Sweetpotato is among the most important food crops in the world and an extremely important food crop for subsistence
farmers in sub-Saharan Africa (SSA). It is grown throughout the African continent and currently around 34.5% of global
sweetpotato area is in Africa. One major limitation in sweetpotato production is cultivar decline, mostly due to the
cumulative effect of virus infection on this vegetatively propagated crop. Thus, viral diseases are considered a major
limiting factor in sweetpotato production worldwide, particularly in SSA. We
used a novel approach, deep sequencing of small RNAs from field-grown sweetpotato samples collected throughout
Africa, to systematically and efficiently identify known and novel virus genome sequences. A total of around 1200
geo-referenced field-grown samples of sweetpotato have been collected from more than ten countries in Africa. Small
RNA populations of these samples have been prepared and sequenced using high throughput next-generation sequencing
technology, and then mapped and assembled to identify known and novel sweetpotato viruses.
Food security remains a huge challenge for millions of Africans, particularly for those in sub-Saharan regions, who
depend on agriculture for their subsistence. Emerging and reemerging pathogens, including many viruses, continue to
cause devastating losses of food production in Africa. Current knowledge of crop viruses in Africa is limited and
sporadic at best. Novel virus genome identification technology through deep sequencing of small RNA population is
potentially applicable to continental surveys as its efficiency in virus identification has been proven with both
greenhouse and field grown samples. This technology can then be applied to systematically determine the total virus
genome sequences (virome) on a number of other major crop plants in Africa. Public availability of such information
will provide the scientific community and government unprecedented possibilities to understand crop virus distribution
in Africa, guide phytosanitory requirements, predict risks of future epidemics, and suggest regional disease management
strategies.