BREAD: Determining the Pan-African Sweet Potato Virome: Understanding Virus Diversity, Distribution and Evolution and their Impacts on Sweet Potato Production in Africa

项目负责人：费张军（博伊斯·汤普森植物研究所）合作负责人：Jan Kreuze（秘鲁国际马铃薯中心）Martin Chiona（赞比亚国家农业研究组织），Paul Demo（马拉维知识中心），Britta Kowalski（安哥拉知识中心），Douglas Miano（肯尼亚农业研究所，肯尼亚），Settumba Mukasa（乌干达Makerere大学），Joseph Ndunguru（坦桑尼亚Mikocheni农业研究所），Ian Robertson和Elizabeth Ngadze（津巴布韦大学），Steffen Schulz（埃塞俄比亚知识中心）和Martine Tachin（坦桑尼亚阿博梅-卡拉维大学）。甘薯是世界上最重要的粮食作物之一，也是撒哈拉以南非洲（SSA）自给农民极其重要的粮食作物。它生长在整个非洲大陆，目前全球约34.5%的红薯面积在非洲。红薯生产的一个主要限制是品种下降，这主要是由于病毒感染对这种无性繁殖作物的累积影响。因此，病毒性疾病被认为是世界范围内红薯生产的主要限制因素，特别是在SSA。该项目的目标是评估一种新的方法，即对在非洲各地收集的田间种植的甘薯样本中的小rna进行深度测序，以系统有效地鉴定已知和新的病毒基因组序列。将从非洲十多个国家收集总共约1750份地理参照田间种植甘薯样本。这些样品的小RNA群体将使用高通量下一代测序技术进行制备和测序，然后组装以鉴定已知和新的甘薯病毒。更广泛的影响：粮食安全对数百万非洲人来说仍然是一个巨大的挑战，特别是对撒哈拉以南地区的人来说，他们依靠农业为生。新出现和重新出现的病原体，包括许多病毒，继续给非洲粮食生产造成毁灭性损失。目前对非洲作物病毒的了解是有限的，充其量是零星的。通过小RNA群体深度测序的新型病毒基因组鉴定技术可能适用于大陆调查，因为其在病毒鉴定方面的效率已在温室和田间样品中得到证实。然后，该技术可用于系统地确定非洲许多其他主要作物（如玉米、水稻、番茄、豆类和木薯）的病毒基因组总序列（病毒组）。向公众提供此类信息将为科学界和政府提供前所未有的可能性，以了解作物病毒在非洲的分布，指导植物检疫要求，预测未来流行病的风险，并提出区域疾病管理战略。本项目产生的数据将通过项目网站（可通过http://bti.cornell.edu/ZhangjunFei.php访问）发布，原始和处理过的小RNA序列也将分别通过EBI Sequence Read Archive和NCBI Gene Expression Omnibus提供。新病毒基因组序列将存入GenBank。

PI: Zhangjun Fei (Boyce Thompson Institute for Plant Research)Co-PIs: Jan Kreuze [International Potato Center (CIP), Peru]Key Collaborators: Martin Chiona (National Agricultural Research Organization, Zambia), Paul Demo (CIP-Malawi), Britta Kowalski (CIP-Angola), Douglas Miano (Kenya Agricultural Research Institute, Kenya), Settumba Mukasa (Makerere University, Uganda), Joseph Ndunguru (Mikocheni Agricultural Research Institute, Tanzania), Ian Robertson and Elizabeth Ngadze (University of Zimbabwe), Steffen Schulz (CIP-Ethiopia) and Martine Tachin (Université d'Abomey-Calavi, Rép. BéninSweet potato 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 sweet potato area is in Africa. One major limitation in sweet potato 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 sweet potato production worldwide, and particularly in SSA. The objective of this project is to evaluate a novel approach, deep sequencing of small RNAs from field-grown sweet potato samples collected throughout Africa, to systematically and efficiently identify known and novel virus genome sequences. A total of around 1750 geo-referenced field-grown samples of sweet potato will be collected from more than ten countries in Africa. Small RNA populations of these samples will be prepared and sequenced using high throughput next-generation sequencing technology, and then assembled to identify known and novel sweet potatoviruses.Broader Impacts: 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 such as maize, rice, tomato, bean, and cassava. Public availability of such information will provide the scientific community and government unprecedented possibilities to understand crop virus distribution in Africa, guide phytosanitary requirements, predict risks of future epidemics, and suggest regional disease management strategies. Data generated under this project will be disseminated through the project website (accessible via http://bti.cornell.edu/ZhangjunFei.php) and raw and processed small RNA sequences will also be available through EBI Sequence Read Archive and NCBI Gene Expression Omnibus, respectively. Novel virus genome sequences will be deposited into GenBank.