High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato.

Breeders have made important efforts to develop genotypes able to resist virus attacks in sweetpotato, a major crop providing food security and poverty alleviation to smallholder farmers in many regions of Sub-Saharan Africa, Asia and Latin America. However, a lack of accurate objective quantitative methods for this selection target in sweetpotato prevents a consistent and extensive assessment of large breeding populations. In this study, an approach to characterize and classify resistance in sweetpotato was established by assessing total yield loss and virus load after the infection of the three most common viruses (SPFMV, SPCSV, SPLCV). Twelve sweetpotato genotypes with contrasting reactions to virus infection were grown in the field under three different treatments: pre-infected by the three viruses, un-infected and protected from re-infection, and un-infected but exposed to natural infection. Virus loads were assessed using ELISA, (RT-)qPCR, and loop-mediated isothermal amplification (LAMP) methods, and also through multispectral reflectance and canopy temperature collected using an unmanned aerial vehicle. Total yield reduction compared to control and the arithmetic sum of (RT-)qPCR relative expression ratios were used to classify genotypes into four categories: resistant, tolerant, susceptible, and sensitives. Using 14 remote sensing predictors, machine learning algorithms were trained to classify all plots under the said categories. The study found that remotely sensed predictors were effective in discriminating the different virus response categories. The results suggest that using machine learning and remotely sensed data, further complemented by fast and sensitive LAMP assays to confirm results of predicted classifications could be used as a high throughput approach to support virus resistance phenotyping in sweetpotato breeding.

Haplotype-based phylogenetic analysis and population genomics uncover the origin and domestication of sweetpotato.

The hexaploid sweetpotato (Ipomoea batatas) is one of the most important root crops worldwide. However, its genetic origin remains controversial, and its domestication history remains unknown. In this study, we used a range of genetic evidence and a newly developed haplotype-based phylogenetic analysis to identify two probable progenitors of sweetpotato. The diploid progenitor was likely closely related to Ipomoea aequatoriensis and contributed the B1 subgenome, IbT-DNA2, and the lineage 1 type of chloroplast genome to sweetpotato. The tetraploid progenitor of sweetpotato was most likely I. batatas 4x, which donated the B2 subgenome, IbT-DNA1, and the lineage 2 type of chloroplast genome. Sweetpotato most likely originated from reciprocal crosses between the diploid and tetraploid progenitors, followed by a subsequent whole-genome duplication. In addition, we detected biased gene exchanges between the subgenomes; the rate of B1 to B2 subgenome conversions was nearly three times higher than that of B2 to B1 subgenome conversions. Our analyses revealed that genes involved in storage root formation, maintenance of genome stability, biotic resistance, sugar transport, and potassium uptake were selected during the speciation and domestication of sweetpotato. This study sheds light on the evolution of sweetpotato and paves the way for improvement of this crop.