Genomic Prediction of The Performance of Tropical Doubled Haploid Maize Lines under Artificial Striga hermonthica (Del.) Benth. Infestation.

Striga doubled haploid genomic prediction maize breeding sparse phenotyping

Journal

G3 (Bethesda, Md.)
ISSN: 2160-1836
Titre abrégé: G3 (Bethesda)
Pays: England
ID NLM: 101566598

Informations de publication

Date de publication:
12 Aug 2024
Historique:
received: 31 05 2024
revised: 23 07 2024
accepted: 09 08 2024
medline: 12 8 2024
pubmed: 12 8 2024
entrez: 12 8 2024
Statut: aheadofprint

Résumé

Striga hermonthica (Del.) Benth., a parasitic weed, causes substantial yield losses in maize production in sub-Saharan Africa (SSA). 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 (DH) maize lines. We genotyped 606 DH lines with 8,439 rAmpSeq markers. A training set of 116 DH lines crossed to two testers was phenotyped under artificial Striga infestation at three 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 to 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 DH lines with desirable genomic estimated breeding values (GEBVs) for reduced number of emerged Striga plants (STR) at 8, 10, and 12 weeks after planting. The GEBVs of DH 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 DH technology for line development coupled with forward breeding for major adaptive traits will enhance genetic gains in breeding for Striga resistance in maize.

Identifiants

pubmed: 39129203
pii: 7731522
doi: 10.1093/g3journal/jkae186
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.

Auteurs

Joan J C Kimutai (JJC)

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041-00621, Nairobi, Kenya.
West Africa Centre for Crop Improvement (WACCI), University of Ghana, PMB LG 30, Accra, Ghana.

Dan Makumbi (D)

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041-00621, Nairobi, Kenya.

Juan Burgueño (J)

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

Paulino Pérez-Rodríguez (P)

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

Jose Crossa (J)

Biometrics and Statistics Unit, CIMMYT, Apdo. Postal 6-641, 06600, Mexico DF, Mexico.
Socioeconomía, Estadística e Informática, Colegio de Postgraduados, Edo. de México 56230, Montecillos, México.

Manje Gowda (M)

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041-00621, Nairobi, Kenya.

Abebe Menkir (A)

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

Angela Pacheco (A)

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

Beatrice E Ifie (BE)

West Africa Centre for Crop Improvement (WACCI), University of Ghana, PMB LG 30, Accra, Ghana.
Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University, Aberystwyth, SY23 3EE, Wales, United Kingdom.

Pangirayi Tongoona (P)

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

Eric Y Danquah (EY)

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

Boddupalli M Prasanna (BM)

International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041-00621, Nairobi, Kenya.

Classifications MeSH