Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids

Liang, Z and Gupta, S K and Yeh, C T and Zhang, Y and Ngu, D W and Kumar, R and Patil, H T and Mungra, K D and Yadav, D V and Rathore, A and Srivastava, R K and Gupta, R and Yang, J and Varshney, R K and Schnable, P S and Schnable, J C (2018) Phenotypic Data from Inbred Parents Can Improve Genomic Prediction in Pearl Millet Hybrids. G3: Genes, Genomes, Genetics, 8. pp. 2513-2522. ISSN 2160-1836

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Abstract

Background: Pearl millet is a non-model grain and fodder crop adapted to extremely hot and dry environments globally. In India, a great deal of public and private sectors' investment has focused on developing pearl millet single cross hybrids based on the cytoplasmic-genetic male sterility (CMS) system, while in Africa most pearl millet production relies on open pollinated varieties. Pearl millet lines were phenotyped for both the inbred parents and hybrids stage. Many breeding efforts focus on phenotypic selection of inbred parents to generate improved parental lines and hybrids. This study evaluated two genotyping techniques and four genomic selection schemes in pearl millet. Results: Despite the fact that 6× more sequencing data were generated per sample for RAD-seq than for tGBS, tGBS yielded more than 2× as many informative SNPs (defined as those having MAF > 0.05) than RAD-seq. A genomic prediction scheme utilizing only data from hybrids generated prediction accuracies (median) ranging from 0.73-0.74 (1000-grain weight), 0.87-0.89 (days to flowering time), 0.48-0.51 (grain yield) and 0.72-0.73 (plant height). For traits with little to no heterosis, hybrid only and hybrid/inbred prediction schemes performed almost equivalently. For traits with significant mid-parent heterosis, the direct inclusion of phenotypic data from inbred lines significantly (p<0.05) reduced prediction accuracy when all lines were analyzed together. However, when inbreds and hybrid trait values were both scored relative to the mean trait values for the respective populations, the inclusion of inbred phenotypic datasets moderately improved genomic predictions of the hybrid genomic estimated breeding values. Conclusion: Here we show that modern approaches to genotyping by sequencing can enable genomic selection in pearl millet. While historical pearl millet breeding records include a wealth of phenotypic data from inbred lines, we demonstrate that the naive incorporation of this data into a hybrid breeding program can reduce prediction accuracy, while controlling for the effects of heterosis per se allowed inbred genotype and trait data to improve the accuracy of genomic estimated breeding values for pearl millet hybrids.

Item Type: Article
Divisions: Research Program : Asia
Research Program : Genetic Gains
CRP: CGIAR Research Program on Dryland Cereals
Uncontrolled Keywords: Pearl millet, genomic selection, hybrid breeding, genotyping, GenPred, shared data, resources, pearl millet breeding, pearl millet hybrids, breeding values, pearlmillet population, phenotypic selection
Subjects: Others > Plant Breeding
Mandate crops > Millets > Pearl Millet
Others > Genetics and Genomics
Depositing User: Mr Ramesh K
Date Deposited: 05 Jul 2018 10:52
Last Modified: 05 Jul 2018 11:00
URI: http://oar.icrisat.org/id/eprint/10786
Official URL: http://dx.doi.org/10.1534/g3.118.200242
Projects: UNSPECIFIED
Funders: UNSPECIFIED
Acknowledgement: This work was supported by an CGIAR-US Universities Linkage Program on Dryland Cereals (404-40-89) to PSS, JCS, SKG and RKS.
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