Genome‐wide analysis and prediction of Fusarium head blight resistance in soft red winter wheat

Abstract

Fusarium head blight (FHB) is a disease in wheat (Triticum aestivum L.) caused by the fungal pathogen Fusarium graminearum Schwabe. Fusarium head blight poses potential economic losses and health risks due to the accumulation of the mycotoxin deoxynivalenol (DON) on infected seed heads. The objectives of this study were to identify novel FHB resistance loci using a genome‐wide association study (GWAS) approach and to evaluate two genomic selection (GS) approaches to improve prediction accuracies for FHB traits in a population of 354 soft red winter wheat (SRWW) genotypes. The GS approaches included GS+GWAS, where markers associated with a trait were used as fixed effects, and multivariate GS (MVGS), where correlated traits were used as covariates. The population was evaluated in FHB nurseries in Fayetteville and Newport, AR, and Winnsboro, LA, from 2014 to 2017. Genotypes were phenotyped for DON, Fusarium‐damaged kernels (FDK), incidence (INC), and severity (SEV). Forty‐two single nucleotide polymorphism (SNP) markers were significantly (false discovery rate, q [FDRq] ≤ .10) associated with resistance traits across 17 chromosomes. Ten significant SNPs were identified for DON, notably on chromosomes 2BL and 3BL. Eleven were identified for FDK, notably on chromosomes 4BL, 3AL, 1BL, 5BL, and 5DL. Nine were identified for INC, notably on chromosomes 2BS, 2BL, 7BL, 5DL, 6AS, and 5DS. Twelve were identified for SEV, notably on chromosomes 3BL, 4AL, and 4BL. The naïve GS models significantly outperformed the GS+GWAS model for all traits, whereas MVGS models significantly outperformed the naïve GS models for all traits. Results from this study will facilitate the development of SRWW cultivars with improved FHB resistance.

Merging Genomics and Transcriptomics for Predicting Fusarium Head Blight Resistance in Wheat

“…Since genetic resistance is considered the most environmentally friendly and effective strategy to control diseases, several studies have aimed to increase the achievable gain of predictive breeding for FHB resistance in cereals [ 5 , 6 , 7 ]. Prediction model improvements range from up-weighting markers linked to major QTL like Fhb1 [ 8 ] to the usage of pre-existing information [ 9 ] or traits that are correlated with FHB resistance [ 10 , 11 ]. Anther retention is one promising choice for the latter strategy, since an open-flowering behavior increases plant resistance to initial infection by Fusarium spp.…”

Evaluation of Genomic Prediction for Fusarium Head Blight Resistance with a Multi-Parental Population

“…Thus, our findings were in agreement with results from Bernardo [ 54 ]. Recently, Larkin et al [ 57 ] reported that GS plus QTL performed worse than native GS, while Rice and Lipka [ 76 ] showed that the benefits of GS plus QTL were on a trait-by-trait basis. Therefore, application of the GS plus QTL model should take into account the trait, effect of QTL, and the property of the genetic architecture underlying the trait.…”

“…Jia and Jannink [ 52 ] reported that for genetically correlated quantitative traits, multivariate genomic selection (MVGS) model on multiple correlated traits outperformed the single-trait (univariate) GS model. With the application of the MVGS model on FHB related traits including INC, SEV, FDK and DON and plant height, Larkin et al [ 57 ] found that MVGS performed better for all these FHB resistance traits except for DON. In our study, we found MVGS did not perform better than the single trait prediction model for all these FHB related traits in the test of Year 2015.…”

“…GS has been evaluated to predict FHB resistance traits in a number of previous reports [ 29 , 30 , 31 , 57 , 58 ]. However, only a limited number of factors contributing to accuracies of GS for FHB resistance traits were investigated in these studies.…”

Introduction to the special Crop Science issue: Celebrating the International Year of Plant Health

“…Larkin et al. (2020) present genome‐wide association study (GWAS) and genomic prediction to identify markers associated with resistance to Fusarium head blight in soft red winter wheat. The disease is caused by the fungal pathogen Fusarium graminearum , which causes accumulation of the mycotoxin deoxynivalenol in infected seed heads.…”