Deep assessment of genomic diversity in cassava for herbicide tolerance and starch biosynthesis
Review statusPeer Review
MetadataShow full item record
Duitama, Jorge; Kafuri, Lina; Tello, Daniel; Leiva, Ana María; Hofinger, Bernhard; Datta, Sneha; Lentini, Zaida; Aranzales, Ericson; Till, Bradley; Ceballos, Hernán. 2017. Deep assessment of genomic diversity in cassava for herbicide tolerance and starch biosynthesis . Computational and Structural Biotechnology Journal In press.
Permanent link to cite or share this item: http://hdl.handle.net/10568/78827
Cassava is one of the most important food security crops in tropical countries, and a competitive resource for the starch, food, feed and ethanol industries. However, genomics research in this crop is much less developed compared to other economically important crops such as rice or maize. The International Center for Tropical Agriculture (CIAT) maintains the largest cassava germplasm collection in the world. Unfortunately, the genetic potential of this diversity for breeding programs remains underexploited due to the difficulties in phenotypic screening and lack of deep genomic information about the different accessions. A chromosome-level assembly of the cassava reference genome was released this year and only a handful of studies have been made, mainly to find quantitative trait loci (QTL) on breeding populations with limited variability. This work presents the results of pooled targeted resequencing of more than 1,500 cassava accessions from the CIAT germplasm collection to obtain a dataset of more than 2,000 variants within genes related to starch functional properties and herbicide tolerance. Results of twelve bioinformatic pipelines for variant detection in pooled samples were compared to ensure the quality of the variant calling process. Predictions of functional impact were performed using two separate methods to prioritize interesting variation for genotyping and cultivar selection. Targeted resequencing, either by pooled samples or by similar approaches such as Ecotilling or capture, emerges as a cost effective alternative to whole genome sequencing to identify interesting alleles of genes related to relevant traits within large germplasm collections.