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Cervantes-Pérez SA, Zogli P, Amini S, Thibivilliers S, Tennant S, Hossain MS, Xu H, Meyer I, Nooka A, Ma P, Yao Q, Naldrett MJ, Farmer A, Martin O, Bhattacharya S, Kläver J, Libault M. Single-cell transcriptome atlases of soybean root and mature nodule reveal new regulatory programs that control the nodulation process. PLANT COMMUNICATIONS 2024; 5:100984. [PMID: 38845198 DOI: 10.1016/j.xplc.2024.100984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/21/2024] [Accepted: 06/03/2024] [Indexed: 07/14/2024]
Abstract
The soybean root system is complex. In addition to being composed of various cell types, the soybean root system includes the primary root, the lateral roots, and the nodule, an organ in which mutualistic symbiosis with N-fixing rhizobia occurs. A mature soybean root nodule is characterized by a central infection zone where atmospheric nitrogen is fixed and assimilated by the symbiont, resulting from the close cooperation between the plant cell and the bacteria. To date, the transcriptome of individual cells isolated from developing soybean nodules has been established, but the transcriptomic signatures of cells from the mature soybean nodule have not yet been characterized. Using single-nucleus RNA-seq and Molecular Cartography technologies, we precisely characterized the transcriptomic signature of soybean root and mature nodule cell types and revealed the co-existence of different sub-populations of B. diazoefficiens-infected cells in the mature soybean nodule, including those actively involved in nitrogen fixation and those engaged in senescence. Mining of the single-cell-resolution nodule transcriptome atlas and the associated gene co-expression network confirmed the role of known nodulation-related genes and identified new genes that control the nodulation process. For instance, we functionally characterized the role of GmFWL3, a plasma membrane microdomain-associated protein that controls rhizobial infection. Our study reveals the unique cellular complexity of the mature soybean nodule and helps redefine the concept of cell types when considering the infection zone of the soybean nodule.
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Affiliation(s)
| | - Prince Zogli
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Sahand Amini
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA
| | - Sandra Thibivilliers
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA
| | - Sutton Tennant
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA
| | - Md Sabbir Hossain
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA
| | - Hengping Xu
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA
| | - Ian Meyer
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Akash Nooka
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Pengchong Ma
- School of Computing, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Qiuming Yao
- School of Computing, University of Nebraska-Lincoln, Lincoln, NE 68503, USA
| | - Michael J Naldrett
- Proteomics and Metabolomics Facility, Center for Biotechnology, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Andrew Farmer
- National Center for Genome Resources, Santa Fe, NM 87505, USA
| | - Olivier Martin
- INRAE, Université Paris-Saclay, Institut des Sciences des Plantes de Paris Saclay, IPS2, Batiment 630 Plateau du Moulon, Rue Noetzlin, 91192 Gif sur Yvette Cedex, France
| | | | | | - Marc Libault
- Division of Plant Science and Technology, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65211, USA; Interdisciplinary Plant Group of Missouri-Columbia, Columbia, MO 65211, USA.
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2
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Tu T, Gao Z, Li L, Chen J, Ye K, Xu T, Mai S, Han Q, Chen C, Wu S, Dong Y, Chen J, Huang L, Guan Y, Xie F, Chen X. Soybean symbiotic-nodule zonation and cell differentiation are defined by NIN2 signaling and GH3-dependent auxin homeostasis. Dev Cell 2024:S1534-5807(24)00424-6. [PMID: 39053471 DOI: 10.1016/j.devcel.2024.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/18/2024] [Accepted: 07/02/2024] [Indexed: 07/27/2024]
Abstract
Symbiotic nodules comprise two classes, indeterminate and determinate, defined by the presence/absence of apical meristem and developmental zonation. Why meristem and zonation are absent from determinate nodules remains unclear. Here, we define cell types in developing soybean nodules, highlighting the undifferentiated infection zones and differentiated nitrogen-fixation zones. Auxin governs infection zone maintenance. GRETCHEN HAGEN 3 (GH3) enzymes deactivate auxin by conjugation and promote cell differentiation. gh3 mutants increased undifferentiated cells and enlarged infection zones. The central symbiosis-transcription factor NIN2a activates GH3.1 to reduce auxin levels and facilitates cell differentiation. High auxin promotes NIN2a protein accumulation and enhances signaling, further deactivating auxin and depleting infection zones. Our findings shed light on the NIN2a-GH3-auxin module that drives soybean nodule cell differentiation. This study challenges our understanding of determinate nodule development and proposes that the regulation of nodule zonation offers valuable insights into broader mechanisms of cell differentiation across plant species.
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Affiliation(s)
- Tianli Tu
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Zhen Gao
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Linfang Li
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Jiansheng Chen
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Kangzhuo Ye
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Tao Xu
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Siyuan Mai
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Qingqing Han
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Chaofan Chen
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Shengwei Wu
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China; College of Agriculture and Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
| | - Yankun Dong
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiaomei Chen
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Laimei Huang
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Yuefeng Guan
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, China
| | - Fang Xie
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Xu Chen
- Haixia Institute of Science and Technology, Horticultural Plant Biology and Metabolomics Center, Fujian Agriculture and Forestry University, Fuzhou, China.
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3
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Araya S, Elia P, Quigley CV, Song Q. Genetic variation and genetic complexity of nodule occupancy in soybean inoculated with USDA110 and USDA123 rhizobium strains. BMC Genomics 2023; 24:520. [PMID: 37667205 PMCID: PMC10478483 DOI: 10.1186/s12864-023-09627-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/26/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Symbiotic nitrogen fixation differs among Bradyrhizobium japonicum strains. Soybean inoculated with USDA123 has a lower yield than strains known to have high nitrogen fixation efficiency, such as USDA110. In the main soybean-producing area in the Midwest of the United States, USDA123 has a high nodule incidence in field-grown soybean and is competitive but inefficient in nitrogen fixation. In this study, a high-throughput system was developed to characterize nodule number among 1,321 Glycine max and 69 Glycine soja accessions single inoculated with USDA110 and USDA123. RESULTS Seventy-three G. max accessions with significantly different nodule number of USDA110 and USDA123 were identified. After double inoculating 35 of the 73 accessions, it was observed that PI189939, PI317335, PI324187B, PI548461, PI562373, and PI628961 were occupied by USDA110 and double-strain nodules but not by USDA123 nodules alone. PI567624 was only occupied by USDA110 nodules, and PI507429 restricted all strains. Analysis showed that 35 loci were associated with nodule number in G. max when inoculated with strain USDA110 and 35 loci with USDA123. Twenty-three loci were identified in G. soja when inoculated with strain USDA110 and 34 with USDA123. Only four loci were common across two treatments, and each locus could only explain 0.8 to 1.5% of phenotypic variation. CONCLUSIONS High-throughput phenotyping systems to characterize nodule number and occupancy were developed, and soybean germplasm restricting rhizobium strain USDA123 but preferring USDA110 was identified. The larger number of minor effects and a small few common loci controlling the nodule number indicated trait genetic complexity and strain-dependent nodulation restriction. The information from the present study will add to the development of cultivars that limit USDA123, thereby increasing nitrogen fixation efficiency and productivity.
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Affiliation(s)
- Susan Araya
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA
| | - Patrick Elia
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA
| | - Charles V Quigley
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA.
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Kim Y, Wang J, Ma C, Jong C, Jin M, Cha J, Wang J, Peng Y, Ni H, Li H, Yang M, Chen Q, Xin D. GmTCP and GmNLP Underlying Nodulation Character in Soybean Depending on Nitrogen. Int J Mol Sci 2023; 24:ijms24097750. [PMID: 37175456 PMCID: PMC10178161 DOI: 10.3390/ijms24097750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 04/19/2023] [Accepted: 04/21/2023] [Indexed: 05/15/2023] Open
Abstract
Soybean is a cereal crop with high protein and oil content which serves as the main source of plant-based protein and oil for human consumption. The symbiotic relationship between legumes and rhizobia contributes significantly to soybean yield and quality, but the underlying molecular mechanisms remain poorly understood, hindering efforts to improve soybean productivity. In this study, we conducted a transcriptome analysis and identified 22 differentially expressed genes (DEGs) from nodule-related quantitative trait loci (QTL) located in chromosomes 12 and 19. Subsequently, we performed functional characterisation and haplotype analysis to identify key candidate genes among the 22 DEGs that are responsive to nitrate. Our findings identified GmTCP (TEOSINTE-BRANCHED1/CYCLOIDEA/PCF) and GmNLP (NIN-LIKE PROTEIN) as the key candidate genes that regulate the soybean nodule phenotype in response to nitrogen concentration. We conducted homologous gene mutant analysis in Arabidopsis thaliana, which revealed that the homologous genes of GmTCP and GmNLP play a vital role in regulating root development in response to nitrogen concentration. We further performed overexpression and gene knockout of GmTCP and GmNLP through hairy root transformation in soybeans and analysed the effects of GmTCP and GmNLP on nodulation under different nitrogen concentrations using transgenic lines. Overexpressing GmTCP and GmNLP resulted in significant differences in soybean hairy root nodulation phenotypes, such as nodule number (NN) and nodule dry weight (NDW), under varying nitrate conditions. Our results demonstrate that GmTCP and GmNLP are involved in regulating soybean nodulation in response to nitrogen concentration, providing new insights into the mechanism of soybean symbiosis establishment underlying different nitrogen concentrations.
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Affiliation(s)
- Yunchol Kim
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Jinhui Wang
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Chao Ma
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Cholnam Jong
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Myongil Jin
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Jinmyong Cha
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Jing Wang
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Yang Peng
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Hejia Ni
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Haibo Li
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Mingliang Yang
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Qingshan Chen
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
| | - Dawei Xin
- College of Agriculture, Northeast Agricultural University, Harbin 150036, China
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5
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Huang M, Zhang L, Zhou L, Yung WS, Wang Z, Xiao Z, Wang Q, Wang X, Li MW, Lam HM. Identification of the accessible chromatin regions in six tissues in the soybean. Genomics 2022; 114:110364. [PMID: 35421559 DOI: 10.1016/j.ygeno.2022.110364] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 02/25/2022] [Accepted: 04/06/2022] [Indexed: 01/14/2023]
Abstract
Accessible chromatin regions (ACRs) are tightly associated with gene expressions in the genome. Conserved non-coding cis-regulatory elements, such as transcription factor binding motifs, are usually found in ACRs, indicating an essential regulatory role of ACRs in the plant genome architecture. However, there have been few studies on soybean ACRs, especially those focusing on specific tissues. Hence, in this study, with the convenient ATAC-seq, we identified the ACRs in six soybean tissues, including root, leaf bud, flower, flower bud, developing seed, and pod. In total, the ACRs occupied about 3.3% of the entire soybean genome. By integrating the results from RNA-seq and transcription factor (TF) ChIP-seq, ACRs were found to be tightly associated with gene expressions and TF binding capacities in soybean. Together, these data provide a comprehensive understanding of the genomic features of ACRs in soybean. As a collection of essential genomic resources, these processed data are made available at datahub.wildsoydb.org.
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Affiliation(s)
- Mingkun Huang
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China; Lushan Botanical Garden Jiangxi Province and Chinese Academy of Sciences, NO.9 Zhiqing Road, Lushan, Jiujiang, Jiangxi, PR China.
| | - Ling Zhang
- Lushan Botanical Garden Jiangxi Province and Chinese Academy of Sciences, NO.9 Zhiqing Road, Lushan, Jiujiang, Jiangxi, PR China
| | - Limeng Zhou
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Wai-Shing Yung
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Zhili Wang
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Zhixia Xiao
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Qianwen Wang
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Xin Wang
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China
| | - Man-Wah Li
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China.
| | - Hon-Ming Lam
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong, SAR, PR China.
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Goyal RK, Mattoo AK, Schmidt MA. Rhizobial-Host Interactions and Symbiotic Nitrogen Fixation in Legume Crops Toward Agriculture Sustainability. Front Microbiol 2021; 12:669404. [PMID: 34177848 PMCID: PMC8226219 DOI: 10.3389/fmicb.2021.669404] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 04/29/2021] [Indexed: 11/13/2022] Open
Abstract
Symbiotic nitrogen fixation (SNF) process makes legume crops self-sufficient in nitrogen (N) in sharp contrast to cereal crops that require an external input by N-fertilizers. Since the latter process in cereal crops results in a huge quantity of greenhouse gas emission, the legume production systems are considered efficient and important for sustainable agriculture and climate preservation. Despite benefits of SNF, and the fact that chemical N-fertilizers cause N-pollution of the ecosystems, the focus on improving SNF efficiency in legumes did not become a breeder’s priority. The size and stability of heritable effects under different environment conditions weigh significantly on any trait useful in breeding strategies. Here we review the challenges and progress made toward decoding the heritable components of SNF, which is considerably more complex than other crop allelic traits since the process involves genetic elements of both the host and the symbiotic rhizobial species. SNF-efficient rhizobial species designed based on the genetics of the host and its symbiotic partner face the test of a unique microbiome for its success and productivity. The progress made thus far in commercial legume crops with relevance to the dynamics of host–rhizobia interaction, environmental impact on rhizobial performance challenges, and what collectively determines the SNF efficiency under field conditions are also reviewed here.
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Affiliation(s)
- Ravinder K Goyal
- Agriculture and Agri-Food Canada, Lacombe Research and Development Centre, Lacombe, AB, Canada
| | - Autar K Mattoo
- Sustainable Agricultural Systems Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville Agricultural Research Center, Beltsville, MD, United States
| | - Maria Augusta Schmidt
- Agriculture and Agri-Food Canada, Lacombe Research and Development Centre, Lacombe, AB, Canada
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