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Yuan Y, Lyu B, Qi J, Liu X, Wang Y, Delaplace P, Du Y. A novel regulator of wheat tillering LT1 identified by using an upgraded BSA method, uni-BSA. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:47. [PMID: 38939116 PMCID: PMC11199477 DOI: 10.1007/s11032-024-01484-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 06/04/2024] [Indexed: 06/29/2024]
Abstract
Branching/tillering is a critical process for plant architecture and grain yield. However, Branching is intricately controlled by both endogenous and environmental factors. The underlying mechanisms of tillering in wheat remain poorly understood. In this study, we identified Less Tiller 1 (LT1) as a novel regulator of wheat tillering using an enhanced bulked segregant analysis (BSA) method, uni-BSA. This method effectively reduces alignment noise caused by the high repetitive sequence content in the wheat genome. Loss-of-function of LT1 results in fewer tillers due to defects in axillary meristem initiation and bud outgrowth. We mapped LT1 to a 6 Mb region on the chromosome 2D short arm and validated a nucleotide-binding (NB) domain encoding gene as LT1 using CRISPR/Cas9. Furthermore, the lower sucrose concentration in the shoot bases of lt1 might result in inadequate bud outgrowth due to disturbances in the sucrose biosynthesis pathways. Co-expression analysis suggests that LT1 controls tillering by regulating TaROX/TaLAX1, the ortholog of the Arabidopsis tiller regulator REGULATOR OF AXILLARY MERISTEM FORMATION (ROX) or the rice axillary meristem regulator LAX PANICLE1 (LAX1). This study not only offers a novel genetic resource for cultivating optimal plant architecture but also underscores the importance of our innovative BSA method. This uni-BSA method enables the swift and precise identification of pivotal genes associated with significant agronomic traits, thereby hastening gene cloning and crop breeding processes in wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01484-7.
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Affiliation(s)
- Yundong Yuan
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
- Plant Sciences, Gembloux Agro-Bio Tech, University of Liège, Liège, Belgium
| | - Bo Lyu
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
| | - Juan Qi
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
| | - Xin Liu
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
| | - Yuanzhi Wang
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
| | - Pierre Delaplace
- Plant Sciences, Gembloux Agro-Bio Tech, University of Liège, Liège, Belgium
| | - Yanfang Du
- National Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, 271018 China
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2
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Han H, Yang J, Qi K, Zhu H, Wu P, Zhou S, Zhang J, Guo B, Liu W, Guo X, Lu Y, Yang X, Li X, Li L. Introgression of chromosome 5P from Agropyron cristatum enhances grain weight in a wheat background. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:165. [PMID: 38904787 DOI: 10.1007/s00122-024-04670-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024]
Abstract
KEY MESSAGE A grain weight locus from Agropyron cristatum chromosome 5P increases grain weight in different wheat backgrounds and is localized to 5PL (bin 7-12). Thousand-grain weight is an important trait in wheat breeding, with a narrow genetic basis being the main factor limiting improvement. Agropyron cristatum, a wild relative of wheat, harbors many desirable genes for wheat improvement. Here, we found that the introduction of the 5P chromosome from A. cristatum into wheat significantly increased the thousand-grain weight by 2.55-7.10 g, and grain length was the main contributor to grain weight. An increase in grain weight was demonstrated in two commercial wheat varieties, indicating that the grain weight locus was not affected by the wheat background. To identify the chromosome segment harboring the grain weight locus, three A. cristatum 5P deletion lines, two wheat-A. cristatum 5P translocation lines and genetic populations of these lines were used to evaluate agronomic traits. We found that the translocation lines harboring the long arm of A. cristatum chromosome 5P (5PL) exhibited high grain weight and grain length, and the genetic locus associated with increased grain weight was mapped to 5PL (bin 7-12). An increase in grain weight did not adversely affect other agronomic traits in translocation line 5PT2, which is a valuable germplasm resource. Overall, we identified a grain weight locus from chromosome 5PL and provided valuable germplasm for improving wheat grain weight.
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Affiliation(s)
- Haiming Han
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China.
| | - Junli Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
- State Key Laboratory of Crop Stress Biology for Arid Areas and College of Agronomy, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Kai Qi
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Haoyu Zhu
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Panqiang Wu
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Shenghui Zhou
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Jinpeng Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Baojin Guo
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Weihua Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Xiaomin Guo
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Yuqing Lu
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Xinming Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Xiuquan Li
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China
| | - Lihui Li
- State Key Laboratory of Crop Gene Resources and Breeding, Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization (MARA), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing, 100081, China.
- Zhongyuan Research Center, Chinese Academy of Agricultural Sciences (CAAS), Xinxiang, 453519, Henan, China.
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3
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Ye B, Liu Y, Wang Z, Shen L, Yin C, Shen K, Sun J, Xu X, Sun M, Wu J, He Z, Yu X, Lu F, Hao Y, Guo Z. Genetic basis of geographical differentiation, breeding selection, domestication effects, and breeding application for TaJAZ1 in wheat. J Genet Genomics 2024; 51:665-668. [PMID: 38295875 DOI: 10.1016/j.jgg.2024.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/19/2024] [Accepted: 01/19/2024] [Indexed: 03/08/2024]
Affiliation(s)
- Botao Ye
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yangyang Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ziying Wang
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liping Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China; China National Botanical Garden, Beijing 100093, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
| | - Kuocheng Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiaqiang Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xiaowan Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mengjing Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jianhui Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; International Maize and Wheat Improvement Center China Office, c/o CAAS, Beijing 100081, China
| | - Xuchang Yu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fei Lu
- University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China; CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
| | - Zifeng Guo
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China; China National Botanical Garden, Beijing 100093, China.
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4
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Ai G, He C, Bi S, Zhou Z, Liu A, Hu X, Liu Y, Jin L, Zhou J, Zhang H, Du D, Chen H, Gong X, Saeed S, Su H, Lan C, Chen W, Li Q, Mao H, Li L, Liu H, Chen D, Kaufmann K, Alazab KF, Yan W. Dissecting the molecular basis of spike traits by integrating gene regulatory networks and genetic variation in wheat. PLANT COMMUNICATIONS 2024; 5:100879. [PMID: 38486454 PMCID: PMC11121755 DOI: 10.1016/j.xplc.2024.100879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/25/2024] [Accepted: 03/11/2024] [Indexed: 04/30/2024]
Abstract
Spike architecture influences both grain weight and grain number per spike, which are the two major components of grain yield in bread wheat (Triticum aestivum L.). However, the complex wheat genome and the influence of various environmental factors pose challenges in mapping the causal genes that affect spike traits. Here, we systematically identified genes involved in spike trait formation by integrating information on genomic variation and gene regulatory networks controlling young spike development in wheat. We identified 170 loci that are responsible for variations in spike length, spikelet number per spike, and grain number per spike through genome-wide association study and meta-QTL analyses. We constructed gene regulatory networks for young inflorescences at the double ridge stage and the floret primordium stage, in which the spikelet meristem and the floret meristem are predominant, respectively, by integrating transcriptome, histone modification, chromatin accessibility, eQTL, and protein-protein interactome data. From these networks, we identified 169 hub genes located in 76 of the 170 QTL regions whose polymorphisms are significantly associated with variation in spike traits. The functions of TaZF-B1, VRT-B2, and TaSPL15-A/D in establishment of wheat spike architecture were verified. This study provides valuable molecular resources for understanding spike traits and demonstrates that combining genetic analysis and developmental regulatory networks is a robust approach for dissection of complex traits.
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Affiliation(s)
- Guo Ai
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Chao He
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Siteng Bi
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ziru Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ankui Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yanyan Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Liujie Jin
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - JiaCheng Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Heping Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Dengxiang Du
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hao Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xin Gong
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Sulaiman Saeed
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Handong Su
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Caixia Lan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Qiang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Lin Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome, Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Hao Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Kerstin Kaufmann
- Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität Zu Berlin, 10115 Berlin, Germany
| | - Khaled F Alazab
- Plant Research Department, Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 13759, Egypt
| | - Wenhao Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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5
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Zhang L, Zhou H, Fu X, Zhou N, Liu M, Bai S, Zhao X, Cheng R, Li S, Zhang D. Identification and map-based cloning of an EMS-induced mutation in wheat gene TaSP1 related to spike architecture. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:119. [PMID: 38709271 DOI: 10.1007/s00122-024-04621-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 04/10/2024] [Indexed: 05/07/2024]
Abstract
KEY MESSAGE A candidate gene TaSP1 related to spike shape was cloned, and the gene-specific marker was developed to efficiently track the superior haplotype in common wheat. Spike shape, an important factor that affects wheat grain yield, is mainly defined by spike length (SPL), spikelet number (SPN), and compactness. Zhoumai32 mutant 1160 (ZM1160), a mutant obtained from ethyl methane sulfonate (EMS) treatment of hexaploid wheat variety Zhoumai32, was used to identify and clone the candidate gene that conditioned the spike shape. Genetic analysis of an F2 population derived from a cross of ZM1160 and Bainong207 suggested that the compact spike shape in ZM1160 was controlled by a single recessive gene, and therefore, the mutated gene was designated as Tasp1. With polymorphic markers identified through bulked segregant analysis (BSA), the gene was mapped to a 2.65-cM interval flanked by markers YZU0852 and MIS46239 on chromosome 7D, corresponding to a 0.42-Mb physical interval of Chinese spring (CS) reference sequences (RefSeq v1.0). To fine map TaSP1, 15 and seven recombinants were, respectively, screened from 1599 and 1903 F3 plants derived from the heterozygous F2 plants. Finally, TaSP1 was delimited to a 21.9 Kb (4,870,562 to 4,892,493 bp) Xmis48123-Xmis48104 interval. Only one high-confidence gene TraesCS7D02G010200 was annotated in this region, which encodes an unknown protein with a putative vWA domain. Quantitative reverse transcription PCR (qRT-PCR) analysis showed that TraesCS7D02G010200 was mainly expressed in the spike. Haplotype analysis of 655 wheat cultivars using the candidate gene-specific marker Xg010200p2 identified a superior haplotype TaSP1b with longer spike and more spikelet number. TaSP1 is beneficial to the improvement in wheat spike shape.
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Affiliation(s)
- Lin Zhang
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Huidan Zhou
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Xian Fu
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Niuniu Zhou
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Mengjie Liu
- School of Life Sciences, Henan University, Kaifeng, 475001, China
| | - Shenglong Bai
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Xinpeng Zhao
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China
| | - Ruiru Cheng
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
| | - Suoping Li
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
| | - Dale Zhang
- State Key Laboratory of Crop Stress Adaptation and Improvement, College of Agricultural Sciences, Henan University, Kaifeng, 475001, Henan, China.
- The Zhongzhou Laboratory for Integrative Biology, Zhengzhou, 450000, Henan, China.
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6
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Awan MJA, Farooq MA, Naqvi RZ, Karamat U, Bukhari SAR, Waqas MAB, Mahmood MA, Buzdar MI, Rasheed A, Amin I, Saeed NA, Mansoor S. Deciphering the differential expression patterns of yield-related negative regulators in hexaploid wheat cultivars and hybrids at different growth stages. Mol Biol Rep 2024; 51:537. [PMID: 38642174 DOI: 10.1007/s11033-024-09454-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 03/18/2024] [Indexed: 04/22/2024]
Abstract
BACKGROUND Hexaploid bread wheat underwent a series of polyploidization events through interspecific hybridizations that conferred adaptive plasticity and resulted in duplication and neofunctionalization of major agronomic genes. The genetic architecture of polyploid wheat not only confers adaptive plasticity but also offers huge genetic diversity. However, the contribution of different gene copies (homeologs) encoded from different subgenomes (A, B, D) at different growth stages remained unexplored. METHODS In this study, hybrid of elite cultivars of wheat were developed via reciprocal crosses (cytoplasm swapping) and phenotypically evaluated. We assessed differential expression profiles of yield-related negative regulators in these cultivars and their F1 hybrids and identified various cis-regulatory signatures by employing bioinformatics tools. Furthermore, the preferential expression patterns of the syntenic triads encoded from A, B, and D subgenomes were assessed to decipher their functional redundancy at six different growth stages. RESULTS Hybrid progenies showed better heterosis such as up to 17% increase in the average number of grains and up to 50% increase in average thousand grains weight as compared to mid-parents. Based on the expression profiling, our results indicated significant dynamic transcriptional expression patterns, portraying the different homeolog-dominance at the same stage in the different cultivars and their hybrids. Albeit belonging to same syntenic triads, a dynamic trend was observed in the regulatory signatures of these genes that might be influencing their expression profiles. CONCLUSION These findings can substantially contribute and provide insights for the selective introduction of better cultivars into traditional and hybrid breeding programs which can be harnessed for the improvement of future wheat.
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Affiliation(s)
- Muhammad Jawad Akbar Awan
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Muhammad Awais Farooq
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, College of Horticulture, Hebei Agricultural University, Baoding, China
| | - Rubab Zahra Naqvi
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Umer Karamat
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Collaborative Innovation Center of Vegetable Industry in Hebei, College of Horticulture, Hebei Agricultural University, Baoding, China
- Guangdong Key Laboratory for New Technology Research of Vegetables, Vegetable Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Sayyad Ali Raza Bukhari
- School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia
- Department of Biotechnology, University of Sargodha, Sargodha, Pakistan
| | - Muhammad Abu Bakar Waqas
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Muhammad Arslan Mahmood
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Muhammad Ismail Buzdar
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Awais Rasheed
- Department of Plant Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS) & CIMMYT-China office, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Imran Amin
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Nasir A Saeed
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan
| | - Shahid Mansoor
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Constituent College of Pakistan Institute of Engineering and Applied Sciences, Jhang Road, Faisalabad, Pakistan.
- International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan.
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Kartseva T, Aleksandrov V, Alqudah AM, Arif MAR, Kocheva K, Doneva D, Prokopova K, Börner A, Misheva S. GWAS in a Collection of Bulgarian Old and Modern Bread Wheat Accessions Uncovers Novel Genomic Loci for Grain Protein Content and Thousand Kernel Weight. PLANTS (BASEL, SWITZERLAND) 2024; 13:1084. [PMID: 38674493 PMCID: PMC11054703 DOI: 10.3390/plants13081084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/03/2024] [Accepted: 04/10/2024] [Indexed: 04/28/2024]
Abstract
Genetic enhancement of grain production and quality is a priority in wheat breeding projects. In this study, we assessed two key agronomic traits-grain protein content (GPC) and thousand kernel weight (TKW)-across 179 Bulgarian contemporary and historic varieties and landraces across three growing seasons. Significant phenotypic variation existed for both traits among genotypes and seasons, and no discernible difference was evident between the old and modern accessions. To understand the genetic basis of the traits, we conducted a genome-wide association study with MLM using phenotypic data from the crop seasons, best linear unbiased estimators, and genotypic data from the 25K Infinium iSelect array. As a result, we detected 16 quantitative trait nucleotides (QTNs) associated with GPC and 15 associated with TKW, all of which passed the false discovery rate threshold. Seven loci favorably influenced GPC, resulting in an increase of 1.4% to 8.1%, while four loci had a positive impact on TKW with increases ranging from 1.9% to 8.4%. While some loci confirmed previously published associations, four QTNs linked to GPC on chromosomes 2A, 7A, and 7B, as well as two QTNs related to TKW on chromosomes 1B and 6A, may represent novel associations. Annotations for proteins involved in the senescence-associated nutrient remobilization and in the following buildup of resources required for seed germination have been found for selected putative candidate genes. These include genes coding for storage proteins, cysteine proteases, cellulose-synthase, alpha-amylase, transcriptional regulators, and F-box and RWP-RK family proteins. Our findings highlight promising genomic regions for targeted breeding programs aimed at improving grain yield and protein content.
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Affiliation(s)
- Tania Kartseva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Vladimir Aleksandrov
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Ahmad M. Alqudah
- Biological Science Program, Department of Biological and Environmental Sciences, College of Art and Science, Qatar University, Doha P.O. Box 2713, Qatar;
| | - Mian Abdur Rehman Arif
- Nuclear Institute for Agriculture and Biology College, Pakistan Institute of Engineering and Applied Sciences (NIAB-C, PIEAS), Jhang Road, Faisalabad 38000, Pakistan;
| | - Konstantina Kocheva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Dilyana Doneva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Katelina Prokopova
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
| | - Andreas Börner
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK Gatersleben), OT Gatersleben, Corrensstraße 3, 06466 Seeland, Germany;
| | - Svetlana Misheva
- Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 21, 1113 Sofia, Bulgaria; (T.K.); (V.A.)
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8
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Wang J, Wang E, Cheng S, Ma A. Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228. BMC PLANT BIOLOGY 2024; 24:271. [PMID: 38605289 PMCID: PMC11008026 DOI: 10.1186/s12870-024-04913-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 03/15/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228. METHODS The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits. RESULTS A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25-17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds. CONCLUSION This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.
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Affiliation(s)
- Jiansheng Wang
- College of Chemistry and Environment Engineering, Pingdingshan University, North to Weilailu road, New district, Pingdingshan, Henan, 467000, China.
- Henan Key Laboratory of Germplasm Innovation and Utilization of Eco-economic Woody Plant, Pingdingshan, Henan, China.
| | - Erwei Wang
- Pingdingshan Academy of Agricultural Science, Pingdingshan, Henan, 467001, China
| | - Shiping Cheng
- College of Chemistry and Environment Engineering, Pingdingshan University, North to Weilailu road, New district, Pingdingshan, Henan, 467000, China
- Henan Key Laboratory of Germplasm Innovation and Utilization of Eco-economic Woody Plant, Pingdingshan, Henan, China
| | - Aichu Ma
- Pingdingshan Academy of Agricultural Science, Pingdingshan, Henan, 467001, China
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Caldara M, Gullì M, Graziano S, Riboni N, Maestri E, Mattarozzi M, Bianchi F, Careri M, Marmiroli N. Microbial consortia and biochar as sustainable biofertilisers: Analysis of their impact on wheat growth and production. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 917:170168. [PMID: 38244628 DOI: 10.1016/j.scitotenv.2024.170168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/11/2024] [Accepted: 01/12/2024] [Indexed: 01/22/2024]
Abstract
The European Union is among the top wheat producers in the world, but its productivity relies on adequate soil fertilisation. Biofertilisers, either alone or in combination with biochar, can be a preferable alternative to chemical fertilisers. However, the addition of biofertilisers, specifically plant growth promoting microbes (PGPM), could modify grain composition, and/or deteriorate the soil composition. In this study, the two wheat cultivars Triticum aestivum (Bramante) and T. durum (Svevo) were cultivated in open fields for two consecutive years in the presence of a commercial PGPM mix supplied alone or in combination with biochar. An in-depth analysis was conducted by collecting physiological and agronomic data throughout the growth period. The effects of PGPM and biochar were investigated in detail; specifically, soil chemistry and rhizosphere microbial composition were characterized, along with the treatment effects on seed storage proteins. The results demonstrated that the addition of commercial microbial consortia and biochar, alone or in combination, did not modify the rhizospheric microbial community; however, it increased grain yield, especially in the cultivar Svevo (increase of 6.8 %-13.6 %), even though the factors driving the most variations were associated with both climate and cultivar. The total gluten content of the flours was not affected, whereas the main effect of the treatments was a variation in gliadins and low-molecular-weight-glutenin subunits in both cultivars when treated with PGPM and biochar. This suggested improved grain quality, especially regarding the viscoelastic properties of the dough, when the filling period occurred in a dry climate. The results indicate that the application of biofertilisers and biochar may aid the effective management of sustainable wheat cultivation, to support environmental health without altering the biodiversity of the resident microbiome.
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Affiliation(s)
- Marina Caldara
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Mariolina Gullì
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Sara Graziano
- Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Nicolò Riboni
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Elena Maestri
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; National Interuniversity Consortium for Environmental Sciences (CINSA), Parco Area delle Scienze, 43124 Parma, Italy
| | - Monica Mattarozzi
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Federica Bianchi
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center CIDEA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Maria Careri
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy
| | - Nelson Marmiroli
- Department of Chemistry, Life Science and Environmental Sustainability, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; Interdepartmental Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze, 43124 Parma, Italy; National Interuniversity Consortium for Environmental Sciences (CINSA), Parco Area delle Scienze, 43124 Parma, Italy.
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10
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Li Z, Luo Q, Gan Y, Li X, Ou X, Deng Y, Fu S, Tang Z, Tan F, Luo P, Ren T. Identification and validation of major and stable quantitative trait locus for falling number in common wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:83. [PMID: 38491113 DOI: 10.1007/s00122-024-04588-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 02/22/2024] [Indexed: 03/18/2024]
Abstract
KEY MESSAGE A major and stable QTL, QFn.sau-1B.2, which can explain 13.6% of the PVE in FN and has a positive effect on resistance in SGR, was mapped and validated. The falling number (FN) is considered one of the most important quality traits of wheat grain and is the most important quality evaluation index for wheat trade worldwide. The quantitative trait loci (QTLs) for FN were mapped in three years of experiments. 23, 30, and 58 QTLs were identified using the ICIM-BIP, ICIM-MET, and ICIM-EPI methods, respectively. Among them, seven QTLs were considered stable. QFn.sau-1B.2, which was mapped to the 1BL chromosome, can explain 13.6% of the phenotypic variation on average and is considered a major and stable QTL for FN. This QTL was mapped in a 1 cM interval and is flanked by the markers AX-110409346 and AX-108743901. Epistatic analysis indicated that QFN.sau-1B.2 has a strong influence on FN through both additive and epistatic effects. The Kompetitive Allele-Specific PCR marker KASP-AX-108743901, which is closely linked to QFn.sau-1B.2, was designed. The genetic effect of QFn.sau-1B.2 on FN was successfully confirmed in Chuannong18 × T1208 and CN17 × CN11 populations. Moreover, the results of the additive effects of favorable alleles for FN showed that the QTLs for FN had significant effects not only on FN but also on the resistance to spike germination. Within the interval of QFn.sau-1B.2, 147 high-confidence genes were found. According to the gene annotation and the transcriptome data, four genes might be associated with FN. QFn.sau-1B.2 may provide a new resource for the high-quality breeding of wheat in the future.
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Affiliation(s)
- Zhi Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Qinyi Luo
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Yujie Gan
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Xinli Li
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Xia Ou
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Yawen Deng
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Shulan Fu
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Zongxiang Tang
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Feiquan Tan
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Peigao Luo
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China
| | - Tianheng Ren
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China.
- College of Agronomy, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, Sichuan, China.
- Key Laboratory of Plant Genetics and Breeding at, Sichuan Agricultural University of Sichuan Province, Wenjiang, Chengdu, 611130, Sichuan, China.
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11
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Bi C, Wei C, Li J, Wen S, Zhao H, Yu J, Shi X, Zhang Y, Liu Q, Zhang Y, Li B, You M. A novel variation of TaGW2-6B increases grain weight without penalty in grain protein content in wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:15. [PMID: 38362529 PMCID: PMC10864231 DOI: 10.1007/s11032-024-01455-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 01/23/2024] [Indexed: 02/17/2024]
Abstract
Yield and quality are two crucial breeding objects of wheat therein grain weight and grain protein content (GPC) are two key relevant factors correspondingly. Investigations of their genetic mechanisms represent special significance for breeding. In this study, 199 F2 plants and corresponding F2:3 families derived from Nongda3753 (ND3753) and its EMS-generated mutant 564 (M564) were used to investigate the genetic basis of larger grain and higher GPC of M564. QTL analysis identified a total of 33 environmentally stable QTLs related to thousand grain weight (TGW), grain area (GA), grain circle (GC), grain length (GL), grain width (GW), and GPC on chromosomes 1B, 2A, 2B, 4D, 6B, and 7D, respectively, among which QGw.cau-6B.1, QTgw.cau-6B.1, QGa.cau-6B.1, and QGc.cau-6B.1 shared overlap confidence interval on chromosome 6B. This interval contained the TaGW2 gene playing the same role as the QTLs, so TaGW2-6B was cloned and sequenced. Sequence alignment revealed two G/A SNPs between two parents, among which the SNP in the seventh exon led to a premature termination in M564. A KASP marker was developed based on the SNP, and single-marker analysis on biparental populations showed that the mutant allele could significantly increase GW and TGW, but had no effect on GPC. Distribution detection of the mutant allele through KASP marker genotyping and sequence alignment against databases ascertained that no materials harbored this allele within natural populations. This allele was subsequently introduced into three different varieties through molecular marker-assisted backcrossing, and it was revealed that the allele had a significant effect on simultaneously increasing GW, TGW, and even GPC in all of three backgrounds. Summing up the above, it could be concluded that a novel elite allele of TaGW2-6B was artificially created and might play an important role in wheat breeding for high yield and quality. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01455-y.
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Affiliation(s)
- Chan Bi
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Chaoxiong Wei
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Jinghui Li
- Wheat Center, Henan Institute of Science and Technology, Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang, 453003 China
| | - Shaozhe Wen
- Department of Landscape and Garden, Yangzhou Polytechnic College, Yangzhou, 225009 China
| | - Huanhuan Zhao
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Jiazheng Yu
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Xintian Shi
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Yuan Zhang
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Qiaofeng Liu
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Yufeng Zhang
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Baoyun Li
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
| | - Mingshan You
- State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Ministry of Education, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193 China
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12
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Lindsay P, Swentowsky KW, Jackson D. Cultivating potential: Harnessing plant stem cells for agricultural crop improvement. MOLECULAR PLANT 2024; 17:50-74. [PMID: 38130059 DOI: 10.1016/j.molp.2023.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023]
Abstract
Meristems are stem cell-containing structures that produce all plant organs and are therefore important targets for crop improvement. Developmental regulators control the balance and rate of cell divisions within the meristem. Altering these regulators impacts meristem architecture and, as a consequence, plant form. In this review, we discuss genes involved in regulating the shoot apical meristem, inflorescence meristem, axillary meristem, root apical meristem, and vascular cambium in plants. We highlight several examples showing how crop breeders have manipulated developmental regulators to modify meristem growth and alter crop traits such as inflorescence size and branching patterns. Plant transformation techniques are another innovation related to plant meristem research because they make crop genome engineering possible. We discuss recent advances on plant transformation made possible by studying genes controlling meristem development. Finally, we conclude with discussions about how meristem research can contribute to crop improvement in the coming decades.
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Affiliation(s)
- Penelope Lindsay
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - David Jackson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, 430070, China.
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13
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López-Fernández M, García-Abadillo J, Uauy C, Ruiz M, Giraldo P, Pascual L. Genome wide association in Spanish bread wheat landraces identifies six key genomic regions that constitute potential targets for improving grain yield related traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:244. [PMID: 37957405 PMCID: PMC10643358 DOI: 10.1007/s00122-023-04492-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023]
Abstract
KEY MESSAGE Association mapping conducted in 189 Spanish bread wheat landraces revealed six key genomic regions that constitute stable QTLs for yield and include 15 candidate genes. Genetically diverse landraces provide an ideal population to conduct association analysis. In this study, association mapping was conducted in a collection of 189 Spanish bread wheat landraces whose genomic diversity had been previously assessed. These genomic data were combined with characterization for yield-related traits, including grain size and shape, and phenological traits screened across five seasons. The association analysis revealed a total of 881 significant marker trait associations, involving 434 markers across the genome, that could be grouped in 366 QTLs based on linkage disequilibrium. After accounting for days to heading, we defined 33 high density QTL genomic regions associated to at least four traits. Considering the importance of detecting stable QTLs, 6 regions associated to several grain traits and thousand kernel weight in at least three environments were selected as the most promising ones to harbour targets for breeding. To dissect the genetic cause of the observed associations, we studied the function and in silico expression of the 413 genes located inside these six regions. This identified 15 candidate genes that provide a starting point for future analysis aimed at the identification and validation of wheat yield related genes.
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Affiliation(s)
- Matilde López-Fernández
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Julián García-Abadillo
- Department of Biotechnology and Plant Biology, Centre for Biotechnology and Plant Genomics (CBGP), Universidad Politécnica de Madrid (UPM), Madrid, Spain
| | - Cristobal Uauy
- John Innes Centre, Norwich Research Park, Norwich, NR4 7UH, UK
| | - Magdalena Ruiz
- Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA), CSIC, Autovía A2, Km. 36.2. Finca La Canaleja, 28805, Alcalá de Henares, Madrid, Spain
| | - Patricia Giraldo
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.
| | - Laura Pascual
- Department of Biotechnology-Plant Biology, School of Agricultural, Food and Biosystems Engineering (ETSIAAB), Universidad Politécnica de Madrid (UPM), Madrid, Spain
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14
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Dallinger HG, Löschenberger F, Bistrich H, Ametz C, Hetzendorfer H, Morales L, Michel S, Buerstmayr H. Predictor bias in genomic and phenomic selection. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:235. [PMID: 37878079 PMCID: PMC10600307 DOI: 10.1007/s00122-023-04479-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 09/08/2023] [Indexed: 10/26/2023]
Abstract
KEY MESSAGE NIRS of wheat grains as phenomic predictors for grain yield show inflated prediction ability and are biased toward grain protein content. Estimating the breeding value of individuals using genome-wide marker data (genomic prediction) is currently one of the most important drivers of breeding progress in major crops. Recently, phenomic technologies, including remote sensing and aerial hyperspectral imaging of plant canopies, have made it feasible to predict the breeding value of individuals in the absence of genetic marker data. This is commonly referred to as phenomic prediction. Hyperspectral measurements in the form of near-infrared spectroscopy have been used since the 1980 s to predict compositional parameters of harvest products. Moreover, in recent studies NIRS from grains was used to predict grain yield. The same studies showed that phenomic prediction can outperform genomic prediction for grain yield. The genome is static and not environment dependent, thereby limiting genomic prediction ability. Gene expression is tissue specific and differs under environmental influences, leading to a tissue- and environment-specific phenome, potentially explaining the higher predictive ability of phenomic prediction. Here, we compare genomic prediction and phenomic prediction from hyperspectral measurements of wheat grains for the prediction of a variety of traits including grain yield. We show that phenomic predictions outperform genomic prediction for some traits. However, phenomic predictions are biased toward the information present in the predictor. Future studies on this topic should investigate whether population parameters are retained in phenomic prediction as they are in genomic prediction. Furthermore, we find that unbiased phenomic prediction abilities are considerably lower than previously reported and recommend a method to circumvent this issue.
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Affiliation(s)
- Hermann Gregor Dallinger
- Institute of Biotechnology in Plant Production, Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria.
- Saatzucht Donau GesmbH & Co KG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria.
| | | | - Herbert Bistrich
- Saatzucht Donau GesmbH & Co KG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria
| | - Christian Ametz
- Saatzucht Donau GesmbH & Co KG, Saatzuchtstrasse 11, 2301, Probstdorf, Austria
| | | | - Laura Morales
- Institute of Biotechnology in Plant Production, Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria
| | - Sebastian Michel
- Institute of Biotechnology in Plant Production, Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria
| | - Hermann Buerstmayr
- Institute of Biotechnology in Plant Production, Department of Agrobiotechnology, IFA-Tulln, University of Natural Resources and Life Sciences Vienna, Konrad-Lorenz-Str. 20, 3430, Tulln, Austria
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15
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Valladares García AP, Desiderio F, Simeone R, Ravaglia S, Ciorba R, Fricano A, Guerra D, Blanco A, Cattivelli L, Mazzucotelli E. QTL mapping for kernel-related traits in a durum wheat x T. dicoccum segregating population. FRONTIERS IN PLANT SCIENCE 2023; 14:1253385. [PMID: 37849841 PMCID: PMC10577384 DOI: 10.3389/fpls.2023.1253385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/28/2023] [Indexed: 10/19/2023]
Abstract
Durum wheat breeding relies on grain yield improvement to meet its upcoming demand while coping with climate change. Kernel size and shape are the determinants of thousand kernel weight (TKW), which is a key component of grain yield, and the understanding of the genetic control behind these traits supports the progress in yield potential. The present study aimed to dissect the genetic network responsible for kernel size components (length, width, perimeter, and area) and kernel shape traits (width-to-length ratio and formcoefficient) as well as their relationships with kernel weight, plant height, and heading date in durum wheat. Quantitative Trait Locus (QTL) mapping was performed on a segregating population of 110 recombinant inbred lines, derived from a cross between the domesticated emmer wheat accession MG5323 and the durum wheat cv. Latino, evaluated in four different environments. A total of 24 QTLs stable across environments were found and further grouped in nine clusters on chromosomes 2A, 2B, 3A, 3B, 4B, 6B, and 7A. Among them, a QTL cluster on chromosome 4B was associated with kernel size traits and TKW, where the parental MG5323 contributed the favorable alleles, highlighting its potential to improve durum wheat germplasm. The physical positions of the clusters, defined by the projection on the T. durum reference genome, overlapped with already known genes (i.e., BIG GRAIN PROTEIN 1 on chromosome 4B). These results might provide genome-based guidance for the efficient exploitation of emmer wheat diversity in wheat breeding, possibly through yield-related molecular markers.
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Affiliation(s)
- Ana Paola Valladares García
- Instituto de Conservación y Mejora de la Agrodiversidad Valenciana (COMAV), Universitat Politècnica de València, Valencia, Spain
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Francesca Desiderio
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Rosanna Simeone
- Department of Soil, Plant and Food Sciences (DiSSPA), Genetics and Plant Breeding Section, University of Bari Aldo Moro, Bari, Italy
| | | | - Roberto Ciorba
- Council for Agricultural Research and Economics (CREA) - Research Centre for Olive, Fruit and Citrus Crops, Rome, Italy
| | - Agostino Fricano
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Davide Guerra
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Antonio Blanco
- Department of Soil, Plant and Food Sciences (DiSSPA), Genetics and Plant Breeding Section, University of Bari Aldo Moro, Bari, Italy
| | - Luigi Cattivelli
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
| | - Elisabetta Mazzucotelli
- Council for Agricultural Research and Economics (CREA) - Research Centre for Genomics and Bioinformatics, Fiorenzuola d’Arda, Italy
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16
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Gao J, Hu X, Gao C, Chen G, Feng H, Jia Z, Zhao P, Yu H, Li H, Geng Z, Fu J, Zhang J, Cheng Y, Yang B, Pang Z, Xiang D, Jia J, Su H, Mao H, Lan C, Chen W, Yan W, Gao L, Yang W, Li Q. Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat. PLANT BIOTECHNOLOGY JOURNAL 2023; 21:1966-1977. [PMID: 37392004 PMCID: PMC10502759 DOI: 10.1111/pbi.14104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 04/11/2023] [Accepted: 06/07/2023] [Indexed: 07/02/2023]
Abstract
Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.
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Affiliation(s)
- Jie Gao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Xin Hu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Chunyan Gao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Guang Chen
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Hui Feng
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Zhen Jia
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Peimin Zhao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Haiyang Yu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Huaiwen Li
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Zedong Geng
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Jingbo Fu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Jun Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Yikeng Cheng
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Bo Yang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Zhanghan Pang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Daoquan Xiang
- Aquatic and Crop Resource DevelopmentNational Research Council CanadaSaskatoonSaskatchewanCanada
| | - Jizeng Jia
- Institute of Crop SciencesChinese Academy of Crop Sciences (CAAS)BeijingChina
| | - Handong Su
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Caixia Lan
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina
| | - Wei Chen
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina
| | - Wenhao Yan
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina
| | - Lifeng Gao
- Institute of Crop SciencesChinese Academy of Crop Sciences (CAAS)BeijingChina
| | - Wanneng Yang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhanChina
| | - Qiang Li
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- The Center of Crop NanobiotechnologyHuazhong Agricultural UniversityWuhanChina
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17
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Zhao Y, Liu Z. Ring the yield: regulation of spike architecture by an E3 ubiquitin ligase in crops. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:4889-4891. [PMID: 37702014 PMCID: PMC10498019 DOI: 10.1093/jxb/erad281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
This article comments on:
Zhang J, Li C, Li L, Xi Y, Wang J, Mao X, Jing R. 2023. RING finger E3 ubiquitin ligase gene TaAIRP2-1B controls spike length in wheat. Journal of Experimental Botany 74, 5014–5025.
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Affiliation(s)
- Yusheng Zhao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Zhiyong Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
- Hainan Yazhou Bay Seed Laboratory, Sanya City, Hainan Province, China
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18
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Liu Y, Chen J, Yin C, Wang Z, Wu H, Shen K, Zhang Z, Kang L, Xu S, Bi A, Zhao X, Xu D, He Z, Zhang X, Hao C, Wu J, Gong Y, Yu X, Sun Z, Ye B, Liu D, Zhang L, Shen L, Hao Y, Ma Y, Lu F, Guo Z. A high-resolution genotype-phenotype map identifies the TaSPL17 controlling grain number and size in wheat. Genome Biol 2023; 24:196. [PMID: 37641093 PMCID: PMC10463835 DOI: 10.1186/s13059-023-03044-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Large-scale genotype-phenotype association studies of crop germplasm are important for identifying alleles associated with favorable traits. The limited number of single-nucleotide polymorphisms (SNPs) in most wheat genome-wide association studies (GWASs) restricts their power to detect marker-trait associations. Additionally, only a few genes regulating grain number per spikelet have been reported due to sensitivity of this trait to variable environments. RESULTS We perform a large-scale GWAS using approximately 40 million filtered SNPs for 27 spike morphology traits. We detect 132,086 significant marker-trait associations and the associated SNP markers are located within 590 associated peaks. We detect additional and stronger peaks by dividing spike morphology into sub-traits relative to GWAS results of spike morphology traits. We propose that the genetic dissection of spike morphology is a powerful strategy to detect signals for grain yield traits in wheat. The GWAS results reveal that TaSPL17 positively controls grain size and number by regulating spikelet and floret meristem development, which in turn leads to enhanced grain yield per plant. The haplotypes at TaSPL17 indicate geographical differentiation, domestication effects, and breeding selection. CONCLUSION Our study provides valuable resources for genetic improvement of spike morphology and a fast-forward genetic solution for candidate gene detection and cloning in wheat.
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Affiliation(s)
- Yangyang Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jun Chen
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Ziying Wang
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - He Wu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kuocheng Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiliang Zhang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Lipeng Kang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Song Xu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Aoyue Bi
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Xuebo Zhao
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Daxing Xu
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China
| | - Zhonghu He
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, Beijing, 100081, China
| | - Xueyong Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Chenyang Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Jianhui Wu
- State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Yan Gong
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Xuchang Yu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiwen Sun
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Botao Ye
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Danni Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lili Zhang
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Liping Shen
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China
| | - Yuanfeng Hao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
| | - Youzhi Ma
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China.
| | - Fei Lu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, 10011, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100093, China.
| | - Zifeng Guo
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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19
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Zhang Y, Miao H, Xiao Y, Wang C, Zhang J, Shi X, Xie S, Wang C, Li T, Deng P, Chen C, Zhang H, Ji W. An intron-located single nucleotide variation of TaGS5-3D is related to wheat grain size through accumulating intron retention transcripts. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:193. [PMID: 37606787 DOI: 10.1007/s00122-023-04439-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/31/2023] [Indexed: 08/23/2023]
Abstract
KEY MESSAGE Thirty-three stable QTL for 13 yield-related traits across ten environments were identified in the PD34/MY47 RIL population, and a candidate gene TaGS5-3D in Qmt.nwafu.3D was preliminarily identified to affect grain-related traits through accumulation of specific transcripts. Dissecting the genetic basis of yield-related traits is pivotal for improvement of wheat yield potential. In this study, a recombinant inbred line (RIL) population genotyped by SNP markers was used to detect quantitative trait loci (QTL) related to yield-related traits in ten environments. A total of 102 QTL were detected, including 33 environmentally stable QTL and 69 putative QTL. Among them, Qmt.nwafu.3D was identified as a pleiotropic QTL in the physical interval of 149.77-154.11 Mb containing a potential candidate gene TaGS5-3D. An SNP (T > C) was detected in its ninth intron, and TaGS5-3D-C was validated as a superior allele associated with larger grains using a CAPS marker. Interestingly, we found that TaGS5-3D-C was closely related to significantly up-regulated expression of intron-retained transcript (TaGS5-3D-PD34.1), while TaGS5-3D-T was related to dominant expression of normal splicing transcript (TaGS5-3D-MY47.1). Our results indicated that alternative splicing associated with the SNP T/C could be involved in the regulation of grain-related traits, laying a foundation for the functional analysis of TaGS5-3D and its greater potential application in high-yield wheat breeding.
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Affiliation(s)
- Yaoyuan Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Hanxiao Miao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Yi Xiao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Chao Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Junjie Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Xiaoxi Shi
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Songfeng Xie
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
| | - Changyou Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Tingdong Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Pingchuan Deng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Chunhuan Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China
| | - Hong Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
| | - Wanquan Ji
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling, 712100, China.
- Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.
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20
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Song C, Xie K, Hu X, Zhou Z, Liu A, Zhang Y, Du J, Jia J, Gao L, Mao H. Genome wide association and haplotype analyses for the crease depth trait in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 14:1203253. [PMID: 37465391 PMCID: PMC10350514 DOI: 10.3389/fpls.2023.1203253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 06/14/2023] [Indexed: 07/20/2023]
Abstract
Wheat grain has a complex structure that includes a crease on one side, and tissues within the crease region play an important role in nutrient transportation during wheat grain development. However, the genetic architecture of the crease region is still unclear. In this study, 413 global wheat accessions were resequenced and a method was developed for evaluating the phenotypic data of crease depth (CD). The CD values exhibited continuous and considerable large variation in the population, and the broad-sense heritability was 84.09%. CD was found to be positively correlated with grain-related traits and negatively with quality-related traits. Analysis of differentiation of traits between landraces and cultivars revealed that grain-related traits and CD were simultaneously improved during breeding improvement. Moreover, 2,150.8-Mb genetic segments were identified to fall within the selective sweeps between the landraces and cultivars; they contained some known functional genes for quality- and grain-related traits. Genome-wide association study (GWAS) was performed using around 10 million SNPs generated by genome resequencing and 551 significant SNPs and 18 QTLs were detected significantly associated with CD. Combined with cluster analysis of gene expression, haplotype analysis, and annotated information of candidate genes, two promising genes TraesCS3D02G197700 and TraesCS5A02G292900 were identified to potentially regulate CD. To the best of our knowledge, this is the first study to provide the genetic basis of CD, and the genetic loci identified in this study may ultimately assist in wheat breeding programs.
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Affiliation(s)
- Chengxiang Song
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Kaidi Xie
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Zhihua Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Ankui Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yuwei Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jiale Du
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jizeng Jia
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Lifeng Gao
- Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing, China
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
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21
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Liu B, Li L, Fu C, Zhang Y, Bai B, Du J, Zeng J, Bian Y, Liu S, Song J, Luo X, Xie L, Sun M, Xu X, Xia X, Cao S. Genetic dissection of grain morphology and yield components in a wheat line with defective grain filling. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:165. [PMID: 37392240 DOI: 10.1007/s00122-023-04410-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/22/2023] [Indexed: 07/03/2023]
Abstract
KEY MESSAGE We identified stable QTL for grain morphology and yield component traits in a wheat defective grain filling line and validated genetic effects in a panel of cultivars using breeding-relevant markers. Grain filling capacity is essential for grain yield and appearance quality in cereal crops. Identification of genetic loci for grain filling is important for wheat improvement. However, there are few genetic studies on grain filling in wheat. Here, a defective grain filling (DGF) line wdgf1 characterized by shrunken grains was identified in a population derived from multi-round crosses involving nine parents and a recombinant inbreed line (RIL) population was generated from the cross between wdgf1 and a sister line with normal grains. We constructed a genetic map of the RIL population using the wheat 15K single nucleotide polymorphism chip and detected 25 stable quantitative trait loci (QTL) for grain morphology and yield components, including three for DGF, eleven for grain size, six for thousand grain weight, three for grain number per spike and two for spike number per m2. Among them, QDGF.caas-7A is co-located with QTGW.caas-7A and can explain 39.4-64.6% of the phenotypic variances, indicating that this QTL is a major locus controlling DGF. Sequencing and linkage mapping showed that TaSus2-2B and Rht-B1 were candidate genes for QTGW.caas-2B and the QTL cluster (QTGW.caas-4B, QGNS.caas-4B, and QSN.caas-4B), respectively. We developed kompetitive allele-specific PCR markers tightly linked to the stable QTL without corresponding to known yield-related genes, and validated their genetic effects in a diverse panel of wheat cultivars. These findings not only lay a solid foundation for genetic dissection underlying grain filling and yield formation, but also provide useful tools for marker-assisted breeding.
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Affiliation(s)
- Bingyan Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Lingli Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Chao Fu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Yingjun Zhang
- Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences, Laboratory of Crop Genetics and Breeding of Hebei, Shijiazhuang, China
| | - Bin Bai
- Wheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Jiuyuan Du
- Wheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China
| | - Jianqi Zeng
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Yingjie Bian
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Siyang Liu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Jie Song
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Xumei Luo
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Lina Xie
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Mengjing Sun
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Xiaowan Xu
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Shuanghe Cao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.
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22
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Chang C, Zhang H, Lu J, Si H, Ma C. Genetic Improvement of Wheat with Pre-Harvest Sprouting Resistance in China. Genes (Basel) 2023; 14:genes14040837. [PMID: 37107595 PMCID: PMC10137347 DOI: 10.3390/genes14040837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/03/2023] Open
Abstract
Wheat pre-harvest sprouting (PHS) refers to the germination of seeds directly on the spike due to rainy weather before harvest, which often results in yield reduction, quality deterioration, and seed value loss. In this study, we reviewed the research progress in the quantitative trait loci (QTL) detection and gene excavation related to PHS resistance in wheat. Simultaneously, the identification and creation of germplasm resources and the breeding of wheat with PHS resistance were expounded in this study. Furthermore, we also discussed the prospect of molecular breeding during genetic improvement of PHS-resistant wheat.
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23
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Niu J, Si Y, Tian S, Liu X, Shi X, Ma S, Yu Z, Ling HQ, Zheng S. A Wheat 660 K SNP array-based high-density genetic map facilitates QTL mapping of flag leaf-related traits in wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:51. [PMID: 36913011 DOI: 10.1007/s00122-023-04248-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/26/2022] [Indexed: 06/18/2023]
Abstract
A high-density genetic map containing 122,620 SNP markers was constructed, which facilitated the identification of eight major flag leaf-related QTL in relatively narrow intervals. The flag leaf plays an important role in photosynthetic capacity and yield potential in wheat. In this study, we used a recombinant inbred line population containing 188 lines derived from a cross between 'Lankao86' (LK86) and 'Ermangmai' to construct a genetic map using the Wheat 660 K single-nucleotide polymorphism (SNP) array. The high-density genetic map contains 122,620 SNP markers spanning 5185.06 cM. It shows good collinearity with the physical map of Chinese Spring and anchors multiple sequences of previously unplaced scaffolds onto chromosomes. Based on the high-density genetic map, we identified seven, twelve, and eight quantitative trait loci (QTL) for flag leaf length (FLL), width (FLW), and area (FLA) across eight environments, respectively. Among them, three, one, and four QTL for FLL, FLW, and FLA are major and stably express in more than four environments. The physical distance between the flanking markers for QFll.igdb-3B/QFlw.igdb-3B/QFla.igdb-3B is only 444 kb containing eight high confidence genes. These results suggested that we could directly map the candidate genes in a relatively small region by the high-density genetic map constructed with the Wheat 660 K array. Furthermore, the identification of environmentally stable QTL for flag leaf morphology laid a foundation for the following gene cloning and flag leaf morphology improvement.
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Affiliation(s)
- Jianqing Niu
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Yaoqi Si
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Shuiquan Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaolin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Shi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Shengwei Ma
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Zhongqing Yu
- National Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Taian, China
| | - Hong-Qing Ling
- Hainan Yazhou Bay Seed Lab, Sanya, Hainan, China.
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.
| | - Shusong Zheng
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China.
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24
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Zhao J, Li X, Qiao L, Zheng X, Wu B, Guo M, Feng M, Qi Z, Yang W, Zheng J. Identification of structural variations related to drought tolerance in wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:37. [PMID: 36897407 DOI: 10.1007/s00122-023-04283-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/07/2022] [Indexed: 06/18/2023]
Abstract
Structural variations are common in plant genomes, affecting meiotic recombination and distorted segregation in wheat. And presence/absence variations can significantly affect drought tolerance in wheat. Drought is a major abiotic stress limiting wheat production. Common wheat has a complex genome with three sub-genomes, which host large numbers of structural variations (SVs). SVs play critical roles in understanding the genetic contributions of plant domestication and phenotypic plasticity, but little is known about their genomic characteristics and their effects on drought tolerance. In the present study, high-resolution karyotypes of 180 doubled haploids (DHs) were developed. Signal polymorphisms between the parents involved with 8 presence-absence variations (PAVs) of tandem repeats (TR) distributed on the 7 (2A, 4A, 5A, 7A, 3B, 7B, and 2D) of 21 chromosomes. Among them, PAV on chromosome 2D showed distorted segregation, others transmit normal conforming to a 1:1 segregation ration in the population; and a PAVs recombination occurred on chromosome 2A. Association analysis of PAV and phenotypic traits under different water regimes, we found PAVs on chromosomes 4A, 5A, and 7B showed negative effect on grain length (GL) and grain width (GW); PAV.7A had opposite effect on grain thickness (GT) and spike length (SL), with the effect on traits differing under different water regimes. PAVs on linkage group 2A, 4A, 7A, 2D, and 7B associated with the drought tolerance coefficients (DTCs), and significant negative effect on drought resistance values (D values) were detected in PAV.7B. Additionally, quantitative trait loci (QTL) associated with phenotypic traits using the 90 K SNP array showed QTL for DTCs and grain-related traits in chromosomes 4A, and 5A, 3B were co-localized in differential regions of PAVs. These PAVs can cause the differentiation of the target region of SNP and could be used for genetic improvement of agronomic traits under drought stress via marker-assisted selection (MAS) breeding.
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Affiliation(s)
- Jiajia Zhao
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Xiaohua Li
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Ling Qiao
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Bangbang Wu
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Meijun Guo
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
- Jinzhong University, Jinzhong, China
| | - Meichen Feng
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China
| | - Zengjun Qi
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Wude Yang
- College of Agriculture, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Taigu, China.
| | - Jun Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China.
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25
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Xu D, Hao Q, Yang T, Lv X, Qin H, Wang Y, Jia C, Liu W, Dai X, Zeng J, Zhang H, He Z, Xia X, Cao S, Ma W. Impact of "Green Revolution" gene Rht-B1b on coleoptile length of wheat. FRONTIERS IN PLANT SCIENCE 2023; 14:1147019. [PMID: 36938052 PMCID: PMC10017974 DOI: 10.3389/fpls.2023.1147019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Wheat coleoptile is a sheath-like structure that helps to deliver the first leaf from embryo to the soil surface. Here, a RIL population consisting of 245 lines derived from Zhou 8425B × Chinese Spring cross was genotyped by the high-density Illumina iSelect 90K assay for coleoptile length (CL) QTL mapping. Three QTL for CL were mapped on chromosomes 2BL, 4BS and 4DS. Of them, two major QTL QCL.qau-4BS and QCL.qau-4DS were detected, which could explain 9.1%-22.2% of the phenotypic variances across environments on Rht-B1 and Rht-D1 loci, respectively. Several studies have reported that Rht-B1b may reduce the length of wheat CL but no study has been carried out at molecular level. In order to verify that the Rht-B1 gene is the functional gene for the 4B QTL, an overexpression line Rht-B1b-OE and a CRISPR/SpCas9 line Rht-B1b-KO were studied. The results showed that Rht-B1b overexpression could reduce the CL, while loss-of-function of Rht-B1b would increase the CL relative to that of the null transgenic plants (TNL). To dissect the underlying regulatory mechanism of Rht-B1b on CL, comparative RNA-Seq was conducted between Rht-B1b-OE and TNL. Transcriptome profiles revealed a few key pathways involving the function of Rht-B1b in coleoptile development, including phytohormones, circadian rhythm and starch and sucrose metabolism. Our findings may facilitate wheat breeding for longer coleoptiles to improve seedling early vigor for better penetration through the soil crust in arid regions.
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Affiliation(s)
- Dengan Xu
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Qianlin Hao
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Tingzhi Yang
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Xinru Lv
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Huimin Qin
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Yalin Wang
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Chenfei Jia
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Wenxing Liu
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Xuehuan Dai
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Jianbin Zeng
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Hongsheng Zhang
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xianchun Xia
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shuanghe Cao
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wujun Ma
- College of Agronomy, Qingdao Agricultural University, Qingdao, China
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26
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Jiang P, Fan X, Zhang G, Wu L, He Y, Li C, Zhang X. Cost-effective duplex Kompetitive Allele Specific PCR markers for homologous genes facilitating wheat breeding. BMC PLANT BIOLOGY 2023; 23:119. [PMID: 36855097 PMCID: PMC9976436 DOI: 10.1186/s12870-023-04116-y] [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: 08/29/2022] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Owing to successful cloning of wheat functional genes in recent years, more traits can be selected by diagnostic markers, and consequently, effective molecular markers will be powerful tools in wheat breeding programs. RESULTS The present study proposed a cost-effective duplex Kompetitive Allele Specific PCR (dKASP) marker system that combined multiplex PCR and KASP™ technology to yield twice the efficiency at half the cost compared with the common KASP™ markers and provide great assistance in breeding selection. Three dKASP markers for the major genes controlling plant height (Rht-B1/Rht-D1), grain hardness (Pina-D1/Pinb-D1), and high-molecular-weight glutenin subunits (Glu-A1/Glu-D1) were successfully developed and applied in approved wheat varieties growing in the middle and lower reaches of the Yangtze River and advanced lines from our breeding program. Three markers were used to test six loci with high efficiency. In the approved wheat varieties, Rht-B1b was the most important dwarfing allele, and the number of accessions carrying Pinb-D1b was much greater than that of the accessions carrying Pina-D1b. Moreover, the number of accessions carrying favorable alleles for weak-gluten wheat (Null/Dx2) was much greater than that of the accessions carrying favorable alleles for strong-gluten wheat (Ax1 or Ax2*/Dx5). In the advanced lines, Rht-B1b and Pinb-D1b showed a significant increase compared with the approved varieties, and the strong-gluten (Ax1 or Ax2*/Dx5) and weak-gluten (Null/Dx2) types also increased. CONCLUSION A cost-effective dKASP marker system that combined multiplex PCR and KASP™ technology was proposed to achieve double the efficiency at half the cost compared with the common KASP™ markers. Three dKASP markers for the major genes controlling PH (Rht-B1/Rht-D1), GH (Pina-D1/Pinb-D1), and HMW-GS (Glu-A1/Glu-D1) were successfully developed, which would greatly improve the efficiency of marker-assisted selection of wheat.
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Affiliation(s)
- Peng Jiang
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China
| | - Xiangyun Fan
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China
| | - Guangxu Zhang
- Lianyungang Institute of Agricultural Sciences, Lianyungang, 222000, Jiangsu, China
| | - Lei Wu
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China
| | - Yi He
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China
| | - Chang Li
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China
| | - Xu Zhang
- CIMMYT-JAAS Joint Center for Wheat Diseases, Jiangsu Academy of Agricultural Sciences, Nanjing, 210014, Jiangsu, China.
- Collaborative Innovation Center for Modern Crop Production co-sponsored by Province and Ministry, Nanjing, 210095, Jiangsu, China.
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27
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Ma C, Liu L, Liu T, Jia Y, Jiang Q, Bai H, Ma S, Li S, Wang Z. QTL Mapping for Important Agronomic Traits Using a Wheat55K SNP Array-Based Genetic Map in Tetraploid Wheat. PLANTS (BASEL, SWITZERLAND) 2023; 12:847. [PMID: 36840195 PMCID: PMC9964379 DOI: 10.3390/plants12040847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 01/31/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
Wheat yield is highly correlated with plant height, heading date, spike characteristics, and kernel traits. In this study, we used the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line population of 165 lines constructed by crossing two tetraploid wheat materials, Icaro and Y4. A genetic linkage map with a total length of 6244.51 cM was constructed, covering 14 chromosomes of tetraploid wheat. QTLs for 12 important agronomic traits, including plant height (PH), heading date (HD), awn color (AC), spike-branching (SB), and related traits of spike and kernel, were mapped in multiple environments, while combined QTL-by-environment interactions and epistatic effects were analyzed for each trait. A total of 52 major or stable QTLs were identified, among which may be some novel loci controlling PH, SB, and kernel length-width ratio (LWR), etc., with LOD values ranging from 2.51 to 54.49, thereby explaining 2.40-66.27% of the phenotypic variation. Based on the 'China Spring' and durum wheat reference genome annotations, candidate genes were predicted for four stable QTLs, QPH.nwafu-2B.2 (165.67-166.99 cM), QAC.nwafu-3A.1 (419.89-420.52 cM), QAC.nwafu-4A.1 (424.31-447.4 cM), and QLWR.nwafu-7A.1 (166.66-175.46 cM). Thirty-one QTL clusters and 44 segregation distortion regions were also detected, and 38 and 18 major or stable QTLs were included in these clusters and segregation distortion regions, respectively. These results provide QTLs with breeding application potential in tetraploid wheat that broadens the genetic basis of important agronomic traits such as PH, HD, AC, SB, etc., and benefits wheat breeding.
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Affiliation(s)
- Chao Ma
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Le Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Tianxiang Liu
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Yatao Jia
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Qinqin Jiang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Haibo Bai
- Agricultural Bio-Technology Research Center, Ningxia Academy of Agriculture and Forestry Science, Yinchuan 750002, China
| | - Sishuang Ma
- Agricultural Bio-Technology Research Center, Ningxia Academy of Agriculture and Forestry Science, Yinchuan 750002, China
| | - Shuhua Li
- Agricultural Bio-Technology Research Center, Ningxia Academy of Agriculture and Forestry Science, Yinchuan 750002, China
| | - Zhonghua Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
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28
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Dong C, Zhang L, Zhang Q, Yang Y, Li D, Xie Z, Cui G, Chen Y, Wu L, Li Z, Liu G, Zhang X, Liu C, Chu J, Zhao G, Xia C, Jia J, Sun J, Kong X, Liu X. Tiller Number1 encodes an ankyrin repeat protein that controls tillering in bread wheat. Nat Commun 2023; 14:836. [PMID: 36788238 PMCID: PMC9929037 DOI: 10.1038/s41467-023-36271-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 01/23/2023] [Indexed: 02/16/2023] Open
Abstract
Wheat (Triticum aestivum L.) is a major staple food for more than one-third of the world's population. Tiller number is an important agronomic trait in wheat, but only few related genes have been cloned. Here, we isolate a wheat mutant, tiller number1 (tn1), with much fewer tillers. We clone the TN1 gene via map-based cloning: TN1 encodes an ankyrin repeat protein with a transmembrane domain (ANK-TM). We show that a single amino acid substitution in the third conserved ankyrin repeat domain causes the decreased tiller number of tn1 mutant plants. Resequencing and haplotype analysis indicate that TN1 is conserved in wheat landraces and modern cultivars. Further, we reveal that the expression level of the abscisic acid (ABA) biosynthetic gene TaNCED3 and ABA content are significantly increased in the shoot base and tiller bud of the tn1 mutants; TN1 but not tn1 could inhibit the binding of TaPYL to TaPP2C via direct interaction with TaPYL. Taken together, we clone a key wheat tiller number regulatory gene TN1, which promotes tiller bud outgrowth probably through inhibiting ABA biosynthesis and signaling.
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Affiliation(s)
- Chunhao Dong
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lichao Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Qiang Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.,State Key Lab of Rice Biology, China National Rice Research Institute, Hangzhou, 310006, China
| | - Yuxin Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Danping Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhencheng Xie
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Guoqing Cui
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Yaoyu Chen
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Lifen Wu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Zhan Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Guoxiang Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xueying Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Cuimei Liu
- National Centre for Plant Gene Research (Beijing), Innovation Academy for Seed Design, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jinfang Chu
- National Centre for Plant Gene Research (Beijing), Innovation Academy for Seed Design, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Guangyao Zhao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Chuan Xia
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jizeng Jia
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jiaqiang Sun
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Xiuying Kong
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Xu Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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29
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Kong B, Ma J, Zhang P, Chen T, Liu Y, Che Z, Shahinnia F, Yang D. Deciphering key genomic regions controlling flag leaf size in wheat via integration of meta-QTL and in silico transcriptome assessment. BMC Genomics 2023; 24:33. [PMID: 36658498 PMCID: PMC9854125 DOI: 10.1186/s12864-023-09119-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/05/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Grain yield is a complex and polygenic trait influenced by the photosynthetic source-sink relationship in wheat. The top three leaves, especially the flag leaf, are considered the major sources of photo-assimilates accumulated in the grain. Determination of significant genomic regions and candidate genes affecting flag leaf size can be used in breeding for grain yield improvement. RESULTS With the final purpose of understanding key genomic regions for flag leaf size, a meta-analysis of 521 initial quantitative trait loci (QTLs) from 31 independent QTL mapping studies over the past decades was performed, where 333 loci eventually were refined into 64 meta-QTLs (MQTLs). The average confidence interval (CI) of these MQTLs was 5.28 times less than that of the initial QTLs. Thirty-three MQTLs overlapped the marker trait associations (MTAs) previously reported in genome-wide association studies (GWAS) for flag leaf traits in wheat. A total of 2262 candidate genes for flag leaf size, which were involved in the peroxisome, basal transcription factor, and tyrosine metabolism pathways were identified in MQTL regions by the in silico transcriptome assessment. Of these, the expression analysis of the available genes revealed that 134 genes with > 2 transcripts per million (TPM) were highly and specifically expressed in the leaf. These candidate genes could be critical to affect flag leaf size in wheat. CONCLUSIONS The findings will make further insight into the genetic determinants of flag leaf size and provide some reliable MQTLs and putative candidate genes for the genetic improvement of flag leaf size in wheat.
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Affiliation(s)
- Binxue Kong
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Jingfu Ma
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Peipei Zhang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
| | - Tao Chen
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Yuan Liu
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, 730000, China
| | - Fahimeh Shahinnia
- Bavarian State Research Centre for Agriculture, Institute for Crop Science and Plant Breeding, 85354, Freising, Germany
| | - Delong Yang
- State Key Laboratory of Aridland Crop Science, Lanzhou, 730070, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China.
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Zhao J, Sun L, Gao H, Hu M, Mu L, Cheng X, Wang J, Zhao Y, Li Q, Wang P, Li H, Zhang Y. Genome-wide association study of yield-related traits in common wheat ( Triticum aestivum L.) under normal and drought treatment conditions. FRONTIERS IN PLANT SCIENCE 2023; 13:1098560. [PMID: 36684753 PMCID: PMC9846334 DOI: 10.3389/fpls.2022.1098560] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
The primary goal of modern wheat breeding is to develop new high-yielding and widely adaptable varieties. We analyzed four yield-related agronomic traits in 502 wheat accessions under normal conditions (NC) and drought treatment (DT) conditions over three years. The genome-wide association analysis identified 51 yield-related and nine drought-resistance-related QTL, including 13 for the thousand-grain weight (TGW), 30 for grain length (GL), three for grain width (GW), five for spike length (SL) and nine for stress tolerance index (STI) QTL in wheat. These QTL, containing 72 single nucleotide polymorphisms (SNPs), explained 2.23 - 7.35% of the phenotypic variation across multiple environments. Eight stable SNPs on chromosomes 2A, 2D, 3B, 4A, 5B, 5D, and 7D were associated with phenotypic stability under NC and DT conditions. Two of these stable SNPs had association with TGW and STI. Several novel QTL for TGW, GL and SL were identified on different chromosomes. Three linked SNPs were transformed into kompetitive allele-specific PCR (KASP) markers. These results will facilitate the discovery of promising SNPs for yield-related traits and/or drought stress tolerance and will accelerate the development of new wheat varieties with desirable alleles.
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Affiliation(s)
- Jie Zhao
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Lijing Sun
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Huimin Gao
- Institute of Cash Crops, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Mengyun Hu
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Liming Mu
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Xiaohu Cheng
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Jianbing Wang
- Institute of Cereal Crops, Dingxi Academy of Agricultural Sciences, Dingxi, China
| | - Yun Zhao
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Qianying Li
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Peinan Wang
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Hui Li
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
| | - Yingjun Zhang
- Institute of Cereal and Oil Crops, Laboratory of Crop Genetics and Breeding of Hebei, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang, China
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31
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Hui J, Bai H, Lyu X, Ma S, Chen X, Li S. A pleiotropic QTL increased economic water use efficiency in bread wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2023; 13:1067590. [PMID: 36714690 PMCID: PMC9879270 DOI: 10.3389/fpls.2022.1067590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 11/25/2022] [Indexed: 06/18/2023]
Abstract
Wheat is one of the most important food crops in the world and drought can severely impact on wheat productivity. The identification and deployment of genes for improved water use efficiency (WUE) can help alleviate yield loss under water limitation. In this study, a high-density genetic linkage map of wheat recombinant inbred lines (Ningchun 4 x Ningchun 27) containing 8751 specific locus amplified fragment (SLAF) tags (including 14757 SNPs), with a total map distance of 1685 cM and an average inter-marker map distance of 0.19 cM was constructed by SLAF-seq technology. The economic yield WUE and nine related traits under three water treatments was monitored over four years. The results showed that loci conditioning WUE were also associated with grain carbon isotope discrimination (CID), flag leaf chlorophyll content, plant height, 1000-grain weight, grain weight per spike and grain number per spike. One locus on chromosome 2B explained 26.3% WUE variation in multiple environments. Under good soil moisture conditions before flowering, the high CID genotype QWue.acn-2B Ningchun 27, was associated with WUE, high grain weight per spike, and kilo-grain weight. Under rain-fed conditions, the low CID genotype QWue.acn-2B Ningchun 4 tended to maintain more spike number and was associated with improved WUE and yield. The introduction of good chromosome fragments of QWue.acn-2B into elite lines by molecular marker assisted selection will boost up the cultivation of high-yield and water-saving wheat varieties.
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Affiliation(s)
- Jian Hui
- *Correspondence: Jian Hui, ; Shuhua Li,
| | | | | | | | | | - Shuhua Li
- *Correspondence: Jian Hui, ; Shuhua Li,
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32
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Ma J, Liu Y, Zhang P, Chen T, Tian T, Wang P, Che Z, Shahinnia F, Yang D. Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.). BMC PLANT BIOLOGY 2022; 22:607. [PMID: 36550393 PMCID: PMC9784057 DOI: 10.1186/s12870-022-03989-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes. RESULTS The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites. CONCLUSIONS Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.
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Grants
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- GHSJ 2020-Z4 Research Program Sponsored by State Key Laboratory of Aridland Crop Science, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 21YF5NA089 Key Research and Development Program of Gansu Province, China
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 2022CYZC-44 Industrial Support Plan of Colleges and Universities in Gansu Province
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 31760385 National Natural Science Foundation of China
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- 22ZD6NA010 Key Sci & Tech Special Project of Gansu Province
- Key Sci & Tech Special Project of Gansu Province
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Affiliation(s)
- Jingfu Ma
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
- College of Agronomy, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Yuan Liu
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peipei Zhang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China
| | - Tao Chen
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Tian Tian
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Peng Wang
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China
| | - Zhuo Che
- Plant Seed Master Station of Gansu Province, Lanzhou, Gansu, China
| | - Fahimeh Shahinnia
- Institute for Crop Science and Plant Breeding, Bavarian State Research Centre for Agriculture, Freising, Germany
| | - Delong Yang
- State Key Lab of Aridland Crop Science, Lanzhou, Gansu, China.
- College of Life Science and Technology, Gansu Agricultural University, Lanzhou, Gansu, China.
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33
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Wang Z, Dhakal S, Cerit M, Wang S, Rauf Y, Yu S, Maulana F, Huang W, Anderson JD, Ma XF, Rudd JC, Ibrahim AMH, Xue Q, Hays DB, Bernardo A, St. Amand P, Bai G, Baker J, Baker S, Liu S. QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster. FRONTIERS IN PLANT SCIENCE 2022; 13:1057701. [PMID: 36570880 PMCID: PMC9768232 DOI: 10.3389/fpls.2022.1057701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 11/04/2022] [Indexed: 06/17/2023]
Abstract
In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.
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Affiliation(s)
- Zhen Wang
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Smit Dhakal
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Mustafa Cerit
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shichen Wang
- Genomics and Bioinformatics Service Center, Texas A&M AgriLife Research, College Station, TX, United States
| | - Yahya Rauf
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shuhao Yu
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Frank Maulana
- Noble Research Institute, Ardmore, OK, United States
| | - Wangqi Huang
- Noble Research Institute, Ardmore, OK, United States
| | | | - Xue-Feng Ma
- Noble Research Institute, Ardmore, OK, United States
| | - Jackie C. Rudd
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Amir M. H. Ibrahim
- Department of Soil and Crop Science, Texas A&M University, College Station, TX, United States
| | - Qingwu Xue
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Dirk B. Hays
- Department of Soil and Crop Science, Texas A&M University, College Station, TX, United States
| | - Amy Bernardo
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Paul St. Amand
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Guihua Bai
- Central Small Grain Genotyping Lab and Hard Winter Wheat Genetics Research Unit, U.S. Department of Agriculture-Agricultural Research Service, Manhattan, KS, United States
| | - Jason Baker
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shannon Baker
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
| | - Shuyu Liu
- Texas A&M AgriLife Research and Extension Center, Amarillo, TX, United States
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Zhao J, Zheng X, Qiao L, Yang C, Wu B, He Z, Tang Y, Li G, Yang Z, Zheng J, Qi Z. Genome-wide association study reveals structural chromosome variations with phenotypic effects in wheat (Triticum aestivum L.). THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 112:1447-1461. [PMID: 36345647 DOI: 10.1111/tpj.16023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 10/26/2022] [Accepted: 11/01/2022] [Indexed: 06/16/2023]
Abstract
Structural chromosome variations (SCVs) are large-scale genomic variations that can be detected by fluorescence in situ hybridization (FISH). SCVs have played important roles in the genome evolution of wheat (Triticum aestivum L.), but little is known about their genetic effects. In this study, a total of 543 wheat accessions from the Chinese wheat mini-core collection and the Shanxi Province wheat collection were used for chromosome analysis using oligonucleotide probe multiplex FISH. A total of 139 SCVs including translocations, pericentric inversions, presence/absence variations (PAVs), and copy number variations (CNVs) in heterochromatin were identified at 230 loci. The distribution frequency of SCVs varied between ecological regions and between landraces and modern cultivars. Structural analysis using SCVs as markers clearly divided the landraces and modern cultivars into different groups. There are very clear instances illustrating alien introgression and wide application of foreign germplasms improved the chromosome diversity of Chinese modern wheat cultivars. A genome-wide association study (GWAS) identified 29 SCVs associated with 12 phenotypic traits, and five (RT4AS•4AL-1DS/1DL•1DS-4AL, Mg2A-3, Mr3B-10, Mr7B-13, and Mr4A-7) of them were further validated using a doubled haploid population and advanced sib-lines, implying the potential value of these SCVs. Importantly, the number of favored SCVs that were associated with agronomic trait improvement was significantly higher in modern cultivars compared to landraces, indicating positive selection in wheat breeding. This study demonstrates the significant effects of SCVs during wheat breeding and provides an efficient method of mining favored SCVs in wheat and other crops.
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Affiliation(s)
- Jiajia Zhao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Xingwei Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Ling Qiao
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Chenkang Yang
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Bangbang Wu
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Ziming He
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Yuqing Tang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
| | - Guangrong Li
- Center for Informational Biology, School of Life Science and Technology, University of Electronic and Technology of China, Chengdu, 611731, China
| | - Zujun Yang
- Center for Informational Biology, School of Life Science and Technology, University of Electronic and Technology of China, Chengdu, 611731, China
| | - Jun Zheng
- Institute of Wheat Research, State Key Laboratory of Sustainable Dryland Agriculture, Shanxi Agricultural University, Linfen, 041000, China
| | - Zengjun Qi
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China
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Khan N, Zhang Y, Wang J, Li Y, Chen X, Yang L, Zhang J, Li C, Li L, Ur Rehman S, Reynolds MP, Zhang L, Zhang X, Mao X, Jing R. TaGSNE, a WRKY transcription factor, overcomes the trade-off between grain size and grain number in common wheat and is associated with root development. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:6678-6696. [PMID: 35906966 DOI: 10.1093/jxb/erac327] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 07/26/2022] [Indexed: 05/28/2023]
Abstract
Wheat is one of the world's major staple food crops, and breeding for improvement of grain yield is a priority under the scenarios of climate change and population growth. WRKY transcription factors are multifaceted regulators in plant growth, development, and responses to environmental stimuli. In this study, we identify the WRKY gene TaGSNE (Grain Size and Number Enhancer) in common wheat, and find that it has relatively high expression in leaves and roots, and is induced by multiple abiotic stresses. Eleven single-nucleotide polymorphisms were identified in TaGSNE, forming two haplotypes in multiple germplasm collections, named as TaGSNE-Hap-1 and TaGSNE-Hap-2. In a range of different environments, TaGSNE-Hap-2 was significantly associated with increases in thousand-grain weight (TGW; 3.0%) and spikelet number per spike (4.1%), as well as with deeper roots (10.1%) and increased root dry weight (8.3%) at the mid-grain-filling stage, and these were confirmed in backcross introgression populations. Furthermore, transgenic rice lines overexpressing TaGSNE had larger panicles, more grains, increased grain size, and increased grain yield relative to the wild-type control. Analysis of geographic and temporal distributions revealed that TaGSNE-Hap-2 is positively selected in China and Pakistan, and TaGSNE-Hap-1 in Europe. Our findings demonstrate that TaGSNE overcomes the trade-off between TGW/grain size and grain number, leading us to conclude that these elite haplotypes and their functional markers could be utilized in marker-assisted selection for breeding high-yielding varieties.
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Affiliation(s)
- Nadia Khan
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Department of Genetics, University of Karachi, Pakistan
| | - Yanfei Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, China
| | - Jingyi Wang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yuying Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, China
| | - Xin Chen
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lili Yang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jie Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chaonan Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Long Li
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Shoaib Ur Rehman
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Institute of Plant Breeding and Biotechnology, Muhammad Nawaz Shareef University of Agriculture, Multan 60000, Pakistan
| | | | - Lichao Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xueyong Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinguo Mao
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ruilian Jing
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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36
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Peters Haugrud AR, Zhang Q, Green AJ, Xu SS, Faris JD. Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions. G3 (BETHESDA, MD.) 2022; 13:6762085. [PMID: 36250796 PMCID: PMC9911061 DOI: 10.1093/g3journal/jkac281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 09/27/2022] [Indexed: 11/09/2022]
Abstract
Crop yield gains are needed to keep pace with a growing global population and decreasing resources to produce food. Cultivated emmer wheat is a progenitor of durum wheat and a useful source of genetic variation for trait improvement in durum. Here, we evaluated a recombinant inbred line population derived from a cross between the North Dakota durum wheat variety Divide and the cultivated emmer wheat accession PI 272527 consisting of 219 lines. The population was evaluated in 3 field environments and 2 greenhouse experiments to identify quantitative trait locus associated with 11 yield-related traits that were expressed in a consistent manner over multiple environments. We identified 27 quantitative trait locus expressed in at least 2 field environments, 17 of which were also expressed under greenhouse conditions. Seven quantitative trait locus regions on chromosomes 1B, 2A, 2B, 3A, 3B, 6A, and 7B had pleiotropic effects on multiple yield-related traits. The previously cloned genes Q and FT-B1, which are known to be associated with development and morphology, were found to consistently be associated with multiple traits across environments. PI 272527 contributed beneficial alleles for quantitative trait locus associated with multiple traits, especially for seed morphology quantitative trait locus on chromosomes 1B, 2B, and 6A. Three recombinant inbred lines with increased grain size and weight compared to Divide were identified and demonstrated the potential for improvement of durum wheat through deployment of beneficial alleles from the cultivated emmer parent. The findings from this study provide knowledge regarding stable and robust quantitative trait locus that breeders can use for improving yield in durum wheat.
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Affiliation(s)
| | - Qijun Zhang
- Department of Plant Sciences, North Dakota State University, Fargo, ND 58102, USA
| | - Andrew J Green
- Department of Plant Sciences, North Dakota State University, Fargo, ND 58102, USA
| | - Steven S Xu
- USDA-ARS Western Regional Research Center, Albany, CA 94710, USA
| | - Justin D Faris
- Corresponding author: Cereal Crops Research Unit, Edward T. Schafer Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Fargo, ND 58102, USA.
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37
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Transcriptional signatures of wheat inflorescence development. Sci Rep 2022; 12:17224. [PMID: 36241895 PMCID: PMC9568521 DOI: 10.1038/s41598-022-21571-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/28/2022] [Indexed: 01/06/2023] Open
Abstract
In order to maintain global food security, it will be necessary to increase yields of the cereal crops that provide most of the calories and protein for the world's population, which includes common wheat (Triticum aestivum L.). An important wheat yield component is the number of grain-holding spikelets which form on the spike during inflorescence development. Characterizing the gene regulatory networks controlling the timing and rate of inflorescence development will facilitate the selection of natural and induced gene variants that contribute to increased spikelet number and yield. In the current study, co-expression and gene regulatory networks were assembled from a temporal wheat spike transcriptome dataset, revealing the dynamic expression profiles associated with the progression from vegetative meristem to terminal spikelet formation. Consensus co-expression networks revealed enrichment of several transcription factor families at specific developmental stages including the sequential activation of different classes of MIKC-MADS box genes. This gene regulatory network highlighted interactions among a small number of regulatory hub genes active during terminal spikelet formation. Finally, the CLAVATA and WUSCHEL gene families were investigated, revealing potential roles for TtCLE13, TtWOX2, and TtWOX7 in wheat meristem development. The hypotheses generated from these datasets and networks further our understanding of wheat inflorescence development.
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Bai X, Zhou Y, Islam MA, Zhang W, Ning L, Ling B, Wang Y, Xu Z, Sun D, Chen M. A soybean
GmDREB3
gene contributes to drought tolerance in wheat. Food Energy Secur 2022. [DOI: 10.1002/fes3.426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Affiliation(s)
- Xingxuan Bai
- College of Agriculture Shanxi Agricultural University Taigu Shanxi China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
| | - Yongbin Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
| | - Md Ashraful Islam
- College of Agriculture Shanxi Agricultural University Taigu Shanxi China
| | - Weibin Zhang
- Maize Research Institute Shanxi Agricultural University Xinzhou China
| | - Lei Ning
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
| | - Bingqi Ling
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
| | - Yanxia Wang
- Shijiazhuang Academy of Agricultural and Forestry Sciences Research Center of Wheat Engineering Technology of Hebei Shijiazhuang Hebei China
| | - Zhao‐Shi Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
| | - Daizhen Sun
- College of Agriculture Shanxi Agricultural University Taigu Shanxi China
| | - Ming Chen
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS)/Key Laboratory of Biology and Genetic Improvement of Triticeae Crops Ministry of Agriculture Beijing China
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Zhang Y, Miao H, Wang C, Zhang J, Zhang X, Shi X, Xie S, Li T, Deng P, Wang C, Chen C, Zhang H, Ji W. Genetic identification of the pleiotropic gene Tasg-D1/2 affecting wheat grain shape by regulating brassinolide metabolism. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2022; 323:111392. [PMID: 35868348 DOI: 10.1016/j.plantsci.2022.111392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 06/08/2022] [Accepted: 07/16/2022] [Indexed: 06/15/2023]
Abstract
Improving yield potential is a major goal of wheat breeding that depends on identifying key genetic loci. In this study, two residual heterozygous line RHL351- and RHL78-derived populations were employed for genetic linkage map construction and QTL detection. Two genetic populations indicated a robust grain-size QTL between Marker6 and Marker10. It covered a 95.54-99.38 Mb physical interval and was named Qpleio.nwafu.3D, containing the candidate gene Tasg (TraesCS3D02G137200). Intriguingly, RNA-seq analysis and sequencing revealed two different allelic variants in Tasg, named Tasg-D1 (G>A) and Tasg-D2 (C>G), respectively. Although the relationship between Tasg-D1 and grain size had been demonstrated previously, here we provided the first genetic evidence that C/G allelic variation in Tasg-D2 was associated with grain shape and size through a newly developed dCAPS marker. In addition, transcriptome comparison indicated that Tasg-D1/2 might primarily contribute to significant expression differences in brassinolide (BR) metabolism-related genes rather than those related to BR responses in developing grains and spikes. Our study provided new evidence and a breeder-friendly dCAPS marker for improving grain size through the selection of Tasg, as well as a basis to understand Tasg function in the future.
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Affiliation(s)
- Yaoyuan Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Hanxiao Miao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Chao Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Junjie Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Xiangyu Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Xiaoxi Shi
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Songfeng Xie
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China
| | - Tingdong Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China
| | - Pingchuan Deng
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China
| | - Changyou Wang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China
| | - Chunhuan Chen
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China
| | - Hong Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China.
| | - Wanquan Ji
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Agronomy, Northwest A&F University, Yangling 712100, China; Shaanxi Research Station of Crop Gene Resources and Germplasm Enhancement, Ministry of Agriculture, Yangling 712100, China.
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Wang Y, Qiao L, Yang C, Li X, Zhao J, Wu B, Zheng X, Li P, Zheng J. Identification of genetic loci for flag-leaf-related traits in wheat ( Triticum aestivum L.) and their effects on grain yield. FRONTIERS IN PLANT SCIENCE 2022; 13:990287. [PMID: 36160981 PMCID: PMC9493265 DOI: 10.3389/fpls.2022.990287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 08/08/2022] [Indexed: 06/16/2023]
Abstract
Flag-leaf-related traits including length (FLL), width (FLW), area (FLA), thickness (FLT), and volume (FLV) of flag leaves are the most important determinants of plant architecture and yield in wheat. Understanding the genetic basis of these traits could accelerate the breeding of high yield wheat varieties. In this study, we constructed a doubled haploid (DH) population and analyzed flag-leaf-related traits in five experimental locations/years using the wheat 90K single-nucleotide polymorphism array. It's worth noting that a novel method was used to measure FLT and FLV easily. Leaf thickness at two-thirds of the leaf length from tip to collar represented the average leaf thickness as measured with freehand sections and was used to calculate the leaf volume. In addition, flag-leaf-related traits showed positive correlations with yield related traits under two different water regimes. A total of 79 quantitative trait loci (QTL) controlling the five traits were detected among all chromosomes except 4D and 5A, explaining 3.09-14.52% of the phenotypic variation. Among them, 15 stable QTL were identified in more than three environments, including two major QTL for FLT, six for FLW, three for FLA, two for FLT and two for FLV. DH lines with positive alleles at both QTL regions had an average FLL (9.90%), FLW (32.87%), FLT (6.62%), FLA (18.47%), and FLV (20.87%) greater than lines with contrasting alleles. QFLT-2B, QFLV-2A, and QFLV-7D were co-located with yield-related traits. The 15 QTL were validated by tightly linked kompetitive allele specific PCR (KASP) markers in a recombinant inbred line (RIL) population derived from a different cross. QFLL-4A, QFLW-4B, QFLA-5D.1, QFLA-7A, QFLA-7D.1, QFLT-2B, QFLT-6A, QFLV-2A, and QFLV-7D are likely novel loci. These results provide a better understanding of the genetic basis underlying flag-leaf-related traits. Also, target regions for fine mapping and marker-assisted selection were identified and these will be valuable for breeding high yielding bread wheat.
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Affiliation(s)
- Ying Wang
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
- School of Life Sciences, Shanxi University, Taiyuan, China
| | - Ling Qiao
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Chenkang Yang
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
- School of Life Sciences, Shanxi University, Taiyuan, China
| | - Xiaohua Li
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Jiajia Zhao
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Bangbang Wu
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Xingwei Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
| | - Pengbo Li
- Institute of Cotton Research, Shanxi Agricultural University, Yuncheng, China
| | - Jun Zheng
- Institute of Wheat Research, Shanxi Agricultural University, Linfen, China
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41
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Ren P, Zhao D, Zeng Z, Yan X, Zhao Y, Lan C, Wang C. Pleiotropic effect analysis and marker development for grain zinc and iron concentrations in spring wheat. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:49. [PMID: 37313424 PMCID: PMC10248664 DOI: 10.1007/s11032-022-01317-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 08/02/2022] [Indexed: 06/15/2023]
Abstract
Wheat (Triticum aestivum L.) is one of the main food crops in the world and a primary source of zinc (Zn) and iron (Fe) in the human body. The genetic mechanisms underlying related traits have been clarified, thereby providing a molecular theoretical foundation for the development of germplasm resources. In this study, a total of 23,536 high-quality DArT markers was used to map quantitative trait loci (QTL) of grain Zn (GZn) and grain Fe (GFe) concentrations in recombinant inbred lines crossed by Avocet/Chilero. A total of 17 QTLs was located on chromosomes 1BL, 2BL, 3BL, 4AL, 4BS, 5AL, 5DL, 6AS, 6BS, 6DS, and 7AS accounting for 0.38-16.62% of the phenotypic variance. QGZn.haust-4AL, QGZn.haust-7AS.1, and QGFe.haust-6BS were detected on chromosomes 4AL, 6BS, and 7AS, accounting for 10.63-16.62% of the phenotypic variance. Four stable QTLs, QGZn.haust-4AL, QGFe.haust-1BL, QGFe.haust-4AL, and QGFe.haust-5DL, were located on chromosomes 1BL, 4AL, and 5DL. Three pleiotropic effects loci for GZn and GFe concentrations were located on chromosomes 1BL, 4AL, and 5DL. Two high-throughput Kompetitive Allele Specific PCR markers were developed by closely linking single-nucleotide polymorphisms on chromosomes 4AL and 5DL, which were validated by a germplasm panel. Therefore, it is the most important that quantitative trait loci and KASP marker for grain zinc and iron concentrations were developed for utilizing in marker-assisted breeding and biofortification of wheat grain in breeding programs.
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Affiliation(s)
- Pengxun Ren
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
- The Shennong Laboratory, Zhengzhou, 450002 Henan China
| | - Dehui Zhao
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
- The Shennong Laboratory, Zhengzhou, 450002 Henan China
| | - Zhankui Zeng
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
- The Shennong Laboratory, Zhengzhou, 450002 Henan China
| | - Xuefang Yan
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
| | - Yue Zhao
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
- The Shennong Laboratory, Zhengzhou, 450002 Henan China
| | - Caixia Lan
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070 Hubei China
| | - Chunping Wang
- College of Agronomy, Henan University of Science and Technology, Luoyang, 471000 Henan China
- The Shennong Laboratory, Zhengzhou, 450002 Henan China
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Song J, Xu D, Dong Y, Li F, Bian Y, Li L, Luo X, Fei S, Li L, Zhao C, Zhang Y, Xia X, Ni Z, He Z, Cao S. Fine mapping and characterization of a major QTL for grain weight on wheat chromosome arm 5DL. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3237-3246. [PMID: 35904627 DOI: 10.1007/s00122-022-04182-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 07/14/2022] [Indexed: 06/15/2023]
Abstract
We fine mapped QTL QTKW.caas-5DL for thousand kernel weight in wheat, predicted candidate genes and developed a breeding-applicable marker. Thousand kernel weight (TKW) is an important yield component trait in wheat, and identification of the underlying genetic loci is helpful for yield improvement. We previously identified a stable quantitative trait locus (QTL) QTKW.caas-5DL for TKW in a Doumai/Shi4185 recombinant inbred line (RIL) population. Here we performed fine mapping of QTKW.caas-5DL using secondary populations derived from 15 heterozygous recombinants and delimited the QTL to an approximate 3.9 Mb physical interval from 409.9 to 413.8 Mb according to the Chinese Spring (CS) reference genome. Analysis of genomic synteny showed that annotated genes in the physical interval had high collinearity among CS and eight other wheat genomes. Seven genes with sequence variation and/or differential expression between parents were predicted as candidates for QTKW.caas-5DL based on whole-genome resequencing and transcriptome assays. A kompetitive allele-specific PCR (KASP) marker for QTKW.caas-5DL was developed, and genotyping confirmed a significant association with TKW but not with other yield component traits in a panel of elite wheat cultivars. The superior allele of QTKW.caas-5DL was frequent in a panel of cultivars, suggesting that it had undergone positive selection. These findings not only lay a foundation for map-based cloning of QTKW.caas-5DL but also provide an efficient tool for marker-assisted selection.
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Affiliation(s)
- Jie Song
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100094, China
| | - Dengan Xu
- Shandong Province Key Laboratory of Dryland Farming Technology, College of Agronomy, Qingdao Agricultural University, Qingdao, 266109, Shandong, China
| | - Yan Dong
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Faji Li
- Crop Research Institute, Shandong Academy of Agricultural Sciences, 202 Gongye North Road, Jinan, 250100, Shandong, China
| | - Yingjie Bian
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lingli Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xumei Luo
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Shuaipeng Fei
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lei Li
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Cong Zhao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Yong Zhang
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Xianchun Xia
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhongfu Ni
- State Key Laboratory of Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, College of Agronomy, China Agricultural University, 2 Yuanmingyuan West Road, Beijing, 100094, China
| | - Zhonghu He
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Shuanghe Cao
- Institute of Crop Sciences, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
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Liu X, Xu Z, Feng B, Zhou Q, Ji G, Guo S, Liao S, Lin D, Fan X, Wang T. Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map. FRONTIERS IN PLANT SCIENCE 2022; 13:967432. [PMID: 36110352 PMCID: PMC9468616 DOI: 10.3389/fpls.2022.967432] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 08/04/2022] [Indexed: 06/01/2023]
Abstract
Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.
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Affiliation(s)
- Xiaofeng Liu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shaodan Guo
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Dian Lin
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Innovative Academy for Seed Design, Chinese Academy of Sciences, Beijing, China
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Chen H, Wei J, Tian R, Zeng Z, Tang H, Liu Y, Xu Q, Deng M, Jiang Q, Chen G, Liu Y, Li W, Qi P, Jiang Y, Jiang Y, Tang L, Wei Y, Zheng Y, Lan X, Ma J. A major quantitative trait locus for wheat total root length associated with precipitation distribution. FRONTIERS IN PLANT SCIENCE 2022; 13:995183. [PMID: 36092437 PMCID: PMC9451531 DOI: 10.3389/fpls.2022.995183] [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: 07/18/2022] [Accepted: 08/03/2022] [Indexed: 06/15/2023]
Abstract
Optimizing root system architecture (RSA) allows crops to better capture water and nutrients and adapt to harsh environment. Parental reproductive environment (PRE) has been reported to significantly affect growth and development throughout the life cycle of the next generation. In this study, 10 RSA-related traits were evaluated in seedling stage from five independent hydroponic tests using seeds harvested from five different PREs. Based on the Wheat55K SNP array-based genetic map, quantitative trait loci (QTL) for these traits were detected in a recombinant inbred line population. Twenty-eight putative QTL for RSA-related traits were detected, covering thirteen chromosomal regions. A major QTL, QTrl.sicau-2SY-4D for total root length (TRL), which was likely independent of PREs, explained 15.81-38.48% of phenotypic variations and was located at 14.96-19.59 Mb on chromosome arm 4DS. Interestingly, it showed pleiotropic effects on TRL, root area, root volume, root forks, root dry weight, and shoot dry weight. The functional marker KASP-Rht-D1 for Rht-D1 was used to genotype 2SY population and remapping QTL for TRL showed that QTrl.sicau-2SY-4D was not linked to Rht-D1. The kompetitive allele-specific PCR (KASP) marker, KASP-AX-110527441 linked to this major QTL, was developed and used to successfully validate its effect in three different genetic populations. Further analysis suggested that the positive allele at QTrl.sicau-2SY-4D was mainly utilized in wheat breeding of northwest China where precipitation was significantly lower, indicating that wheat requires longer TRL to capture water and nutrients in arid or semi-arid regions due to deficient precipitation. Additionally, four genes (TraesCS4D03G0059800, TraesCS4D03G0057800, TraesCS4D03G0064000, and TraesCS4D03G0064400) possibly related to root development were predicted in physical interval of QTrl.sicau-2SY-4D. Taken together, these results enrich our understanding on the genetic basis of RSA and provide a potentially valuable TRL QTL for wheat breeding.
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Affiliation(s)
- Huangxin Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Jiatai Wei
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Rong Tian
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Zhaoyong Zeng
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Huaping Tang
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yanlin Liu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Qiang Xu
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Mei Deng
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Qiantao Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Guoyue Chen
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yaxi Liu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Wei Li
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Pengfei Qi
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yunfeng Jiang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Yun Jiang
- Institute of Biotechnology and Nuclear Technology Research, Sichuan Academy of Agricultural Sciences, Chengdu, China
| | - Liwei Tang
- Panzhihua Academy of Agricultural and Forestry Sciences, Panzhihua, China
| | - Yuming Wei
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Youliang Zheng
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Xiujin Lan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
| | - Jian Ma
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, China
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
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Li Y, Umanzor S, Ng C, Huang M, Marty-Rivera M, Bailey D, Aydlett M, Jannink JL, Lindell S, Yarish C. Skinny kelp ( Saccharina angustissima) provides valuable genetics for the biomass improvement of farmed sugar kelp ( Saccharina latissima). JOURNAL OF APPLIED PHYCOLOGY 2022; 34:2551-2563. [PMID: 36033835 PMCID: PMC9391627 DOI: 10.1007/s10811-022-02811-1] [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: 02/28/2022] [Revised: 07/25/2022] [Accepted: 07/25/2022] [Indexed: 06/15/2023]
Abstract
UNLABELLED Saccharina latissima (sugar kelp) is one of the most widely cultivated brown marine macroalgae species in the North Atlantic and the eastern North Pacific Oceans. To meet the expanding demands of the sugar kelp mariculture industry, selecting and breeding sugar kelp that is best suited to offshore farm environments is becoming necessary. To that end, a multi-year, multi-institutional breeding program was established by the U.S. Department of Energy's (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program. Hybrid sporophytes were generated using 203 unique gametophyte cultures derived from wild-collected Saccharina spp. for two seasons of farm trials (2019-2020 and 2020-2021). The wild sporophytes were collected from 10 different locations within the Gulf of Maine (USA) region, including both sugar kelp (Saccharina latissima) and the skinny kelp species (Saccharina angustissima). We harvested 232 common farm plots during these two seasons with available data. We found that farmed kelp plots with skinny kelp as parents had an average increased yield over the mean (wet weight 2.48 ± 0.90 kg m-1 and dry weight 0.32 ± 0.10 kg m-1) in both growing seasons. We also found that blade length positively correlated with biomass in skinny kelp x sugar kelp crosses or pure sugar kelp crosses. The skinny x sugar progenies had significantly longer and narrower blades than the pure sugar kelp progenies in both seasons. Overall, these findings suggest that sugar x skinny kelp crosses provide improved yield compared to pure sugar kelp crosses. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s10811-022-02811-1.
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Affiliation(s)
- Yaoguang Li
- Department of Ecology & Evolutionary Biology, University of Connecticut, Stamford, CT 06901-2315 USA
| | - Schery Umanzor
- Department of Ecology & Evolutionary Biology, University of Connecticut, Stamford, CT 06901-2315 USA
- College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Juneau, AK 99775 USA
| | - Crystal Ng
- Department of Ecology & Evolutionary Biology, University of Connecticut, Stamford, CT 06901-2315 USA
| | - Mao Huang
- Section On Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY 14853 USA
| | - Michael Marty-Rivera
- Department of Ecology & Evolutionary Biology, University of Connecticut, Stamford, CT 06901-2315 USA
| | - David Bailey
- Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA
| | - Margaret Aydlett
- Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA
| | - Jean-Luc Jannink
- Section On Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY 14853 USA
- United States Department of Agriculture - Agriculture Research Service, Ithaca, NY 14853 USA
| | - Scott Lindell
- Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA
| | - Charles Yarish
- Department of Ecology & Evolutionary Biology, University of Connecticut, Stamford, CT 06901-2315 USA
- Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543 USA
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Yu Q, Feng B, Xu Z, Fan X, Zhou Q, Ji G, Liao S, Gao P, Wang T. Genetic Dissection of Three Major Quantitative Trait Loci for Spike Compactness and Length in Bread Wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2022; 13:882655. [PMID: 35677243 PMCID: PMC9168683 DOI: 10.3389/fpls.2022.882655] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 03/24/2022] [Indexed: 06/15/2023]
Abstract
Spike compactness (SC) and length (SL) are the components of spike morphology and are strongly related to grain yield in wheat (Triticum aestivum L.). To investigate quantitative trait loci (QTL) associated with SC and SL, a recombinant inbred lines (RIL) population derived from the cross of Bailangmai (BLM, a Tibet landrace) and Chuanyu 20 (CY20, an improved variety) was employed in six environments. Three genomic regions responsible for SC and SL traits were identified on chromosomes 2A and 2D using bulked segregant exome sequencing (BSE-Seq). By constructing genetic maps, six major QTL were repeatedly detected in more than four environments and the best linear unbiased estimation (BLUE) datasets, explaining 7.00-28.56% of the phenotypic variation and the logarithm of the odd (LOD) score varying from 2.50 to 13.22. They were co-located on three loci, designed as QSc/Sl.cib-2AS, QSc/Sl.cib-2AL, and QSc/Sl.cib-2D, respectively. Based on the flanking markers, their interactions and effects on the corresponding trait and other agronomic traits were also analyzed. Comparison analysis showed that QSc/Sl.cib-2AS and QSc/Sl.cib-2AL were possibly two novel loci for SC and SL. QSc/Sl.cib-2AS and QSc/Sl.cib-2D showed pleiotropic effects on plant height and grain morphology, while QSc/Sl.cib-2AL showed effects on spikelet number per spike (SNS) and grain width (GW). Based on the gene annotation, orthologous search, and spatiotemporal expression patterns of genes, TraesCS2A03G0410600 and TraesCS2A03G0422300 for QSc/Sl.cib-2AS, and TraesCS2D03G1129300 and TraesCS2D03G1131500 for QSc/Sl.cib-2D were considered as potential candidate genes, respectively. These results will be useful for fine mapping and developing new varieties with high yield in the future.
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Affiliation(s)
- Qin Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- College of Life Sciences, Sichuan University, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Bo Feng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Zhibin Xu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Xiaoli Fan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Qiang Zhou
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Guangsi Ji
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Simin Liao
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ping Gao
- College of Life Sciences, Sichuan University, Chengdu, China
| | - Tao Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
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Li T, Li Q, Wang J, Yang Z, Tang Y, Su Y, Zhang J, Qiu X, Pu X, Pan Z, Zhang H, Liang J, Liu Z, Li J, Yan W, Yu M, Long H, Wei Y, Deng G. High-resolution detection of quantitative trait loci for seven important yield-related traits in wheat (Triticum aestivum L.) using a high-density SLAF-seq genetic map. BMC Genom Data 2022; 23:37. [PMID: 35562674 PMCID: PMC9107147 DOI: 10.1186/s12863-022-01050-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 04/06/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Yield-related traits including thousand grain weight (TGW), grain number per spike (GNS), grain width (GW), grain length (GL), plant height (PH), spike length (SL), and spikelet number per spike (SNS) are greatly associated with grain yield of wheat (Triticum aestivum L.). To detect quantitative trait loci (QTL) associated with them, 193 recombinant inbred lines derived from two elite winter wheat varieties Chuanmai42 and Chuanmai39 were employed to perform QTL mapping in six/eight environments. RESULTS A total of 30 QTLs on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 4A, 5A, 5B, 6A, 6D, 7A, 7B and 7D were identified. Among them, six major QTLs QTgw.cib-6A.1, QTgw.cib-6A.2, QGw.cib-6A, QGl.cib-3A, QGl.cib-6A, and QSl.cib-2D explaining 5.96-23.75% of the phenotypic variance were detected in multi-environments and showed strong and stable effects on corresponding traits. Three QTL clusters on chromosomes 2D and 6A containing 10 QTLs were also detected, which showed significant pleiotropic effects on multiple traits. Additionally, three Kompetitive Allele Specific PCR (KASP) markers linked with five of these major QTLs were developed. Candidate genes of QTgw.cib-6A.1/QGl.cib-6A and QGl.cib-3A were analyzed based on the spatiotemporal expression patterns, gene annotation, and orthologous search. CONCLUSIONS Six major QTLs for TGW, GL, GW and SL were detected. Three KASP markers linked with five of these major QTLs were developed. These QTLs and KASP markers will be useful for elucidating the genetic architecture of grain yield and developing new wheat varieties with high and stable yield in wheat.
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Affiliation(s)
- Tao Li
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.,Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.,State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Qiao Li
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Jinhui Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zhao Yang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yanyan Tang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yan Su
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Juanyu Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xvebing Qiu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Xi Pu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zhifen Pan
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Haili Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Junjun Liang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Zehou Liu
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Jun Li
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, Sichuan, China
| | - Wuyun Yan
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Maoqun Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Hai Long
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.,State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, 611130, China
| | - Guangbing Deng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China.
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Niu X, Feng P, Liu DL, Wang B, Waters C, Zhao N, Ma T. Deficit Irrigation at Pre-Anthesis Can Balance Wheat Yield and Water Use Efficiency under Future Climate Change in North China Plain. BIOLOGY 2022; 11:biology11050692. [PMID: 35625420 PMCID: PMC9138343 DOI: 10.3390/biology11050692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/23/2022] [Accepted: 04/27/2022] [Indexed: 11/16/2022]
Abstract
Background. Deficit irrigation (DI) is a feasible strategy to enhance crop WUE and also has significant compensation effects on yield. Previous studies have found that DI has great potential to maintain crop production as full irrigation (FI) does. Therefore, adopting DI to improve crop production and safeguard groundwater resources is of great importance in water scarce regions, e.g., the North China Plain (NCP). Under the background of global warming, it is worth investigating whether DI continues to play such a key role under future climate scenarios. Methods. We studied the response of winter wheat yield and WUE to different DI levels at pre-anthesis under two Shared Socioeconomic Pathways (SSPs) scenarios (SSP245 and SSP585) using the Agricultural Production Systems Simulator (APSIM) model driven by 21 general circulation models (GCMs) from the Coupled Model Inter-Comparison Project phase 6 (CMIP6). Additionally, we explored the effects of different nitrogen (N) fertilizer application rates on DI. Results. We found that simulated wheat yield would increase by 3.5–45.0%, with WUE increasing by 8.8–46.4% across all treatments under future climate change. Moderate deficit irrigation (DI3, ≤0.4 PAWC at the sowing to flowering stage) under the N3 (150 kg N ha−1) condition was identified as the optimum irrigation schedule for the study site under future climate change. However, compensation effects of DI3 on yield and WUE became weak in the future, which was mainly due to increased growing season rainfall projected by GCMs. In addition, we found that N fertilizer application could mitigate the effect of DI3. Conclusions. We highlight that in water scarce regions of NCP, DI remains an effective strategy to maintain higher yield and enhance water use under future climate scenarios. Results strongly suggest that moderate deficit irrigation under a 150 kg N ha−1 condition could mitigate the contradiction between production and water consumption and ensure food safety in the NCP.
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Affiliation(s)
- Xiaoli Niu
- College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471000, China; (X.N.); (N.Z.); (T.M.)
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Pine Gully Road, Wagga Wagga, NSW 2650, Australia
| | - Puyu Feng
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China;
| | - De-Li Liu
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Pine Gully Road, Wagga Wagga, NSW 2650, Australia
- Climate Change Research Centre, University of New South Wales, High Street, Sydney, NSW 2052, Australia
- Correspondence: (D.-L.L.); (B.W.)
| | - Bin Wang
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, Pine Gully Road, Wagga Wagga, NSW 2650, Australia
- Correspondence: (D.-L.L.); (B.W.)
| | - Cathy Waters
- NSW Department of Primary Industries, 34 Hampden Street, Dubbo, NSW 2830, Australia;
| | - Na Zhao
- College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471000, China; (X.N.); (N.Z.); (T.M.)
| | - Tiancheng Ma
- College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471000, China; (X.N.); (N.Z.); (T.M.)
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49
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Katz A, Byrne P, Reid S, Bratschun S, Haley S, Pearce S. Identification and validation of a QTL for spikelet number on chromosome arm 6BL of common wheat ( Triticum aestivum L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2022; 42:17. [PMID: 37309457 PMCID: PMC10248590 DOI: 10.1007/s11032-022-01288-7] [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: 07/30/2021] [Accepted: 03/07/2022] [Indexed: 06/14/2023]
Abstract
To provide food security for a growing world population, it will be necessary to increase yields of staple crops such as wheat (Triticum aestivum L.). Yield is a complex, polygenic trait influenced by grain weight and number, which are negatively correlated with one another. Spikelet number is an important determinant of grain number, but allelic variants impacting its expression are often associated with heading date, constraining their use in wheat germplasm that must be adapted for specific environments. Identification and characterization of genetic variants affecting spikelet number will increase selection efficiency through their deployment in breeding programs. In this study, a quantitative trait locus (QTL) on chromosome arm 6BL for spikelet number was identified and validated using an association mapping panel, a recombinant inbred line population, and seven derived heterogeneous inbred families. The superior allele, QSn.csu-6Bb, was associated with an increase of 0.248 to 0.808 spikelets per spike across multiple environments that varied for mean spikelet number. Despite epistatic interactions between QSn.csu-6B and three other loci (WAPO-A1, VRN-D3, and PPD-B1), genotypes with a greater number of superior alleles at these loci consistently exhibit higher spikelet number. The frequency of superior alleles at these loci varies among winter wheat varieties adapted to different latitudes of the US Great Plains, revealing opportunities for breeders to select for increased spikelet number using simple molecular markers. This work lays the foundation for the positional cloning of the genetic variant underlying the QSn.csu-6B QTL to strengthen our understanding of spikelet number determination in wheat. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-022-01288-7.
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Affiliation(s)
- Andrew Katz
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Patrick Byrne
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Scott Reid
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Sarah Bratschun
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Scott Haley
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
| | - Stephen Pearce
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523 USA
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50
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Yang Z, Wang Z, Wang W, Xie X, Chai L, Wang X, Feng X, Li J, Peng H, Su Z, You M, Yao Y, Xin M, Hu Z, Liu J, Liang R, Ni Z, Sun Q, Guo W. ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat. PLANT PHYSIOLOGY 2022; 188:1950-1965. [PMID: 35088857 PMCID: PMC8968352 DOI: 10.1093/plphys/kiac029] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/10/2021] [Indexed: 05/31/2023]
Abstract
Accurate germplasm characterization is a vital step for accelerating crop genetic improvement, which remains largely infeasible for crops such as bread wheat (Triticum aestivum L.), which has a complex genome that undergoes frequent introgression and contains many structural variations. Here, we propose a genomic strategy called ggComp, which integrates resequencing data with copy number variations and stratified single-nucleotide polymorphism densities to enable unsupervised identification of pairwise germplasm resource-based Identity-By-Descent (gIBD) blocks. The reliability of ggComp was verified in wheat cultivar Nongda5181 by dissecting parental-descent patterns represented by inherited genomic blocks. With gIBD blocks identified among 212 wheat accessions, we constructed a multi-scale genomic-based germplasm network. At the whole-genome level, the network helps to clarify pedigree relationship, demonstrate genetic flow, and identify key founder lines. At the chromosome level, we were able to trace the utilization of 1RS introgression in modern wheat breeding by hitchhiked segments. At the single block scale, the dissected germplasm-based haplotypes nicely matched with previously identified alleles of "Green Revolution" genes and can guide allele mining and dissect the trajectory of beneficial alleles in wheat breeding. Our work presents a model-based framework for precisely evaluating germplasm resources with genomic data. A database, WheatCompDB (http://wheat.cau.edu.cn/WheatCompDB/), is available for researchers to exploit the identified gIBDs with a multi-scale network.
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Affiliation(s)
| | | | | | - Xiaoming Xie
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Lingling Chai
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Xiaobo Wang
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Xibo Feng
- Tibet Key Experiments of Crop Cultivation and Farming/College of Plant Science, Tibet Agriculture and Animal Husbandry University, Linzhi 860000, China
| | - Jinghui Li
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Wheat Center, Henan Institute of Science and Technology/Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang 453003, China
| | - Huiru Peng
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhenqi Su
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Mingshan You
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yingyin Yao
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Mingming Xin
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhaorong Hu
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Jie Liu
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Rongqi Liang
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhongfu Ni
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Qixin Sun
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
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