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Keller B, Soto J, Steier A, Portilla-Benavides AE, Raatz B, Studer B, Walter A, Muller O, Urban MO. Linking photosynthesis and yield reveals a strategy to improve light use efficiency in a climbing bean breeding population. J Exp Bot 2024; 75:901-916. [PMID: 37878015 PMCID: PMC10837016 DOI: 10.1093/jxb/erad416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 10/21/2023] [Indexed: 10/26/2023]
Abstract
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.
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Affiliation(s)
- Beat Keller
- Crop Science, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Jonatan Soto
- Bean Program, Crops for nutrition and health, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Angelina Steier
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | | | - Bodo Raatz
- Bean Program, Crops for nutrition and health, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Bruno Studer
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Achim Walter
- Crop Science, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Onno Muller
- Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Milan O Urban
- Bean Program, Crops for nutrition and health, International Center for Tropical Agriculture (CIAT), Cali, Colombia
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Keller B, Ariza-Suarez D, Portilla-Benavides AE, Buendia HF, Aparicio JS, Amongi W, Mbiu J, Msolla SN, Miklas P, Porch TG, Burridge J, Mukankusi C, Studer B, Raatz B. Improving Association Studies and Genomic Predictions for Climbing Beans With Data From Bush Bean Populations. Front Plant Sci 2022; 13:830896. [PMID: 35557726 PMCID: PMC9085748 DOI: 10.3389/fpls.2022.830896] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/25/2022] [Indexed: 05/29/2023]
Abstract
Common bean (Phaseolus vulgaris L.) has two major origins of domestication, Andean and Mesoamerican, which contribute to the high diversity of growth type, pod and seed characteristics. The climbing growth habit is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation, and yield. However, breeding efforts in climbing beans have been limited and independent from bush type beans. To advance climbing bean breeding, we carried out genome-wide association studies and genomic predictions using 1,869 common bean lines belonging to five breeding panels representing both gene pools and all growth types. The phenotypic data were collected from 17 field trials and were complemented with 16 previously published trials. Overall, 38 significant marker-trait associations were identified for growth habit, 14 for DF, 13 for 100 seed weight, three for SdFe, and one for yield. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth habits were confirmed from earlier studies and four plausible candidate genes for SdFe and 100 seed weight were newly identified. Furthermore, the genomic prediction accuracy for SdFe and yield in climbing beans improved up to 8.8% when bush-type bean lines were included in the training population. In conclusion, a large population from different gene pools and growth types across multiple breeding panels increased the power of genomic analyses and provides a solid and diverse germplasm base for genetic improvement of common bean.
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Affiliation(s)
- Beat Keller
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Daniel Ariza-Suarez
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
- Bean Program, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | | | - Hector Fabio Buendia
- Bean Program, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | | | - Winnyfred Amongi
- Bean Program, International Center for Tropical Agriculture (CIAT), Kampala, Uganda
| | - Julius Mbiu
- Tanzania Agricultural Research Institute (TARI), Dodoma, Tanzania
| | - Susan Nchimbi Msolla
- Department of Crop Science and Horticulture, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Phillip Miklas
- Department of Agriculture, Agriculture Research Service (USDA-ARS), Prosser, WA, United States
| | - Timothy G. Porch
- Department of Agriculture, Agriculture Research Service (USDA-ARS), Tropical Agriculture Research Station, Mayaguez, PR, United States
| | - James Burridge
- Department of Plant Science, The Pennsylvania State University, University Park, PA, United States
| | - Clare Mukankusi
- Bean Program, International Center for Tropical Agriculture (CIAT), Kampala, Uganda
| | - Bruno Studer
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Bodo Raatz
- Bean Program, International Center for Tropical Agriculture (CIAT), Cali, Colombia
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Keller B, Ariza-Suarez D, de la Hoz J, Aparicio JS, Portilla-Benavides AE, Buendia HF, Mayor VM, Studer B, Raatz B. Genomic Prediction of Agronomic Traits in Common Bean ( Phaseolus vulgaris L.) Under Environmental Stress. Front Plant Sci 2020; 11:1001. [PMID: 32774338 PMCID: PMC7381332 DOI: 10.3389/fpls.2020.01001] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 06/18/2020] [Indexed: 05/19/2023]
Abstract
In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50-80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.
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Affiliation(s)
- Beat Keller
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Daniel Ariza-Suarez
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Juan de la Hoz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Johan Steven Aparicio
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | | | - Hector Fabio Buendia
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Victor Manuel Mayor
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Bruno Studer
- Molecular Plant Breeding, Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
| | - Bodo Raatz
- Bean Program, Agrobiodiversity Area, International Center for Tropical Agriculture (CIAT), Cali, Colombia
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