Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava

Authors: PHUMICHAI, CHALERMPOL - Kasetsart University; AIEMNAKA, PORNSAK - Kasetsart University; NATHAISON, PIYAPORN - Kasetsart University; HUNSAWATTANAKUL, SIRIKAN - Kasetsart University; FUNGFOO, PHASAKORN - Kasetsart University; ROJANARIDPICHED, CHAREINSUK - Kasetsart University; VICHUKIT, VICHAN - Kasetsart University; KONGSIL, PASAJEE - Kasetsart University; KITTIPADAKUL, PIYA - Kasetsart University; SORRELLS, MARK - Cornell University; WANNARAT, WANNASIRI - Kasetsart University; CHUNWONGSE, JULAPARK - Kasetsart University; TONGYOO, PUMIPAT - Kasetsart University; KIJKHUNASATIAN, CHOOKIAT - National Center For Genetic Engineering And Biotechnology (BIOTEC); CHOTINEERANAT, SUNEE - National Center For Genetic Engineering And Biotechnology (BIOTEC); PIYACHOMKWAN, KUAKOON - National Center For Genetic Engineering And Biotechnology (BIOTEC); WOLFE, MARNIN - Cornell University; Jannink, Jean-Luc

Submitted to: Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/25/2021
Publication Date: 10/18/2021
Citation: Phumichai, C., Aiemnaka, P., Nathaison, P., Hunsawattanakul, S., Fungfoo, P., Rojanaridpiched, C., Vichukit, V., Kongsil, P., Kittipadakul, P., Sorrells, M.E., Wannarat, W., Chunwongse, J., Tongyoo, P., Kijkhunasatian, C., Chotineeranat, S., Piyachomkwan, K., Wolfe, M.D., Jannink, J. 2021. Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava. Theoretical and Applied Genetics. 135:145-171. https://doi.org/10.1007/s00122-021-03956-2.
DOI: https://doi.org/10.1007/s00122-021-03956-2

Interpretive Summary: Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We identified regions of the genome affecting these traits to clarify their molecular mechanisms and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped with 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected. Genomic selection models were developed. Prediction accuracies ranged from 0.00 to 0.71 for the four yield-related traits and 0.33-0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs.

Technical Abstract: Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We carried out a genome-wide association study to clarify the molecular mechanisms underlying these traits and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection (GS) using parametric, semi-parametric, and nonparametric GS models with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped via genotyping-by-sequencing, and 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected by the fixed and random model circulating probability unification (FarmCPU), Bayesian-information and linkage-disequilibrium iteratively nested keyway and compressed mixed linear model, respectively. GS models were developed, and forward predictabilities using all the prediction methods resulted in values of - 0.001–0.71 for the four yield-related traits and 0.33–0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs.