Development of a molecular-based detection tool for sweet potato leaf curl viruses and determination of their incidence levels in Tanzania

Abstract

Sweet potato (Ipomoea batatas L.) is an important food security crop in sub-Saharan Africa, where its production is constrained by devastating diseases; including those caused by sweet potato leaf curl viruses (SPLCVs; Begomovirus; Geminiviridae). The objective of this study was to develop a molecular-based diagnostic detection tool for SPLCVs, as well as to generate information on their geographical distribution and incidence in Tanzania. A comprehensive survey of SPLCVs was done in all major sweet potato growing areas in Tanzania. Incidences of SPLCVs and their causative diseases were determined visually and by polymerase chain reaction (PCR), using primers designed, optimised and validated. DNA was extracted from 4166 sweet potato leaf samples and detection of SPLCVs was done. Visual incidence of disease symptoms ranged from 0 to 100%; while PCR-based incidence of SPLCVs ranged from 0 to 60%. The highest mean PCR-based incidence of SPLCVs was 32%. SPLCVs occurred in all sweet potato growing areas. There was a negative correlation between the visually assessed incidence of disease symptoms and PCR-based incidence of SPCLVs (r = -0.122 and R2 = 0.012). A weak positive correlation between altitude and PCR-based incidence of SPLCVs was also found. In ten-fold serially diluted sweet potato DNA samples, using our new primer pair d1-SPLCVF/d1-SPLCVR, the detection limit of SPLCVs was at the dilution of 10-3. The youngest fully expanded leaf of the sweet potato plant was the best for PCR detection of SPLCVs. These findings will be useful for strategic deployment of planting material and conducting sweet potato breeding experiments for resistance against SPLCVs.