Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages

Authors: SOMO, MOHAMED - Cornell University; KULEMBEKA, HENERIKO - Agricultural Research Institute - Naliendele; MTUNDA, KIDDO - Agricultural Research Institute - Naliendele; MREMA, EMMANUEL - Agricultural Research Institute - Naliendele; SALUM, KASELE - Agricultural Research Institute - Naliendele; WOLFE, MARNIN - Cornell University; RABBI, ISMAIL - International Institute For Tropical Agriculture; EGESI, CHIEDOZIE - International Institute For Tropical Agriculture; KAWUKI, ROBERT - National Crops Resources Research Institute; Jannink, Jean-Luc; OZIMATI, ALFRED - National Crops Resources Research Institute; LOZANO, ROBERTO - Cornell University

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/11/2019
Publication Date: 5/13/2020
Citation: Somo, M., Kulembeka, H., Mtunda, K., Mrema, E., Salum, K., Wolfe, M., Rabbi, I., Egesi, C., Kawuki, R., Jannink, J., Ozimati, A., Lozano, R. 2020. Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages. Crop Science. 60(2):896-913. https://doi.org/10.1002/csc2.20003.
DOI: https://doi.org/10.1002/csc2.20003

Interpretive Summary: Genomic selection involves analyzing a training population with both DNA markers and field evaluations to develop a statistical model that can predict performance using only DNA markers. Assembly of a training population (TP) is an important component of effective genomic selection-based breeding programs. We examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This was the first genomic selection and genome-wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. Clones in the early breeding stage provided more reliable trait prediction accuracy and were better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, we found that adding clones from two distinct populations did not improve the prediction accuracy of either population. Including data from neighboring Uganda in either population also did not improve trait prediction accuracy.

Technical Abstract: Assembly of a training population (TP) is an important component of effective genomic selection-based breeding programs. In this study, we examined the power of diverse germplasm assembled from two cassava (Manihot esculenta Crantz) breeding programs in Tanzania at different breeding stages to predict traits and discover quantitative trait loci (QTL). This is the first genomic selection and genome-wide association study (GWAS) on Tanzanian cassava data. We detected QTL associated with cassava mosaic disease (CMD) resistance on chromosomes 12 and 16; QTL conferring resistance to cassava brown streak disease (CBSD) on chromosomes 9 and 11; and QTL on chromosomes 2, 3, 8, and 10 associated with resistance to CBSD for root necrosis. We detected a QTL on chromosome 4 and two QTL on chromosome 12 conferring dual resistance to CMD and CBSD. The use of clones in the same stage to construct TPs provided higher trait prediction accuracy than TPs with a mixture of clones from multiple breeding stages. Moreover, clones in the early breeding stage provided more reliable trait prediction accuracy and are better candidates for constructing a TP. Although larger TP sizes have been associated with improved accuracy, in this study, adding clones from Kibaha to those from Ukiriguru and vice versa did not improve the prediction accuracy of either population. Including the Ugandan TP in either population did not improve trait prediction accuracy. This study applied genomic prediction to understand the implications of constructing TP from clones at different breeding stages pooled from different locations on trait accuracy.