Improving Association Studies and Genomic Predictions for Climbing Beans With Data From Bush Bean Populations

GWAS of resistance to three bacterial diseases in the Andean common bean diversity panel

Bacterial brown spot (BBS) caused by Pseudomonas syringae pv. syringae (Pss), common bacterial blight (CBB) caused by Xanthomonas axonopodis pv. phaseoli (Xap) and Xanthomonas fuscans subsp. fuscans (Xff), and halo bacterial blight (HBB), caused by Pseudomonas syringae pv. phaseolicola (Psph), are major bacterial diseases that severely affect common bean yields and global food security. Andean-origin dry beans, representing large-seeded market classes, are particularly susceptible. Using 140,325 SNPs, a multi-locus GWAS was conducted on subsets of the Andean diversity panel (ADP) phenotyped for BBS in South Africa, CBB in Puerto Rico, South Africa, and Zambia, and HBB in South Africa, through natural infection, artificial inoculation, or both. Twenty-four QTL associated with resistance were identified: nine for BBS, eight for CBB, and seven for HBB. Four QTL intervals on Pv01, Pv03, Pv05, and Pv08 overlapped with BBS and HBB resistance. A genomic interval on Pv01, near the fin gene, which determines growth habit, was linked to resistance to all three pathogens. Different QTLs were detected for BBS and CBB resistance when phenotyped under natural infection versus artificial inoculation. These results underscore the importance of combining phenotyping methods in multi-GWAS to capture the full genetic spectrum. Previously recognized CBB resistance QTL SAP6 and SU91 and HBB resistance QTL HB4.2, and HB5.1, were observed. Other common (MAF >0.25) and rare (MAF <0.05) resistance QTL were also detected. Overall, these findings enhance the understanding and utilization of bacterial resistance present in ADP for the development of common beans with improved resistance.

Linking photosynthesis and yield reveals a strategy to improve light use efficiency in a climbing bean breeding population

Photosynthesis drives plant physiology, biomass accumulation, and yield. Photosynthetic efficiency, specifically the operating efficiency of PSII (Fq'/Fm'), is highly responsive to actual growth conditions, especially to fluctuating photosynthetic photon fluence rate (PPFR). Under field conditions, plants constantly balance energy uptake to optimize growth. The dynamic regulation complicates the quantification of cumulative photochemical energy uptake based on the intercepted solar energy, its transduction into biomass, and the identification of efficient breeding lines. Here, we show significant effects on biomass related to genetic variation in photosynthetic efficiency of 178 climbing bean (Phaseolus vulgaris L.) lines. Under fluctuating conditions, the Fq'/Fm' was monitored throughout the growing period using hand-held and automated chlorophyll fluorescence phenotyping. The seasonal response of Fq'/Fm' to PPFR (ResponseG:PPFR) achieved significant correlations with biomass and yield, ranging from 0.33 to 0.35 and from 0.22 to 0.31 in two glasshouse and three field trials, respectively. Phenomic yield prediction outperformed genomic predictions for new environments in four trials under different growing conditions. Investigating genetic control over photosynthesis, one single nucleotide polymorphism (Chr09_37766289_13052) on chromosome 9 was significantly associated with ResponseG:PPFR in proximity to a candidate gene controlling chloroplast thylakoid formation. In conclusion, photosynthetic screening facilitates and accelerates selection for high yield potential.

Genome-wide association mapping for component traits of drought tolerance in dry beans (Phaseolus vulgaris L.)

Understanding the genetic basis of traits of economic importance under drought stressed and well-watered conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgaris L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An andean and middle-american diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stressed and well-watered conditions for two successive seasons. Agronomic and physiological traits, viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using the filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the panel was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under drought stressed conditions. Population structure analysis revealed two sub-populations, which corresponded to the andean and middle-american gene pools. Markers explained 0.08-0.10, 0.22-0.23, 0.29-0.32, 0.43-0.44, 0.65-0.66 and 0.69-0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under drought stressed conditions. For well-watered conditions, R2 varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10-03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across drought stressed and well-watered conditions. Most of the identified genes had known biological functions related to regulating the response to drought stress. The findings provide new insights into the genetic architecture of drought stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.

Novel candidate loci for morpho-agronomic and seed quality traits detected by targeted genotyping-by-sequencing in common bean

Phaseolus vulgaris L., known as common bean, is one of the most important grain legumes cultivated around the world for its immature pods and dry seeds, which are rich in protein and micronutrients. Common bean offers a cheap food and protein sources to ameliorate food shortage and malnutrition around the world. However, the genetic basis of most important traits in common bean remains unknown. This study aimed at identifying QTL and candidate gene models underlying twenty-six agronomically important traits in common bean. For this, we assembled and phenotyped a diversity panel of 200 P. vulgaris genotypes in the greenhouse, comprising determinate bushy, determinate climbing and indeterminate climbing beans. The panel included dry beans and snap beans from different breeding programmes, elite lines and landraces from around the world with a major focus on accessions of African, European and South American origin. The panel was genotyped using a cost-conscious targeted genotyping-by-sequencing (GBS) platform to take advantage of highly polymorphic SNPs detected in previous studies and in diverse germplasm. The detected single nucleotide polymorphisms (SNPs) were applied in marker-trait analysis and revealed sixty-two quantitative trait loci (QTL) significantly associated with sixteen traits. Gene model identification via a similarity-based approach implicated major candidate gene models underlying the QTL associated with ten traits including, flowering, yield, seed quality, pod and seed characteristics. Our study revealed six QTL for pod shattering including three new QTL potentially useful for breeding. However, the panel was evaluated in a single greenhouse environment and the findings should be corroborated by evaluations across different field environments. Some of the detected QTL and a number of candidate gene models only elucidate the understanding of the genetic nature of these traits and provide the basis for further studies. Finally, the study showed the possibility of using a limited number of SNPs in performing marker-trait association in common bean by applying a highly scalable targeted GBS approach. This targeted GBS approach is a cost-efficient strategy for assessment of the genetic basis of complex traits and can enable geneticists and breeders to identify novel loci and targets for marker-assisted breeding more efficiently.