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Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.

ABSTRACT: Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst for FAW, random-based training sets (RBTS) and pedigree-based training sets (PBTSs) were designed. PAs achieved with BLUPs varied from 0.66 to 0.82 for MW-resistance traits, and for FAW resistance, 0.694 to 0.714 for RBTS of 37%, and 0.843 to 0.844 for RBTS of 85%, and these were at least two-fold those from BLUEs. For PBTS, FAW resistance PAs were generally higher than those for RBTS, except for one dataset. GP models generally showed similar PAs across individual traits whilst the TS designation was determinant, since a positive correlation (R = 0.92***) between TS size and PAs was observed for RBTS, and for the PBTS, it was negative (R = 0.44**). This study pioneered the use of GS for maize resistance to insect pests in sub-Saharan Africa.

SUBMITTER: Badji A

PROVIDER: S-EPMC7823878 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.

Badji Arfang A Machida Lewis L Kwemoi Daniel Bomet DB Kumi Frank F Okii Dennis D Mwila Natasha N Agbahoungba Symphorien S Ibanda Angele A Bararyenya Astere A Nghituwamhata Selma Ndapewa SN Odong Thomas T Wasswa Peter P Otim Michael M Ochwo-Ssemakula Mildred M Talwana Herbert H Asea Godfrey G Kyamanywa Samuel S Rubaihayo Patrick P

Plants (Basel, Switzerland) 20201224 1

Genomic selection (GS) can accelerate variety improvement when training set (TS) size and its relationship with the breeding set (BS) are optimized for prediction accuracies (PAs) of genomic prediction (GP) models. Sixteen GP algorithms were run on phenotypic best linear unbiased predictors (BLUPs) and estimators (BLUEs) of resistance to both fall armyworm (FAW) and maize weevil (MW) in a tropical maize panel. For MW resistance, 37% of the panel was the TS, and the BS was the remainder, whilst f ...[more]

PMID: 33374402

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Project description:Genetically modified plants expressing insecticidal proteins from Bacillus thuringiensis (Bt) offer valuable options for managing insect pests with considerable environmental and economic benefits. Despite the benefits provided by Bt crops, the continuous expression of these insecticidal proteins imposes strong selection for resistance in target pest populations. Bt maize (Zea mays) hybrids have been successful in controlling fall armyworm (Spodoptera frugiperda), the main maize pest in Brazil since 2008; however, field-evolved resistance to the protein Cry1F has recently been reported. Therefore it is important to assess the possibility of cross-resistance between Cry1F and other Cry proteins expressed in Bt maize hybrids. In this study, an F2 screen followed by subsequent selection on MON 89034 maize was used to select an S. frugiperda strain (RR) able to survive on the Bt maize event MON 89034, which expresses the Cry1A.105 and Cry2Ab2 proteins. Field-collected insects from maize expressing the Cry1F protein (event TC1507) represented most of the positive (resistance allele-containing) (iso)families found. The RR strain showed high levels of resistance to Cry1F, which apparently also conferred high levels of cross resistance to Cry1A.105 and Cry1Ab, but had only low-level (10-fold) resistance to Cry2Ab2. Life history studies to investigate fitness costs associated with the resistance in RR strain revealed only small reductions in reproductive rate when compared to susceptible and heterozygous strains, but the RR strain produced 32.2% and 28.4% fewer females from each female relative to the SS and RS (pooled) strains, respectively. Consistent with the lack of significant resistance to Cry2Ab2, MON 89034 maize in combination with appropriate management practices continues to provide effective control of S. frugiperda in Brazil. Nevertheless, the occurrence of Cry1F resistance in S. frugiperda across Brazil, and the cross-resistance to Cry1Ab and Cry1A.105, indicates that current Cry1-based maize hybrids face a challenge in managing S. frugiperda in Brazil and highlights the importance of effective insect resistance management for these technologies.

Dataset Information

Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.

Publications

Factors Influencing Genomic Prediction Accuracies of Tropical Maize Resistance to Fall Armyworm and Weevils.

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