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Dong Y, Li G, Zhang X, Feng Z, Li T, Li Z, Xu S, Xu S, Liu W, Xue J. Genome-Wide Association Study for Maize Hybrid Performance in a Typical Breeder Population. Int J Mol Sci 2024; 25:1190. [PMID: 38256265 PMCID: PMC10816832 DOI: 10.3390/ijms25021190] [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: 11/28/2023] [Revised: 01/14/2024] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Maize is one of the major crops that has demonstrated success in the utilization of heterosis. Developing high-yield hybrids is a crucial part of plant breeding to secure global food demand. In this study, we conducted a genome-wide association study (GWAS) for 10 agronomic traits using a typical breeder population comprised 442 single-cross hybrids by evaluating additive, dominance, and epistatic effects. A total of 49 significant single nucleotide polymorphisms (SNPs) and 69 significant pairs of epistasis were identified, explaining 26.2% to 64.3% of the phenotypic variation across the 10 traits. The enrichment of favorable genotypes is significantly correlated to the corresponding phenotype. In the confident region of the associated site, 532 protein-coding genes were discovered. Among these genes, the Zm00001d044211 candidate gene was found to negatively regulate starch synthesis and potentially impact yield. This typical breeding population provided a valuable resource for dissecting the genetic architecture of yield-related traits. We proposed a novel mating strategy to increase the GWAS efficiency without utilizing more resources. Finally, we analyzed the enrichment of favorable alleles in the Shaan A and Shaan B groups, as well as in each inbred line. Our breeding practice led to consistent results. Not only does this study demonstrate the feasibility of GWAS in F1 hybrid populations, it also provides a valuable basis for further molecular biology and breeding research.
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Affiliation(s)
- Yuan Dong
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Guoliang Li
- National Maize Improvement Center of China, Key Laboratory of Crop Heterosis and Utilization (MOE), China Agricultural University, Beijing 100193, China
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, 06466 Seeland, Germany
| | - Xinghua Zhang
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Zhiqian Feng
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Ting Li
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Zhoushuai Li
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Shizhong Xu
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Shutu Xu
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Wenxin Liu
- National Maize Improvement Center of China, Key Laboratory of Crop Heterosis and Utilization (MOE), China Agricultural University, Beijing 100193, China
| | - Jiquan Xue
- Key Laboratory of Biology and Genetic Breeding of Maize in Arid Area of Northwest Region, College of Agronomy, Northwest A&F University, Yangling 712100, China
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Qian F, Jing J, Zhang Z, Chen S, Sang Z, Li W. GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize. PLANTS (BASEL, SWITZERLAND) 2023; 12:3806. [PMID: 38005703 PMCID: PMC10674677 DOI: 10.3390/plants12223806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/31/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023]
Abstract
Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield.
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Affiliation(s)
- Fu Qian
- Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China; (F.Q.); (Z.Z.); (S.C.)
- The Key Laboratory of Oasis Eco-Agriculture, College of Agriculture, Shihezi University, Shihezi 832003, China;
| | - Jianguo Jing
- The Key Laboratory of Oasis Eco-Agriculture, College of Agriculture, Shihezi University, Shihezi 832003, China;
| | - Zhanqin Zhang
- Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China; (F.Q.); (Z.Z.); (S.C.)
| | - Shubin Chen
- Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China; (F.Q.); (Z.Z.); (S.C.)
| | - Zhiqin Sang
- Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832000, China; (F.Q.); (Z.Z.); (S.C.)
| | - Weihua Li
- The Key Laboratory of Oasis Eco-Agriculture, College of Agriculture, Shihezi University, Shihezi 832003, China;
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