Location: Grain Legume Genetics Physiology ResearchTitle: Genomic predictions in climbing beans and their genetic associations with bush bean populations
|KELLER, BEAT - International Center For Tropical Agriculture (CIAT)|
|ARIZA-SUAREZ, DANIEL - International Center For Tropical Agriculture (CIAT)|
|PORTILLA-BENAVIDES, ANA - International Center For Tropical Agriculture (CIAT)|
|BUENDIA, HECTOR - International Center For Tropical Agriculture (CIAT)|
|APARICIO, J - International Center For Tropical Agriculture (CIAT)|
|AMONGI, WINNYFRED - Association For Strengthening Agricultural Research In Eastern And Central Africa (ASARECA)|
|MBIU, J - Plant Health Services - Tanzania|
|NCHIMBI-MSOLLA, S - Sokoine University Of Agriculture|
|Miklas, Phillip - Phil|
|Porch, Timothy - Tim|
|BURRIDGE, JAMES - Pennsylvania State University|
|MUKANKUSI, CLAIRE - Association For Strengthening Agricultural Research In Eastern And Central Africa (ASARECA)|
|STUDER, BRUNO - Eth Zurich|
|RAATZ, BODO - International Center For Tropical Agriculture (CIAT)|
Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/25/2022
Publication Date: 4/25/2022
Citation: Keller, B., Ariza-Suarez, D., Portilla-Benavides, A., Buendia, H., Aparicio, J., Amongi, W., Mbiu, J., Nchimbi-Msolla, S., Miklas, P.N., Porch, T.G., Burridge, J., Mukankusi, C., Studer, B., Raatz, B. 2022. Genomic predictions in climbing beans and their genetic associations with bush bean populations. Frontiers in Plant Science. 13. Article 830896. https://doi.org/10.3389/fpls.2022.830896.
Interpretive Summary: Dry edible bean is a major food crop high in protein, vitamins, and minerals for human diets worldwide, and are an important crop for subsistence farmers in East Africa. Compared to beans with bush growth habits - climbing beans in East Africa provide 3 to 10x the yield potential, but require a much longer growing season. Breeding efforts for climbing beans have been negligible. This study was conducted to facilitate breeding strategies and improvements of climbing beans. Field trials in Colombia, Tanzania, and Uganda compared 1600 beans lines with contrasting growth habits for climbing ability, maturity, nitrogen content, iron concentration in the seed, and yield. A total of 38 chromosomal regions influencing these traits in the genome were identified and used to develop models to enhance selection efficiency for the traits. In summary, this study provides molecular strategies to increase selection efficiency for breeding improved climbing beans with enhanced traits (eg increased nitrogen fixation, earlier maturity, increased yield). Improved climbing beans will improve food security and livelihoods of small holder farmers in East Africa.
Technical Abstract: Common bean (Phaseolus vulgaris L.) has two major origins for domestication, Andean and Mesoamerican, which contributed to high genetic diversity reflected by different pod and seed characteristics and growth types. Climbing ability is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation and yield. Hence, climbing beans produce valuable food with high nutritional quality under low input conditions. However, breeding of climbing beans has been limited. We sought to conduct a comprehensive phenotypic and genetic analysis in common bean to facilitate breeding strategies and improvements of climbing beans. Genome-wide association studies and genomic predictions for 1,600 common bean lines belonging to five breeding panels representing Andean and Mesoamerican gene pools and all growth types were used in this sudy. Overall, 38 QTL affecting growth habit and climbing ability, 14 for DF, 13 for 100 seed weight, 3 for SdFe and one for yield were identified. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth type were confirmed from earlier studies, indicating the high detection power of our panel. Factor analysis and genotype by environment interaction (GxE) models performed best for genomic predictions for different traits. For the climbing bean lines, across trials, prediction accuracies of 77.4%, 67.4%, 63.5% and 72.5% were obtained for 100SdW, DF, SdFe and yield. Interestingly, the prediction accuracies for DF, SdFe and yield, were improved when bush type bean lines were included in the training population. In summary, a comprehensive breeding population using diversity from different gene pools and growth types across multiple breeding panels and origins provided molecular strategies to increase selection efficiency for common bean across all growth types.