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

Abstract

Key message

GWAS identified eight yield-related, peak starch type of waxy and wild-type starch and 21 starch pasting property-related traits (QTLs). Prediction ability of eight GS models resulted in low to high predictability, depending on trait, heritability, and genetic architecture.

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.

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Data availability

Phenotypic data used in the analyses and the genotypic data are available in Cassavabase (http://cassavabase.org/search/traits). The imputed SNP genotypic data obtained from the 276 genotypes used in this study are available in Cassavabase.

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Acknowledgements

We would like to thank James Tanaka for his assistance in the laboratory of Dr. Mark Sorrells.

Funding

This work was supported by Kasetsart University Research and Development Institute (KURDI), Grant Number รหัส ศ-ข(กษ)2.57, and was partially supported by the Center of Excellence on Agricultural Biotechnology, Office of the Permanent Secretary, Ministry of Higher Education, Science, Research and Innovation (AG-BIO/MHESI) Grant Number (60-005-001)J. The authors would also like to thank TTDI for providing supporting plant materials.

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CP and JC designed the experiment. PA, PN, SH, PJK, PK, WW, and CP conducted the field experiments. CR and VV provided germplasm. CK, SC, and KP conducted the starch pasting properties experiments. CP, PF, and PT performed data analysis. CP, SC, and PJK wrote the first draft of the manuscript. CP, MS, JJ, and MW revised the manuscript. All authors read and approved the manuscript.

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Correspondence to Chalermpol Phumichai.

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Communicated by Damaris Odeny.

Supplementary Information

Below is the link to the electronic supplementary material.

List of 276 cassava genotypes including 247 wild-type and 29 waxy cassava starch types (PDF 189 KB)

122_2021_3956_MOESM2_ESM.pdf

Manhattan and quantile–quantile plots (QQ) plots comparing different yield-related traits data using compressed mixed linear (CMLM) model (PDF 194 KB)

122_2021_3956_MOESM3_ESM.pdf

Manhattan and quantile–quantile plots (QQ) plots comparing different yield-related traits data using multi‐locus mixed model (MLMM) (PDF 85 KB)

122_2021_3956_MOESM4_ESM.pdf

Manhattan and quantile–quantile plots (QQ) plots comparing different waxy and wild-type starch cassava using compressed mixed linear (CMLM) model, multi‐locus mixed model (MLMM) model, and fixed and random model circulating probability unification (FarmCPU) model (PDF 61 KB)

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Phumichai, C., Aiemnaka, P., Nathaisong, P. et al. Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava. Theor Appl Genet 135, 145–171 (2022). https://doi.org/10.1007/s00122-021-03956-2

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