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Dwivedi SL, Heslop-Harrison P, Amas J, Ortiz R, Edwards D. Epistasis and pleiotropy-induced variation for plant breeding. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 38875130 DOI: 10.1111/pbi.14405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 05/07/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.
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Affiliation(s)
| | - Pat Heslop-Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- Department of Genetics and Genome Biology, Institute for Environmental Futures, University of Leicester, Leicester, UK
| | - Junrey Amas
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - David Edwards
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
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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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