Genomics of maize resistance to kernel contamination with fumonisins using a multiparental advanced generation InterCross maize population (MAGIC)

Abstract

Maize kernel is exposed to several fungal species, most notably Fusarium verticillioides, which can contaminate maize kernels with fumonisins. In an effort to increase genetic gains and avoid the laborious tasks of conventional breeding, the use of marker-assisted selection or genomic selection programs was proposed. To this end, in the present study a Genome Wide Association Study (GWAS) was performed on 339 RILs of a Multiparental Advanced Generation InterCross (MAGIC) population that had previously been used to locate Quantitative Trait Locus (QTL) for resistance to Fusarium Ear Rot (FER). Six QTLs for fumonisin content were detected in the bins 3.08, 4.07, 4.10, 7.03-7.04, 9.04-9.05 and 10.04-10.5. Five of the six QTLs collocate in regions where QTLs for FER were also found. However, the genetic variation for fumonisin content in kernel is conditioned by many other QTLs of small effect that could show QTL x environment interaction effects. Although a genomic selection approach to directly reduce fumonisin content in the kernel could be suitable, improving resistance to fumonisin content by genomic selection for FER would be more advisable.

Meta-analysis and co-expression analysis revealed stable QTL and candidate genes conferring resistances to Fusarium and Gibberella ear rots while reducing mycotoxin contamination in maize

“…Fifteen publications were SNP-based QTL mapping studies which were used to collect relevant information required for the QTL meta-analysis ( Supplementary File 2 ) ( Chen et al., 2016 ; Giomi et al., 2016 ; Han et al., 2016 ; Kebede et al., 2016 ; Maschietto et al., 2017 ; Han et al., 2018 ; Galić et al., 2019 ; Wen et al., 2020 ; Yuan et al., 2020a ; Galiano-Carneiro et al., 2021 ; Giomi et al., 2021 ; Wen et al., 2021b ; Zhou et al., 2021 ; Feng et al., 2022 ; Guo et al., 2022 ). Seven papers were related to genome-wide association study and used to cross-validate the meta-analysis ( Butrón et al., 2019 ; Samayoa et al., 2019 ; Wu et al., 2020 ; Gaikpa et al., 2021 ; Gesteiro et al., 2021 ; Liu et al., 2021 ; da Silva et al., 2022 ).…”

Genomics and Pathways Involved in Maize Resistance to Fusarium Ear Rot and Kernel Contamination With Fumonisins

“…Moreover, moderate to high genotypic correlation coefficients for resistance to fumonisin accumulation have been reported between inbred lines and test crosses ( Löffler et al, 2011 ; Hung and Holland, 2012 ; Padua et al, 2016 ). The search for quantitative trait loci (QTLs) for resistance to fumonisin accumulation has been only performed on few mapping populations, most of which are bi-parental populations ( Robertson-Hoyt et al, 2006 ; Maschietto et al, 2017 ; Morales et al, 2019 ; Samayoa et al, 2019 ; Gesteiro et al, 2021 ). In this sense, this study intends to gain additional insight into the genetic basis of resistance to kernel infection by exploring genetic variability in a new mapping population derived from a cross between two inbreds with contrasting values for both FER and fumonisin accumulation in kernels.…”

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines

“…Most previous mapping studies inferred the existence of genetic background and main-effect QTL interaction via this above approach [19]. GWAS have been widely applied to the genetic analysis for complex traits in family-based populations, including nested-association mapping (NAM) [38] and MAGIC populations [39], thus proven to be a powerful tool for uncovering the basis of key agronomic traits in maize. In this study, not only CSL analysis but also GWAS with and without population structure models were used to estimate the effect of genetic background on QTL for kernel traits in the reciprocal ILs.…”