Genomic prediction of the performance of tropical doubled haploid maize lines under artificial Striga hermonthica (Del.) Benth. infestation

Author:

Kimutai Joan J C12ORCID,Makumbi Dan1ORCID,Burgueño Juan3ORCID,Pérez-Rodríguez Paulino4ORCID,Crossa Jose34ORCID,Gowda Manje1ORCID,Menkir Abebe5ORCID,Pacheco Angela3ORCID,Ifie Beatrice E26ORCID,Tongoona Pangirayi2ORCID,Danquah Eric Y2ORCID,Prasanna Boddupalli M1ORCID

Affiliation:

1. Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT) , P.O. Box 1041–00621, Nairobi , Kenya

2. West Africa Centre for Crop Improvement (WACCI), University of Ghana , PMB 30 Legon, Accra , Ghana

3. Biometrics and Statistics Unit, CIMMYT , Apdo. Postal 6–641, 06600 Mexico DF , Mexico

4. Socioeconomía, Estadística e Informática, Colegio de Postgraduados , Edo. de México 56230, Montecillos , Mexico

5. International Institute of Tropical Agriculture (IITA) , Oyo Road, PMB 5320, Ibadan, 200001 , Nigeria

6. Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University , Aberystwyth, SY23 3EE Wales , UK

Abstract

Abstract Striga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa. Breeding for Striga resistance in maize is constrained by limited genetic diversity for Striga resistance within the elite germplasm and phenotyping capacity under artificial Striga infestation. Genomics-enabled approaches have the potential to accelerate identification of Striga resistant lines for hybrid development. The objectives of this study were to evaluate the accuracy of genomic selection for traits associated with Striga resistance and grain yield (GY) and to predict genetic values of tested and untested doubled haploid maize lines. We genotyped 606 doubled haploid lines with 8,439 rAmpSeq markers. A training set of 116 doubled haploid lines crossed to 2 testers was phenotyped under artificial Striga infestation at 3 locations in Kenya. Heritability for Striga resistance parameters ranged from 0.38–0.65 while that for GY was 0.54. The prediction accuracies for Striga resistance-associated traits across locations, as determined by cross-validation (CV) were 0.24–0.53 for CV0 and from 0.20 to 0.37 for CV2. For GY, the prediction accuracies were 0.59 and 0.56 for CV0 and CV2, respectively. The results revealed 300 doubled haploid lines with desirable genomic estimated breeding values for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The genomic estimated breeding values of doubled haploid lines for Striga resistance-associated traits in the training and testing sets were similar in magnitude. These results highlight the potential application of genomic selection in breeding for Striga resistance in maize. The integration of genomic-assisted strategies and doubled haploid technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.

Funder

Bill and Melinda Gates Foundation

Foundation for Food and Agriculture Research

United States Agency for International Development

Accelerating Genetic Gains in Maize and Wheat

Improved Livelihoods

Achieving Sustainable Striga Control for Poor Farmers in Africa

Publisher

Oxford University Press (OUP)

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