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Liu G, Qiu D, Lu Y, Wu Y, Han X, Jiao Y, Wang T, Yang J, You A, Chen J, Zhang Z. Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice ( Oryza sativa L.). Genes (Basel) 2023; 14:2201. [PMID: 38137023 PMCID: PMC10742856 DOI: 10.3390/genes14122201] [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: 11/01/2023] [Revised: 12/06/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.
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Affiliation(s)
- Gang Liu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Dongfeng Qiu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yuxia Lu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yan Wu
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
- Hubei Hongshan Laboratory, Wuhan 430070, China
| | - Xuesong Han
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Yaru Jiao
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Tingbao Wang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Jinsong Yang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Aiqing You
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
| | - Jianguo Chen
- School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Zaijun Zhang
- Key Laboratory of Crop Molecular Breeding, Ministry of Agriculture and Rural Affairs/Hubei Key Laboratory of Food Crop Germplasm and Genetic Improvement, Institute of Food Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China; (G.L.); (D.Q.); (Y.L.); (Y.W.); (X.H.); (Y.J.); (T.W.); (J.Y.); (A.Y.)
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Wang Y, Liu H, Meng Y, Liu J, Ye G. Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes. FRONTIERS IN PLANT SCIENCE 2023; 14:1194119. [PMID: 37324692 PMCID: PMC10267709 DOI: 10.3389/fpls.2023.1194119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 05/02/2023] [Indexed: 06/17/2023]
Abstract
Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.
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Affiliation(s)
- Yamei Wang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- School of Agriculture, Sun Yat-sen University, Shenzhen, China
| | - Hongyan Liu
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Yun Meng
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Sanya Nanfan Research Institute of Hainan University, Hainan University, Sanya, China
| | - Jindong Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Guoyou Ye
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Strategic Innovation Platform, International Rice Research Institute, Manila, Philippines
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Dwivedi SL, Garcia-Oliveira AL, Govindaraj M, Ortiz R. Biofortification to avoid malnutrition in humans in a changing climate: Enhancing micronutrient bioavailability in seed, tuber, and storage roots. FRONTIERS IN PLANT SCIENCE 2023; 14:1119148. [PMID: 36794214 PMCID: PMC9923027 DOI: 10.3389/fpls.2023.1119148] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 01/12/2023] [Indexed: 06/18/2023]
Abstract
Malnutrition results in enormous socio-economic costs to the individual, their community, and the nation's economy. The evidence suggests an overall negative impact of climate change on the agricultural productivity and nutritional quality of food crops. Producing more food with better nutritional quality, which is feasible, should be prioritized in crop improvement programs. Biofortification refers to developing micronutrient -dense cultivars through crossbreeding or genetic engineering. This review provides updates on nutrient acquisition, transport, and storage in plant organs; the cross-talk between macro- and micronutrients transport and signaling; nutrient profiling and spatial and temporal distribution; the putative and functionally characterized genes/single-nucleotide polymorphisms associated with Fe, Zn, and β-carotene; and global efforts to breed nutrient-dense crops and map adoption of such crops globally. This article also includes an overview on the bioavailability, bioaccessibility, and bioactivity of nutrients as well as the molecular basis of nutrient transport and absorption in human. Over 400 minerals (Fe, Zn) and provitamin A-rich cultivars have been released in the Global South. Approximately 4.6 million households currently cultivate Zn-rich rice and wheat, while ~3 million households in sub-Saharan Africa and Latin America benefit from Fe-rich beans, and 2.6 million people in sub-Saharan Africa and Brazil eat provitamin A-rich cassava. Furthermore, nutrient profiles can be improved through genetic engineering in an agronomically acceptable genetic background. The development of "Golden Rice" and provitamin A-rich dessert bananas and subsequent transfer of this trait into locally adapted cultivars are evident, with no significant change in nutritional profile, except for the trait incorporated. A greater understanding of nutrient transport and absorption may lead to the development of diet therapy for the betterment of human health.
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Affiliation(s)
| | - Ana Luísa Garcia-Oliveira
- International Maize and Wheat Research Center, Centro Internacional de Mejoramiento de Maíz. y Trigo (CIMMYT), Nairobi, Kenya
- Department of Molecular Biology, College of Biotechnology, CCS Haryana Agricultural University, Hissar, India
| | - Mahalingam Govindaraj
- HarvestPlus Program, Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Rodomiro Ortiz
- Swedish University of Agricultural Sciences, Lomma, Sweden
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Muvunyi BP, Zou W, Zhan J, He S, Ye G. Multi-Trait Genomic Prediction Models Enhance the Predictive Ability of Grain Trace Elements in Rice. Front Genet 2022; 13:883853. [PMID: 35812754 PMCID: PMC9257107 DOI: 10.3389/fgene.2022.883853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/05/2022] [Indexed: 11/13/2022] Open
Abstract
Multi-trait (MT) genomic prediction models enable breeders to save phenotyping resources and increase the prediction accuracy of unobserved target traits by exploiting available information from non-target or auxiliary traits. Our study evaluated different MT models using 250 rice accessions from Asian countries genotyped and phenotyped for grain content of zinc (Zn), iron (Fe), copper (Cu), manganese (Mn), and cadmium (Cd). The predictive performance of MT models compared to a traditional single trait (ST) model was assessed by 1) applying different cross-validation strategies (CV1, CV2, and CV3) inferring varied phenotyping patterns and budgets; 2) accounting for local epistatic effects along with the main additive effect in MT models; and 3) using a selective marker panel composed of trait-associated SNPs in MT models. MT models were not statistically significantly (p < 0.05) superior to ST model under CV1, where no phenotypic information was available for the accessions in the test set. After including phenotypes from auxiliary traits in both training and test sets (MT-CV2) or simply in the test set (MT-CV3), MT models significantly (p < 0.05) outperformed ST model for all the traits. The highest increases in the predictive ability of MT models relative to ST models were 11.1% (Mn), 11.5 (Cd), 33.3% (Fe), 95.2% (Cu) and 126% (Zn). Accounting for the local epistatic effects using a haplotype-based model further improved the predictive ability of MT models by 4.6% (Cu), 3.8% (Zn), and 3.5% (Cd) relative to MT models with only additive effects. The predictive ability of the haplotype-based model was not improved after optimizing the marker panel by only considering the markers associated with the traits. This study first assessed the local epistatic effects and marker optimization strategies in the MT genomic prediction framework and then illustrated the power of the MT model in predicting trace element traits in rice for the effective use of genetic resources to improve the nutritional quality of rice grain.
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Affiliation(s)
- Blaise Pascal Muvunyi
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Wenli Zou
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Junhui Zhan
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Sang He
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- *Correspondence: Sang He, ; Guoyou Ye,
| | - Guoyou Ye
- CAAS-IRRI Joint Laboratory for Genomics-Assisted Germplasm Enhancement, Agricultural Genomics Institute in Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Rice Breeding Innovations Platform, International Rice Research Institute, Los Baños, Philippines
- *Correspondence: Sang He, ; Guoyou Ye,
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