Genetic dissection of Striga hermonthica (Del.) Benth. resistance via genome-wide association and genomic prediction in tropical maize germplasm

Abstract

Key message Genome-wide association revealed that resistance to Striga hermonthica is influenced by multiple genomic regions with moderate effects. It is possible to increase genetic gains from selection for Striga resistance using genomic prediction. Abstract Striga hermonthica (Del.) Benth., commonly known as the purple witchweed or giant witchweed, is a serious problem for maize-dependent smallholder farmers in sub-Saharan Africa. Breeding for Striga resistance in maize is complicated due to limited genetic variation, complexity of resistance and challenges with phenotyping. This study was conducted to (i) evaluate a set of diverse tropical maize lines for their responses to Striga under artificial infestation in three environments in Kenya; (ii) detect quantitative trait loci associated with Striga resistance through genome-wide association study (GWAS); and (iii) evaluate the effectiveness of genomic prediction (GP) of Striga-related traits. An association mapping panel of 380 inbred lines was evaluated in three environments under artificial Striga infestation in replicated trials and genotyped with 278,810 single-nucleotide polymorphism (SNP) markers. Genotypic and genotype x environment variations were significant for measured traits associated with Striga resistance. Heritability estimates were moderate (0.42) to high (0.92) for measured traits. GWAS revealed 57 SNPs significantly associated with Striga resistance indicator traits and grain yield (GY) under artificial Striga infestation with low to moderate effect. A set of 32 candidate genes physically near the significant SNPs with roles in plant defense against biotic stresses were identified. GP with different cross-validations revealed that prediction of performance of lines in new environments is better than prediction of performance of new lines for all traits. Predictions across environments revealed high accuracy for all the traits, while inclusion of GWAS-detected SNPs led to slight increase in the accuracy. The item-based collaborative filtering approach that incorporates related traits evaluated in different environments to predict GY and Striga-related traits outperformed GP for Striga resistance indicator traits. The results demonstrated the polygenic nature of resistance to S. hermonthica, and that implementation of GP in Striga resistance breeding could potentially aid in increasing genetic gain for this important trait.

Agronomic Performance Of S1 Maize Lines Derived From A Bi-Parental Cross Under Infested And Striga Free Environments

“…Moderated high heritability estimates have been observed indicating the potential for these traits to be improved through recurrent selection.The high heritability estimates for grain yield, days to 50% anthesis, and Striga damage at 8 and 10 WAP suggest that reasonable genetic gain for these traits could be expected from selection. These findings are corroborated to previous reports under artificial Striga infestation (Menkir and Meseka, 2019), but are greater than those reported by Gowda et al (2021) in inbred lines of maize under Striga infestation.…”

Genome-Wide Association Studies for Striga asiatica Resistance in Tropical Maize

“…Markers for Striga counts Interestingly, in this study, markers for total Striga plants emerged were found on chromosome 7 just like markers for Striga damage rating which have been also found by Adewale et al [21] to be located on several chromosomes including number 7. Working on Striga hermonthica, Gowda et al [22] also found SNP markers for emerged Striga plants and Striga counts at chromosomes 5 and 7, respectively. These findings are in line with the observations from this study that also found the markers total Striga plants emerged at chromosomes 5, 6, and 7 for Striga asiatica, a strain that is found in southern Africa.…”

“…These resistance mechanisms could be exploited in breeding better varieties; however, the heritability for Striga resistance is low [ 16 , 17 ]. When heritability is low, the use of molecular markers is usually effective [ 22 ]. The SNP markers identified in this study for the total number of Striga plants emerged could thus go a long way if they are validated and utilised in breeding programs.…”

“…The development of new varieties using the convectional breeding approach is usually labour-intensive and slow [ 22 ]. New breeding methodologies have been proposed with the advent of molecular markers.…”

“…There is need to identify SNP markers in maize that are associated with resistance to Striga using genome-wide association study (GWAS) because SNP markers are abundantly available in the maize genome, codominant, evenly distributed throughout the genome, and highly reproducible and polymorphic. However, to date, only reports exist for Striga hermonthica found in east Africa and absent for Striga asiatica found in southern Africa [ 13 , 18 , 21 , 22 ]. Identification of SNP markers will solidify convectional breeding methods and bring rejuvenation to maize production in resource poor African farmers by reducing yield losses due to Striga infestation [ 13 ].…”