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Mathieu L, Ballini E, Morel JB, Méteignier LV. The root of plant-plant interactions: Belowground special cocktails. CURRENT OPINION IN PLANT BIOLOGY 2024; 80:102547. [PMID: 38749206 DOI: 10.1016/j.pbi.2024.102547] [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: 03/13/2024] [Revised: 04/16/2024] [Accepted: 04/18/2024] [Indexed: 06/14/2024]
Abstract
Plants interact with each other via a multitude of processes among which belowground communication facilitated by specialized metabolites plays an important but overlooked role. Until now, the exact targets, modes of action, and resulting phenotypes that these metabolites induce in neighboring plants have remained largely unknown. Moreover, positive interactions driven by the release of root exudates are prevalent in both natural field conditions and controlled laboratory environments. In particular, intraspecific positive interactions suggest a genotypic recognition mechanism in addition to non-self perception in plant roots. This review concentrates on recent discoveries regarding how plants interact with one another through belowground signals in intra- and interspecific mixtures. Furthermore, we elaborate on how an enhanced understanding of these interactions can propel the field of agroecology forward.
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Affiliation(s)
- Laura Mathieu
- PHIM Plant Health Institute, Univ Montpellier, INRAE, CIRAD, Institut Agro, IRD, Montpellier, France
| | - Elsa Ballini
- PHIM Plant Health Institute, Univ Montpellier, INRAE, CIRAD, Institut Agro, IRD, Montpellier, France
| | - Jean-Benoit Morel
- PHIM Plant Health Institute, Univ Montpellier, INRAE, CIRAD, Institut Agro, IRD, Montpellier, France
| | - Louis-Valentin Méteignier
- PHIM Plant Health Institute, Univ Montpellier, INRAE, CIRAD, Institut Agro, IRD, Montpellier, France.
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2
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Huo Q, Song R, Ma Z. Recent advances in exploring transcriptional regulatory landscape of crops. FRONTIERS IN PLANT SCIENCE 2024; 15:1421503. [PMID: 38903438 PMCID: PMC11188431 DOI: 10.3389/fpls.2024.1421503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 05/23/2024] [Indexed: 06/22/2024]
Abstract
Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.
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Affiliation(s)
| | | | - Zeyang Ma
- State Key Laboratory of Maize Bio-breeding, Frontiers Science Center for Molecular Design Breeding, Joint International Research Laboratory of Crop Molecular Breeding, National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing, China
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3
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Song Y, Zhang Y, Wang X, Yu X, Liao Y, Zhang H, Li L, Wang Y, Liu B, Li W. Telomere-to-telomere reference genome for Panax ginseng highlights the evolution of saponin biosynthesis. HORTICULTURE RESEARCH 2024; 11:uhae107. [PMID: 38883331 PMCID: PMC11179851 DOI: 10.1093/hr/uhae107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 03/31/2024] [Indexed: 06/18/2024]
Abstract
Ginseng (Panax ginseng) is a representative of Chinese traditional medicine, also used worldwide, while the triterpene saponin ginsenoside is the most important effective compound within it. Ginseng is an allotetraploid, with complex genetic background, making the study of its metabolic evolution challenging. In this study, we assembled a telomere-to-telomere ginseng reference genome, constructed of 3.45 Gb with 24 chromosomes and 77 266 protein-coding genes. Additionally, the reference genome was divided into two subgenomes, designated as subgenome A and B. Subgenome A contains a larger number of genes, whereas subgenome B has a general expression advantage, suggesting that ginseng subgenomes experienced asymmetric gene loss with biased gene expression. The two subgenomes separated approximately 6.07 million years ago, and subgenome B shows the closest relation to Panax vietnamensis var. fuscidiscus. Comparative genomics revealed an expansion of gene families associated with ginsenoside biosynthesis in both ginseng subgenomes. Furthermore, both tandem duplications and proximal duplications play crucial roles in ginsenoside biosynthesis. We also screened functional genes identified in previous research and found that some of these genes located in colinear regions between subgenomes have divergence functions, revealing an unbalanced evolution in both subgenomes and the saponin biosynthesis pathway in ginseng. Our work provides important resources for future genetic studies and breeding programs of ginseng, as well as the biosynthesis of ginsenosides.
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Affiliation(s)
- Yiting Song
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yating Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xu Wang
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Xikai Yu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yi Liao
- College of Horticulture, South China Agricultural University, Guangzhou 510642, China
| | - Hao Zhang
- Institute of Special Animal and Plant Sciences, Chinese Academy of Agricultural Sciences, Changchun 130112, China
| | - Linfeng Li
- Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Coastal Ecosystems Research Station of Yangtze River Estuary, Institute of Biodiversity Science and Institute of Eco-Chongming, School of Life Sciences, Fudan University, Songhu Road 2005, Shanghai 200433, China
| | - Yingping Wang
- State-Local Joint Engineering Research Center of Ginseng Breeding and Application, Jilin Agricultural University, Changchun 130118, China
| | - Bao Liu
- Key Laboratory of Molecular Epigenetics of the Ministry of Education (MOE), Northeast Normal University, Changchun 130024, China
| | - Wei Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Kunpeng Institute of Modern Agriculture at Foshan, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
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4
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Ai G, He C, Bi S, Zhou Z, Liu A, Hu X, Liu Y, Jin L, Zhou J, Zhang H, Du D, Chen H, Gong X, Saeed S, Su H, Lan C, Chen W, Li Q, Mao H, Li L, Liu H, Chen D, Kaufmann K, Alazab KF, Yan W. Dissecting the molecular basis of spike traits by integrating gene regulatory networks and genetic variation in wheat. PLANT COMMUNICATIONS 2024; 5:100879. [PMID: 38486454 PMCID: PMC11121755 DOI: 10.1016/j.xplc.2024.100879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/25/2024] [Accepted: 03/11/2024] [Indexed: 04/30/2024]
Abstract
Spike architecture influences both grain weight and grain number per spike, which are the two major components of grain yield in bread wheat (Triticum aestivum L.). However, the complex wheat genome and the influence of various environmental factors pose challenges in mapping the causal genes that affect spike traits. Here, we systematically identified genes involved in spike trait formation by integrating information on genomic variation and gene regulatory networks controlling young spike development in wheat. We identified 170 loci that are responsible for variations in spike length, spikelet number per spike, and grain number per spike through genome-wide association study and meta-QTL analyses. We constructed gene regulatory networks for young inflorescences at the double ridge stage and the floret primordium stage, in which the spikelet meristem and the floret meristem are predominant, respectively, by integrating transcriptome, histone modification, chromatin accessibility, eQTL, and protein-protein interactome data. From these networks, we identified 169 hub genes located in 76 of the 170 QTL regions whose polymorphisms are significantly associated with variation in spike traits. The functions of TaZF-B1, VRT-B2, and TaSPL15-A/D in establishment of wheat spike architecture were verified. This study provides valuable molecular resources for understanding spike traits and demonstrates that combining genetic analysis and developmental regulatory networks is a robust approach for dissection of complex traits.
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Affiliation(s)
- Guo Ai
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Chao He
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Siteng Bi
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ziru Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ankui Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xin Hu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yanyan Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Liujie Jin
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - JiaCheng Zhou
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Heping Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Dengxiang Du
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hao Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xin Gong
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Sulaiman Saeed
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Handong Su
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Caixia Lan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Qiang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Hailiang Mao
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Lin Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome, Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Hao Liu
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Kerstin Kaufmann
- Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität Zu Berlin, 10115 Berlin, Germany
| | - Khaled F Alazab
- Plant Research Department, Nuclear Research Center, Egyptian Atomic Energy Authority, Cairo 13759, Egypt
| | - Wenhao Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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5
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Liu Q, Ma W, Chen R, Li ST, Wang Q, Wei C, Hong Y, Sun HX, Cheng Q, Zhao J, Kang J. Multiome in the Same Cell Reveals the Impact of Osmotic Stress on Arabidopsis Root Tip Development at Single-Cell Level. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2308384. [PMID: 38634607 DOI: 10.1002/advs.202308384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Revised: 02/27/2024] [Indexed: 04/19/2024]
Abstract
Cell-specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single-cell mono-omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA-seq and scATAC-seq datasets, accurate data integration remains a challenge, particularly when investigating cell-type-specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell-type level, 12,968 peak-to-gene linkage is captured at the bona fide single-cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo-time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress-related gene-linked cis-regulatory elements (gl-cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress.
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Affiliation(s)
- Qing Liu
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
| | - Wei Ma
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
| | - Ruiying Chen
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Qifan Wang
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
| | - Cai Wei
- BGI Research, Beijing, 102601, China
| | - Yiguo Hong
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Hai-Xi Sun
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qi Cheng
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
| | - Jianjun Zhao
- State Key Laboratory of North China Crop Improvement and Regulation, Key Laboratory of Vegetable Germplasm Innovation and Utilization of Hebei, Ministry of Education of China-Hebei Province Joint Innovation Center for Efficient Green Vegetable Industry, International Joint R & D Center of Hebei Province in Modern Agricultural Biotechnology, College of Life Sciences, College of Horticulture, Hebei Agricultural University, Baoding, 071000, China
| | - Jingmin Kang
- BGI Research, Beijing, 102601, China
- BGI Research, Shenzhen, 518083, China
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von der Mark C, Minne M, De Rybel B. Studying plant vascular development using single-cell approaches. CURRENT OPINION IN PLANT BIOLOGY 2024; 78:102526. [PMID: 38479078 DOI: 10.1016/j.pbi.2024.102526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/20/2024] [Accepted: 02/28/2024] [Indexed: 04/07/2024]
Abstract
Vascular cells form a highly complex and heterogeneous tissue. Its composition, function, shape, and arrangement vary with the developmental stage and between organs and species. Understanding the transcriptional regulation underpinning this complexity thus requires a high-resolution technique that is capable of capturing rapid events during vascular cell formation. Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) approaches provide powerful tools to extract transcriptional information from these lowly abundant and dynamically changing cell types, which allows the reconstruction of developmental trajectories. Here, we summarize and reflect on recent studies using single-cell transcriptomics to study vascular cell types and discuss current and future implementations of sc/snRNA-seq approaches in the field of vascular development.
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Affiliation(s)
- Claudia von der Mark
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium; VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Max Minne
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium; VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Bert De Rybel
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium; VIB Center for Plant Systems Biology, Ghent, Belgium.
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7
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Islam MT, Liu Y, Hassan MM, Abraham PE, Merlet J, Townsend A, Jacobson D, Buell CR, Tuskan GA, Yang X. Advances in the Application of Single-Cell Transcriptomics in Plant Systems and Synthetic Biology. BIODESIGN RESEARCH 2024; 6:0029. [PMID: 38435807 PMCID: PMC10905259 DOI: 10.34133/bdr.0029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/28/2024] [Indexed: 03/05/2024] Open
Abstract
Plants are complex systems hierarchically organized and composed of various cell types. To understand the molecular underpinnings of complex plant systems, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for revealing high resolution of gene expression patterns at the cellular level and investigating the cell-type heterogeneity. Furthermore, scRNA-seq analysis of plant biosystems has great potential for generating new knowledge to inform plant biosystems design and synthetic biology, which aims to modify plants genetically/epigenetically through genome editing, engineering, or re-writing based on rational design for increasing crop yield and quality, promoting the bioeconomy and enhancing environmental sustainability. In particular, data from scRNA-seq studies can be utilized to facilitate the development of high-precision Build-Design-Test-Learn capabilities for maximizing the targeted performance of engineered plant biosystems while minimizing unintended side effects. To date, scRNA-seq has been demonstrated in a limited number of plant species, including model plants (e.g., Arabidopsis thaliana), agricultural crops (e.g., Oryza sativa), and bioenergy crops (e.g., Populus spp.). It is expected that future technical advancements will reduce the cost of scRNA-seq and consequently accelerate the application of this emerging technology in plants. In this review, we summarize current technical advancements in plant scRNA-seq, including sample preparation, sequencing, and data analysis, to provide guidance on how to choose the appropriate scRNA-seq methods for different types of plant samples. We then highlight various applications of scRNA-seq in both plant systems biology and plant synthetic biology research. Finally, we discuss the challenges and opportunities for the application of scRNA-seq in plants.
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Affiliation(s)
- Md Torikul Islam
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Yang Liu
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Md Mahmudul Hassan
- Department of Genetics and Plant Breeding,
Patuakhali Science and Technology University, Dumki, Patuakhali 8602, Bangladesh
| | - Paul E. Abraham
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Jean Merlet
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education,
University of Tennessee Knoxville, Knoxville, TN 37996, USA
| | - Alice Townsend
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education,
University of Tennessee Knoxville, Knoxville, TN 37996, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - C. Robin Buell
- Center for Applied Genetic Technologies,
University of Georgia, Athens, GA 30602, USA
- Department of Crop and Soil Sciences,
University of Georgia, Athens, GA 30602, USA
- Institute of Plant Breeding, Genetics, and Genomics,
University of Georgia, Athens, GA 30602, USA
| | - Gerald A. Tuskan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Xiaohan Yang
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- The Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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8
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Yan H, Mendieta JP, Zhang X, Marand AP, Liang Y, Luo Z, Minow MAA, Roulé T, Wagner D, Tu X, Wang Y, Zhong S, Wessler SR, Schmitz RJ. Evolution of plant cell-type-specific cis -regulatory elements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.08.574753. [PMID: 38260561 PMCID: PMC10802394 DOI: 10.1101/2024.01.08.574753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Cis -regulatory elements (CREs) are critical in regulating gene expression, and yet our understanding of CRE evolution remains a challenge. Here, we constructed a comprehensive single-cell atlas of chromatin accessibility in Oryza sativa , integrating data from 104,029 nuclei representing 128 discrete cell states across nine distinct organs. We used comparative genomics to compare cell-type resolved chromatin accessibility between O. sativa and 57,552 nuclei from four additional grass species ( Zea mays, Sorghum bicolor, Panicum miliaceum , and Urochloa fusca ). Accessible chromatin regions (ACRs) had different levels of conservation depending on the degree of cell-type specificity. We found a complex relationship between ACRs with conserved noncoding sequences, cell-type specificity, conservation, and tissue-specific switching. Additionally, we found that epidermal ACRs were less conserved compared to other cell types, potentially indicating that more rapid regulatory evolution has occurred in the L1 epidermal layer of these species. Finally, we identified and characterized a conserved subset of ACRs that overlapped the repressive histone modification H3K27me3, implicating them as potentially critical silencer CREs maintained by evolution. Collectively, this comparative genomics approach highlights the dynamics of cell-type-specific CRE evolution in plants.
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Xiao Y, Xi Z, Wang F, Wang J. Genomic asymmetric epigenetic modification of transposable elements is involved in gene expression regulation of allopolyploid Brassica napus. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 117:226-241. [PMID: 37797206 DOI: 10.1111/tpj.16491] [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: 05/01/2023] [Revised: 09/20/2023] [Accepted: 09/25/2023] [Indexed: 10/07/2023]
Abstract
Polyploids are common and have a wide geographical distribution and environmental adaptability. Allopolyploidy may lead to the activation of transposable elements (TE). However, the mechanism of epigenetic modification of TEs in the establishment and evolution of allopolyploids remains to be explored. We focused on the TEs of model allopolyploid Brassica napus (An An Cn Cn ), exploring the TE characteristics of the genome, epigenetic modifications of TEs during allopolyploidization, and regulation of gene expression by TE methylation. In B. napus, approximately 50% of the genome was composed of TEs. TEs increased with proximity to genes, especially DNA transposons. TE methylation levels were negatively correlated with gene expression, and changes in TE methylation levels were able to regulate the expression of neighboring genes related to responses to light intensity and stress, which promoted powerful adaptation of allopolyploids to new environments. TEs can be synergistically regulated by RNA-directed DNA methylation pathways and histone modifications. The epigenetic modification levels of TEs tended to be similar to those of the diploid parents during the genome evolution of B. napus. The TEs of the An subgenome were more likely to be modified, and the imbalance in TE number and epigenetic modification level in the An and Cn subgenomes may lead to the establishment of subgenome dominance. Our study analyzed the characteristics of TE location, DNA methylation, siRNA, and histone modification in B. napus and highlighted the importance of TE epigenetic modifications during the allopolyploidy process, providing support for revealing the mechanism of allopolyploid formation and evolution.
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Affiliation(s)
- Yafang Xiao
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, 430072, China
| | - Zengde Xi
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, 430072, China
| | - Fei Wang
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, 430072, China
| | - Jianbo Wang
- State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan, 430072, China
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Wang Z, Miao L, Chen Y, Peng H, Ni Z, Sun Q, Guo W. Deciphering the evolution and complexity of wheat germplasm from a genomic perspective. J Genet Genomics 2023; 50:846-860. [PMID: 37611848 DOI: 10.1016/j.jgg.2023.08.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 07/29/2023] [Accepted: 08/09/2023] [Indexed: 08/25/2023]
Abstract
Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.
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Affiliation(s)
- Zihao Wang
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Lingfeng Miao
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Yongming Chen
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Huiru Peng
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Zhongfu Ni
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Qixin Sun
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China
| | - Weilong Guo
- Frontiers Science Center for Molecular Design Breeding, Key Laboratory of Crop Heterosis and Utilization, Beijing Key Laboratory of Crop Genetic Improvement, China Agricultural University, Beijing 100193, China.
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11
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Zhang K, Zhao X, Zhao Y, Zhang Z, Liu Z, Liu Z, Yu Y, Li J, Ma Y, Dong Y, Pang X, Jin X, Li N, Liu B, Wendel JF, Zhai J, Long Y, Wang T, Gong L. Cell type-specific cytonuclear coevolution in three allopolyploid plant species. Proc Natl Acad Sci U S A 2023; 120:e2310881120. [PMID: 37748065 PMCID: PMC10556624 DOI: 10.1073/pnas.2310881120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/25/2023] [Indexed: 09/27/2023] Open
Abstract
Cytonuclear disruption may accompany allopolyploid evolution as a consequence of the merger of different nuclear genomes in a cellular environment having only one set of progenitor organellar genomes. One path to reconcile potential cytonuclear mismatch is biased expression for maternal gene duplicates (homoeologs) encoding proteins that target to plastids and/or mitochondria. Assessment of this transcriptional form of cytonuclear coevolution at the level of individual cells or cell types remains unexplored. Using single-cell (sc-) and single-nucleus (sn-) RNAseq data from eight tissues in three allopolyploid species, we characterized cell type-specific variations of cytonuclear coevolutionary homoeologous expression and demonstrated the temporal dynamics of expression patterns across development stages during cotton fiber development. Our results provide unique insights into transcriptional cytonuclear coevolution in plant allopolyploids at the single-cell level.
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Affiliation(s)
- Keren Zhang
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Xueru Zhao
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Yue Zhao
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Zhibin Zhang
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Zhijian Liu
- Department of Biology, School of Life Sciences, Institute of Plant and Food Science, Southern University of Science and Technology, Shenzhen, Guangdong518055, China
| | - Ziyu Liu
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Yanan Yu
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Juzuo Li
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Yiqiao Ma
- Jilin Academy of Vegetable and Flower Science, Changchun, Jilin130033, China
| | - Yuefan Dong
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Xi Pang
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Xin Jin
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Ning Li
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Bao Liu
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Jonathan F. Wendel
- Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA50010
| | - Jixian Zhai
- Department of Biology, School of Life Sciences, Institute of Plant and Food Science, Southern University of Science and Technology, Shenzhen, Guangdong518055, China
| | - Yanping Long
- Department of Biology, School of Life Sciences, Institute of Plant and Food Science, Southern University of Science and Technology, Shenzhen, Guangdong518055, China
| | - Tianya Wang
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
| | - Lei Gong
- Key Laboratory of Molecular Epigenetics of the Ministry of Education, Northeast Normal University, Changchun, Jilin130024, China
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Cao S, He Z, Chen R, Luo Y, Fu LY, Zhou X, He C, Yan W, Zhang CY, Chen D. scPlant: A versatile framework for single-cell transcriptomic data analysis in plants. PLANT COMMUNICATIONS 2023; 4:100631. [PMID: 37254480 PMCID: PMC10504592 DOI: 10.1016/j.xplc.2023.100631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/13/2023] [Accepted: 05/24/2023] [Indexed: 06/01/2023]
Abstract
Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users. The scPlant pipeline is implemented with numerous functions for diverse analytical tasks, ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.
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Affiliation(s)
- Shanni Cao
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Zhaohui He
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Ruidong Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Yuting Luo
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Liang-Yu Fu
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Xinkai Zhou
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Chao He
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Wenhao Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Chen-Yu Zhang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China.
| | - Dijun Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China.
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