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Liu Y, Li H, Liu J, Wang Y, Jiang C, Zhou Z, Zhuo L, Li W, Fernie AR, Jackson D, Yan J, Luo Y. The additive function of YIGE2 and YIGE1 in regulating maize ear length. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024. [PMID: 38804053 DOI: 10.1111/tpj.16851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/29/2024]
Abstract
Ear length (EL) is a key trait that greatly contributes to yield in maize. Although dozens of EL quantitative trait loci have been mapped, very few causal genes have been cloned, and the molecular mechanisms remain largely unknown. Our previous study showed that YIGE1 is involved in sugar and auxin pathways to regulate ear inflorescence meristem (IM) development and thus affects EL in maize. Here, we reveal that YIGE2, the paralog of YIGE1, regulates maize ear development and EL through auxin pathway. Knockout of YIGE2 causes a significant decrease of auxin level, IM length, floret number, EL, and grain yield. yige1 yige2 double mutants had even shorter IM and ears implying that these two genes redundantly regulate IM development and EL. The genes controlling auxin levels are differential expressed in yige1 yige2 double mutants, leading to lower auxin level. These results elucidated the critical role of YIGE2 and the redundancy between YIGE2 and YIGE1 in maize ear development, providing a new genetic resource for maize yield improvement.
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Affiliation(s)
- Yu Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Huinan Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Jie Liu
- Yazhouwan National Laboratory, Sanya, 572024, China
| | - Yuebin Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Chenglin Jiang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Ziqi Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Lin Zhuo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Wenqiang Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
| | - Alisdair R Fernie
- Department of Molecular Physiology, Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm, 14476, Germany
| | - David Jackson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, 11724, USA
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
- Yazhouwan National Laboratory, Sanya, 572024, China
| | - Yun Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
- Hubei Hongshan Laboratory, Wuhan, 430070, China
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Zhang X, Sun J, Zhang Y, Li J, Liu M, Li L, Li S, Wang T, Shaw RK, Jiang F, Fan X. Hotspot Regions of Quantitative Trait Loci and Candidate Genes for Ear-Related Traits in Maize: A Literature Review. Genes (Basel) 2023; 15:15. [PMID: 38275597 PMCID: PMC10815758 DOI: 10.3390/genes15010015] [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: 11/10/2023] [Revised: 12/12/2023] [Accepted: 12/16/2023] [Indexed: 01/27/2024] Open
Abstract
In this study, hotspot regions, QTL clusters, and candidate genes for eight ear-related traits of maize (ear length, ear diameter, kernel row number, kernel number per row, kernel length, kernel width, kernel thickness, and 100-kernel weight) were summarized and analyzed over the past three decades. This review aims to (1) comprehensively summarize and analyze previous studies on QTLs associated with these eight ear-related traits and identify hotspot bin regions located on maize chromosomes and key candidate genes associated with the ear-related traits and (2) compile major and stable QTLs and QTL clusters from various mapping populations and mapping methods and techniques providing valuable insights for fine mapping, gene cloning, and breeding for high-yield and high-quality maize. Previous research has demonstrated that QTLs for ear-related traits are distributed across all ten chromosomes in maize, and the phenotypic variation explained by a single QTL ranged from 0.40% to 36.76%. In total, 23 QTL hotspot bins for ear-related traits were identified across all ten chromosomes. The most prominent hotspot region is bin 4.08 on chromosome 4 with 15 QTLs related to eight ear-related traits. Additionally, this study identified 48 candidate genes associated with ear-related traits. Out of these, five have been cloned and validated, while twenty-eight candidate genes located in the QTL hotspots were defined by this study. This review offers a deeper understanding of the advancements in QTL mapping and the identification of key candidates associated with eight ear-related traits. These insights will undoubtedly assist maize breeders in formulating strategies to develop higher-yield maize varieties, contributing to global food security.
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Affiliation(s)
- Xingjie Zhang
- School of Agriculture, Yunnan University, Kunming 650500, China; (X.Z.); (J.L.); (M.L.); (L.L.); (S.L.)
| | - Jiachen Sun
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, China; (J.S.); (T.W.)
| | - Yudong Zhang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China; (Y.Z.); (R.K.S.); (F.J.)
| | - Jinfeng Li
- School of Agriculture, Yunnan University, Kunming 650500, China; (X.Z.); (J.L.); (M.L.); (L.L.); (S.L.)
| | - Meichen Liu
- School of Agriculture, Yunnan University, Kunming 650500, China; (X.Z.); (J.L.); (M.L.); (L.L.); (S.L.)
| | - Linzhuo Li
- School of Agriculture, Yunnan University, Kunming 650500, China; (X.Z.); (J.L.); (M.L.); (L.L.); (S.L.)
| | - Shaoxiong Li
- School of Agriculture, Yunnan University, Kunming 650500, China; (X.Z.); (J.L.); (M.L.); (L.L.); (S.L.)
| | - Tingzhao Wang
- College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, China; (J.S.); (T.W.)
| | - Ranjan Kumar Shaw
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China; (Y.Z.); (R.K.S.); (F.J.)
| | - Fuyan Jiang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China; (Y.Z.); (R.K.S.); (F.J.)
| | - Xingming Fan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming 650205, China; (Y.Z.); (R.K.S.); (F.J.)
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Li T, Yang H, Zhang X, Zhu L, Zhang J, Wei N, Li R, Dong Y, Feng Z, Zhang X, Xue J, Xu S. Genetic architecture of ear traits based on association mapping and co-expression networks in maize inbred lines and hybrids. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:78. [PMID: 37928364 PMCID: PMC10624778 DOI: 10.1007/s11032-023-01426-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/23/2023] [Indexed: 11/07/2023]
Abstract
Ear traits are key contributors to grain yield in maize; therefore, exploring their genetic basis facilitates the improvement of grain yield. However, the underlying molecular mechanisms of ear traits remain obscure in both inbred lines and hybrids. Here, two association panels, respectively, comprising 203 inbred lines (IP) and 246 F1 hybrids (HP) were employed to identify candidate genes for six ear traits. The IP showed higher phenotypic variation and lower phenotypic mean than the HP for all traits, except ear tip-barrenness length. By conducting a genome-wide association study (GWAS) across multiple environments, 101 and 228 significant single-nucleotide polymorphisms (SNPs) associated with six ear traits were identified in the IP and HP, respectively. Of these significant SNPs identified in the HP, most showed complete-incomplete dominance and over-dominance effects for each ear trait. Combining a gene co-expression network with GWAS results, 186 and 440 candidate genes were predicted in the IP and HP, respectively, including known ear development genes ids1 and sid1. Of these, nine candidate genes were detected in both populations and expressed in maize ear and spikelet tissues. Furthermore, two key shared genes (GRMZM2G143330 and GRMZM2G171139) in both populations were found to be significantly associated with ear traits in the maize Goodman diversity panel with high-density variations. These findings advance our knowledge of the genetic architecture of ear traits between inbred lines and hybrids and provide a valuable resource for the genetic improvement of ear traits in maize. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01426-9.
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Affiliation(s)
- Ting Li
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Haoxiang Yang
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Xiaojun Zhang
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Liangjia Zhu
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Jun Zhang
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Ningning Wei
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Ranran Li
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Yuan Dong
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Zhiqian Feng
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Xinghua Zhang
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Jiquan Xue
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
| | - Shutu Xu
- The Key Laboratory of Biology and Genetics Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, 712100 Shaanxi China
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Wang J, Zhao S, Zhang Y, Lu X, Du J, Wang C, Wen W, Guo X, Zhao C. Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system. FRONTIERS IN PLANT SCIENCE 2023; 14:1248446. [PMID: 37701799 PMCID: PMC10493325 DOI: 10.3389/fpls.2023.1248446] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/09/2023] [Indexed: 09/14/2023]
Abstract
The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears.
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Affiliation(s)
- Jinglu Wang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Shuaihao Zhao
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Ying Zhang
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Xianju Lu
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jianjun Du
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Chuanyu Wang
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Weiliang Wen
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Xinyu Guo
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Chunjiang Zhao
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- National Engineering Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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Dong Z, Wang Y, Bao J, Li Y, Yin Z, Long Y, Wan X. The Genetic Structures and Molecular Mechanisms Underlying Ear Traits in Maize ( Zea mays L.). Cells 2023; 12:1900. [PMID: 37508564 PMCID: PMC10378120 DOI: 10.3390/cells12141900] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Maize (Zea mays L.) is one of the world's staple food crops. In order to feed the growing world population, improving maize yield is a top priority for breeding programs. Ear traits are important determinants of maize yield, and are mostly quantitatively inherited. To date, many studies relating to the genetic and molecular dissection of ear traits have been performed; therefore, we explored the genetic loci of the ear traits that were previously discovered in the genome-wide association study (GWAS) and quantitative trait locus (QTL) mapping studies, and refined 153 QTL and 85 quantitative trait nucleotide (QTN) clusters. Next, we shortlisted 19 common intervals (CIs) that can be detected simultaneously by both QTL mapping and GWAS, and 40 CIs that have pleiotropic effects on ear traits. Further, we predicted the best possible candidate genes from 71 QTL and 25 QTN clusters that could be valuable for maize yield improvement.
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Affiliation(s)
- Zhenying Dong
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
| | - Yanbo Wang
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Jianxi Bao
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Ya’nan Li
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Zechao Yin
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Yan Long
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
| | - Xiangyuan Wan
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
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Xu Y, Wang R, Ma P, Cao J, Cao Y, Zhou Z, Li T, Wu J, Zhang H. A novel maize microRNA negatively regulates resistance to Fusarium verticillioides. MOLECULAR PLANT PATHOLOGY 2022; 23:1446-1460. [PMID: 35700097 PMCID: PMC9452762 DOI: 10.1111/mpp.13240] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 05/02/2022] [Accepted: 05/25/2022] [Indexed: 05/21/2023]
Abstract
Although microRNAs (miRNAs) regulate the defence response against multiple pathogenic fungi in diverse plant species, few efforts have been devoted to deciphering the involvement of miRNA in resistance to Fusarium verticillioides, a major pathogenic fungus affecting maize production. In this study, we discovered a novel F. verticillioides-responsive miRNA designated zma-unmiR4 in maize kernels. The expression of zma-unmiR4 was significantly repressed in the resistant maize line but induced in the susceptible lines upon exposure to F. verticillioides exposure, whereas its target gene ZmGA2ox4 exhibited the opposite pattern of expression. Heterologous overexpression of zma-unmiR4 in Arabidopsis resulted in enhanced growth and compromised resistance to F. verticillioides. By contrast, transgenic plants overexpressing ZmGA2ox4 or the homologue AtGA2ox7 showed impaired growth and enhanced resistance to F. verticillioides. Moreover, zma-unmiR4-mediated suppression of AtGA2ox7 disturbed the accumulation of bioactive gibberellin (GA) in transgenic plants and perturbed the expression of a set of defence-related genes in response to F. verticillioides. Exogenous application of GA or a GA biosynthesis inhibitor modulated F. verticillioides resistance in different plants. Taken together, our results suggest that the zma-unmiR4-ZmGA2ox4 module might act as a major player in balancing growth and resistance to F. verticillioides in maize.
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Affiliation(s)
- Yufang Xu
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Renjie Wang
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Peipei Ma
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Jiansheng Cao
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Yan Cao
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Zijian Zhou
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Tao Li
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
| | - Jianyu Wu
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
- State Key Laboratory of Wheat and Maize Crop Science, Collaborative Innovation Center of Henan Grain CropsHenan Agricultural UniversityZhengzhouChina
| | - Huiyong Zhang
- College of Life SciencesHenan Agricultural UniversityZhengzhouChina
- State Key Laboratory of Wheat and Maize Crop Science, Collaborative Innovation Center of Henan Grain CropsHenan Agricultural UniversityZhengzhouChina
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Ma P, Li H, Liu E, He K, Song Y, Dong C, Wang Z, Zhang X, Zhou Z, Xu Y, Wu J, Zhang H. Evaluation and Identification of Resistance Lines and QTLs of Maize to Seedborne Fusarium verticillioides. PLANT DISEASE 2022; 106:2066-2073. [PMID: 35259305 DOI: 10.1094/pdis-10-21-2247-re] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Internal fungal contamination in cereal grains may affect plant growth and result in health concerns for humans and animals. Fusarium verticillioides is a seedborne fungus that can systemically infect maize. However, few efforts had been devoted to studying the genetics of maize resistance to seedborne F. verticillioides. In this study, we developed a disease evaluation method to identify resistance to seedborne F. verticillioides in maize, by which a set of 121 diverse maize inbred lines were evaluated. A 160 F10-generation recombinant inbred line (RIL) population derived from a cross of the resistant (BT-1) and susceptible (N6) inbred line was further used to identify major quantitative trait loci (QTLs) for seedborne F. verticillioides resistance. Eighteen inbred lines with a high resistance to seedborne F. verticillioides were characterized and could be used as potential germplasm resources for genetic improvement of maize resistance. Six QTLs with high heritability across multiple environments were detected on chromosomes 3, 4, 6, and 10, among which was a major QTL, qISFR4-1. Located on chromosome 4 at the interval of 12922609-13418025, qISFR4-1 could explain 16.63% of the total phenotypic variance. Distinct expression profiles of eight candidate genes in qISFR4-1 between BT-1 and N6 inbred lines suggested their pivotal regulatory roles in seedborne F. verticillioides resistance. Taken together, these results will improve our understanding of the resistant mechanisms of seedborne F. verticillioides and would provide valuable germplasm resources for disease resistance breeding in maize.
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Affiliation(s)
- Peipei Ma
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
- College of Agronomy, Synergetic Innovation Center of Henan Grain Crops and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou 450002, China
| | - Haojie Li
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Enpeng Liu
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Kewei He
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Yunxia Song
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Chaopei Dong
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Zhao Wang
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Xuecai Zhang
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), 06600 Mexico DF, Mexico
| | - Zijian Zhou
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Yufang Xu
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
| | - Jianyu Wu
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
- College of Agronomy, Synergetic Innovation Center of Henan Grain Crops and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou 450002, China
| | - Huiyong Zhang
- College of Life Sciences, Henan Agricultural University, Zhengzhou 450002, China
- College of Agronomy, Synergetic Innovation Center of Henan Grain Crops and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou 450002, China
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