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Wang Z, Niu Y, Xie Y, Huang C, Yung WS, Li MW, Wong FL, Lam HM. QTL mapping and BSR-seq revealed loci and candidate genes associated with the sporadic multifoliolate phenotype in soybean (Glycine max). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:262. [PMID: 39511005 PMCID: PMC11543727 DOI: 10.1007/s00122-024-04765-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: 06/13/2024] [Accepted: 10/15/2024] [Indexed: 11/15/2024]
Abstract
KEY MESSAGE The QTLs and candidate genes governing the multifoliolate phenotype were identified by combining linkage mapping with BSR-seq, revealing a possible interplay between genetics and the environment in soybean leaf development. Soybean, as a legume, is typified by trifoliolate leaves. Although multifoliolate leaves (compound leaves with more than three leaflets each) have been reported in soybean, including sporadic appearances in the first compound leaves in a recombinant inbred line (RIL) population from a cross between cultivated soybean C08 and wild soybean W05 from this study, the genetic basis of this phenomenon is still unclear. Here, we integrated quantitative trait locus (QTL) mapping with bulked segregant RNA sequencing (BSR-seq) to identify the genetic loci associated with the multifoliolate phenotype in soybean. Using linkage mapping, ten QTLs related to the multifoliolate trait were identified. Among these, a significant and major QTL, qMF-2-1 on chromosome 2 and consistently detected across biological replicates, explained more than 10% of the phenotypic variation. Together with BSR-seq analyses, which analyzed the RILs with the highest multifoliolate frequencies and those with the lowest frequencies as two distinct bulks, two candidate genes were identified: Glyma.06G204300 encoding the transcription factor TCP5, and Glyma.06G204400 encoding LONGIFOLIA 2 (LNG2). Transcriptome analyses revealed that stress-responsive genes were significantly differentially expressed between high-multifoliolate occurrence lines and low occurrence ones, indicating environmental factors probably influence the appearance of multifoliolate leaves in soybean through stress-responsive genes. Hence, this study offers new insights into the genetic mechanism behind the multifoliolate phenotype in soybean.
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Affiliation(s)
- Zhili Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Yongchao Niu
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Yichun Xie
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Cheng Huang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
- Key Laboratory of the Ministry of Education for Crop Physiology and Molecular Biology, College of Agronomy, Hunan Agricultural University, Changsha, 410128, China
| | - Wai-Shing Yung
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China
| | - Man-Wah Li
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Fuk-Ling Wong
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China
| | - Hon-Ming Lam
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China.
- Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China.
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Li B, Wang Z, Jiang H, Luo JH, Guo T, Tian F, Rossi V, He Y. ZmCCT10-relayed photoperiod sensitivity regulates natural variation in the arithmetical formation of male germinal cells in maize. THE NEW PHYTOLOGIST 2023; 237:585-600. [PMID: 36266961 DOI: 10.1111/nph.18559] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Extensive mutational screening studies have documented genes regulating anther and pollen development. Knowledge concerning how formation of male germinal cell is arithmetically controlled in natural populations, under different environmental conditions, is lacking. We counted pollen number within a single anther and a maize-teosinte BC2 S3 recombinant inbred line population to identify ZmCCT10 as a major determinant of pollen number variation. ZmCCT10 was originally identified as a photoperiod-sensitive negative regulator of flowering. ZmCCT10 inactivation, after transposon insertion within its promoter, is proposed to have accelerated maize spread toward higher latitudes, thus allowing temperate maize to flower under long-day conditions. We showed that the active ZmCCT10 allele decreased pollen formation. As different active and inactive ZmCCT10 alleles have been found in natural maize populations, this represents the first report of a gene controlling pollen number in a crop natural population. These findings suggest that higher pollen number, which provides a competitive advantage in open-pollinated populations, may have been one of the major driving forces for the selection of an inactive ZmCCT10 allele during tropical maize domestication. We provide evidence that ZmCCT10 has opposite effects on cell proliferation of archesporial and tapetum cells and it modulates expression of key regulators during early anther development.
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Affiliation(s)
- Bo Li
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Zi Wang
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Huan Jiang
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Jin-Hong Luo
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Ting Guo
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Feng Tian
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
| | - Vincenzo Rossi
- Council for Agricultural Research and Economics, Research Centre for Cereal and Industrial Crops, Bergamo, 24126, Italy
| | - Yan He
- MOE Key Laboratory of Crop Heterosis and Utilization, National Maize Improvement Center of China, China Agricultural University, Beijing, 100094, China
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3
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Wang Z, Huang C, Niu Y, Yung WS, Xiao Z, Wong FL, Huang M, Wang X, Man CK, Sze CC, Liu A, Wang Q, Chen Y, Liu S, Wu C, Liu L, Hou W, Han T, Li MW, Lam HM. QTL analyses of soybean root system architecture revealed genetic relationships with shoot-related traits. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4507-4522. [PMID: 36422673 DOI: 10.1007/s00122-022-04235-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
The genetic basis of soybean root system architecture (RSA) and the genetic relationship between shoot and RSA were revealed by integrating data from recombinant inbred population grafting and QTL mapping. Variations in root system architecture (RSA) affect the functions of roots and thus play vital roles in plant adaptations and agricultural productivity. The aim of this study was to unravel the genetic relationship between RSA traits and shoot-related traits in soybean. This study characterized RSA variability at seedling stage in a recombinant inbred population, derived from a cross between cultivated soybean C08 and wild soybean W05, and performed high-resolution quantitative trait locus (QTL) mapping. In total, 34 and 41 QTLs were detected for RSA-related and shoot-related traits, respectively, constituting eight QTL clusters. Significant QTL correspondence was found between shoot biomass and RSA-related traits, consistent with significant correlations between these phenotypes. RSA-related QTLs also overlapped with selection regions in the genome, suggesting the cultivar RSA could be a partial consequence of domestication. Using reciprocal grafting, we confirmed that shoot-derived signals affected root development and the effects were controlled by multiple loci. Meanwhile, RSA-related QTLs were found to co-localize with four soybean flowering-time loci. Consistent with the phenotypes of the parental lines of our RI population, diminishing the function of flowering controlling E1 family through RNA interference (RNAi) led to reduced root growth. This implies that the flowering time-related genes within the RSA-related QTLs are actually contributing to RSA. To conclude, this study identified the QTLs that determine RSA through controlling root growth indirectly via regulating shoot functions, and discovered superior alleles from wild soybean that could be used to improve the root structure in existing soybean cultivars.
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Affiliation(s)
- Zhili Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Cheng Huang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- College of Agronomy, Hunan Agricultural University, Changsha, 410128, China
| | - Yongchao Niu
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Wai-Shing Yung
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Zhixia Xiao
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Fuk-Ling Wong
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Mingkun Huang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Lushan Botanical Garden, Chinese Academy of Sciences, Jiujiang, 332900, Jiangxi, China
| | - Xin Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Chun-Kuen Man
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Ching-Ching Sze
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Ailin Liu
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Qianwen Wang
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China
| | - Yinglong Chen
- The UWA Institute of Agriculture, & School of Agriculture and Environment, The University of Western Australia, Perth, WA6001, Australia
- State Key Laboratory of Soil Erosion and Dryland Farming On the Loess Plateau, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Shuo Liu
- State Key Laboratory of Soil Erosion and Dryland Farming On the Loess Plateau, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Cunxiang Wu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, The Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Lifeng Liu
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, The Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Wensheng Hou
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, The Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Tianfu Han
- Ministry of Agriculture and Rural Affairs Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, The Chinese Academy of Agricultural Sciences, 12 Zhongguancun South Street, Beijing, 100081, China
| | - Man-Wah Li
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
| | - Hon-Ming Lam
- Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
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Zhang A, Zhao T, Hu X, Zhou Y, An Y, Pei H, Sun D, Sun G, Li C, Ren X. Identification of QTL underlying the main stem related traits in a doubled haploid barley population. FRONTIERS IN PLANT SCIENCE 2022; 13:1063988. [PMID: 36531346 PMCID: PMC9751491 DOI: 10.3389/fpls.2022.1063988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
Lodging reduces grain yield in cereal crops. The height, diameter and strength of stem are crucial for lodging resistance, grain yield, and photosynthate transport in barley. Understanding the genetic basis of stem benefits barley breeding. Here, we evaluated 13 stem related traits after 28 days of heading in a barley DH population in two consecutive years. Significant phenotypic correlations between lodging index (LI) and other stem traits were observed. Three mapping methods using the experimental data and the BLUP data, detected 27 stable and major QTLs, and 22 QTL clustered regions. Many QTLs were consistent with previously reported traits for grain filling rate, internodes, panicle and lodging resistance. Further, candidate genes were predicted for stable and major QTLs and were associated with plant development and adverse stress in the transition from vegetative stage to reproductive stage. This study provided potential genetic basis and new information for exploring barley stem morphology, and laid a foundation for map-based cloning and further fine mapping of these QTLs.
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Affiliation(s)
- Anyong Zhang
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Ting Zhao
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Xue Hu
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yu Zhou
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yue An
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Haiyi Pei
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Dongfa Sun
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Genlou Sun
- Department of Biology, Saint Mary’s University, Halifax, NS, Canada
| | - Chengdao Li
- College of Science, Health, Engineering and Education, Murdoch University, Murdoch, WA, Australia
| | - Xifeng Ren
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
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5
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Zhang F, Ding Y, Zhang J, Tang M, Cao Y, Zhang L, Ma Z, Qi J, Mu X, Xia L, Tang B. Comparative transcriptomic reveals the molecular mechanism of maize hybrid Zhengdan538 in response to water deficit. PHYSIOLOGIA PLANTARUM 2022; 174:e13818. [PMID: 36345780 DOI: 10.1111/ppl.13818] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 09/23/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Heterosis, known as one of the most successful strategies for increasing grain yield and abiotic/biotic stress tolerance, has been widely exploited in maize breeding. However, the underlying molecular processes are still to be elucidated. The maize hybrid "Zhengdan538" shows high tolerance to drought stress. The transcriptomes of the seedling leaves of its parents, "ZhengA88" and "ZhengT22" and their reciprocal F1 hybrid under well-watered and water deficit conditions, were analyzed by RNA sequencing (RNA-Seq). Transcriptome profiling of the reciprocal hybrid revealed 2994-4692 differentially expressed genes (DEGs) under well-watered and water-deficit conditions, which were identified by comparing with their parents. The reciprocal hybrid was more closely related to the parental line "ZhengT22" than to the parental line "ZhengA88" in terms of gene expression patterns under water-deficit condition. Furthermore, genes showed expression level dominance (ELD), especially the high-parental ELD (Class 3 and 5), accounted for the largest proportion of DEGs between the reciprocal F1 hybrid and their parental lines under water deficit. These ELD genes mainly participated in photosynthesis, energy biosynthesis, and metabolism processes. The results indicated that ELD genes played important roles in hybrid tolerance to water deficit. Moreover, a set of important drought-responsive transcription factors were found to be encoded by the identified ELD genes and are thought to function in improving drought tolerance in maize hybrid plants. Our results provide a better understanding of the molecular mechanism of drought tolerance in hybrid maize.
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Affiliation(s)
- Fengqi Zhang
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Yong Ding
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Jun Zhang
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Minqiang Tang
- The Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Ministry of Education), College of Forestry, Hainan University, Haikou, China
| | - Yanyong Cao
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Lanxun Zhang
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Zhiyan Ma
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Jianshuang Qi
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Xinyuan Mu
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Laikun Xia
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
| | - Baojun Tang
- Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology/Henan International Joint Laboratory on Maize Precision Production, Zhengzhou, China
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6
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Sun G, Zhang X, Duan H, Gao J, Li N, Su P, Xie H, Li W, Fu Z, Huang Y, Tang J. Dissection of the genetic architecture of peduncle vascular bundle-related traits in maize by a genome-wide association study. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1042-1053. [PMID: 35080335 PMCID: PMC9129077 DOI: 10.1111/pbi.13782] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 12/20/2021] [Accepted: 01/17/2022] [Indexed: 06/14/2023]
Abstract
The peduncle vascular system of maize is critical for the transport of photosynthetic products, nutrients, and water from the roots and leaves to the ear. Accordingly, it positively affects the grain yield. However, the genetic basis of peduncle vascular bundle (PVB)-related traits in maize remains unknown. Thus, 15 PVB-related traits of 386 maize inbred lines were investigated at three locations (Yongcheng, 17YC; Kaifeng, 20KF; and Yuanyang, 20YY). The repeatability for the 15 traits ranged from 35.53% to 92.13%. A genome-wide association study was performed and 69 non-redundant quantitative trait loci (QTL) were detected, including 9, 41, and 27 QTL identified at 17YC, 20KF, and 20YY, respectively. These QTL jointly explained 4.72% (SLL) to 37.30% (NSVB) of the phenotypic variation. Eight QTL were associated with the same trait at two locations. Furthermore, four pleiotropic QTL were identified. Moreover, one QTL (qPVB44), associated with NSVB_20KF, was co-localized with a previously reported locus related to kernel width, implying qPVB44 may affect the kernel width by modulating the number of small vascular bundles. Examinations of the 69 QTL identified 348 candidate genes that were classified in five groups. Additionally, 26 known VB-related homologous genes (e.g. VLN2, KNOX1, and UGT72B3) were detected in 20 of the 69 QTL. A comparison of the NSVB between a Zmvln2 EMS mutant and its wild type elucidated the function of the candidate gene ZmVLN2. These results are important for clarifying the genetic basis of PVB-related traits and may be useful for breeding new high-yielding maize cultivars.
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Affiliation(s)
- Gaoyang Sun
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
- College of AgronomySichuan Agricultural UniversityChengduChina
| | - Xuehai Zhang
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Haiyang Duan
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Jionghao Gao
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Na Li
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Pingping Su
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Huiling Xie
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Weihua Li
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Zhiyuan Fu
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
| | - Yubi Huang
- College of AgronomySichuan Agricultural UniversityChengduChina
| | - Jihua Tang
- National Key Laboratory of Wheat and Maize Crop ScienceCollege of AgronomyHenan Agricultural UniversityZhengzhouChina
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7
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Guo S, Zhou G, Wang J, Lu X, Zhao H, Zhang M, Guo X, Zhang Y. High-Throughput Phenotyping Accelerates the Dissection of the Phenotypic Variation and Genetic Architecture of Shank Vascular Bundles in Maize (Zea mays L.). PLANTS 2022; 11:plants11101339. [PMID: 35631765 PMCID: PMC9145235 DOI: 10.3390/plants11101339] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/16/2022] [Accepted: 05/16/2022] [Indexed: 11/18/2022]
Abstract
The vascular bundle of the shank is an important ‘flow’ organ for transforming maize biological yield to grain yield, and its microscopic phenotypic characteristics and genetic analysis are of great significance for promoting the breeding of new varieties with high yield and good quality. In this study, shank CT images were obtained using the standard process for stem micro-CT data acquisition at resolutions up to 13.5 μm. Moreover, five categories and 36 phenotypic traits of the shank including related to the cross-section, epidermis zone, periphery zone, inner zone and vascular bundle were analyzed through an automatic CT image process pipeline based on the functional zones. Next, we analyzed the phenotypic variations in vascular bundles at the base of the shank among a group of 202 inbred lines based on comprehensive phenotypic information for two environments. It was found that the number of vascular bundles in the inner zone (IZ_VB_N) and the area of the inner zone (IZ_A) varied the most among the different subgroups. Combined with genome-wide association studies (GWAS), 806 significant single nucleotide polymorphisms (SNPs) were identified, and 1245 unique candidate genes for 30 key traits were detected, including the total area of vascular bundles (VB_A), the total number of vascular bundles (VB_N), the density of the vascular bundles (VB_D), etc. These candidate genes encode proteins involved in lignin, cellulose synthesis, transcription factors, material transportation and plant development. The results presented here will improve the understanding of the phenotypic traits of maize shank and provide an important phenotypic basis for high-throughput identification of vascular bundle functional genes of maize shank and promoting the breeding of new varieties with high yield and good quality.
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Affiliation(s)
- Shangjing Guo
- College of Agronomy, Liaocheng University, Liaocheng 252059, China; (S.G.); (G.Z.)
| | - Guoliang Zhou
- College of Agronomy, Liaocheng University, Liaocheng 252059, China; (S.G.); (G.Z.)
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
| | - Jinglu Wang
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
| | - Xianju Lu
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
| | - Huan Zhao
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
| | - Minggang Zhang
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
| | - Xinyu Guo
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
- Correspondence: (X.G.); (Y.Z.)
| | - Ying Zhang
- Beijing Key Lab of Digital Plant, Research Center of Information Technology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (J.W.); (X.L.); (H.Z.); (M.Z.)
- Correspondence: (X.G.); (Y.Z.)
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8
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Zheng Y, Hou P, Zhu L, Song W, Liu H, Huang Y, Wang H, Guo J. Genome-Wide Association Study of Vascular Bundle-Related Traits in Maize Stalk. FRONTIERS IN PLANT SCIENCE 2021; 12:699486. [PMID: 34504506 PMCID: PMC8423097 DOI: 10.3389/fpls.2021.699486] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/18/2021] [Indexed: 06/13/2023]
Abstract
The vascular bundle plays an important role in nutrient transportation in plants and exerts great influence on crop yield. Maize is widely used for food, feed, and fuel, producing the largest yield in the world. However, genes and molecular mechanism controlling vascular bundle-related traits in maize have largely remained undiscovered. In this study, a natural population containing 248 diverse maize inbred lines genotyped with high-throughput SNP markers was used for genome-wide association study. The results showed that broad variations existed for the vascular bundle-related traits which are subject to genetic structure and it was suitable for association analysis. In this study, we identified 15, 13, 2, 1, and 5 SNPs significantly associated with number of small vascular bundle, number of large vascular bundle, average area of single small vascular bundle, average area of single large vascular bundle, and cross-sectional area, respectively. The 210 candidate genes in the confidence interval can be classified into ten biological processes, three cellular components, and eight molecular functions. As for the Kyoto Encyclopedia of Genes and Genomes analysis of the candidate genes, a total of six pathways were identified. Finally, we found five genes related to vascular development, three genes related to cell wall, and two genes related to the mechanical strength of the stalk. Our results provide the further understanding of the genetic foundation of vascular bundle-related traits in maize stalk.
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Affiliation(s)
- Yunxiao Zheng
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Peng Hou
- Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Liying Zhu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Weibin Song
- State Key Laboratory of Agrobiotechnology, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China
| | - Han Liu
- State Key Laboratory of Agrobiotechnology, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China
- Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Yaqun Huang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Hong Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Baoding, China
| | - Jinjie Guo
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Baoding, China
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9
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Liang Y, Liu HJ, Yan J, Tian F. Natural Variation in Crops: Realized Understanding, Continuing Promise. ANNUAL REVIEW OF PLANT BIOLOGY 2021; 72:357-385. [PMID: 33481630 DOI: 10.1146/annurev-arplant-080720-090632] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Crops feed the world's population and shape human civilization. The improvement of crop productivity has been ongoing for almost 10,000 years and has evolved from an experience-based to a knowledge-driven practice over the past three decades. Natural alleles and their reshuffling are long-standing genetic changes that affect how crops respond to various environmental conditions and agricultural practices. Decoding the genetic basis of natural variation is central to understanding crop evolution and, in turn, improving crop breeding. Here, we review current advances in the approaches used to map the causal alleles of natural variation, provide refined insights into the genetics and evolution of natural variation, and outline how this knowledge promises to drive the development of sustainable agriculture under the dome of emerging technologies.
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Affiliation(s)
- Yameng Liang
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China; ,
| | - Hai-Jun Liu
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna BioCenter, 1030 Vienna, Austria;
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China;
| | - Feng Tian
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China; ,
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10
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Zhang X, Lu M, Xia A, Xu T, Cui Z, Zhang R, Liu W, He Y. Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population. BMC Genomics 2021; 22:386. [PMID: 34034669 PMCID: PMC8152318 DOI: 10.1186/s12864-021-07723-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/12/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear. RESULTS A linkage population including 191 BC2F8 inbred lines generated from the maize line Mo17 and the teosinte line X26-4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively. CONCLUSIONS The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.
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Affiliation(s)
- Xiaolei Zhang
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China
| | - Ming Lu
- Maize Research Institute, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, China
| | - Aiai Xia
- Sanya institute of China Agricultural University, Sanya, 572025, China
| | - Tao Xu
- Tieling Academy of Agricultural Sciences, Tieling, 112000, China
| | - Zhenhai Cui
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
| | - Ruiying Zhang
- Quality and Safety Institute of Agricultural Products, Heilongjiang Academy of Agricultural Sciences, Harbin, 150086, China.
| | - Wenguo Liu
- Maize Research Institute, Jilin Academy of Agricultural Sciences, Gongzhuling, 136100, China.
| | - Yan He
- Sanya institute of China Agricultural University, Sanya, 572025, China.
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11
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El Hage F, Virlouvet L, Lopez-Marnet PL, Griveau Y, Jacquemot MP, Coursol S, Méchin V, Reymond M. Responses of Maize Internode to Water Deficit Are Different at the Biochemical and Histological Levels. FRONTIERS IN PLANT SCIENCE 2021; 12:628960. [PMID: 33719300 PMCID: PMC7952650 DOI: 10.3389/fpls.2021.628960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 01/22/2021] [Indexed: 06/12/2023]
Abstract
Maize feeding value is strongly linked to plant digestibility. Cell wall composition and structure can partly explain cell wall digestibility variations, and we recently showed that tissue lignification and lignin spatial distribution also contribute to cell wall digestibility variations. Although the genetic determinism of digestibility and cell wall composition has been studied for more than 20 years, little is available concerning that of tissue lignification. Moreover, maize yield is negatively impacted by water deficit, and we newly highlighted the impact of water deficit on cell wall digestibility and composition together with tissue lignification. Consequently, the aim of this study was to explore the genetic mechanisms of lignin distribution in link with cell wall composition and digestibility under contrasted water regimes. Maize internodes from a recombinant inbred line (RIL) population grown in field trials with contrasting irrigation scenarios were biochemically and histologically quantified. Results obtained showed that biochemical and histological traits have different response thresholds to water deficit. Histological profiles were therefore only modified under pronounced water deficit, while most of the biochemical traits responded whatever the strength of the water deficit. Three main clusters of quantitative trait locus (QTL) for histological traits were detected. Interestingly, overlap between the biochemical and histological clusters is rare, and one noted especially colocalizations between histological QTL/clusters and QTL for p-coumaric acid content. These findings reinforce the suspected role of tissue p-coumaroylation for both the agronomic properties of plants as well as their digestibility.
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Affiliation(s)
- Fadi El Hage
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
- Ecole Doctorale n° 567: Science du Végétal: Du gène à l’écosystème, Université Paris-Saclay, Orsay, France
| | - Laetitia Virlouvet
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Paul-Louis Lopez-Marnet
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
- Ecole Doctorale n° 581: ABIES, Paris, France
| | - Yves Griveau
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Marie-Pierre Jacquemot
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Sylvie Coursol
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Valérie Méchin
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
| | - Matthieu Reymond
- Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris-Saclay, Versailles, France
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12
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Zhang Y, Wang J, Du J, Zhao Y, Lu X, Wen W, Gu S, Fan J, Wang C, Wu S, Wang Y, Liao S, Zhao C, Guo X. Dissecting the phenotypic components and genetic architecture of maize stem vascular bundles using high-throughput phenotypic analysis. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:35-50. [PMID: 32569428 PMCID: PMC7769239 DOI: 10.1111/pbi.13437] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 06/03/2020] [Accepted: 06/15/2020] [Indexed: 05/27/2023]
Abstract
High-throughput phenotyping is increasingly becoming an important tool for rapid advancement of genetic gain in breeding programmes. Manual phenotyping of vascular bundles is tedious and time-consuming, which lags behind the rapid development of functional genomics in maize. More robust and automated techniques of phenotyping vascular bundles traits at high-throughput are urgently needed for large crop populations. In this study, we developed a standard process for stem micro-CT data acquisition and an automatic CT image process pipeline to obtain vascular bundle traits of stems including geometry-related, morphology-related and distribution-related traits. Next, we analysed the phenotypic variation of stem vascular bundles between natural population subgroup (480 inbred lines) based on 48 comprehensively phenotypic information. Also, the first database for stem micro-phenotypes, MaizeSPD, was established, storing 554 pieces of basic information of maize inbred lines, 523 pieces of experimental information, 1008 pieces of CT scanning images and processed images, and 24 192 pieces of phenotypic data. Combined with genome-wide association studies (GWASs), a total of 1562 significant single nucleotide polymorphism (SNPs) were identified for 30 stem micro-phenotypic traits, and 84 unique genes of 20 traits such as VBNum, VBAvArea and PZVBDensity were detected. Candidate genes identified by GWAS mainly encode enzymes involved in cell wall metabolism, transcription factors, protein kinase and protein related to plant signal transduction and stress response. The results presented here will advance our knowledge about phenotypic trait components of stem vascular bundles and provide useful information for understanding the genetic controls of vascular bundle formation and development.
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Affiliation(s)
- Ying Zhang
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Jinglu Wang
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Jianjun Du
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Yanxin Zhao
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular BreedingMaize Research CenterBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Xianju Lu
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Weiliang Wen
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Shenghao Gu
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Jiangchuan Fan
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Chuanyu Wang
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Sheng Wu
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Yongjian Wang
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Shengjin Liao
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Chunjiang Zhao
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
| | - Xinyu Guo
- Beijing Key Lab of Digital PlantNational Engineering Research Center for Information Technology in AgricultureBeijing Research Center for Information Technology in AgricultureBeijing Academy of Agriculture and Forestry SciencesBeijingChina
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13
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QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in Plants. G3-GENES GENOMES GENETICS 2020; 10:2411-2421. [PMID: 32430305 PMCID: PMC7341141 DOI: 10.1534/g3.120.401122] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. While it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as the training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. The average precision was 0.027 for Arabidopsis and 0.029 for rice. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. In addition, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.
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14
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Field Screening of Rice Germplasm ( Oryza sativa L. ssp. japonica) Based on Days to Flowering for Drought Escape. PLANTS 2020; 9:plants9050609. [PMID: 32403343 PMCID: PMC7284638 DOI: 10.3390/plants9050609] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 05/05/2020] [Accepted: 05/05/2020] [Indexed: 11/17/2022]
Abstract
Terminal drought stress is one of the restrictive factors in rice production and is expected to upsurge under the current situation of climate change. The study evaluated the performance of 2030 rice genotypes under continuous drought stress conditions based on days to flowering (DF). The genotypes under augmented randomized complete block design were sown in May/June of 2017 and 2018 in the field with movable rainout that resulted in huge genetic diversity among the accessions. Descriptive statistics confirmed clear variation among accessions on growth duration, plant height to leaf, plant height to panicle, and germination percentage. Correlation, chemometric, and agglomerative hierarchical cluster analyses were performed that categorized the germplasm into 10 groups. Genotypes in clusters VIII and IX (drought-resistant) revealed better agronomic performance in terms of reduced days to flowering, but conversely taller plant height and higher maturity (%) under severe stress. Genotypes in clusters IV, V, and X were discovered to be drought-susceptible. The screened genotypes like Longjing 12, Longdun 102, Yanjing 22, Liaojing 27, Xiaohongbandao, Songjing 17, and Zaoshuqingsen can be utilized in rice breeding improvement programs for drought tolerance in terms of severe continuous drought, as well as terminal drought stress.
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15
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Chen Q, Yang CJ, York AM, Xue W, Daskalska LL, DeValk CA, Krueger KW, Lawton SB, Spiegelberg BG, Schnell JM, Neumeyer MA, Perry JS, Peterson AC, Kim B, Bergstrom L, Yang L, Barber IC, Tian F, Doebley JF. TeoNAM: A Nested Association Mapping Population for Domestication and Agronomic Trait Analysis in Maize. Genetics 2019; 213:1065-1078. [PMID: 31481533 PMCID: PMC6827374 DOI: 10.1534/genetics.119.302594] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 08/30/2019] [Indexed: 12/21/2022] Open
Abstract
Recombinant inbred lines (RILs) are an important resource for mapping genes controlling complex traits in many species. While RIL populations have been developed for maize, a maize RIL population with multiple teosinte inbred lines as parents has been lacking. Here, we report a teosinte nested association mapping (TeoNAM) population, derived from crossing five teosinte inbreds to the maize inbred line W22. The resulting 1257 BC1S4 RILs were genotyped with 51,544 SNPs, providing a high-density genetic map with a length of 1540 cM. On average, each RIL is 15% homozygous teosinte and 8% heterozygous. We performed joint linkage mapping (JLM) and a genome-wide association study (GWAS) for 22 domestication and agronomic traits. A total of 255 QTL from JLM were identified, with many of these mapping near known genes or novel candidate genes. TeoNAM is a useful resource for QTL mapping for the discovery of novel allelic variation from teosinte. TeoNAM provides the first report that PROSTRATE GROWTH1, a rice domestication gene, is also a QTL associated with tillering in teosinte and maize. We detected multiple QTL for flowering time and other traits for which the teosinte allele contributes to a more maize-like phenotype. Such QTL could be valuable in maize improvement.
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Affiliation(s)
- Qiuyue Chen
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Chin Jian Yang
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Alessandra M York
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Wei Xue
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Lora L Daskalska
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Craig A DeValk
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Kyle W Krueger
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Samuel B Lawton
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | | | - Jack M Schnell
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Michael A Neumeyer
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Joseph S Perry
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Aria C Peterson
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Brandon Kim
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Laura Bergstrom
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Liyan Yang
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
- School of Life Science, Shanxi Normal University, Linfen, Shanxi 041004, China
| | - Isaac C Barber
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
| | - Feng Tian
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - John F Doebley
- Laboratory of Genetics, University of Wisconsin-Madison, Wisconsin 53706
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16
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Xu G, Cao J, Wang X, Chen Q, Jin W, Li Z, Tian F. Evolutionary Metabolomics Identifies Substantial Metabolic Divergence between Maize and Its Wild Ancestor, Teosinte. THE PLANT CELL 2019; 31:1990-2009. [PMID: 31227559 PMCID: PMC6751114 DOI: 10.1105/tpc.19.00111] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 06/03/2019] [Accepted: 06/17/2019] [Indexed: 05/04/2023]
Abstract
Maize (Zea mays subsp mays) was domesticated from its wild ancestor, teosinte (Zea mays subsp parviglumis). Maize's distinct morphology and adaptation to diverse environments required coordinated changes in various metabolic pathways. However, how the metabolome was reshaped since domestication remains poorly understood. Here, we report a comprehensive assessment of divergence in the seedling metabolome between maize and teosinte. In total, 461 metabolites exhibited significant divergence due to selection. Interestingly, teosinte and tropical and temperate maize, representing major stages of maize evolution, targeted distinct sets of metabolites. Alkaloids, terpenoids, and lipids were specifically targeted in the divergence between teosinte and tropical maize, while benzoxazinoids were specifically targeted in the divergence between tropical and temperate maize. To identify genetic factors controlling metabolic divergence, we assayed the seedling metabolome of a large maize-by-teosinte cross population. We show that the recent metabolic divergence between tropical and temperate maize tended to have simpler genetic architecture than the divergence between teosinte and tropical maize. Through integrating transcriptome data, we identified candidate genes contributing to metabolic divergence, many of which were under selection at the nucleotide and transcript levels. Through overexpression or mutant analysis, we verified the roles of Flavanone 3-hydroxylase1, Purple aleurone1, and maize terpene synthase1 in the divergence of their related biosynthesis pathways. Our findings not only provide important insights into domestication-associated changes in the metabolism but also highlight the power of combining omics data for trait dissection.
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Affiliation(s)
- Guanghui Xu
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Jingjing Cao
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
- Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Xufeng Wang
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Qiuyue Chen
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Weiwei Jin
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Zhen Li
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Feng Tian
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing 100193, China
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17
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Cao Y, Liang X, Yin P, Zhang M, Jiang C. A domestication-associated reduction in K + -preferring HKT transporter activity underlies maize shoot K + accumulation and salt tolerance. THE NEW PHYTOLOGIST 2019; 222:301-317. [PMID: 30461018 DOI: 10.1111/nph.15605] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 11/10/2018] [Indexed: 05/26/2023]
Abstract
Maize was domesticated from Balsas teosinte c. 10 000 yr ago. Previous studies have suggested that increased tolerance to environmental stress occurred during maize domestication. However, the underlying genetic basis remains largely unknown. We used a maize (W22)-teosinte recombinant inbred line (RIL) to investigate the salt wild-type tolerance aspects of maize domestication. We revealed that ZmHKT2 is a major QTL that regulates K+ homeostasis in saline soils. ZmHKT2 encodes a K+ -preferring HKT family transporter and probably reduces shoot K+ content by removing K+ ions from root-to-shoot flowing xylem sap, ZmHKT2 deficiency increases xylem sap and shoot K+ concentrations, and increases salt tolerance. A coding sequence polymorphism in the ZmHKT2W22 allele (SNP389-G) confers an amino acid variant ZmHKT2 that increases xylem sap K+ concentration, thereby increasing shoot K+ content and salt tolerance. Additional analyses showed that SNP389-G first existed in teosinte (allele frequency 56% in assayed accessions), then swept through the maize population (allele frequency 98%), and that SNP389-G probably underwent positive selection during maize domestication. We conclude that a domestication-associated reduction in K+ transport activity in ZmHKT2 underlies maize shoot K+ content and salt tolerance, and propose that CRISPR-based editing of ZmHKT2 might provide a feasible strategy for improving maize salt tolerance.
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Affiliation(s)
- Yibo Cao
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
| | - Xiaoyan Liang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
| | - Pan Yin
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
| | - Ming Zhang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
| | - Caifu Jiang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing, 100094, China
- Center for Crop Functional Genomics and Molecular Breeding, China Agricultural University, Beijing, 100094, China
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Liang Y, Liu Q, Wang X, Huang C, Xu G, Hey S, Lin HY, Li C, Xu D, Wu L, Wang C, Wu W, Xia J, Han X, Lu S, Lai J, Song W, Schnable PS, Tian F. ZmMADS69 functions as a flowering activator through the ZmRap2.7-ZCN8 regulatory module and contributes to maize flowering time adaptation. THE NEW PHYTOLOGIST 2019; 221:2335-2347. [PMID: 30288760 DOI: 10.1111/nph.15512] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 09/14/2018] [Indexed: 05/26/2023]
Abstract
Flowering time is a major determinant of the local adaptation of plants. Although numerous loci affecting flowering time have been mapped in maize, their underlying molecular mechanisms and roles in adaptation remain largely unknown. Here, we report the identification and characterization of MADS-box transcription factor ZmMADS69 that functions as a flowering activator through the ZmRap2.7-ZCN8 regulatory module and contributes to adaptation. We show that ZmMADS69 underlies a quantitative trait locus controlling the difference in flowering time between maize and its wild ancestor, teosinte. Maize ZmMADS69 allele is expressed at a higher level at floral transition and confers earlier flowering than the teosinte allele under long days and short days. Overexpression of ZmMADS69 causes early flowering, while a transposon insertion mutant of ZmMADS69 exhibits delayed flowering. ZmMADS69 shows pleiotropic effects for multiple traits of agronomic importance. ZmMADS69 functions upstream of the flowering repressor ZmRap2.7 to downregulate its expression, thereby relieving the repression of the florigen gene ZCN8 and causing early flowering. Population genetic analyses showed that ZmMADS69 was a target of selection and may have played an important role as maize spread from the tropics to temperate zones. Our findings provide important insights into the regulation and adaptation of flowering time.
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Affiliation(s)
- Yameng Liang
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Qiang Liu
- Department of Agronomy, Iowa State University, Ames, IA, 50010-3650, USA
| | - Xufeng Wang
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
- Guangdong Provincial Key Laboratory for Plant Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Cheng Huang
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
- College of Agronomy, Hunan Agricultural University, Changsha, 410128, China
| | - Guanghui Xu
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Stefan Hey
- Department of Agronomy, Iowa State University, Ames, IA, 50010-3650, USA
| | - Hung-Ying Lin
- Department of Agronomy, Iowa State University, Ames, IA, 50010-3650, USA
| | - Cong Li
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Dingyi Xu
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Lishuan Wu
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Chenglong Wang
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Weihao Wu
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Jinliang Xia
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Xu Han
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Sijia Lu
- School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Jinsheng Lai
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Weibin Song
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
| | - Patrick S Schnable
- Department of Agronomy, Iowa State University, Ames, IA, 50010-3650, USA
- Department of Plant Genetics & Breeding, China Agricultural University, Beijing, 100193, China
| | - Feng Tian
- National Maize Improvement Center of China, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing, 100193, China
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Zhang Y, Du J, Wang J, Ma L, Lu X, Pan X, Guo X, Zhao C. High-throughput micro-phenotyping measurements applied to assess stalk lodging in maize (Zea mays L.). Biol Res 2018; 51:40. [PMID: 30368254 PMCID: PMC6203980 DOI: 10.1186/s40659-018-0190-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2017] [Accepted: 10/09/2018] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND The biomechanical properties of maize stalks largely determine their lodging resistance, which affects crop yield per unit area. However, the quantitative and qualitative relationship between micro-phenotypes and the biomechanics of maize stalks is still under examined. In particular, the roles of the number, geometry, and distribution of vascular bundles of stalks in maize lodging resistance remain unclear. Research on these biomechanical properties will benefit from high-resolution micro-phenotypic image acquisition capabilities, which have been improved by modern X-ray imaging devices such as micro-CT and the development of micro-phenotyping analysis software. Hence, high-throughput image analysis and accurate quantification of anatomical phenotypes of stalks are necessary. RESULTS We have updated VesselParser version 1.0 to version 2.0 and have improved its performance, accuracy, and computation strategies. Anatomical characteristics of the second and third stalk internodes of the cultivars 'Jingke968' and 'Jingdan38' were analyzed using VesselParser 2.0. The relationships between lodging resistance and anatomical phenotypes of stalks between the two different maize varieties were investigated. The total area of vascular bundles in the peripheral layer, auxiliary axis diameter, and total area of vascular bundles were revealed to have the highest correlation with mechanical properties, and anatomical phenotypes of maize stalk were better predictors of mechanical properties than macro features observed optically from direct measurement, such as diameter and perimeter. CONCLUSIONS This study demonstrates the utility of VesselParser 2.0 in assessing stalk mechanical properties. The combination of anatomical phenotypes and mechanical behavior research provides unique insights into the problem of stalk lodging, showing that micro phenotypes of vascular bundles are good predictors of maize stalk mechanical properties that may be important indices for the evaluation and identification of the biomechanical properties to improve lodging resistance of future maize varieties.
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Affiliation(s)
- Ying Zhang
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Jianjun Du
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Jinglu Wang
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Liming Ma
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Xianju Lu
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Xiaodi Pan
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Xinyu Guo
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
| | - Chunjiang Zhao
- Beijing Key Lab of Digital Plant, Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Shuguang Huayuan Middle Road, Haidian District, No. 11, Beijing, 100097 People’s Republic of China
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Guo L, Wang X, Zhao M, Huang C, Li C, Li D, Yang CJ, York AM, Xue W, Xu G, Liang Y, Chen Q, Doebley JF, Tian F. Stepwise cis-Regulatory Changes in ZCN8 Contribute to Maize Flowering-Time Adaptation. Curr Biol 2018; 28:3005-3015.e4. [PMID: 30220503 PMCID: PMC6537595 DOI: 10.1016/j.cub.2018.07.029] [Citation(s) in RCA: 102] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Revised: 05/24/2018] [Accepted: 07/09/2018] [Indexed: 12/28/2022]
Abstract
Maize (Zea mays ssp. mays) was domesticated in southwestern Mexico ∼9,000 years ago from its wild ancestor, teosinte (Zea mays ssp. parviglumis) [1]. From its center of origin, maize experienced a rapid range expansion and spread over 90° of latitude in the Americas [2-4], which required a novel flowering-time adaptation. ZEA CENTRORADIALIS 8 (ZCN8) is the maize florigen gene and has a central role in mediating flowering [5, 6]. Here, we show that ZCN8 underlies a major quantitative trait locus (QTL) (qDTA8) for flowering time that was consistently detected in multiple maize-teosinte experimental populations. Through association analysis in a large diverse panel of maize inbred lines, we identified a SNP (SNP-1245) in the ZCN8 promoter that showed the strongest association with flowering time. SNP-1245 co-segregated with qDTA8 in maize-teosinte mapping populations. We demonstrate that SNP-1245 is associated with differential binding by the flowering activator ZmMADS1. SNP-1245 was a target of selection during early domestication, which drove the pre-existing early flowering allele to near fixation in maize. Interestingly, we detected an independent association block upstream of SNP-1245, wherein the early flowering allele that most likely originated from Zea mays ssp. mexicana introgressed into the early flowering haplotype of SNP-1245 and contributed to maize adaptation to northern high latitudes. Our study demonstrates how independent cis-regulatory variants at a gene can be selected at different evolutionary times for local adaptation, highlighting how complex cis-regulatory control mechanisms evolve. Finally, we propose a polygenic map for the pre-Columbian spread of maize throughout the Americas.
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Affiliation(s)
- Li Guo
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Xuehan Wang
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Min Zhao
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Cheng Huang
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Cong Li
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Dan Li
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Chin Jian Yang
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Alessandra M York
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Wei Xue
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Guanghui Xu
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Yameng Liang
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China
| | - Qiuyue Chen
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China; Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - John F Doebley
- Department of Genetics, University of Wisconsin, Madison, WI 53706, USA
| | - Feng Tian
- National Maize Improvement Center, Key Laboratory of Biology and Genetic Improvement of Maize (MOA), Beijing Key Laboratory of Crop Genetic Improvement, Joint International Research Laboratory of Crop Molecular Breeding, China Agricultural University, Beijing 100193, China.
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Jiménez-Galindo JC, Malvar RA, Butrón A, Caicedo M, Ordás B. Fine analysis of a genomic region involved in resistance to Mediterranean corn borer. BMC PLANT BIOLOGY 2018; 18:169. [PMID: 30111285 PMCID: PMC6094900 DOI: 10.1186/s12870-018-1385-3] [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: 11/15/2017] [Accepted: 08/01/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND Sesamia nonagrioides Lefebvere (Mediterranean corn borer, MCB) is the main pest of maize in the Mediterranean area. QTL for MCB stalk tunneling and grain yield under high MCB infestation had been located at bin 8.03-8.05 (4-21 cM and 10-30 cM respectively) in a previous analysis of the EP42 x EP39 RILs mapping population. The objective of the present work was to study with higher resolution those QTL, and validating and estimating with higher precision their locations and effects. To achieve this objective, we developed a set of 38 heterogeneous inbred families (HIFs) which were near-homozygous in the genome, except in the region under study. The HIFs were evaluated in multiple environments under artificial infestation with MCB and genotyped with SNPs. RESULTS The QTL for grain yield under high infestation was confirmed with higher precision and improved reliability at 112.6-116.9 Mb. On the contrary, the location of the QTL for stalk tunneling was not validated probably due to the fixation of some genomic regions during the development of the HIFs. Our study confirmed that the co-localization of the QTL for stalk tunneling and grain yield in the previous study was due to linked genes, not to pleiotropic effects. So, the QTL for grain yield can be used for improving grain yield without undesirable effect on stalk tunneling. CONCLUSIONS The HIF analysis is useful for validating QTL and for conducting deeper studies in traits related to corn borer resistance.
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Affiliation(s)
- José Cruz Jiménez-Galindo
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
- National Institute of Forestry, Agriculture and Livestock Research (INIFAP), Ave. Hidalgo 1213, Cd., 31500 Cuauhtémoc, Chihuahua, Mexico
| | - Rosa Ana Malvar
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
| | - Ana Butrón
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
| | - Marlon Caicedo
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
- National Institute of Agricultural Research (INIAP), 170315 Quito, Ecuador
| | - Bernardo Ordás
- Misión Biológica de Galicia, Spanish National Research Council (CSIC), Apartado 28, 36080 Pontevedra, Spain
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Xu G, Wang X, Huang C, Xu D, Li D, Tian J, Chen Q, Wang C, Liang Y, Wu Y, Yang X, Tian F. Complex genetic architecture underlies maize tassel domestication. THE NEW PHYTOLOGIST 2017; 214:852-864. [PMID: 28067953 PMCID: PMC5363343 DOI: 10.1111/nph.14400] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Accepted: 11/16/2016] [Indexed: 05/02/2023]
Abstract
Maize (Zea mays) tassels underwent profound morphological changes during maize domestication and improvement. Although a number of genes affecting maize inflorescence development have been identified, the genetic basis of the morphological changes in maize tassels since domestication is not well understood. Here, using a large population of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped using 19 838 single nucleotide polymorphism (SNP) markers, we performed high-resolution quantitative trait locus (QTL) mapping for five tassel morphological traits. We showed that the five tassel traits were associated with different genetic architecture features. Known genes for maize inflorescence development identified by mutagenesis were significantly enriched in the tassel trait QTLs, and many of these genes, including ramosa1 (ra1), barren inflorescence2 (bif2), unbranched2 (ub2), zea floricaula leafy2 (zfl2) and barren stalk fastigiate1 (baf1), showed evidence of selection. An in-depth nucleotide diversity analysis at the bif2 locus identified strong selection signatures in the 5'-regulatory region. We also found that several known flowering time genes co-localized with tassel trait QTLs. A further association analysis indicated that the maize photoperiod gene ZmCCT was significantly associated with tassel size variation. Using near-isogenic lines, we narrowed down a major-effect QTL for tassel length, qTL9-1, to a 513-kb physical region. These results provide important insights into the genetic architecture that controls maize tassel evolution.
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Affiliation(s)
- Guanghui Xu
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Xufeng Wang
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Cheng Huang
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Dingyi Xu
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Dan Li
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Jinge Tian
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Qiuyue Chen
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Chenglong Wang
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Yameng Liang
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Yaoyao Wu
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Xiaohong Yang
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
| | - Feng Tian
- National Maize Improvement CenterChina Agricultural UniversityBeijing100193China
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Li D, Wang X, Zhang X, Chen Q, Xu G, Xu D, Wang C, Liang Y, Wu L, Huang C, Tian J, Wu Y, Tian F. The genetic architecture of leaf number and its genetic relationship to flowering time in maize. THE NEW PHYTOLOGIST 2016; 210:256-68. [PMID: 26593156 PMCID: PMC5063108 DOI: 10.1111/nph.13765] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 10/15/2015] [Indexed: 05/03/2023]
Abstract
The number of leaves and their distributions on plants are critical factors determining plant architecture in maize (Zea mays), and leaf number is frequently used as a measure of flowering time, a trait that is key to local environmental adaptation. Here, using a large set of 866 maize-teosinte BC2 S3 recombinant inbred lines genotyped by using 19,838 single nucleotide polymorphism markers, we conducted a comprehensive genetic dissection to assess the genetic architecture of leaf number and its genetic relationship to flowering time. We demonstrated that the two components of total leaf number, the number of leaves above (LA) and below (LB) the primary ear, were under relatively independent genetic control and might be subject to differential directional selection during maize domestication and improvement. Furthermore, we revealed that flowering time and leaf number are commonly regulated at a moderate level. The pleiotropy of the genes ZCN8, dlf1 and ZmCCT on leaf number and flowering time were validated by near-isogenic line analysis. Through fine mapping, qLA1-1, a major-effect locus that specifically affects LA, was delimited to a region with severe recombination suppression derived from teosinte. This study provides important insights into the genetic basis of traits affecting plant architecture and adaptation. The genetic independence of LA from LB enables the optimization of leaf number for ideal plant architecture breeding in maize.
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Affiliation(s)
- Dan Li
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Xufeng Wang
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Xiangbo Zhang
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Qiuyue Chen
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Guanghui Xu
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Dingyi Xu
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Chenglong Wang
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Yameng Liang
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Lishuan Wu
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Cheng Huang
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Jinge Tian
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Yaoyao Wu
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
| | - Feng Tian
- National Maize Improvement Center of ChinaChina Agricultural UniversityBeijing100193China
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Leiboff S, DeAllie CK, Scanlon MJ. Modeling the Morphometric Evolution of the Maize Shoot Apical Meristem. FRONTIERS IN PLANT SCIENCE 2016; 7:1651. [PMID: 27867389 PMCID: PMC5095129 DOI: 10.3389/fpls.2016.01651] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 10/20/2016] [Indexed: 05/04/2023]
Abstract
The maize (Zea mays subsp. mays L.) shoot apical meristem (SAM) is a self-replenishing pool of stem cells that produces all above-ground plant tissues. Improvements in image acquisition and processing techniques have allowed high-throughput, quantitative genetic analyses of SAM morphology. As with other large-scale phenotyping efforts, meaningful descriptions of genetic architecture depend on the collection of relevant measures. In this study, we tested two quantitative image processing methods to describe SAM morphology within the genus Zea, represented by 33 wild relatives of maize and 841 lines from a domesticated maize by wild teosinte progenitor (MxT) backcross population, along with previously reported data from several hundred diverse maize inbred lines. Approximating the MxT SAM as a paraboloid derived eight parabolic estimators of SAM morphology that identified highly overlapping quantitative trait loci (QTL) on eight chromosomes, which implicated previously identified SAM morphology candidate genes along with new QTL for SAM morphological variation. Using a Fourier-transform related method of comprehensive shape analysis, we detected cryptic SAM shape variation that identified QTL on six chromosomes. We found that Fourier transform shape descriptors and parabolic estimation measures are highly correlated and identified similar QTL. Analysis of shoot apex contours from 73 anciently diverged plant taxa further suggested that parabolic shape may be a universal feature of plant SAMs, regardless of evolutionary clade. Future high-throughput examinations of SAM morphology may benefit from the ease of acquisition and phenotypic fidelity of modeling the SAM as a paraboloid.
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