Dec. 9, 2015
Novogene, a leading genomics solution provider with the largest Illumina-based sequencing capacity in China, and the International Center for Tropical Agriculture (CIAT), a global agricultural research and development organization and custodian of the world’s largest cassava gene bank, are partnering to construct a pan-genome of cassava (Manihot esculenta) and one of its closest wild relatives (M. e. peruviana). This novel approach to global cassava genome research is designed to unravel the plant’s complex evolutionary history and genetic diversity with the goal of increasing the production and nutritional value of a primary food source in Africa, Latin America and the Caribbean.
Under the pan-genome sequencing project, Novogene will sequence and assemble cassava genomes provided by CIAT from six different eco-geographic zones, and conduct comparative genomic analysis among these genomes in relation to M. e. peruviana. The pan-genome will include the cassava’s core-genome, containing genes present in all of cassava’s ecogeographic zones of domestication (Mesoamerican-Caribbean, Savanna, Andean, South America Lowland Forest, Amazon, Humid Atlantic Forest and Dry Atlantic Forest); the dispensable-genome, containing genes present in two or more ecogeographic zones; and unique genes specific to single ecogeographic adaptation regions, including those from M. e. peruviana.
Since the initial publication of the cassava reference genome, attempts have been made to characterize cassava through genome resequencing to unlock important sources of genetic diversity to improve varieties that will meet future productivity, nutrition and environmental challenges. However, resequencing has often failed to capture many types of structural variation related to agronomic traits, including copy number variation and presence-absence variation, especially for the most genetically diverse lines and the crop’s wild relatives because the reference genome was developed using a single inbred genome. Next-generation sequencing and state-of-the-art assembly algorithms make the construction of pan-genome maps feasible, and the construction of genome maps for individual or multiple strains provides unprecedented opportunities to investigate detailed genetic diversity at the population level.
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