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Wang D, He Y, Nie L, Guo S, Tu L, Guo X, Wang A, Liu P, Zhu Y, Wu X, Chen Z. Integrated IBD Analysis, GWAS Analysis and Transcriptome Analysis to Identify the Candidate Genes for White Spot Disease in Maize. Int J Mol Sci 2023; 24:10005. [PMID: 37373152 DOI: 10.3390/ijms241210005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/01/2023] [Accepted: 06/08/2023] [Indexed: 06/29/2023] Open
Abstract
Foundation parents (FPs) play an irreplaceable role in maize breeding practices. Maize white spot (MWS) is an important disease in Southwest China that always seriously reduces production. However, knowledge about the genetic mechanism of MWS resistance is limited. In this paper, a panel of 143 elite lines were collected and genotyped by using the MaizeSNP50 chip with approximately 60,000 single nucleotide polymorphisms (SNPs) and evaluated for resistance to MWS among 3 environments, and a genome-wide association study (GWAS) and transcriptome analysis were integrated to reveal the function of the identity-by-descent (IBD) segments for MWS. The results showed that (1) 225 IBD segments were identified only in the FP QB512, 192 were found only in the FP QR273 and 197 were found only in the FP HCL645. (2) The GWAS results showed that 15 common quantitative trait nucleotides (QTNs) were associated with MWS. Interestingly, SYN10137 and PZA00131.14 were in the IBD segments of QB512, and the SYN10137-PZA00131.14 region existed in more than 58% of QR273's descendants. (3) By integrating the GWAS and transcriptome analysis, Zm00001d031875 was found to located in the region of SYN10137-PZA00131.14. These results provide some new insights for the detection of MWS's genetic variation mechanisms.
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Affiliation(s)
- Dong Wang
- College of Agriculture, Guizhou University, Guiyang 550006, China
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Yue He
- College of Agriculture, Guizhou University, Guiyang 550006, China
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Lei Nie
- College of Agriculture, Guizhou University, Guiyang 550006, China
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Shuang Guo
- College of Agriculture, Guizhou University, Guiyang 550006, China
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Liang Tu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Xiangyang Guo
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Angui Wang
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Pengfei Liu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Yunfang Zhu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
| | - Xun Wu
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
- Ministry of Agriculture and Rural Affairs Key Laboratory of Crop Genetic Resources and Germplasm Innovation in Karst Region, Guiyang 550006, China
| | - Zehui Chen
- Institute of Upland Food Crops, Guizhou Academy of Agricultural Sciences, Guiyang 550006, China
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Wang Y, Bao J, Wei X, Wu S, Fang C, Li Z, Qi Y, Gao Y, Dong Z, Wan X. Genetic Structure and Molecular Mechanisms Underlying the Formation of Tassel, Anther, and Pollen in the Male Inflorescence of Maize (Zea mays L.). Cells 2022; 11:cells11111753. [PMID: 35681448 PMCID: PMC9179574 DOI: 10.3390/cells11111753] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 02/08/2023] Open
Abstract
Maize tassel is the male reproductive organ which is located at the plant’s apex; both its morphological structure and fertility have a profound impact on maize grain yield. More than 40 functional genes regulating the complex tassel traits have been cloned up to now. However, the detailed molecular mechanisms underlying the whole process, from male inflorescence meristem initiation to tassel morphogenesis, are seldom discussed. Here, we summarize the male inflorescence developmental genes and construct a molecular regulatory network to further reveal the molecular mechanisms underlying tassel-trait formation in maize. Meanwhile, as one of the most frequently studied quantitative traits, hundreds of quantitative trait loci (QTLs) and thousands of quantitative trait nucleotides (QTNs) related to tassel morphology have been identified so far. To reveal the genetic structure of tassel traits, we constructed a consensus physical map for tassel traits by summarizing the genetic studies conducted over the past 20 years, and identified 97 hotspot intervals (HSIs) that can be repeatedly mapped in different labs, which will be helpful for marker-assisted selection (MAS) in improving maize yield as well as for providing theoretical guidance in the subsequent identification of the functional genes modulating tassel morphology. In addition, maize is one of the most successful crops in utilizing heterosis; mining of the genic male sterility (GMS) genes is crucial in developing biotechnology-based male-sterility (BMS) systems for seed production and hybrid breeding. In maize, more than 30 GMS genes have been isolated and characterized, and at least 15 GMS genes have been promptly validated by CRISPR/Cas9 mutagenesis within the past two years. We thus summarize the maize GMS genes and further update the molecular regulatory networks underlying male fertility in maize. Taken together, the identified HSIs, genes and molecular mechanisms underlying tassel morphological structure and male fertility are useful for guiding the subsequent cloning of functional genes and for molecular design breeding in maize. Finally, the strategies concerning efficient and rapid isolation of genes controlling tassel morphological structure and male fertility and their application in maize molecular breeding are also discussed.
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Affiliation(s)
- Yanbo Wang
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Jianxi Bao
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Xun Wei
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Suowei Wu
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Chaowei Fang
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Ziwen Li
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Yuchen Qi
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Yuexin Gao
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Zhenying Dong
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
- Correspondence: (Z.D.); (X.W.); Tel.: +86-152-1092-0373 (Z.D.); +86-186-0056-1850 (X.W.)
| | - Xiangyuan Wan
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
- Correspondence: (Z.D.); (X.W.); Tel.: +86-152-1092-0373 (Z.D.); +86-186-0056-1850 (X.W.)
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Souza VFD, Pereira GDS, Pastina MM, Parrella RADC, Simeone MLF, Barros BDA, Noda RW, da Costa e Silva L, Magalhães JVD, Schaffert RE, Garcia AAF, Damasceno CMB. QTL mapping for bioenergy traits in sweet sorghum recombinant inbred lines. G3 GENES|GENOMES|GENETICS 2021; 11:6370150. [PMID: 34519766 PMCID: PMC8527507 DOI: 10.1093/g3journal/jkab314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/26/2021] [Indexed: 11/13/2022]
Abstract
Abstract
During the past decade, sweet sorghum (Sorghum bicolor Moench L.) has shown great potential for bioenergy production, especially biofuels. In this study, 223 recombinant inbred lines (RILs) derived from a cross between two sweet sorghum lines (Brandes × Wray) were evaluated in three trials. Single-nucleotide polymorphisms (SNPs) derived from genotyping by sequencing of 272 RILs were used to build a high-density genetic map comprising 3,767 SNPs spanning 1,368.83 cM. Multitrait multiple interval mapping (MT-MIM) was carried out to map quantitative trait loci (QTL) for eight bioenergy traits. A total of 33 QTLs were identified for flowering time, plant height, total soluble solids and sucrose (five QTLs each), fibers (four QTLs), and fresh biomass yield, juice extraction yield, and reducing sugars (three QTLs each). QTL hotspots were found on chromosomes 1, 3, 6, 9, and 10, in addition to other QTLs detected on chromosomes 4 and 8. We observed that 14 out of the 33 mapped QTLs were found in all three trials. Upon further development and validation in other crosses, the results provided by the present study have a great potential to be used in marker-assisted selection in sorghum breeding programs for biofuel production.
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Affiliation(s)
| | - Guilherme da Silva Pereira
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
| | | | | | | | | | | | | | | | | | - Antonio Augusto Franco Garcia
- Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP, 13418-900, Brazil
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Identification of quantitative trait loci for kernel-related traits and the heterosis for these traits in maize (Zea mays L.). Mol Genet Genomics 2019; 295:121-133. [PMID: 31511973 DOI: 10.1007/s00438-019-01608-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 08/31/2019] [Indexed: 12/24/2022]
Abstract
Heterosis has been extensively applied for many traits during maize breeding, but there has been relatively little attention paid to the heterosis for kernel size. In this study, we evaluated a population of 301 recombinant inbred lines derived from a cross between 08-641 and YE478, as well as 298 hybrids from an immortalized F2 (IF2) population to detect quantitative trait loci (QTLs) for six kernel-related traits and the mid-parent heterosis (MPH) for these traits. A total of 100 QTLs, six pairs of loci with epistatic interactions, and five significant QTL × environment interactions were identified in both mapping populations. Seven QTLs accounted for over 10% of the phenotypic variation. Only four QTLs affected both the trait means and the MPH, suggesting the genetic mechanisms for kernel-related traits and the heterosis for kernel size are not completely independent. Moreover, more than half of the QTLs for each trait in the IF2 population exhibited dominance, implying that dominance is more important than other genetic effects for the heterosis for kernel-related traits. Additionally, 20 QTL clusters comprising 46 QTLs were detected across ten chromosomes. Specific chromosomal regions (bins 2.03, 6.04-6.05, and 9.01-9.02) exhibited pleiotropy and congruency across diverse heterotic patterns in previous studies. These results may provide additional insights into the genetic basis for the MPH for kernel-related traits.
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Yi Q, Liu Y, Hou X, Zhang X, Li H, Zhang J, Liu H, Hu Y, Yu G, Li Y, Wang Y, Huang Y. Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.). BMC PLANT BIOLOGY 2019; 19:392. [PMID: 31500559 PMCID: PMC6734583 DOI: 10.1186/s12870-019-2009-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 08/30/2019] [Indexed: 05/02/2023]
Abstract
BACKGROUND Utilization of heterosis in maize could be critical in maize breeding for boosting grain yield. However, the genetic architecture of heterosis is not fully understood. To dissect the genetic basis of yield-related traits and heterosis in maize, 301 recombinant inbred lines derived from 08 to 641 × YE478 and 298 hybrids from the immortalized F2 (IF2) population were used to map quantitative trait loci (QTLs) for nine yield-related traits and mid-parent heterosis. RESULTS We observed 156 QTLs, 28 pairs of loci with epistatic interaction, and 10 significant QTL × environment interactions in the inbred and hybrid mapping populations. The high heterosis in F1 and IF2 populations for kernel weight per ear (KWPE), ear weight per ear (EWPE), and kernel number per row (KNPR) matched the high percentages of QTLs (over 50%) for those traits exhibiting overdominance, whereas a notable predominance of loci with dominance effects (more than 70%) was observed for traits that show low heterosis such as cob weight per ear (CWPE), rate of kernel production (RKP), ear length (EL), ear diameter (ED), cob diameter, and row number (RN). The environmentally stable QTL qRKP3-2 was identified across two mapping populations, while qKWPE9, affecting the trait mean and the mid-parent heterosis (MPH) level, explained over 18% of phenotypic variations. Nine QTLs, qEWPE9-1, qEWPE10-1, qCWPE6, qEL8, qED2-2, qRN10-1, qKWPE9, qKWPE10-1, and qRKP4-3, accounted for over 10% of phenotypic variation. In addition, QTL mapping identified 95 QTLs that were gathered together and integrated into 33 QTL clusters on 10 chromosomes. CONCLUSIONS The results revealed that (1) the inheritance of yield-related traits and MPH in the heterotic pattern improved Reid (PA) × Tem-tropic I (PB) is trait-dependent; (2) a large proportion of loci showed dominance effects, whereas overdominance also contributed to MPH for KNPR, EWPE, and KWPE; (3) marker-assisted selection for markers at genomic regions 1.09-1.11, 2.04, 3.08-3.09, and 10.04-10.05 contributed to hybrid performance per se and heterosis and were repeatedly reported in previous studies using different heterotic patterns is recommended.
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Affiliation(s)
- Qiang Yi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Yinghong Liu
- Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130 China
| | - Xianbin Hou
- College of Agriculture and Food Engineering, Baise University, Baise, 533000 Guangxi China
| | - Xiangge Zhang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Hui Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Junjie Zhang
- College of Life Science, Sichuan Agricultural University, Ya’an, 625014 China
| | - Hanmei Liu
- College of Life Science, Sichuan Agricultural University, Ya’an, 625014 China
| | - Yufeng Hu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Guowu Yu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Yangping Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Yongbin Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
| | - Yubi Huang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130 China
- College of Agronomy, Sichuan Agricultural University, Chengdu, 611130 China
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Zhou Z, Zhang C, Lu X, Wang L, Hao Z, Li M, Zhang D, Yong H, Zhu H, Weng J, Li X. Dissecting the Genetic Basis Underlying Combining Ability of Plant Height Related Traits in Maize. FRONTIERS IN PLANT SCIENCE 2018; 9:1117. [PMID: 30116252 PMCID: PMC6083371 DOI: 10.3389/fpls.2018.01117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 07/11/2018] [Indexed: 05/27/2023]
Abstract
Maize plant height related traits including plant height, ear height, and internode number are tightly linked with biomass, planting density, and grain yield in the field. Previous studies have focused on understanding the genetic basis of plant architecture traits per se, but the genetic basis of combining ability remains poorly understood. In this study, 328 recombinant inbred lines were inter-group crossed with two testers to produce 656 hybrids using the North Carolina II mating design. Both of the parental lines and hybrids were evaluated in two summer maize-growing regions of China in 2015 and 2016. QTL mapping highlighted that 7 out of 16 QTL detected for RILs per se could be simultaneously detected for general combining ability (GCA) effects, suggesting that GCA effects and the traits were genetically controlled by different sets of loci. Among the 35 QTL identified for hybrid performance, 57.1% and 28.5% QTL overlapped with additive/GCA and non-additive/SCA effects, suggesting that the small percentage of hybrid variance due to SCA effects in our design. Two QTL hotspots, located on chromosomes 5 and 10 and including the qPH5-1 and qPH10 loci, were validated for plant height related traits by Ye478 derivatives. Notably, the qPH5-1 locus could simultaneously affect the RILs per se and GCA effects while the qPH10, a major QTL (PVE > 10%) with pleiotropic effects, only affected the GCA effects. These results provide evidence that more attention should be focused on loci that influence combining ability directly in maize hybrid breeding.
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Affiliation(s)
- Zhiqiang Zhou
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chaoshu Zhang
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaohuan Lu
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Liwei Wang
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Zhuanfang Hao
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingshun Li
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Degui Zhang
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongjun Yong
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hanyong Zhu
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Yunnan Wenshanzhou Academy of Agricultural Sciences, Wenshan, China
| | - Jianfeng Weng
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinhai Li
- National Engineering Laboratory for Crop Molecular Breeding, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Yi Q, Liu Y, Zhang X, Hou X, Zhang J, Liu H, Hu Y, Yu G, Huang Y. Comparative mapping of quantitative trait loci for tassel-related traits of maize in F 2:3 and RIL populations. J Genet 2018; 97:253-266. [PMID: 29666344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Tassel architecture is an important trait in maize breeding and hybrid seed production. In this study, we investigated total tassel length (TTL) and tassel branch number (TBN) in 266 F2:3 families across six environments and in 301 recombinant inbred lines (RILs) across three environments, where all the plants were derived from a cross between 08-641 and Ye478. We compared the genetic architecture of the two traits across two generations through combined analysis. In total, 27 quantitative trait loci (QTLs) (15 in F2:3; 16 in RIL), two QTL × environment interactions (both in F2:3), 11 pairs of epistatic interactions (seven in F2:3; four in RIL) and four stable QTLs in both the F2:3 and RILs were detected. The RIL population had higher detection power than the F2:3 population. Nevertheless, QTL × environment interactions and epistatic interactions could be more easily detected in the F2:3 population than in the RILs. Overall, the QTL mapping results in the F2:3 and RILs were greatly influenced by genetic generations and environments. Finally, fine mapping for a novel and major QTL, qTTL-2-3 (bin 2.07), which accounted for over 8.49% of the phenotypic variation across different environments and generations, could be useful in marker-assisted breeding.
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Affiliation(s)
- Qiang Yi
- Agronomy College, Sichuan Agricultural University, Chengdu 611130, Sichuan, People's Republic of China.
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