Genetic Analyses and Genomic Predictions of Root Rot Resistance in Common Bean Across Trials and Populations

Abstract

Root rot in common bean is a disease that causes serious damage to grain production, particularly in the upland areas of Eastern and Central Africa where significant losses occur in susceptible bean varieties. Pythium spp. and Fusarium spp. are among the soil pathogens causing the disease. In this study, a panel of 228 lines, named RR for root rot disease, was developed and evaluated in the greenhouse for Pythium myriotylum and in a root rot naturally infected field trial for plant vigor, number of plants germinated, and seed weight. The results showed positive and significant correlations between greenhouse and field evaluations, as well as high heritability (0.71–0.94) of evaluated traits. In GWAS analysis no consistent significant marker trait associations for root rot disease traits were observed, indicating the absence of major resistance genes. However, genomic prediction accuracy was found to be high for Pythium, plant vigor and related traits. In addition, good predictions of field phenotypes were obtained using the greenhouse derived data as a training population and vice versa. Genomic predictions were evaluated across and within further published data sets on root rots in other panels. Pythium and Fusarium evaluations carried out in Uganda on the Andean Diversity Panel showed good predictive ability for the root rot response in the RR panel. Genomic prediction is shown to be a promising method to estimate tolerance to Pythium, Fusarium and root rot related traits, indicating a quantitative resistance mechanism. Quantitative analyses could be applied to other disease-related traits to capture more genetic diversity with genetic models.

Associated SNPs, Heritabilities, Trait Correlations, and Genomic Breeding Values for Resistance in Snap Beans (Phaseolus vulgaris L.) to Root Rot Caused by Fusarium solani (Mart.) f. sp. phaseoli (Burkholder)

“…Optimum ratio of training to testing populations for achieving the highest repeatable predictive ability was 70:30% training:validation for most traits. This level is within the range of what has been found for other studies of genomic prediction in common bean (Keller et al, 2020;Diaz L. M. et al, 2021;Diaz S. et al, 2021;Shi et al, 2021). At 90% training population, the highest average predictabilities as measured by r were achieved, but standard deviations were much larger, leading to less certainty in whether a prediction was accurate.…”

“…They found sixteen unique SNP associations in an Andean diversity panel on Pv01, Pv02, Pv03, Pv04, Pv07, Pv08, Pv09, and Pv11, and seven unique SNP associations in a Middle American panel on Pv01, Pv03, Pv04, Pv07, and Pv08 ( Zitnick-Anderson et al, 2020 ). Further GWAS studies have been conducted on root rot caused by Pythium spp., Pythium ultimum , Fusarium oxysporum and Rhizoctonia solani in dry bean ( Oladzad et al, 2019 ; Dramadri et al, 2020 ; Diaz L. M. et al, 2021 ; Paulino et al, 2021 ). With F. solani , the studies listed in Supplementary Table 1 have not found major QTL associated with resistance and the general consensus is that resistance is conditioned by several to many genes with small individual effect.…”

“…GS models generally use many markers distributed across the genome, and as a result, are more effective than traditional MAS in selection for traits with many genes with small effect. GS has been applied to common bean for root rot ( Diaz L. M. et al, 2021 ) as well as to agronomic traits ( Keller et al, 2020 ), cooking time ( Diaz S. et al, 2021 ), and nematode resistance ( Wen et al, 2019 ; Shi et al, 2021 ) to discover genotypes with the best breeding values for recombination schemes, but deployment in breeding programs is only beginning.…”

Metabolome Profiling: A Breeding Prediction Tool for Legume Performance under Biotic Stress Conditions

“…are also predominant pathogens that interfere with plant growth by causing damping off and root rot [68]. In African small-scale farms, yield losses of up to 100% caused by the F. solani pathogen in common bean have been reported [69]. In addition, A. euteiches is a soil-borne fungal pathogen that poses a threat to legume production by causing wilting, root rot and consequently yield losses of up to 80% [70,71].…”

Development of a Model for Genomic Prediction of Multiple Traits in Common Bean Germplasm, Based on Population Structure

“…In recent years, an increasing number of studies have focused on the GP of common bean. More advanced research mainly focuses on the breeding and development of the common bean, and the construction model of related single nucleotide polymorphisms (SNPs) is determined by combining genome-wide association analysis (GWAS) and GP [ 15 , 16 , 17 , 18 ]. Other studies have mainly focused on the genomic prediction of a few traits in common bean cultivars using different models [ 19 , 20 , 21 ].…”