1
|
Liu H, Zhang X, Shang Y, Zhao S, Li Y, Zhou X, Huo X, Qiao P, Wang X, Dai K, Li H, Guo J, Shi W. Genome-wide association study reveals genetic loci for ten trace elements in foxtail millet (Setaria italica). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:186. [PMID: 39017920 DOI: 10.1007/s00122-024-04690-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 07/03/2024] [Indexed: 07/18/2024]
Abstract
KEY MESSAGE One hundred and fifty-five QTL for trace element concentrations in foxtail millet were identified using a genome-wide association study, and a candidate gene associated with Ni-Co-Cr concentrations was detected. Foxtail millet (Setaria italica) is an important regional crop known for its rich mineral nutrient content, which has beneficial effects on human health. We assessed the concentrations of ten trace elements (Ba, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, and Zn) in the grain of 408 foxtail millet accessions. Significant differences in the concentrations of five elements (Ba, Co, Ni, Sr, and Zn) were observed between two subpopulations of spring- and summer-sown foxtail millet varieties. Moreover, 84.4% of the element pairs exhibited significant correlations. To identify the genetic factors influencing trace element accumulation, a comprehensive genome-wide association study was conducted, identifying 155 quantitative trait locus (QTL) for the ten trace elements across three different environments. Among them, ten QTL were consistently detected in multiple environments, including qZn2.1, qZn4.4, qCr4.1, qFe6.3, qFe6.5, qCo6.1, qPb7.3, qPb7.5, qBa9.1, and qNi9.1. Thirteen QTL clusters were detected for multiple elements, which partially explained the correlations between elements. Additionally, the different concentrations of five elements between foxtail millet subpopulations were caused by the different frequencies of high-concentration alleles associated with important marker-trait associations. Haplotype analysis identified a candidate gene SETIT_036676mg associated with Ni accumulation, with the GG haplotype significantly increasing Ni-Co-Cr concentrations in foxtail millet. A cleaved amplified polymorphic sequence marker (cNi6676) based on the two haplotypes of SETIT_036676mg was developed and validated. Results of this study provide valuable reference information for the genetic research and improvement of trace element content in foxtail millet.
Collapse
Affiliation(s)
- Hanxiao Liu
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Xin Zhang
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Yuping Shang
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Shaoxing Zhao
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Yingjia Li
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Xutao Zhou
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Xiaoyu Huo
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Pengfei Qiao
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Xin Wang
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Keli Dai
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China
| | - Huixia Li
- Millet Research Institute, Shanxi Agricultural University, Changzhi, 046000, China
| | - Jie Guo
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China.
| | - Weiping Shi
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, China.
| |
Collapse
|
2
|
Kapoor C, Anamika, Mukesh Sankar S, Singh SP, Singh N, Kumar S. Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet. PLANTA 2024; 259:155. [PMID: 38750378 DOI: 10.1007/s00425-024-04423-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 04/25/2024] [Indexed: 05/23/2024]
Abstract
MAIN CONCLUSION Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.
Collapse
Affiliation(s)
- Chandan Kapoor
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
| | - Anamika
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - S Mukesh Sankar
- ICAR-Indian Institute of Spices Research, Kozhikode, Kerala, 673012, India
| | - S P Singh
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Nirupma Singh
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| | - Sudhir Kumar
- ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India
| |
Collapse
|
3
|
LaPorte MF, Suwarno WB, Hannok P, Koide A, Bradbury P, Crossa J, Palacios-Rojas N, Diepenbrock CH. Investigating genomic prediction strategies for grain carotenoid traits in a tropical/subtropical maize panel. G3 (BETHESDA, MD.) 2024; 14:jkae044. [PMID: 38427914 PMCID: PMC11075567 DOI: 10.1093/g3journal/jkae044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/13/2024] [Accepted: 02/22/2024] [Indexed: 03/03/2024]
Abstract
Vitamin A deficiency remains prevalent on a global scale, including in regions where maize constitutes a high percentage of human diets. One solution for alleviating this deficiency has been to increase grain concentrations of provitamin A carotenoids in maize (Zea mays ssp. mays L.)-an example of biofortification. The International Maize and Wheat Improvement Center (CIMMYT) developed a Carotenoid Association Mapping panel of 380 inbred lines adapted to tropical and subtropical environments that have varying grain concentrations of provitamin A and other health-beneficial carotenoids. Several major genes have been identified for these traits, 2 of which have particularly been leveraged in marker-assisted selection. This project assesses the predictive ability of several genomic prediction strategies for maize grain carotenoid traits within and between 4 environments in Mexico. Ridge Regression-Best Linear Unbiased Prediction, Elastic Net, and Reproducing Kernel Hilbert Spaces had high predictive abilities for all tested traits (β-carotene, β-cryptoxanthin, provitamin A, lutein, and zeaxanthin) and outperformed Least Absolute Shrinkage and Selection Operator. Furthermore, predictive abilities were higher when using genome-wide markers rather than only the markers proximal to 2 or 13 genes. These findings suggest that genomic prediction models using genome-wide markers (and assuming equal variance of marker effects) are worthwhile for these traits even though key genes have already been identified, especially if breeding for additional grain carotenoid traits alongside β-carotene. Predictive ability was maintained for all traits except lutein in between-environment prediction. The TASSEL (Trait Analysis by aSSociation, Evolution, and Linkage) Genomic Selection plugin performed as well as other more computationally intensive methods for within-environment prediction. The findings observed herein indicate the utility of genomic prediction methods for these traits and could inform their resource-efficient implementation in biofortification breeding programs.
Collapse
Affiliation(s)
- Mary-Francis LaPorte
- Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA
| | - Willy Bayuardi Suwarno
- Department of Agronomy and Horticulture, Faculty of Agriculture, IPB University, Bogor 16680, Indonesia
| | - Pattama Hannok
- Division of Agronomy, Faculty of Agricultural Production, Maejo University, Chiang Mai 50200, Thailand
- Plant Breeding and Plant Genetics Program, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Akiyoshi Koide
- Department of Plant Sciences, University of California, Davis, Davis, CA 95616, USA
| | - Peter Bradbury
- United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA
| | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco 56130, Mexico
| | - Natalia Palacios-Rojas
- International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera Mexico-Veracruz, Texcoco 56130, Mexico
| | | |
Collapse
|
4
|
He L, Sui Y, Che Y, Liu L, Liu S, Wang X, Cao G. New Insights into the Genetic Basis of Lysine Accumulation in Rice Revealed by Multi-Model GWAS. Int J Mol Sci 2024; 25:4667. [PMID: 38731885 PMCID: PMC11083390 DOI: 10.3390/ijms25094667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 04/21/2024] [Accepted: 04/22/2024] [Indexed: 05/13/2024] Open
Abstract
Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype.
Collapse
Affiliation(s)
- Liqiang He
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Yao Sui
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Yanru Che
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Lihua Liu
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Shuo Liu
- School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China
| | - Xiaobing Wang
- Institute of Tropical Crop Genetic Resources, Chinese Academy of Tropical Agricultural Sciences, Danzhou 571737, China
| | - Guangping Cao
- Hainan Key Laboratory of Crop Genetics and Breeding, Institute of Food Crops, Hainan Academy of Agricultural Sciences, Haikou 571100, China
| |
Collapse
|
5
|
Alemu A, Åstrand J, Montesinos-López OA, Isidro Y Sánchez J, Fernández-Gónzalez J, Tadesse W, Vetukuri RR, Carlsson AS, Ceplitis A, Crossa J, Ortiz R, Chawade A. Genomic selection in plant breeding: Key factors shaping two decades of progress. MOLECULAR PLANT 2024; 17:552-578. [PMID: 38475993 DOI: 10.1016/j.molp.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/22/2024] [Accepted: 03/08/2024] [Indexed: 03/14/2024]
Abstract
Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP-theoretically reaching one when using the Pearson's correlation as a metric-is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.
Collapse
Affiliation(s)
- Admas Alemu
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Johanna Åstrand
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden; Lantmännen Lantbruk, Svalöv, Sweden
| | | | - Julio Isidro Y Sánchez
- Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223 Madrid, Spain
| | - Javier Fernández-Gónzalez
- Centro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223 Madrid, Spain
| | - Wuletaw Tadesse
- International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco
| | - Ramesh R Vetukuri
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Anders S Carlsson
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | | | - José Crossa
- International Maize and Wheat Improvement Center (CIMMYT), Km 45, Carretera México-Veracruz, Texcoco, México 52640, Mexico
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden.
| | - Aakash Chawade
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| |
Collapse
|
6
|
Huynh BL, Stangoulis JCR, Vuong TD, Shi H, Nguyen HT, Duong T, Boukar O, Kusi F, Batieno BJ, Cisse N, Diangar MM, Awuku FJ, Attamah P, Crossa J, Pérez-Rodríguez P, Ehlers JD, Roberts PA. Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.]. Sci Rep 2024; 14:4567. [PMID: 38403625 PMCID: PMC10894872 DOI: 10.1038/s41598-024-55214-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 02/21/2024] [Indexed: 02/27/2024] Open
Abstract
Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016-2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma-optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6-6.9%) and stachyose (2.3-8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4-0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.
Collapse
Affiliation(s)
- Bao-Lam Huynh
- Department of Nematology, University of California, Riverside, CA, USA.
| | - James C R Stangoulis
- College of Science and Engineering, Flinders University, Bedford Park, SA, Australia
| | - Tri D Vuong
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri, Columbia, MO, USA
| | - Haiying Shi
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri, Columbia, MO, USA
| | - Henry T Nguyen
- Division of Plant Science and Technology and National Center for Soybean Biotechnology, University of Missouri, Columbia, MO, USA
| | - Tra Duong
- Department of Nematology, University of California, Riverside, CA, USA
| | - Ousmane Boukar
- International Institute of Tropical Agriculture, Kano, Nigeria
| | - Francis Kusi
- CSIR-Savanna Agricultural Research Institute, Tamale, Ghana
| | - Benoit J Batieno
- Institut de l'Environnement et de Recherches Agricoles, Kamboinse, Burkina Faso
| | - Ndiaga Cisse
- Institut Senegalais de Recherches Agricoles, Thies, Senegal
| | | | | | | | - José Crossa
- International Maize and Wheat Improvement Center, Mexico City, Mexico
| | | | | | - Philip A Roberts
- Department of Nematology, University of California, Riverside, CA, USA.
| |
Collapse
|
7
|
Rakotondramanana M, Wissuwa M, Ramanankaja L, Razafimbelo T, Stangoulis J, Grenier C. Stability of grain zinc concentrations across lowland rice environments favors zinc biofortification breeding. FRONTIERS IN PLANT SCIENCE 2024; 15:1293831. [PMID: 38414643 PMCID: PMC10896981 DOI: 10.3389/fpls.2024.1293831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/18/2024] [Indexed: 02/29/2024]
Abstract
Introduction One-third of the human population consumes insufficient zinc (Zn) to sustain a healthy life. Zn deficiency can be relieved by increasing the Zn concentration ([Zn]) in staple food crops through biofortification breeding. Rice is a poor source of Zn, and in countries predominantly relying on rice without sufficient dietary diversification, such as Madagascar, Zn biofortification is a priority. Methods Multi-environmental trials were performed in Madagascar over two years, 2019 and 2020, to screen a total of 28 genotypes including local and imported germplasm. The trials were conducted in the highlands of Ankazomiriotra, Anjiro, and Behenji and in Morovoay, a location representative of the coastal ecosystem. Contributions of genotype (G), environment (E), and G by E interactions (GEIs) were investigated. Result The grain [Zn] of local Malagasy rice varieties was similar to the internationally established grain [Zn] baseline of 18-20 μg/g for brown rice. While several imported breeding lines reached 50% of our breeding target set at +12 μg/g, only few met farmers' appreciation criteria. Levels of grain [Zn] were stable across E. The G effects accounted for a main fraction of the variation, 76% to 83% of the variation for year 1 and year 2 trials, respectively, while GEI effects were comparatively small, contributing 23% to 9%. This contrasted with dominant E and GEI effects for grain yield. Our results indicate that local varieties tested contained insufficient Zn to alleviate Zn malnutrition, and developing new Zn-biofortified varieties should therefore be a priority. GGE analysis did not distinguish mega-environments for grain [Zn], whereas at least three mega-environments existed for grain yield, differentiated by the presence of limiting environmental conditions and responsiveness to improved soil fertility. Discussion Our main conclusion reveals that grain [Zn] seems to be under strong genetic control in the agro-climatic conditions of Madagascar. We could identify several interesting genotypes as potential donors for the breeding program, among those BF156, with a relatively stable grain [Zn] (AMMI stability value (ASV) = 0.89) reaching our target (>26 μg/g). While selection for grain yield, general adaptation, and farmers' appreciation would have to rely on multi-environment testing, selection for grain [Zn] could be centralized in earlier generations.
Collapse
Affiliation(s)
- Mbolatantely Rakotondramanana
- Rice Research Department, The National Center for Applied Research on Rural Development (FOFIFA), Antananarivo, Madagascar
| | - Matthias Wissuwa
- Crop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Japan
- PhenoRob Cluster and Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Bonn, Germany
| | | | | | - James Stangoulis
- College of Science and Engineering, Flinders University, Bedford Park, SA, Australia
| | - Cécile Grenier
- Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP Institut), Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, Institut national de recherche pour l'agriculture, l'alimentation et l'environnement (INRAE), Institut Agro, Montpellier, France
- Alliance Bioversity-Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia
| |
Collapse
|
8
|
de Verdal H, Baertschi C, Frouin J, Quintero C, Ospina Y, Alvarez MF, Cao TV, Bartholomé J, Grenier C. Optimization of Multi-Generation Multi-location Genomic Prediction Models for Recurrent Genomic Selection in an Upland Rice Population. RICE (NEW YORK, N.Y.) 2023; 16:43. [PMID: 37758969 PMCID: PMC10533757 DOI: 10.1186/s12284-023-00661-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/19/2023] [Indexed: 09/29/2023]
Abstract
Genomic selection is a worthy breeding method to improve genetic gain in recurrent selection breeding schemes. The integration of multi-generation and multi-location information could significantly improve genomic prediction models in the context of shuttle breeding. The Cirad-CIAT upland rice breeding program applies recurrent genomic selection and seeks to optimize the scheme to increase genetic gain while reducing phenotyping efforts. We used a synthetic population (PCT27) of which S0 plants were all genotyped and advanced by selfing and bulk seed harvest to the S0:2, S0:3, and S0:4 generations. The PCT27 was then divided into two sets. The S0:2 and S0:3 progenies for PCT27A and the S0:4 progenies for PCT27B were phenotyped in two locations: Santa Rosa the target selection location, within the upland rice growing area, and Palmira, the surrogate location, far from the upland rice growing area but easier for experimentation. While the calibration used either one of the two sets phenotyped in one or two locations, the validation population was only the PCT27B phenotyped in Santa Rosa. Five scenarios of genomic prediction and 24 models were performed and compared. Training the prediction model with the PCT27B phenotyped in Santa Rosa resulted in predictive abilities ranging from 0.19 for grain zinc concentration to 0.30 for grain yield. Expanding the training set with the inclusion of the PCT27A resulted in greater predictive abilities for all traits but grain yield, with increases from 5% for plant height to 61% for grain zinc concentration. Models with the PCT27B phenotyped in two locations resulted in higher prediction accuracy when the models assumed no genotype-by-environment (G × E) interaction for flowering (0.38) and grain zinc concentration (0.27). For plant height, the model assuming a single G × E variance provided higher accuracy (0.28). The gain in predictive ability for grain yield was the greatest (0.25) when environment-specific variance deviation effect for G × E was considered. While the best scenario was specific to each trait, the results indicated that the gain in predictive ability provided by the multi-location and multi-generation calibration was low. Yet, this approach could lead to increased selection intensity, acceleration of the breeding cycle, and a sizable economic advantage for the program.
Collapse
Affiliation(s)
- Hugues de Verdal
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France.
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France.
| | - Cédric Baertschi
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France
| | - Julien Frouin
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France
| | - Constanza Quintero
- Alliance Bioversity-CIAT, A.A.6713, Km 17 Recta Palmira Cali, Cali, Colombia
| | - Yolima Ospina
- Alliance Bioversity-CIAT, A.A.6713, Km 17 Recta Palmira Cali, Cali, Colombia
| | | | - Tuong-Vi Cao
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France
| | - Jérôme Bartholomé
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France
- Alliance Bioversity-CIAT, A.A.6713, Km 17 Recta Palmira Cali, Cali, Colombia
| | - Cécile Grenier
- CIRAD, UMR AGAP Institut, 34398, Montpellier, France.
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro, 34398, Montpellier, France.
- Alliance Bioversity-CIAT, A.A.6713, Km 17 Recta Palmira Cali, Cali, Colombia.
| |
Collapse
|
9
|
Bukomarhe CB, Kimwemwe PK, Githiri SM, Mamati EG, Kimani W, Mutai C, Nganga F, Nguezet PMD, Mignouna J, Civava RM, Fofana M. Association Mapping of Candidate Genes Associated with Iron and Zinc Content in Rice ( Oryza sativa L.) Grains. Genes (Basel) 2023; 14:1815. [PMID: 37761955 PMCID: PMC10530939 DOI: 10.3390/genes14091815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
Micronutrient deficiencies, particularly of iron (Fe) and zinc (Zn), in the diet contribute to health issues and hidden hunger. Enhancing the Fe and Zn content in globally staple food crops like rice is necessary to address food malnutrition. A Genome-Wide Association Study (GWAS) was conducted using 85 diverse rice accessions from the Democratic Republic of Congo (DRC) to identify genomic regions associated with grain Fe and Zn content. The Fe content ranged from 0.95 to 8.68 mg/100 g on a dry weight basis (dwb) while Zn content ranged from 0.87 to 3.8 mg/100 g (dwb). Using MLM and FarmCPU models, we found 10 significant SNPs out of which one SNP on chromosome 11 was associated with the variation in Fe content and one SNP on chromosome 4 was associated with the Zn content, and both were commonly detected by the two models. Candidate genes belonging to transcription regulator activities, including the bZIP family genes and MYB family genes, as well as transporter activities involved in Fe and Zn homeostasis were identified in the vicinity of the SNP markers and selected. The identified SNP markers hold promise for marker-assisted selection in rice breeding programs aimed at enhancing Fe and Zn content in rice. This study provides valuable insights into the genetic factors controlling Fe and Zn uptake and their transport and accumulation in rice, offering opportunities for developing biofortified rice varieties to combat malnutrition among rice consumers.
Collapse
Affiliation(s)
- Chance Bahati Bukomarhe
- Department of Horticulture and Food Security, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi P.O. Box 62000-00200, Kenya; (P.K.K.); (S.M.G.); (E.G.M.)
- Olusegun O. Research Campus, International Institute of Tropical Agriculture (IITA), Bukavu P.O. Box 1222, Democratic Republic of the Congo; (J.M.); (M.F.)
- Institut National Pour l’Etude et la Recherche Agronomiques (INERA), Kinshasa P.O. Box 2037, Democratic Republic of the Congo;
| | - Paul Kitenge Kimwemwe
- Department of Horticulture and Food Security, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi P.O. Box 62000-00200, Kenya; (P.K.K.); (S.M.G.); (E.G.M.)
- Olusegun O. Research Campus, International Institute of Tropical Agriculture (IITA), Bukavu P.O. Box 1222, Democratic Republic of the Congo; (J.M.); (M.F.)
- Institut National Pour l’Etude et la Recherche Agronomiques (INERA), Kinshasa P.O. Box 2037, Democratic Republic of the Congo;
- Faculty of Agriculture and Environmental Sciences, Université de Kalemie (UNIKAL), Kalemie P.O. Box 570, Democratic Republic of the Congo
| | - Stephen Mwangi Githiri
- Department of Horticulture and Food Security, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi P.O. Box 62000-00200, Kenya; (P.K.K.); (S.M.G.); (E.G.M.)
| | - Edward George Mamati
- Department of Horticulture and Food Security, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi P.O. Box 62000-00200, Kenya; (P.K.K.); (S.M.G.); (E.G.M.)
| | - Wilson Kimani
- International Livestock Research Institute (ILRI), Nairobi P.O. Box 30709-00100, Kenya; (C.M.); (F.N.)
| | - Collins Mutai
- International Livestock Research Institute (ILRI), Nairobi P.O. Box 30709-00100, Kenya; (C.M.); (F.N.)
| | - Fredrick Nganga
- International Livestock Research Institute (ILRI), Nairobi P.O. Box 30709-00100, Kenya; (C.M.); (F.N.)
| | - Paul-Martin Dontsop Nguezet
- International Institute of Tropical Agriculture (IITA), Kalemie P.O. Box 570, Democratic Republic of the Congo;
| | - Jacob Mignouna
- Olusegun O. Research Campus, International Institute of Tropical Agriculture (IITA), Bukavu P.O. Box 1222, Democratic Republic of the Congo; (J.M.); (M.F.)
| | - René Mushizi Civava
- Institut National Pour l’Etude et la Recherche Agronomiques (INERA), Kinshasa P.O. Box 2037, Democratic Republic of the Congo;
- Faculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu P.O. Box 3323, Democratic Republic of the Congo
| | - Mamadou Fofana
- Olusegun O. Research Campus, International Institute of Tropical Agriculture (IITA), Bukavu P.O. Box 1222, Democratic Republic of the Congo; (J.M.); (M.F.)
| |
Collapse
|
10
|
Palanog AD, Nha CT, Descalsota-Empleo GIL, Calayugan MI, Swe ZM, Amparado A, Inabangan-Asilo MA, Hernandez JE, Sta. Cruz PC, Borromeo TH, Lalusin AG, Mauleon R, McNally KL, Swamy BPM. Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits. FRONTIERS IN PLANT SCIENCE 2023; 14:1157507. [PMID: 37035067 PMCID: PMC10073715 DOI: 10.3389/fpls.2023.1157507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 02/20/2023] [Indexed: 06/19/2023]
Abstract
Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1 , and qGW6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.
Collapse
Affiliation(s)
- Alvin D. Palanog
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
- PhilRice Negros Branch Station, Philippine Rice Research Institute, Murcia, Negros Occidental, Philippines
| | | | | | - Mark Ian Calayugan
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
| | - Zin Mar Swe
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| | - Amery Amparado
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| | - Mary Ann Inabangan-Asilo
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| | - Jose E. Hernandez
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
| | - Pompe C. Sta. Cruz
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
| | - Teresita H. Borromeo
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
| | - Antonio G. Lalusin
- College of Agriculture and Food Science, University of the Philippines, Los Baños, Laguna, Philippines
| | - Ramil Mauleon
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
- College of Agriculture, University of Southern Mindanao, Kabacan, North Cotabato, Philippines
| | - Kenneth L. McNally
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| | - B. P. Mallikarjuna Swamy
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| |
Collapse
|
11
|
Tsakirpaloglou N, Bueno-Mota GM, Soriano JC, Arcillas E, Arines FM, Yu SM, Stangoulis J, Trijatmiko KR, Reinke R, Tohme J, Bouis H, Slamet-Loedin IH. Proof of concept and early development stage of market-oriented high iron and zinc rice expressing dicot ferritin and rice nicotianamine synthase genes. Sci Rep 2023; 13:676. [PMID: 36635301 PMCID: PMC9837094 DOI: 10.1038/s41598-022-26854-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 12/21/2022] [Indexed: 01/14/2023] Open
Abstract
Micronutrient deficiencies such as iron (Fe), zinc (Zn), and vitamin A, constitute a severe global public health phenomenon. Over half of preschool children and two-thirds of nonpregnant women of reproductive age worldwide have micronutrient deficiencies. Biofortification is a cost-effective strategy that comprises a meaningful and sustainable means of addressing this issue by delivering micronutrients through staple foods to populations with limited access to diverse diets and other nutritional interventions. Here, we report on the proof-of-concept and early development stage of a collection of biofortified rice events with a high density of Fe and Zn in polished grains that have been pursued further to advance development for product release. In total, eight constructs were developed specifically expressing dicot ferritins and the rice nicotianamine synthase 2 (OsNAS2) gene under different combinations of promoters. A large-scale transformation of these constructs to Bangladesh and Philippines commercial indica cultivars and subsequent molecular screening and confined field evaluations resulted in the identification of a pool of ten events with Fe and Zn concentrations in polished grains of up to 11 μg g-1 and up to 37 μg g-1, respectively. The latter has the potential to reduce the prevalence of inadequate Zn intake for women of childbearing age in Bangladesh and in the Philippines by 30% and 50%, respectively, compared to the current prevalence. To our knowledge, this is the first potential biotechnology public-sector product that adopts the product cycle phase-gated approach, routinely applied in the private sector.
Collapse
Affiliation(s)
- Nikolaos Tsakirpaloglou
- International Rice Research Institute (IRRI), Metro Manila, The Philippines.
- Crop Genome Editing Laboratory (CGEL), Soil and Crop Sciences Department, Texas A&M University and Texas A&M AgriLife Research, College Station, TX, USA.
| | | | | | - Erwin Arcillas
- International Rice Research Institute (IRRI), Metro Manila, The Philippines
| | - Felichi Mae Arines
- International Rice Research Institute (IRRI), Metro Manila, The Philippines
- Board Institute of MIT and Harvard, Cambridge, MA, USA
| | - Su-May Yu
- Institute of Molecular Biology, Academia Sinica, Naknag, Taipei, Taiwan, ROC
| | - James Stangoulis
- College of Science and Engineering, Flinders University, Bedford Park, SA, Australia
| | | | - Russell Reinke
- International Rice Research Institute (IRRI), Metro Manila, The Philippines
| | - Joseph Tohme
- Bioversity International and International Center for Tropical Agriculture (CIAT) Alliance, Cali, Colombia
| | - Howarth Bouis
- International Food Policy Research Institute (IFPRI) - Emeritus Fellow, Washington, DC, USA
| | | |
Collapse
|
12
|
Roy C, Kumar S, Ranjan RD, Kumhar SR, Govindan V. Genomic approaches for improving grain zinc and iron content in wheat. Front Genet 2022; 13:1045955. [PMID: 36437911 PMCID: PMC9683485 DOI: 10.3389/fgene.2022.1045955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 10/24/2022] [Indexed: 09/29/2023] Open
Abstract
More than three billion people worldwide suffer from iron deficiency associated anemia and an equal number people suffer from zinc deficiency. These conditions are more prevalent in Sub-Saharan Africa and South Asia. In developing countries, children under the age of five with stunted growth and pregnant or lactating women were found to be at high risk of zinc and iron deficiencies. Biofortification, defined as breeding to develop varieties of staple food crops whose grain contains higher levels of micronutrients such as iron and zinc, are one of the most promising, cost-effective and sustainable ways to improve the health in resource-poor households, particularly in rural areas where families consume some part of what they grow. Biofortification through conventional breeding in wheat, particularly for grain zinc and iron, have made significant contributions, transferring important genes and quantitative trait loci (QTLs) from wild and related species into cultivated wheat. Nonetheless, the quantitative, genetically complex nature of iron and zinc levels in wheat grain limits progress through conventional breeding, making it difficult to attain genetic gain both for yield and grain mineral concentrations. Wheat biofortification can be achieved by enhancing mineral uptake, source-to-sink translocation of minerals and their deposition into grains, and the bioavailability of the minerals. A number of QTLs with major and minor effects for those traits have been detected in wheat; introducing the most effective into breeding lines will increase grain zinc and iron concentrations. New approaches to achieve this include marker assisted selection and genomic selection. Faster breeding approaches need to be combined to simultaneously increase grain mineral content and yield in wheat breeding lines.
Collapse
Affiliation(s)
- Chandan Roy
- Department of Genetics and Plant Breeding, Agriculture University, Jodhpur, Rajasthan, India
| | - Sudhir Kumar
- Department of Plant Breeding and Genetics, Bihar Agricultural University, Bhagalpur, Bihar, India
| | - Rakesh Deo Ranjan
- Department of Plant Breeding and Genetics, Bihar Agricultural University, Bhagalpur, Bihar, India
| | - Sita Ram Kumhar
- Department of Genetics and Plant Breeding, Agriculture University, Jodhpur, Rajasthan, India
| | - Velu Govindan
- International Maize and Wheat Improvement Center (CIMMYT), Mexico City, Mexico
| |
Collapse
|