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Kutlu I, Çelik S, Karaduman Y, Yorgancılar Ö. Phenotypic and genetic diversity of doubled haploid bread wheat population and molecular validation for spike characteristics, end-use quality, and biofortification capacity. PeerJ 2023; 11:e15485. [PMID: 37312880 PMCID: PMC10259445 DOI: 10.7717/peerj.15485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/10/2023] [Indexed: 06/15/2023] Open
Abstract
Increasing grain quality and nutritional value along with yield in bread wheat is one of the leading breeding goals. Selection of genotypes with desired traits using traditional breeding selection methods is very time-consuming and often not possible due to the interaction of environmental factors. By identifying DNA markers that can be used to identify genotypes with desired alleles, high-quality and bio-fortified bread wheat production can be achieved in a short time and cost-effectively. In the present study, 134 doubled haploid (DH) wheat lines and their four parents were phenotypically evaluated for yield components (spike characteristics), quality parameters, and grain Fe and Zn concentrations in two successive growing seasons. At the same time, ten genic simple sequence repeats (SSR) markers linked to genes related to the traits examined were validated and subsequently used for molecular characterization of trait-specific candidate genotypes. Significant genotypic variations were determined for all studied traits and many genotypes with desired phenotypic values were detected. The evaluation performed with 10 SSR markers revealed significant polymorphism between genotypes. The polymorphic information content (PIC) values of 10 markers ranged from 0.00 to 0.87. Six out of 10 SSRs could be more effective in representing the genotypic differentiation of the DH population as they demonstrated the highest genetic diversity. Both Unweighted Pair Group Method with Arithmetic Mean (UPGMA) clustering and STRUCTURE analyses divided 138 wheat genotypes into five (K = 5) main groups. These analyzes were indicative of genetic variation due to hybridization and segregation in the DH population and the differentiation of the genotypes from their parents. Single marker regression analysis showed that both Xbarc61 and Xbarc146 had significant relationships with grain Fe and Zn concentrations, while Xbarc61 related to spike characteristics and Xbarc146 related to quality traits, separately. Other than these, Xgwm282 was associated with spike harvest index, SDS sedimentation value and Fe grain concentration, while Gwm445 was associated with spikelet number, grain number per spike and grain Fe concentration. These markers were validated for the studied DH population during the present study and they could be effectively used for marker-assisted selection to improve grain yield, quality, and bio-fortification capacity of bread wheat.
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Affiliation(s)
- Imren Kutlu
- Department of Field Crops, Faculty of Agriculture, Osmangazi University, Eskişehir, Turkey
| | - Sadettin Çelik
- Department of Forestry, Genç Vocational School, Bingöl University, Bingöl, Turkey
| | - Yaşar Karaduman
- Department of Food Engineering, Faculty of Agriculture, Osmangazi University, Eskişehir, Turkey
| | - Özcan Yorgancılar
- Department of Biotechnology, Transitional Zone Agricultural Research Institute, Eskişehir, Turkey
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Ma F, Xu Y, Wang R, Tong Y, Zhang A, Liu D, An D. Identification of major QTLs for yield-related traits with improved genetic map in wheat. FRONTIERS IN PLANT SCIENCE 2023; 14:1138696. [PMID: 37008504 PMCID: PMC10063875 DOI: 10.3389/fpls.2023.1138696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 03/08/2023] [Indexed: 06/19/2023]
Abstract
Introduction Identification of stable major quantitative trait loci (QTLs) for yield-related traits is important for yield potential improvement in wheat breeding. Methods In the present study, we genotyped a recombinant inbred line (RIL) population using the Wheat 660K SNP array and constructed a high-density genetic map. The genetic map showed high collinearity with the wheat genome assembly. Fourteen yield-related traits were evaluated in six environments for QTL analysis. Results and Discussion A total of 12 environmentally stable QTLs were identified in at least three environments, explaining up to 34.7% of the phenotypic variation. Of these, QTkw-1B.2 for thousand kernel weight (TKW), QPh-2D.1 (QSl-2D.2/QScn-2D.1) for plant height (PH), spike length (SL) and spikelet compactness (SCN), QPh-4B.1 for PH, and QTss-7A.3 for total spikelet number per spike (TSS) were detected in at least five environments. A set of Kompetitive Allele Specific PCR (KASP) markers were converted based on the above QTLs and used to genotype a diversity panel comprising of 190 wheat accessions across four growing seasons. QPh-2D.1 (QSl-2D.2/QScn-2D.1), QPh-4B.1 and QTss-7A.3 were successfully validated. Compared with previous studies, QTkw-1B.2 and QPh-4B.1 should be novel QTLs. These results provided a solid foundation for further positional cloning and marker-assisted selection of the targeted QTLs in wheat breeding programs.
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Affiliation(s)
- Feifei Ma
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yunfeng Xu
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Ruifang Wang
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
| | - Yiping Tong
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Aimin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, National Center for Plant Gene Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Dongcheng Liu
- State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, Hebei, China
| | - Diaoguo An
- Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, China
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Christov NK, Tsonev S, Dragov R, Taneva K, Bozhanova V, Todorovska EG. Genetic diversity and population structure of modern Bulgarian and foreign durum wheat based on microsatellite and agronomic data. BIOTECHNOL BIOTEC EQ 2022. [DOI: 10.1080/13102818.2022.2116999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022] Open
Affiliation(s)
- Nikolai Kirilov Christov
- Department of Functional Genetics, Abiotic and Biotic Stress, AgroBioInstitute, Agricultural Academy, Sofia, Bulgaria
| | - Stefan Tsonev
- Department of Functional Genetics, Abiotic and Biotic Stress, AgroBioInstitute, Agricultural Academy, Sofia, Bulgaria
| | - Rangel Dragov
- Department of Durum Wheat Breeding, Field Crops Institute, Agricultural Academy, Chirpan, Bulgaria
| | - Krasimira Taneva
- Department of Durum Wheat Breeding, Field Crops Institute, Agricultural Academy, Chirpan, Bulgaria
| | - Violeta Bozhanova
- Department of Durum Wheat Breeding, Field Crops Institute, Agricultural Academy, Chirpan, Bulgaria
| | - Elena Georgieva Todorovska
- Department of Functional Genetics, Abiotic and Biotic Stress, AgroBioInstitute, Agricultural Academy, Sofia, Bulgaria
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Muhammad A, Hu W, Li Z, Li J, Xie G, Wang J, Wang L. Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS. Int J Mol Sci 2020; 21:ijms21165649. [PMID: 32781752 PMCID: PMC7460857 DOI: 10.3390/ijms21165649] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 08/02/2020] [Accepted: 08/05/2020] [Indexed: 12/14/2022] Open
Abstract
Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.
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Affiliation(s)
- Ali Muhammad
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
| | - Weicheng Hu
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
| | - Zhaoyang Li
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
| | - Jianguo Li
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, 100 Daxue Rd., Nanning 530004, China
| | - Guosheng Xie
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
| | - Jibin Wang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, 100 Daxue Rd., Nanning 530004, China
- Correspondence: (J.W.); (L.W.)
| | - Lingqiang Wang
- College of Plant Science and Technology & Biomass and Bioenergy Research Center, Huazhong Agricultural University, Wuhan 430070, China; (A.M.); (W.H.); (Z.L.); (J.L.); (G.X.)
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, 100 Daxue Rd., Nanning 530004, China
- Correspondence: (J.W.); (L.W.)
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Li X, Xu X, Liu W, Li X, Yang X, Ru Z, Li L. Dissection of Superior Alleles for Yield-Related Traits and Their Distribution in Important Cultivars of Wheat by Association Mapping. FRONTIERS IN PLANT SCIENCE 2020; 11:175. [PMID: 32194592 PMCID: PMC7061769 DOI: 10.3389/fpls.2020.00175] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 02/05/2020] [Indexed: 05/18/2023]
Abstract
Uncovering the genetic basis of yield-related traits is important for molecular improvement of wheat cultivars. In this study, a genome-wide association study was conducted using the wheat 55K genotyping assay and a diverse panel of 384 wheat genotypes. The accessions used included 18 founder parents and 15 widely grown cultivars with annual maximum acreages of over 667,000 ha, and the remaining materials were elite cultivars and breeding lines from several major wheat ecological areas of China. Field trials were conducted in five major wheat ecological regions of China over three consecutive years. A total of 460 significant loci were detected for eight yield-related traits. Forty-five superior alleles distributed over 31 loci for which differences in phenotypic values grouped by single nucleotide polymorphism (SNP) reached significant levels (P < 0.05) in nine or more environments, were detected; some of these loci were previously reported. Eleven of the 31 superior allele loci on chromosomes 4A, 5A, 3B, 5B, 6B, 7B, 5D, and 7D had pleiotropic effects. For example, AX-95152512 on 5D was simultaneously related to increased grain weight per spike (GWS) and decreased plant height (PH); AX-109860828 on 5B simultaneously led to a high 1,000-kernel weight (TKW) and short PH; and AX-111600193 on 4A was simultaneously linked to a high TKW and GWS, and short PH. The favorable alleles in each accession ranged from 2 to 30 with an average of 16 at the thirty-one loci in the population, and six accessions (Zhengzhou683, Suzhou7829, Longchun7, Ningmai6, Yunmai35 and Zhen7630) contained more than 27 favorable alleles. A significant association between the number of favorable alleles and yield was observed (r = 0.799, p < 0.0001), suggesting that pyramiding multiple QTL with marker-assisted selection may effectively increase yield of wheat. Furthermore, distribution of superior alleles in founder parents and widely grown cultivars was also discussed here. This study is useful for marker-assisted selection for yield improvement and dissecting the genetic mechanism of important cultivars in wheat.
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Affiliation(s)
- Xiaojun Li
- School of Life Science and Technology, Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding, Henan Province, Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang, China
| | - Xin Xu
- Department of Life Sciences and Technology, Xinxiang University, Xinxiang, China
| | - Weihua Liu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiuquan Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinming Yang
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhengang Ru
- School of Life Science and Technology, Henan Institute of Science and Technology, Collaborative Innovation Center of Modern Biological Breeding, Henan Province, Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang, China
| | - Lihui Li
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Shi W, Hao C, Zhang Y, Cheng J, Zhang Z, Liu J, Yi X, Cheng X, Sun D, Xu Y, Zhang X, Cheng S, Guo P, Guo J. A Combined Association Mapping and Linkage Analysis of Kernel Number Per Spike in Common Wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2017; 8:1412. [PMID: 28868056 PMCID: PMC5563363 DOI: 10.3389/fpls.2017.01412] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 07/31/2017] [Indexed: 05/18/2023]
Abstract
Kernel number per spike (KNPS) in wheat is a key factor that limits yield improvement. In this study, we genotyped a set of 264 cultivars, and a RIL population derived from the cross Yangmai 13/C615 using the 90 K wheat iSelect SNP array. We detected 62 significantly associated signals for KNPS at 47 single nucleotide polymorphism (SNP) loci through genome-wide association analysis of data obtained from multiple environments. These loci were on 19 chromosomes, and the phenotypic variation attributable to each one ranged from 1.53 to 39.52%. Twelve (25.53%) of the loci were also significantly associated with KNPS in the RIL population grown in multiple environments. For example, BS00022896_51-2ATT , BobWhite_c10539_201-2DAA , Excalibur_c73633_120-3BGG , and Kukri_c35508_426-7DTT were significantly associated with KNPS in all environments. Our findings demonstrate the effective integration of association mapping and linkage analysis for KNPS, and underpin KNPS as a target trait for marker-assisted selection and genetic fine mapping.
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Affiliation(s)
- Weiping Shi
- College of Agronomy, Shanxi Agricultural UniversityJinzhong, China
| | - Chenyang Hao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Yong Zhang
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Jingye Cheng
- College of Agronomy, Yangzhou UniversityYangzhou, China
| | - Zheng Zhang
- College of Agronomy, Shanxi Agricultural UniversityJinzhong, China
| | - Jian Liu
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Xin Yi
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Xiaoming Cheng
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Daizhen Sun
- College of Agronomy, Shanxi Agricultural UniversityJinzhong, China
| | - Yanhao Xu
- Hubei Collaborative Innovation Centre for Grain Industry and College of Agriculture, Yangtze UniversityJingzhou, China
| | - Xueyong Zhang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, The National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Shunhe Cheng
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
- Shunhe Cheng
| | - Pingyi Guo
- College of Agronomy, Shanxi Agricultural UniversityJinzhong, China
- Pingyi Guo
| | - Jie Guo
- College of Agronomy, Shanxi Agricultural UniversityJinzhong, China
- *Correspondence: Jie Guo
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Bellucci A, Torp AM, Bruun S, Magid J, Andersen SB, Rasmussen SK. Association Mapping in Scandinavian Winter Wheat for Yield, Plant Height, and Traits Important for Second-Generation Bioethanol Production. FRONTIERS IN PLANT SCIENCE 2015; 6:1046. [PMID: 26635859 PMCID: PMC4660856 DOI: 10.3389/fpls.2015.01046] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Accepted: 11/09/2015] [Indexed: 05/04/2023]
Abstract
A collection of 100 wheat varieties representing more than 100 years of wheat-breeding history in Scandinavia was established in order to identify marker-trait associations for plant height (PH), grain yield (GY), and biomass potential for bioethanol production. The field-grown material showed variations in PH from 54 to 122 cm and in GY from 2 to 6.61 t ha(-1). The release of monomeric sugars was determined by high-throughput enzymatic treatment of ligno-cellulosic material and varied between 0.169 and 0.312 g/g dm for glucose (GLU) and 0.146 and 0.283 g/g dm for xylose (XYL). As expected, PH and GY showed to be highly influenced by genetic factors with repeatability (R) equal to 0.75 and 0.53, respectively, while this was reduced for GLU and XYL (R = 0.09 for both). The study of trait correlations showed how old, low-yielding, tall varieties released higher amounts of monomeric sugars after straw enzymatic hydrolysis, showing reduced recalcitrance to bioconversion compared to modern varieties. Ninety-three lines from the collection were genotyped with the DArTseq(®) genotypic platform and 5525 markers were used for genome-wide association mapping. Six quantitative trait loci (QTLs) for GY, PH, and GLU released from straw were mapped. One QTL for PH was previously reported, while the remaining QTLs constituted new genomic regions linked to trait variation. This paper is one of the first studies in wheat to identify QTLs that are important for bioethanol production based on a genome-wide association approach.
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Affiliation(s)
| | | | | | | | | | - Søren K. Rasmussen
- Plant and Soil Section, Department of Plant and Environmental Sciences, Faculty of Science, University of CopenhagenFrederiksberg, Denmark
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Guo J, Zhang Y, Shi W, Zhang B, Zhang J, Xu Y, Cheng X, Cheng K, Zhang X, Hao C, Cheng S. Association Analysis of Grain-setting Rates in Apical and Basal Spikelets in Bread Wheat (Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2015; 6:1029. [PMID: 26635852 PMCID: PMC4653486 DOI: 10.3389/fpls.2015.01029] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Accepted: 11/06/2015] [Indexed: 05/29/2023]
Abstract
The rates of grain-setting in apical and basal spikelets in wheat directly affect the kernel number per spike (KNPS). In this study, 220 wheat lines from 18 Chinese provinces and five foreign countries were used as a natural population. Phenotypic analysis showed differences in grain-setting rates between apical and basal spikelets. The broad-sense heritability of grain-setting rate in apical spikelets (18.7-21.0%) was higher than that for basal spikelets (9.4-16.4%). Significant correlations were found between KNPS and grain numbers in apical (R (2) = 0.40-0.45, P < 0.01) and basal (R (2) = 0.41-0.56, P < 0.01) spikelets. Seventy two of 106 SSR markers were associated with grain setting, 32 for apical spikelets, and 34 for basal spikelets. The SSR loci were located on 17 chromosomes, except 3A, 3D, 4A, and 7D, and explained 3.7-22.9% of the phenotypic variance. Four markers, Xcfa2153-1A 202 , Xgwm186-5A 118 , Xgwm156-3B 319 , and Xgwm537-7B 210 , showed the largest effects on grain numbers in apical and basal spikelets. High grain numbers in apical and basal spikelets were associated with elite alleles. Ningmai 9, Ning 0569, and Yangmai 18 with high grain-setting rates carried larger numbers of favorable alleles. Comparison of grain numbers in basal and apical spikelets of 35 Yangmai and Ningmai lines indicated that the Ningmai lines had better grain-setting rates (mean 21.4) than the Yangmai lines (16.5).
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Affiliation(s)
- Jie Guo
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
- Institute for Chemical Ecology, Shanxi Agricultural UniversityTaigu, China
| | - Yong Zhang
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Weiping Shi
- Institute for Chemical Ecology, Shanxi Agricultural UniversityTaigu, China
| | - Boqiao Zhang
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Jingjuan Zhang
- Agricultural Science, School of Veterinary and Life Sciences, Murdoch UniversityMurdoch, WA, Australia
| | - Yanhao Xu
- Hubei Collaborative Innovation Centre for Grain Industry/College of Agriculture, Yangtze UniversityJingzhou, China
| | - Xiaoming Cheng
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Kai Cheng
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
| | - Xueyong Zhang
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Chenyang Hao
- Key Laboratory of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture/The National Key Facility for Crop Gene Resources and Genetic Improvement/Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Shunhe Cheng
- Key Laboratory of Wheat Biology and Genetic Improvement for Low and Middle Yangtze Valley (Ministry of Agriculture), Lixiahe Agricultural Institute of Jiangsu ProvinceYangzhou, China
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