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Gélinas Bélanger J, Copley TR, Hoyos-Villegas V, O'Donoughue L. Dissection of the E8 locus in two early maturing Canadian soybean populations. FRONTIERS IN PLANT SCIENCE 2024; 15:1329065. [PMID: 38390301 PMCID: PMC10881665 DOI: 10.3389/fpls.2024.1329065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/15/2024] [Indexed: 02/24/2024]
Abstract
Soybean [Glycine max (L.) Merr.] is a short-day crop for which breeders want to expand the cultivation range to more northern agro-environments by introgressing alleles involved in early reproductive traits. To do so, we investigated quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) regions comprised within the E8 locus, a large undeciphered region (~7.0 Mbp to 44.5 Mbp) associated with early maturity located on chromosome GM04. We used a combination of two mapping algorithms, (i) inclusive composite interval mapping (ICIM) and (ii) genome-wide composite interval mapping (GCIM), to identify major and minor regions in two soybean populations (QS15524F2:F3 and QS15544RIL) having fixed E1, E2, E3, and E4 alleles. Using this approach, we identified three main QTL regions with high logarithm of the odds (LODs), phenotypic variation explained (PVE), and additive effects for maturity and pod-filling within the E8 region: GM04:16,974,874-17,152,230 (E8-r1); GM04:35,168,111-37,664,017 (E8-r2); and GM04:41,808,599-42,376,237 (E8-r3). Using a five-step variant analysis pipeline, we identified Protein far-red elongated hypocotyl 3 (Glyma.04G124300; E8-r1), E1-like-a (Glyma.04G156400; E8-r2), Light-harvesting chlorophyll-protein complex I subunit A4 (Glyma.04G167900; E8-r3), and Cycling dof factor 3 (Glyma.04G168300; E8-r3) as the most promising candidate genes for these regions. A combinatorial eQTL mapping approach identified significant regulatory interactions for 13 expression traits (e-traits), including Glyma.04G050200 (Early flowering 3/E6 locus), with the E8-r3 region. Four other important QTL regions close to or encompassing major flowering genes were also detected on chromosomes GM07, GM08, and GM16. In GM07:5,256,305-5,404,971, a missense polymorphism was detected in the candidate gene Glyma.07G058200 (Protein suppressor of PHYA-105). These findings demonstrate that the locus known as E8 is regulated by at least three distinct genomic regions, all of which comprise major flowering genes.
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Affiliation(s)
- Jérôme Gélinas Bélanger
- Centre de recherche sur les grains (CÉROM) Inc., St-Mathieu-de-Beloeil, QC, Canada
- Department of Plant Science, McGill University, Montréal, QC, Canada
| | - Tanya Rose Copley
- Centre de recherche sur les grains (CÉROM) Inc., St-Mathieu-de-Beloeil, QC, Canada
| | | | - Louise O'Donoughue
- Centre de recherche sur les grains (CÉROM) Inc., St-Mathieu-de-Beloeil, QC, Canada
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Zhu H, Lai R, Chen W, Lu C, Chachar Z, Lu S, Lin H, Fan L, Hu Y, An Y, Li X, Zhang X, Qi Y. Genetic dissection of maize (Zea maysL.) trace element traits using genome-wide association studies. BMC PLANT BIOLOGY 2023; 23:631. [PMID: 38062375 PMCID: PMC10704835 DOI: 10.1186/s12870-023-04643-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023]
Abstract
Maize (Zea mays L.) is an important food and feed crop worldwide and serves as a a vital source of biological trace elements, which are important breeding targets. In this study, 170 maize materials were used to detect QTNs related to the content of Mn, Fe and Mo in maize grains through two GWAS models, namely MLM_Q + K and MLM_PCA + K. The results identified 87 (Mn), 205 (Fe), and 310 (Mo) QTNs using both methods in the three environments. Considering comprehensive factors such as co-location across multiple environments, strict significance threshold, and phenotypic value in multiple environments, 8 QTNs related to Mn, 10 QTNs related to Fe, and 26 QTNs related to Mo were used to identify 44 superior alleles. Consequently, three cross combinations with higher Mn element, two combinations with higher Fe element, six combinations with higher Mo element, and two combinations with multiple element (Mn/Fe/Mo) were predicted to yield offspring with higher numbers of superior alleles, thereby increasing the likelihood of enriching the corresponding elements. Additionally, the candidate genes identified 100 kb downstream and upstream the QTNs featured function and pathways related to maize elemental transport and accumulation. These results are expected to facilitate the screening and development of high-quality maize varieties enriched with trace elements, establish an important theoretical foundation for molecular marker assisted breeding and contribute to a better understanding of the regulatory network governing trace elements in maize.
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Affiliation(s)
- Hang Zhu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- College of Agriculture, Yangtze University, Jingzhou, 434025, Hubei, China
| | - Ruiqiang Lai
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
| | - Weiwei Chen
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Chuanli Lu
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Zaid Chachar
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
| | - Siqi Lu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Huanzhang Lin
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Lina Fan
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Yuanqiang Hu
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
| | - Yuxing An
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China
| | - Xuhui Li
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
| | - Xiangbo Zhang
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
| | - Yongwen Qi
- Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, Guangdong, China.
- Institute of Nanfan & Seed Industry, Guangdong Academy of Science, Guangzhou, 510316, Guangdong, China.
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China.
- College of Agriculture, Yangtze University, Jingzhou, 434025, Hubei, China.
- Heyuan Provincial Academy of Sciences Research Institute, Guangdong Academy of Sciences, GDAS, Heyuan, 517001, Guangdong, China.
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Han X, Tang Q, Xu L, Guan Z, Tu J, Yi B, Liu K, Yao X, Lu S, Guo L. Genome-wide detection of genotype environment interactions for flowering time in Brassica napus. FRONTIERS IN PLANT SCIENCE 2022; 13:1065766. [PMID: 36479520 PMCID: PMC9721451 DOI: 10.3389/fpls.2022.1065766] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 10/31/2022] [Indexed: 06/17/2023]
Abstract
Flowering time is strongly related to the environment, while the genotype-by-environment interaction study for flowering time is lacking in Brassica napus. Here, a total of 11,700,689 single nucleotide polymorphisms in 490 B. napus accessions were used to associate with the flowering time and related climatic index in eight environments using a compressed variance-component mixed model, 3VmrMLM. As a result, 19 stable main-effect quantitative trait nucleotides (QTNs) and 32 QTN-by-environment interactions (QEIs) for flowering time were detected. Four windows of daily average temperature and precipitation were found to be climatic factors highly correlated with flowering time. Ten main-effect QTNs were found to be associated with these flowering-time-related climatic indexes. Using differentially expressed gene (DEG) analysis in semi-winter and spring oilseed rapes, 5,850 and 5,511 DEGs were found to be significantly expressed before and after vernalization. Twelve and 14 DEGs, including 7 and 9 known homologs in Arabidopsis, were found to be candidate genes for stable QTNs and QEIs for flowering time, respectively. Five DEGs were found to be candidate genes for main-effect QTNs for flowering-time-related climatic index. These candidate genes, such as BnaFLCs, BnaFTs, BnaA02.VIN3, and BnaC09.PRR7, were further validated by the haplotype, selective sweep, and co-expression networks analysis. The candidate genes identified in this study will be helpful to breed B. napus varieties adapted to particular environments with optimized flowering time.
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Affiliation(s)
- Xu Han
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Qingqing Tang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Liping Xu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Zhilin Guan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jinxing Tu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Bin Yi
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Kede Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xuan Yao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Shaoping Lu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Liang Guo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
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Ren R, Liu W, Yao M, Jia Y, Huang L, Li W, He X, Guan M, Liu Z, Guan C, Hua W, Xiong X, Qian L. Regional association and transcriptome analysis revealed candidate genes controlling plant height in Brassica napus. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:69. [PMID: 37313473 PMCID: PMC10248621 DOI: 10.1007/s11032-022-01337-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/07/2022] [Indexed: 06/15/2023]
Abstract
Plant height is a key morphological trait in rapeseed, which not only plays an important role in determining plant architecture, but is also an important characteristic related to yield. Presently, the improvement of plant architecture is a major challenge in rapeseed breeding. This work was carried out to identify genetic loci related to plant height in rapeseed. In this study, a genome-wide association study (GWAS) of plant height was performed using a Brassica 60 K Illumina Infinium SNP array and 203 Brassica napus accessions. Eleven haplotypes containing important candidate genes were detected and significantly associated with plant height on chromosomes A02, A03, A05, A07, A08, C03, C06, and C09. Moreover, regional association analysis of 50 resequenced rapeseed inbred lines was used to further analyze these eleven haplotypes and revealed nucleotide variation in the BnFBR12-A08 and BnCCR1-C03 gene regions related to the phenotypic variation in plant height. Furthermore, coexpression network analysis showed that BnFBR12-A08 and BnCCR1-C03 were directly connected with hormone genes and transcription factors and formed a potential network regulating the plant height of rapeseed. Our results will aid in the development of haplotype functional markers to further improve plant height in rapeseed. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01337-1.
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Affiliation(s)
- Rui Ren
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Wei Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Min Yao
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Yuan Jia
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Luyao Huang
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Wenqian Li
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Xin He
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Mei Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Zhongsong Liu
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Chunyun Guan
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Wei Hua
- Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062 China
| | - Xinghua Xiong
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
| | - Lunwen Qian
- Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha, 410128 China
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Wang J, Hu B, Jing Y, Hu X, Guo Y, Chen J, Liu Y, Hao J, Li WX, Ning H. Detecting QTL and Candidate Genes for Plant Height in Soybean via Linkage Analysis and GWAS. FRONTIERS IN PLANT SCIENCE 2022; 12:803820. [PMID: 35126428 PMCID: PMC8813865 DOI: 10.3389/fpls.2021.803820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/20/2021] [Indexed: 05/17/2023]
Abstract
Soybean is an important global crop for edible protein and oil, and plant height is a main breeding goal which is closely related to its plant shape and yield. In this research, a high-density genetic linkage map was constructed by 1996 SNP-bin markers on the basis of a recombinant inbred line population derived from Dongnong L13 × Henong 60. A total of 33 QTL related to plant height were identified, of which five were repeatedly detected in multiple environments. In addition, a 455-germplasm population with 63,306 SNP markers was used for multi-locus association analysis. A total of 62 plant height QTN were detected, of which 26 were detected repeatedly under multiple methods. Two candidate genes, Glyma.02G133000 and Glyma.05G240600, involving in plant height were predicted by pathway analysis in the regions identified by multiple environments and backgrounds, and validated by qRT-PCR. These results enriched the soybean plant height regulatory network and contributed to molecular selection-assisted breeding.
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Affiliation(s)
- Jiajing Wang
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Bo Hu
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Yuliang Jing
- Suihua Branch of Heilongjiang Academy of Agricultural Science, Suihua, China
| | - Xiping Hu
- Key Laboratory of Crop Biotechnology Breeding of the Ministry of Agriculture, Beidahuang Kenfeng Seed Co., Ltd., Harbin, China
| | - Yue Guo
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jiankun Chen
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Yuxi Liu
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jianhui Hao
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Wen-Xia Li
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
| | - Hailong Ning
- Key Laboratory of Soybean Biology, Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin, China
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