV-like viruses were detected in all samples. The results suggest that in these samples, EACMV becomes the dominant virus through vegetative propagation in a greenhouse. This differed from whitefly transmission results. Cassava plants were inoculated with ACMV and another EACMV-like virus, East African cassava mosaic Cameroon virus (EACMCV). Only ACMV was transmitted by whiteflies from these plants to recipient plants, as indicated by sequencing reads and copy number data. These results suggest that whitefly transmission and vegetative transmission lead to different outcomes for ACMV and EACMV-like viruses.
ABSTRACT
Perennial plants which propagate through both seeds and rhizomes are common in agricultural and nonagricultural systems. Due to their multifaceted life cycle, few population models are available for studying such species. We constructed a novel individual-based model to examine the effects of ecological, evolutionary, and anthropogenic factors on the population dynamics of perennial species. To exemplify the application of the model, we presented a case study of an important weed, Sorghum halepense (L.) Pers. (Johnsongrass), in soybean productions in Argentina. The model encompasses a full perennial weed life cycle with both sexual (seeds) and asexual (rhizomes) propagations. The evolution of herbicide resistance was modeled based on either single genes or quantitative effects. Field experiments were conducted in the species' native environment in Argentina to parameterize the model. Simulation results showed that resistance conferred by single-gene mutations was predominantly affected by the initial frequency of resistance alleles and the associated fitness cost. Population dynamics were influenced by evolved resistance, soil tillage, and rhizome fecundity. Despite the pivotal role of rhizomes in driving the population dynamics of Johnsongrass, most herbicides target the aboveground biomass, and chemical solutions to control rhizomes are still very limited. To maintain effective (short-term) and sustainable (long-term) weed management, it is recommended to combine soil tillage with herbicide applications for suppressing the rhizomes and delaying the evolution of resistance. This novel model of seed- and rhizome-propagated plants will also be a useful tool for studying the evolutionary processes of other perennial weeds, cash crops, and invasive species.