1
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Wu R, Veličković M, Burnum-Johnson KE. From single cell to spatial multi-omics: unveiling molecular mechanisms in dynamic and heterogeneous systems. Curr Opin Biotechnol 2024; 89:103174. [PMID: 39126877 DOI: 10.1016/j.copbio.2024.103174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 07/02/2024] [Indexed: 08/12/2024]
Abstract
Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples.
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Affiliation(s)
- Ruonan Wu
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Marija Veličković
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Kristin E Burnum-Johnson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.
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2
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Shen X, Guan Z, Zhang C, Yan Z, Sun C. The multicellular compartmentation of plant specialized metabolism. CURRENT OPINION IN PLANT BIOLOGY 2024; 81:102616. [PMID: 39142253 DOI: 10.1016/j.pbi.2024.102616] [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: 04/03/2024] [Revised: 07/17/2024] [Accepted: 07/22/2024] [Indexed: 08/16/2024]
Abstract
The phenomenon of multicellular compartmentation in biosynthetic pathways has been documented for only a limited subset of specialized metabolites, despite its hypothesized significance in facilitating plant survival and adaptation to environmental stress. Transporters that shuttle metabolic intermediates between cells are hypothesized to be integral components enabling compartmentalized biosynthesis. Nevertheless, our understanding of the multicellular compartmentation of plant specialized metabolism and the associated intermediate transporters remains incomplete. The emergence of single-cell and spatial multiomics techniques holds promise for shedding light on unresolved questions in this field, such as the prevalence of multicellular compartmentation across the plant kingdom and the specific types of specialized metabolites whose biosynthetic pathways are prone to compartmentation. Advancing our understanding of the mechanisms underlying multicellular compartmentation will contribute to improving the production of specialized target metabolites through metabolic engineering or synthetic biology.
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Affiliation(s)
- Xiaofeng Shen
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China; State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Beijing, 100700, China
| | - Zhijing Guan
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China
| | - Chuyi Zhang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China
| | - Zhaojiu Yan
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China
| | - Chao Sun
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100193, China; State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Beijing, 100700, China.
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3
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Goeckeritz CZ, Zheng X, Harkess A, Dresselhaus T. Widespread application of apomixis in agriculture requires further study of natural apomicts. iScience 2024; 27:110720. [PMID: 39280618 PMCID: PMC11399699 DOI: 10.1016/j.isci.2024.110720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/18/2024] Open
Abstract
Apomixis, or asexual reproduction through seeds, is frequent in nature but does not exist in any major crop species, yet the phenomenon has captivated researchers for decades given its potential for clonal seed production and plant breeding. A discussion on whether this field will benefit from the continued study of natural apomicts is warranted given the recent outstanding progress in engineering apomixis. Here, we summarize what is known about its genetic control and the status of applying synthetic apomixis in agriculture. We argue there is still much to be learned from natural apomicts, and learning from them is necessary to improve on current progress and guarantee the effective application of apomixis beyond the few genera it has shown promise in so far. Specifically, we stress the value of studying the repeated evolution of natural apomicts in a phylogenetic and comparative -omics context. Finally, we identify outstanding questions in the field and discuss how technological advancements can be used to help close these knowledge gaps. In particular, genomic resources are lacking for apomicts, and this must be remedied for widespread use of apomixis in agriculture.
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Affiliation(s)
| | - Xixi Zheng
- Cell Biology and Plant Biochemistry, University of Regensburg, 93040 Regensburg, Germany
| | - Alex Harkess
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Thomas Dresselhaus
- Cell Biology and Plant Biochemistry, University of Regensburg, 93040 Regensburg, Germany
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4
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Song S, Wang J, Zhou J, Cheng X, Hu Y, Wang J, Zou J, Zhao Y, Liu C, Hu Z, Chen Q, Xin D. Single-Cell RNA-Sequencing of Soybean Reveals Transcriptional Changes and Antiviral Functions of GmGSTU23 and GmGSTU24 in Response to Soybean Mosaic Virus. PLANT, CELL & ENVIRONMENT 2024. [PMID: 39301882 DOI: 10.1111/pce.15164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 08/20/2024] [Accepted: 09/06/2024] [Indexed: 09/22/2024]
Abstract
Soybean mosaic virus (SMV) stands as a prominent and widespread threat to soybean (Glycine max L. Merr.), the foremost legume crop globally. Attaining a thorough comprehension of the alterations in the transcriptional network of soybeans in response to SMV infection is imperative for a profound insight into the mechanisms of viral pathogenicity and host resistance. In this investigation, we isolated 50 294 protoplasts from the newly developed leaves of soybean plants subjected to both SMV infection and mock inoculation. Subsequently, we utilized single-cell RNA sequencing (scRNA-seq) to construct the transcriptional landscape at a single-cell resolution. Nineteen distinct cell clusters were identified based on the transcriptomic profiles of scRNA-seq. The annotation of three cell types-epidermal cells, mesophyll cells, and vascular cells-was established based on the expression of orthologs to reported marker genes in Arabidopsis thaliana. The differentially expressed genes between the SMV- and mock-inoculated samples were analyzed for different cell types. Our investigation delved deeper into the tau class of glutathione S-transferases (GSTUs), known for their significant contributions to plant responses against abiotic and biotic stress. A total of 57 GSTU genes were identified by a thorough genome-wide investigation in the soybean genome G. max Wm82.a4.v1. Two specific candidates, GmGSTU23 and GmGSTU24, exhibited distinct upregulation in all three cell types in response to SMV infection, prompting their selection for further research. The transient overexpression of GmGSTU23 or GmGSTU24 in Nicotiana benthamiana resulted in the inhibition of SMV infection, indicating the antiviral function of soybean GSTU proteins.
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Affiliation(s)
- Shuang Song
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
- College of Plant Protection, Northeast Agricultural University, Harbin, China
| | - Jing Wang
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jiaying Zhou
- College of Plant Protection, Northeast Agricultural University, Harbin, China
| | - Xiaofei Cheng
- College of Plant Protection, Northeast Agricultural University, Harbin, China
| | - Yuxi Hu
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jinhui Wang
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Jianan Zou
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Ying Zhao
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Chunyan Liu
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Zhenbang Hu
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Qingshan Chen
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Dawei Xin
- National Key Laboratory of Smart Farm Technologies and Systems, College of Agriculture, Northeast Agricultural University, Harbin, China
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5
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Gouran M, Brady SM. The transcriptional integration of environmental cues with root cell type development. PLANT PHYSIOLOGY 2024:kiae425. [PMID: 39288006 DOI: 10.1093/plphys/kiae425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 08/05/2024] [Indexed: 09/19/2024]
Abstract
Plant roots navigate the soil ecosystem with each cell type uniquely responding to environmental stimuli. Below ground, the plant's response to its surroundings is orchestrated at the cellular level, including morphological and molecular adaptations that shape root system architecture as well as tissue and organ functionality. Our understanding of the transcriptional responses at cell type resolution has been profoundly enhanced by studies of the model plant Arabidopsis thaliana. However, both a comprehensive view of the transcriptional basis of these cellular responses to single and combinatorial environmental cues in diverse plant species remains elusive. In this review, we highlight the ability of root cell types to undergo specific anatomical or morphological changes in response to abiotic and biotic stresses or cues and how they collectively contribute to the plant's overall physiology. We further explore interconnections between stress and the temporal nature of developmental pathways and discuss examples of how this transcriptional reprogramming influences cell type identity and function. Finally, we highlight the power of single-cell and spatial transcriptomic approaches to refine our understanding of how environmental factors fine tune root spatiotemporal development. These complex root system responses underscore the importance of spatiotemporal transcriptional mapping, with significant implications for enhanced agricultural resilience.
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Affiliation(s)
- Mona Gouran
- Department of Plant Biology and Genome Center, UC Davis, Davis, CA 95616, USA
| | - Siobhan M Brady
- Department of Plant Biology and Genome Center, UC Davis, Davis, CA 95616, USA
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6
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Tenorio Berrío R, Dubois M. Single-cell transcriptomics reveals heterogeneity in plant responses to the environment: a focus on biotic and abiotic interactions. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:5188-5203. [PMID: 38466621 DOI: 10.1093/jxb/erae107] [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: 11/30/2023] [Accepted: 03/08/2024] [Indexed: 03/13/2024]
Abstract
Biotic and abiotic environmental cues are major factors influencing plant growth and productivity. Interactions with biotic (e.g. symbionts and pathogens) and abiotic (e.g. changes in temperature, water, or nutrient availability) factors trigger signaling and downstream transcriptome adjustments in plants. While bulk RNA-sequencing technologies have traditionally been used to profile these transcriptional changes, tissue homogenization may mask heterogeneity of responses resulting from the cellular complexity of organs. Thus, whether different cell types respond equally to environmental fluctuations, or whether subsets of the responses are cell-type specific, are long-lasting questions in plant biology. The recent breakthrough of single-cell transcriptomics in plant research offers an unprecedented view of cellular responses under changing environmental conditions. In this review, we discuss the contribution of single-cell transcriptomics to the understanding of cell-type-specific plant responses to biotic and abiotic environmental interactions. Besides major biological findings, we present some technical challenges coupled to single-cell studies of plant-environment interactions, proposing possible solutions and exciting paths for future research.
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Affiliation(s)
- Rubén Tenorio Berrío
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Marieke Dubois
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
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7
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Yao J, Chu Q, Guo X, Shao W, Shang N, Luo K, Li X, Chen H, Cheng Q, Mo F, Zheng D, Xu F, Guo F, Zhu QH, Deng S, Chu C, Xu X, Liu H, Fan L. Spatiotemporal transcriptomic landscape of rice embryonic cells during seed germination. Dev Cell 2024; 59:2320-2332.e5. [PMID: 38848718 DOI: 10.1016/j.devcel.2024.05.016] [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: 04/24/2023] [Revised: 02/15/2024] [Accepted: 05/14/2024] [Indexed: 06/09/2024]
Abstract
Characterizing cellular features during seed germination is crucial for understanding the complex biological functions of different embryonic cells in regulating seed vigor and seedling establishment. We performed spatially enhanced resolution omics sequencing (Stereo-seq) and single-cell RNA sequencing (scRNA-seq) to capture spatially resolved single-cell transcriptomes of germinating rice embryos. An automated cell-segmentation model, employing deep learning, was developed to accommodate the analysis requirements. The spatial transcriptomes of 6, 24, 36, and 48 h after imbibition unveiled both known and previously unreported embryo cell types, including two unreported scutellum cell types, corroborated by in situ hybridization and functional exploration of marker genes. Temporal transcriptomic profiling delineated gene expression dynamics in distinct embryonic cell types during seed germination, highlighting key genes involved in nutrient metabolism, biosynthesis, and signaling of phytohormones, reprogrammed in a cell-type-specific manner. Our study provides a detailed spatiotemporal transcriptome of rice embryo and presents a previously undescribed methodology for exploring the roles of different embryonic cells in seed germination.
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Affiliation(s)
- Jie Yao
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China; Hainan Institute, Zhejiang University, Sanya 572025, China
| | - Qinjie Chu
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Xing Guo
- BGI Research, Shenzhen 518103, China; BGI Research, Wuhan 430074, China
| | - Wenwen Shao
- BGI Research, Shenzhen 518103, China; BGI Research, Wuhan 430074, China
| | - Nianmin Shang
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Kang Luo
- College of Computer Science and Technology & Polytechnic Institute, Zhejiang University, Hangzhou 310015, Zhejiang, China
| | - Xiaohan Li
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Hongyu Chen
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Qing Cheng
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Fangyu Mo
- Hainan Institute, Zhejiang University, Sanya 572025, China
| | - Dihuai Zheng
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China
| | - Fan Xu
- College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
| | - Fu Guo
- Hainan Institute, Zhejiang University, Sanya 572025, China
| | - Qian-Hao Zhu
- CSIRO, Agriculture and Food, Canberra, ACT 2601, Australia
| | - Shuiguang Deng
- College of Computer Science and Technology & Polytechnic Institute, Zhejiang University, Hangzhou 310015, Zhejiang, China
| | - Chengcai Chu
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, South China Agricultural University, Guangzhou 510642, China
| | - Xun Xu
- BGI Research, Shenzhen 518103, China
| | - Huan Liu
- BGI Research, Shenzhen 518103, China.
| | - Longjiang Fan
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou 310058, China; Hainan Institute, Zhejiang University, Sanya 572025, China.
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8
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Maciejewski K, Czerwinska P. Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research. Cancers (Basel) 2024; 16:3100. [PMID: 39272958 PMCID: PMC11394603 DOI: 10.3390/cancers16173100] [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: 07/19/2024] [Revised: 08/30/2024] [Accepted: 08/30/2024] [Indexed: 09/15/2024] Open
Abstract
Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research.
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Affiliation(s)
- Kacper Maciejewski
- Undergraduate Research Group "Biobase", Poznan University of Medical Sciences, 61-701 Poznan, Poland
| | - Patrycja Czerwinska
- Undergraduate Research Group "Biobase", Poznan University of Medical Sciences, 61-701 Poznan, Poland
- Department of Cancer Immunology, Poznan University of Medical Sciences, 61-866 Poznan, Poland
- Department of Diagnostics and Cancer Immunology, Greater Poland Cancer Centre, 61-866 Poznan, Poland
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9
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Saarenpää S, Shalev O, Ashkenazy H, Carlos V, Lundberg DS, Weigel D, Giacomello S. Spatial metatranscriptomics resolves host-bacteria-fungi interactomes. Nat Biotechnol 2024; 42:1384-1393. [PMID: 37985875 PMCID: PMC11392817 DOI: 10.1038/s41587-023-01979-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 09/06/2023] [Indexed: 11/22/2023]
Abstract
The interactions of microorganisms among themselves and with their multicellular host take place at the microscale, forming complex networks and spatial patterns. Existing technology does not allow the simultaneous investigation of spatial interactions between a host and the multitude of its colonizing microorganisms, which limits our understanding of host-microorganism interactions within a plant or animal tissue. Here we present spatial metatranscriptomics (SmT), a sequencing-based approach that leverages 16S/18S/ITS/poly-d(T) multimodal arrays for simultaneous host transcriptome- and microbiome-wide characterization of tissues at 55-µm resolution. We showcase SmT in outdoor-grown Arabidopsis thaliana leaves as a model system, and find tissue-scale bacterial and fungal hotspots. By network analysis, we study inter- and intrakingdom spatial interactions among microorganisms, as well as the host response to microbial hotspots. SmT provides an approach for answering fundamental questions on host-microbiome interplay.
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Affiliation(s)
- Sami Saarenpää
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Or Shalev
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Systems Biology of Microbial Communities, University of Tübingen, Tübingen, Germany
| | - Haim Ashkenazy
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
| | - Vanessa Carlos
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
| | - Derek Severi Lundberg
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Detlef Weigel
- Max Planck Institute for Biology Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Stefania Giacomello
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
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10
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Adema K, Schon MA, Nodine MD, Kohlen W. Lost in space: what single-cell RNA sequencing cannot tell you. TRENDS IN PLANT SCIENCE 2024; 29:1018-1028. [PMID: 38570278 DOI: 10.1016/j.tplants.2024.03.010] [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: 11/16/2023] [Revised: 02/21/2024] [Accepted: 03/11/2024] [Indexed: 04/05/2024]
Abstract
Plant scientists are rapidly integrating single-cell RNA sequencing (scRNA-seq) into their workflows. Maximizing the potential of scRNA-seq requires a proper understanding of the spatiotemporal context of cells. However, positional information is inherently lost during scRNA-seq, limiting its potential to characterize complex biological systems. In this review we highlight how current single-cell analysis pipelines cannot completely recover spatial information, which confounds biological interpretation. Various strategies exist to identify the location of RNA, from classical RNA in situ hybridization to spatial transcriptomics. Herein we discuss the possibility of utilizing this spatial information to supervise single-cell analyses. An integrative approach will maximize the potential of each technology, and lead to insights which go beyond the capability of each individual technology.
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Affiliation(s)
- Kelvin Adema
- Laboratory of Cell and Developmental Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Michael A Schon
- Laboratory of Cell and Developmental Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands; Laboratory of Molecular Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Michael D Nodine
- Laboratory of Molecular Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Wouter Kohlen
- Laboratory of Cell and Developmental Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands; Laboratory of Molecular Biology, Cluster of Plant Developmental Biology, Department of Plant Sciences, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
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11
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Liu L, Chen A, Li Y, Mulder J, Heyn H, Xu X. Spatiotemporal omics for biology and medicine. Cell 2024; 187:4488-4519. [PMID: 39178830 DOI: 10.1016/j.cell.2024.07.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/05/2024] [Accepted: 07/23/2024] [Indexed: 08/26/2024]
Abstract
The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.
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Affiliation(s)
| | - Ao Chen
- BGI Research, Shenzhen 518083, China
| | | | - Jan Mulder
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Holger Heyn
- Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain
| | - Xun Xu
- BGI Research, Hangzhou 310030, China; BGI Research, Shenzhen 518083, China.
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12
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Yin R, Chen R, Xia K, Xu X. A single-cell transcriptome atlas reveals the trajectory of early cell fate transition during callus induction in Arabidopsis. PLANT COMMUNICATIONS 2024; 5:100941. [PMID: 38720464 PMCID: PMC11369778 DOI: 10.1016/j.xplc.2024.100941] [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: 11/18/2023] [Revised: 04/16/2024] [Accepted: 05/06/2024] [Indexed: 06/16/2024]
Abstract
The acquisition of pluripotent callus from somatic cells plays an important role in plant development studies and crop genetic improvement. This developmental process incorporates a series of cell fate transitions and reprogramming. However, our understanding of cell heterogeneity and mechanisms of cell fate transition during callus induction remains quite limited. Here, we report a time-series single-cell transcriptome experiment on Arabidopsis root explants that were induced in callus induction medium for 0, 1, and 4 days, and the construction of a detailed single-cell transcriptional atlas of the callus induction process. We identify the cell types responsible for initiating the early callus: lateral root primordium-initiating (LRPI)-like cells and quiescent center (QC)-like cells. LRPI-like cells are derived from xylem pole pericycle cells and are similar to lateral root primordia. We delineate the developmental trajectory of the dedifferentiation of LRPI-like cells into QC-like cells. QC-like cells are undifferentiated pluripotent acquired cells that appear in the early stages of callus formation and play a critical role in later callus development and organ regeneration. We also identify the transcription factors that regulate QC-like cells and the gene expression signatures that are related to cell fate decisions. Overall, our cell-lineage transcriptome atlas for callus induction provides a distinct perspective on cell fate transitions during callus formation, significantly improving our understanding of callus formation.
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Affiliation(s)
- Ruilian Yin
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 10049, China; BGI Research, Beijing 102601, China
| | - Ruiying Chen
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 10049, China; BGI Research, Beijing 102601, China
| | - Keke Xia
- BGI Research, Beijing 102601, China.
| | - Xun Xu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 10049, China; BGI Research, Beijing 102601, China; Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen 518120, Guangdong, China.
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13
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Ye K, Bu F, Zhong L, Dong Z, Ma Z, Tang Z, Zhang Y, Yang X, Xu X, Wang E, Lucas WJ, Huang S, Liu H, Zheng J. Mapping the molecular landscape of Lotus japonicus nodule organogenesis through spatiotemporal transcriptomics. Nat Commun 2024; 15:6387. [PMID: 39080318 PMCID: PMC11289483 DOI: 10.1038/s41467-024-50737-8] [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: 03/01/2024] [Accepted: 07/18/2024] [Indexed: 08/02/2024] Open
Abstract
Legumes acquire nitrogen-fixing ability by forming root nodules. Transferring this capability to more crops could reduce our reliance on nitrogen fertilizers, thereby decreasing environmental pollution and agricultural production costs. Nodule organogenesis is complex, and a comprehensive transcriptomic atlas is crucial for understanding the underlying molecular events. Here, we utilized spatial transcriptomics to investigate the development of nodules in the model legume, Lotus japonicus. Our investigation has identified the developmental trajectories of two critical regions within the nodule: the infection zone and peripheral tissues. We reveal the underlying biological processes and provide gene sets to achieve symbiosis and material exchange, two essential aspects of nodulation. Among the candidate regulatory genes, we illustrate that LjNLP3, a transcription factor belonging to the NIN-LIKE PROTEIN family, orchestrates the transition of nodules from the differentiation to maturation. In summary, our research advances our understanding of nodule organogenesis and provides valuable data for developing symbiotic nitrogen-fixing crops.
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Affiliation(s)
- Keyi Ye
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China.
| | - Fengjiao Bu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
| | | | - Zhaonian Dong
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
| | - Zhaoxu Ma
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
- National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan), College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhanpeng Tang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
| | - Yu Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
- School of Agriculture, Sun Yat-sen University, Shenzhen, 518107, China
| | - Xueyong Yang
- State Key Laboratory of Vegetable Biobreeding, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xun Xu
- State Key Laboratory of Agricultural Genomics, BGI Research, Shenzhen, 518083, China
| | - Ertao Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, SIBS, Chinese Academy of Sciences, Shanghai, China
| | - William J Lucas
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
- Department of Plant Biology, College of Biological Sciences, University of California, Davis, CA, 95616, USA
| | - Sanwen Huang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
- National Key Laboratory of Tropical Crop Breeding, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan, 571101, China
| | - Huan Liu
- BGI Research, Wuhan, 430074, China.
- State Key Laboratory of Agricultural Genomics, BGI Research, Shenzhen, 518083, China.
| | - Jianshu Zheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China.
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14
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Rhaman MS, Ali M, Ye W, Li B. Opportunities and Challenges in Advancing Plant Research with Single-cell Omics. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae026. [PMID: 38996445 DOI: 10.1093/gpbjnl/qzae026] [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: 04/12/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 07/14/2024]
Abstract
Plants possess diverse cell types and intricate regulatory mechanisms to adapt to the ever-changing environment of nature. Various strategies have been employed to study cell types and their developmental progressions, including single-cell sequencing methods which provide high-dimensional catalogs to address biological concerns. In recent years, single-cell sequencing technologies in transcriptomics, epigenomics, proteomics, metabolomics, and spatial transcriptomics have been increasingly used in plant science to reveal intricate biological relationships at the single-cell level. However, the application of single-cell technologies to plants is more limited due to the challenges posed by cell structure. This review outlines the advancements in single-cell omics technologies, their implications in plant systems, future research applications, and the challenges of single-cell omics in plant systems.
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Affiliation(s)
- Mohammad Saidur Rhaman
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Muhammad Ali
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Wenxiu Ye
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
| | - Bosheng Li
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Weifang 261325, China
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15
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Zhang B, Zhang H, Xia Y. Harnessing spatial transcriptomics for advancing plant regeneration research. TRENDS IN PLANT SCIENCE 2024; 29:718-720. [PMID: 38418271 DOI: 10.1016/j.tplants.2024.02.004] [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: 12/11/2023] [Revised: 02/03/2024] [Accepted: 02/19/2024] [Indexed: 03/01/2024]
Abstract
Song et al. utilized spatial transcriptomics to study the molecular characteristics of various cells - such as shoot primordia and chlorenchyma cells - in tomato callus during shoot regeneration. This research enhances our knowledge of shoot regeneration and demonstrates the potential of spatial transcriptomics in advancing plant biology.
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Affiliation(s)
- Bingxu Zhang
- Department of Biology, Hong Kong Baptist University, Hong Kong, SAR, China
| | - Hailei Zhang
- Department of Biology, Hong Kong Baptist University, Hong Kong, SAR, China
| | - Yiji Xia
- Department of Biology, Hong Kong Baptist University, Hong Kong, SAR, China; State Key Laboratory of Agrobiotechnology, School of Life Sciences, The Chinese University of Hong Kong, Hong Kong, SAR, China.
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16
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Vong GYW, McCarthy K, Claydon W, Davis SJ, Redmond EJ, Ezer D. AraLeTA: An Arabidopsis leaf expression atlas across diurnal and developmental scales. PLANT PHYSIOLOGY 2024; 195:1941-1953. [PMID: 38428997 PMCID: PMC11213249 DOI: 10.1093/plphys/kiae117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/08/2024] [Accepted: 02/09/2024] [Indexed: 03/03/2024]
Abstract
Mature plant leaves are a composite of distinct cell types, including epidermal, mesophyll, and vascular cells. Notably, the proportion of these cells and the relative transcript concentrations within different cell types may change over time. While gene expression data at a single-cell level can provide cell-type-specific expression values, it is often too expensive to obtain these data for high-resolution time series. Although bulk RNA-seq can be performed in a high-resolution time series, RNA-seq using whole leaves measures average gene expression values across all cell types in each sample. In this study, we combined single-cell RNA-seq data with time-series data from whole leaves to assemble an atlas of cell-type-specific changes in gene expression over time for Arabidopsis (Arabidopsis thaliana). We inferred how the relative transcript concentrations of different cell types vary across diurnal and developmental timescales. Importantly, this analysis revealed 3 subgroups of mesophyll cells with distinct temporal profiles of expression. Finally, we developed tissue-specific gene networks that form a community resource: an Arabidopsis Leaf Time-dependent Atlas (AraLeTa). This allows users to extract gene networks that are confirmed by transcription factor-binding data and specific to certain cell types at certain times of day and at certain developmental stages. AraLeTa is available at https://regulatorynet.shinyapps.io/araleta/.
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Affiliation(s)
- Gina Y W Vong
- Department of Biology, University of York, York YO10 5DD, UK
| | - Kayla McCarthy
- Department of Biology, University of York, York YO10 5DD, UK
| | - Will Claydon
- Department of Biology, University of York, York YO10 5DD, UK
| | - Seth J Davis
- Department of Biology, University of York, York YO10 5DD, UK
| | - Ethan J Redmond
- Department of Biology, University of York, York YO10 5DD, UK
| | - Daphne Ezer
- Department of Biology, University of York, York YO10 5DD, UK
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17
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Huang K, Xu Y, Feng T, Lan H, Ling F, Xiang H, Liu Q. The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research. BIOLOGY 2024; 13:451. [PMID: 38927331 PMCID: PMC11200756 DOI: 10.3390/biology13060451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024]
Abstract
Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.
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Affiliation(s)
- Kongwei Huang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510641, China
| | - Yixue Xu
- Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Animal Science and Technology, Guangxi University, Nanning 530005, China;
| | - Tong Feng
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hong Lan
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Fei Ling
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510641, China
| | - Hai Xiang
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Qingyou Liu
- Guangdong Provincial Key Laboratory of Animal Molecular Design and Precise Breeding, School of Life Science and Engineering, Foshan University, Foshan 528225, China
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18
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Lv Z, Jiang S, Kong S, Zhang X, Yue J, Zhao W, Li L, Lin S. Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants. PLANTS (BASEL, SWITZERLAND) 2024; 13:1679. [PMID: 38931111 PMCID: PMC11207393 DOI: 10.3390/plants13121679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/31/2024] [Accepted: 06/14/2024] [Indexed: 06/28/2024]
Abstract
"Omics" typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell's metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.
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Affiliation(s)
- Zhuo Lv
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Shuaijun Jiang
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Shuxin Kong
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Xu Zhang
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Jiahui Yue
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Wanqi Zhao
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
- College of Life Science, Nanjing Forestry University, Nanjing 210037, China
| | - Long Li
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
| | - Shuyan Lin
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China; (Z.L.); (S.J.); (S.K.); (X.Z.); (J.Y.); (W.Z.); (L.L.)
- Bamboo Research Institute, Nanjing Forestry University, Nanjing 210037, China
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19
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Lian X, Zhong L, Bai Y, Guang X, Tang S, Guo X, Wei T, Yang F, Zhang Y, Huang G, Zhang J, Shao L, Lei G, Li Z, Sahu SK, Zhang S, Liu H, Hu F. Spatiotemporal transcriptomic atlas of rhizome formation in Oryza longistaminata. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:1652-1668. [PMID: 38345936 PMCID: PMC11123419 DOI: 10.1111/pbi.14294] [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: 10/10/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 02/22/2024]
Abstract
Rhizomes are modified stems that grow underground and produce new individuals genetically identical to the mother plant. Recently, a breakthrough has been made in efforts to convert annual grains into perennial ones by utilizing wild rhizomatous species as donors, yet the developmental biology of this organ is rarely studied. Oryza longistaminata, a wild rice species featuring strong rhizomes, provides a valuable model for exploration of rhizome development. Here, we first assembled a double-haplotype genome of O. longistaminata, which displays a 48-fold improvement in contiguity compared to the previously published assembly. Furthermore, spatiotemporal transcriptomics was performed to obtain the expression profiles of different tissues in O. longistaminata rhizomes and tillers. Two spatially reciprocal cell clusters, the vascular bundle 2 cluster and the parenchyma 2 cluster, were determined to be the primary distinctions between the rhizomes and tillers. We also captured meristem initiation cells in the sunken area of parenchyma located at the base of internodes, which is the starting point for rhizome initiation. Trajectory analysis further indicated that the rhizome is regenerated through de novo generation. Collectively, these analyses revealed a spatiotemporal transcriptional transition underlying the rhizome initiation, providing a valuable resource for future perennial crop breeding.
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Affiliation(s)
- Xiaoping Lian
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Liyuan Zhong
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Yixuan Bai
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Xuanmin Guang
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Sijia Tang
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Xing Guo
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Tong Wei
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Feng Yang
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Yujiao Zhang
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Guangfu Huang
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Jing Zhang
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Lin Shao
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Guijie Lei
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Zheng Li
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Shilai Zhang
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
| | - Huan Liu
- State Key Laboratory of Agricultural GenomicsBGI‐ShenzhenShenzhenGuangdongChina
| | - Fengyi Hu
- New Cornerstone Science Laboratory, State Key Laboratory for Conservation and Utilization of Bio‐Resources in Yunnan, Key Laboratory of Biology and Germplasm Innovation of Perennial rice (Co‐construction by Ministry and Province) of Ministry of Agriculture and Rural Affairs, Center of Innovation for Perennial Rice Technology in Yunnan, School of AgricultureYunnan UniversityKunmingChina
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20
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Zhang Y, Lee RY, Tan CW, Guo X, Yim WWY, Lim JC, Wee FY, Yang WU, Kharbanda M, Lee JYJ, Ngo NT, Leow WQ, Loo LH, Lim TK, Sobota RM, Lau MC, Davis MJ, Yeong J. Spatial omics techniques and data analysis for cancer immunotherapy applications. Curr Opin Biotechnol 2024; 87:103111. [PMID: 38520821 DOI: 10.1016/j.copbio.2024.103111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 03/01/2024] [Accepted: 03/03/2024] [Indexed: 03/25/2024]
Abstract
In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.
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Affiliation(s)
- Yue Zhang
- Duke-NUS Medical School, Singapore 169856, Singapore
| | - Ren Yuan Lee
- Yong Loo Lin School of Medicine, National University of Singapore, 169856 Singapore; Singapore Thong Chai Medical Institution, Singapore 169874, Singapore
| | - Chin Wee Tan
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Victoria 3052, Australia; Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia; Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4102, Australia
| | - Xue Guo
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - Willa W-Y Yim
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - Jeffrey Ct Lim
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - Felicia Yt Wee
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - W U Yang
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - Malvika Kharbanda
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Victoria 3052, Australia; Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia; immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Jia-Ying J Lee
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore
| | - Nye Thane Ngo
- Department of Anatomical Pathology, Singapore General Hospital, Singapore 169856, Singapore
| | - Wei Qiang Leow
- Department of Anatomical Pathology, Singapore General Hospital, Singapore 169856, Singapore
| | - Lit-Hsin Loo
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore
| | - Tony Kh Lim
- Department of Anatomical Pathology, Singapore General Hospital, Singapore 169856, Singapore
| | - Radoslaw M Sobota
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore
| | - Mai Chan Lau
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore; Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A⁎STAR), Singapore 138648, Singapore
| | - Melissa J Davis
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Victoria 3052, Australia; Department of Medical Biology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia; Frazer Institute, Faculty of Medicine, The University of Queensland, Brisbane, Queensland 4102, Australia; immunoGENomics Cancer Institute (SAiGENCI), Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia; Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Joe Yeong
- Institute of Molecular Cell Biology (IMCB), Agency of Science, Technology and Research (A⁎STAR), Singapore 169856, Singapore; Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore.
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21
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Chu LX, Wang WJ, Gu XP, Wu P, Gao C, Zhang Q, Wu J, Jiang DW, Huang JQ, Ying XW, Shen JM, Jiang Y, Luo LH, Xu JP, Ying YB, Chen HM, Fang A, Feng ZY, An SH, Li XK, Wang ZG. Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine. Mil Med Res 2024; 11:31. [PMID: 38797843 PMCID: PMC11129507 DOI: 10.1186/s40779-024-00537-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.
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Affiliation(s)
- Liu-Xi Chu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Wen-Jia Wang
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Xin-Pei Gu
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Screening, Southern Medical University, Guangzhou, 510515, China
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Ping Wu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Chen Gao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Quan Zhang
- Integrative Muscle Biology Laboratory, Division of Regenerative and Rehabilitative Sciences, University of Tennessee Health Science Center, Memphis, TN, 38163, United States
| | - Jia Wu
- Key Laboratory for Laboratory Medicine, Ministry of Education, Zhejiang Provincial Key Laboratory of Medical Genetics, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Da-Wei Jiang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jun-Qing Huang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China
| | - Xin-Wang Ying
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jia-Men Shen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi Jiang
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Li-Hua Luo
- School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou, 324025, Zhejiang, China
| | - Jun-Peng Xu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi-Bo Ying
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Hao-Man Chen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Ao Fang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Zun-Yong Feng
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, 119074, Singapore.
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599, Singapore.
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, 138673, Singapore.
| | - Shu-Hong An
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China.
| | - Xiao-Kun Li
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
| | - Zhou-Guang Wang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China.
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22
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Li R, Du K, Zhang C, Shen X, Yun L, Wang S, Li Z, Sun Z, Wei J, Li Y, Guo B, Sun C. Single-cell transcriptome profiling reveals the spatiotemporal distribution of triterpenoid saponin biosynthesis and transposable element activity in Gynostemma pentaphyllum shoot apexes and leaves. FRONTIERS IN PLANT SCIENCE 2024; 15:1394587. [PMID: 38779067 PMCID: PMC11109411 DOI: 10.3389/fpls.2024.1394587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024]
Abstract
Gynostemma pentaphyllum (Thunb.) Makino is an important producer of dammarene-type triterpenoid saponins. These saponins (gypenosides) exhibit diverse pharmacological benefits such as anticancer, antidiabetic, and immunomodulatory effects, and have major potential in the pharmaceutical and health care industries. Here, we employed single-cell RNA sequencing (scRNA-seq) to profile the transcriptomes of more than 50,000 cells derived from G. pentaphyllum shoot apexes and leaves. Following cell clustering and annotation, we identified five major cell types in shoot apexes and four in leaves. Each cell type displayed substantial transcriptomic heterogeneity both within and between tissues. Examining gene expression patterns across various cell types revealed that gypenoside biosynthesis predominantly occurred in mesophyll cells, with heightened activity observed in shoot apexes compared to leaves. Furthermore, we explored the impact of transposable elements (TEs) on G. pentaphyllum transcriptomic landscapes. Our findings the highlighted the unbalanced expression of certain TE families across different cell types in shoot apexes and leaves, marking the first investigation of TE expression at the single-cell level in plants. Additionally, we observed dynamic expression of genes involved in gypenoside biosynthesis and specific TE families during epidermal and vascular cell development. The involvement of TE expression in regulating cell differentiation and gypenoside biosynthesis warrant further exploration. Overall, this study not only provides new insights into the spatiotemporal organization of gypenoside biosynthesis and TE activity in G. pentaphyllum shoot apexes and leaves but also offers valuable cellular and genetic resources for a deeper understanding of developmental and physiological processes at single-cell resolution in this species.
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Affiliation(s)
- Rucan Li
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ke Du
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chuyi Zhang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaofeng Shen
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingling Yun
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shu Wang
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ziqin Li
- College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Zhiying Sun
- College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
| | - Jianhe Wei
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Baolin Guo
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Sun
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Li J, Wang Y, Raina MA, Xu C, Su L, Guo Q, Ma Q, Wang J, Xu D. scBSP: A fast and accurate tool for identifying spatially variable genes from spatial transcriptomic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592851. [PMID: 38765956 PMCID: PMC11100755 DOI: 10.1101/2024.05.06.592851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Spatially resolved transcriptomics have enabled the inference of gene expression patterns within two and three-dimensional space, while introducing computational challenges due to growing spatial resolutions and sparse expressions. Here, we introduce scBSP, an open-source, versatile, and user-friendly package designed for identifying spatially variable genes in large-scale spatial transcriptomics. scBSP implements sparse matrix operation to significantly increase the computational efficiency in both computational time and memory usage, processing the high-definition spatial transcriptomics data for 19,950 genes on 181,367 spots within 10 seconds. Applied to diverse sequencing data and simulations, scBSP efficiently identifies spatially variable genes, demonstrating fast computational speed and consistency across various sequencing techniques and spatial resolutions for both two and three-dimensional data with up to millions of cells. On a sample with hundreds of thousands of sports, scBSP identifies SVGs accurately in seconds to on a typical desktop computer.
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24
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Wang Y, Luo Y, Guo X, Li Y, Yan J, Shao W, Wei W, Wei X, Yang T, Chen J, Chen L, Ding Q, Bai M, Zhuo L, Li L, Jackson D, Zhang Z, Xu X, Yan J, Liu H, Liu L, Yang N. A spatial transcriptome map of the developing maize ear. NATURE PLANTS 2024; 10:815-827. [PMID: 38745100 DOI: 10.1038/s41477-024-01683-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 04/03/2024] [Indexed: 05/16/2024]
Abstract
A comprehensive understanding of inflorescence development is crucial for crop genetic improvement, as inflorescence meristems give rise to reproductive organs and determine grain yield. However, dissecting inflorescence development at the cellular level has been challenging owing to a lack of specific marker genes to distinguish among cell types, particularly in different types of meristems that are vital for organ formation. In this study, we used spatial enhanced resolution omics-sequencing (Stereo-seq) to construct a precise spatial transcriptome map of the developing maize ear primordium, identifying 12 cell types, including 4 newly defined cell types found mainly in the inflorescence meristem. By extracting the meristem components for detailed clustering, we identified three subtypes of meristem and validated two MADS-box genes that were specifically expressed at the apex of determinate meristems and involved in stem cell determinacy. Furthermore, by integrating single-cell RNA transcriptomes, we identified a series of spatially specific networks and hub genes that may provide new insights into the formation of different tissues. In summary, this study provides a valuable resource for research on cereal inflorescence development, offering new clues for yield improvement.
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Affiliation(s)
- Yuebin Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Yun Luo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xing Guo
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
- BGI Research, Wuhan, China
| | - Yunfu Li
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Jiali Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Wenwen Shao
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
- BGI Research, Wuhan, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Wenjie Wei
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Xiaofeng Wei
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
- China National GeneBank, Shenzhen, China
| | - Tao Yang
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
- China National GeneBank, Shenzhen, China
| | - Jing Chen
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
- China National GeneBank, Shenzhen, China
| | - Lihua Chen
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
| | - Qian Ding
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Minji Bai
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Lin Zhuo
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Li Li
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
| | - David Jackson
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Zuxin Zhang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Xun Xu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Huan Liu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen, China.
- Guangdong Laboratory of Lingnan Modern Agriculture, Agricultural Genomics Institute at Shenzhen, Shenzhen, China.
| | - Lei Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
- Hubei Hongshan Laboratory, Wuhan, China.
| | - Ning Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
- Hubei Hongshan Laboratory, Wuhan, China.
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25
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Li X, Li B, Gu S, Pang X, Mason P, Yuan J, Jia J, Sun J, Zhao C, Henry R. Single-cell and spatial RNA sequencing reveal the spatiotemporal trajectories of fruit senescence. Nat Commun 2024; 15:3108. [PMID: 38600080 PMCID: PMC11006883 DOI: 10.1038/s41467-024-47329-x] [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: 10/15/2023] [Accepted: 03/26/2024] [Indexed: 04/12/2024] Open
Abstract
The senescence of fruit is a complex physiological process, with various cell types within the pericarp, making it highly challenging to elucidate their individual roles in fruit senescence. In this study, a single-cell expression atlas of the pericarp of pitaya (Hylocereus undatus) is constructed, revealing exocarp and mesocarp cells undergoing the most significant changes during the fruit senescence process. Pseudotime analysis establishes cellular differentiation and gene expression trajectories during senescence. Early-stage oxidative stress imbalance is followed by the activation of resistance in exocarp cells, subsequently senescence-associated proteins accumulate in the mesocarp cells at late-stage senescence. The central role of the early response factor HuCMB1 is unveiled in the senescence regulatory network. This study provides a spatiotemporal perspective for a deeper understanding of the dynamic senescence process in plants.
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Affiliation(s)
- Xin Li
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
- Queensland Alliance for Agriculture & Food Innovation, Queensland Biosciences Precinct, The University of Queensland, St Lucia, QLD 4072, Australia
- National Demonstration Center for Experimental Food Processing and Safety Education, Luoyang, 471023, China
| | - Bairu Li
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Shaobin Gu
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Xinyue Pang
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Patrick Mason
- Queensland Alliance for Agriculture & Food Innovation, Queensland Biosciences Precinct, The University of Queensland, St Lucia, QLD 4072, Australia
| | - Jiangfeng Yuan
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Jingyu Jia
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Jiaju Sun
- College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, 471023, China
| | - Chunyan Zhao
- Institute of Environment and Health, Jianghan University, Wuhan, 430056, China.
| | - Robert Henry
- Queensland Alliance for Agriculture & Food Innovation, Queensland Biosciences Precinct, The University of Queensland, St Lucia, QLD 4072, Australia.
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Sun X, Liu Z, Liu R, Bucher J, Zhao J, Visser RGF, Bonnema G. Transcriptomic analyses to summarize gene expression patterns that occur during leaf initiation of Chinese cabbage. HORTICULTURE RESEARCH 2024; 11:uhae059. [PMID: 38689699 PMCID: PMC11059812 DOI: 10.1093/hr/uhae059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 02/19/2024] [Indexed: 05/02/2024]
Abstract
In Chinese cabbage, rosette leaves expose their adaxial side to the light converting light energy into chemical energy, acting as a source for the growth of the leafy head. In the leafy head, the outer heading leaves expose their abaxial side to the light while the inner leaves are shielded from the light and have become a sink organ of the growing Chinese cabbage plant. Interestingly, variation in several ad/abaxial polarity genes is associated with the typical leafy head morphotype. The initiation of leaf primordia and the establishment of leaf ad/abaxial polarity are essential steps in the initiation of marginal meristem activity leading to leaf formation. Understanding the molecular genetic mechanisms of leaf primordia formation, polar differentiation, and leaf expansion is thus relevant to understand leafy head formation. As Brassica's are mesa-hexaploids, many genes have multiple paralogues, complicating analysis of the genetic regulation of leaf development. In this study, we used laser dissection of Chinese cabbage leaf primordia and the shoot apical meristem (SAM) to compare gene expression profiles between both adaxial and abaxial sides and the SAM aiming to capture transcriptome changes underlying leaf primordia development. We highlight genes with roles in hormone pathways and transcription factors. We also assessed gene expression gradients along expanded leaf blades from the same plants to analyze regulatory links between SAM, leaf primordia and the expanding rosette leaf. The catalogue of differentially expressed genes provides insights in gene expression patterns involved in leaf development and form a starting point to unravel leafy head formation.
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Affiliation(s)
- XiaoXue Sun
- 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, College of Horticulture, Hebei Agricultural University, Baoding 071000, China
| | - Zihan Liu
- Plant Breeding, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
| | - Rui 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, College of Horticulture, Hebei Agricultural University, Baoding 071000, China
| | - Johan Bucher
- Plant Breeding, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
| | - 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, College of Horticulture, Hebei Agricultural University, Baoding 071000, China
| | - Richard G F Visser
- Plant Breeding, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
| | - Guusje Bonnema
- Plant Breeding, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
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27
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Gao Z, He Y. Molecular epigenetic understanding of winter memory in Arabidopsis. PLANT PHYSIOLOGY 2024; 194:1952-1961. [PMID: 37950890 DOI: 10.1093/plphys/kiad597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 10/13/2023] [Accepted: 11/03/2023] [Indexed: 11/13/2023]
Affiliation(s)
- Zheng Gao
- National Key Laboratory of Wheat Improvement, Peking-Tsinghua Center for Life Sciences, School of Advanced Agricultural Sciences, Peking University, Beijing 100871, China
| | - Yuehui He
- National Key Laboratory of Wheat Improvement, Peking-Tsinghua Center for Life Sciences, School of Advanced Agricultural Sciences, Peking University, Beijing 100871, China
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong 261325, China
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28
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Grones C, Eekhout T, Shi D, Neumann M, Berg LS, Ke Y, Shahan R, Cox KL, Gomez-Cano F, Nelissen H, Lohmann JU, Giacomello S, Martin OC, Cole B, Wang JW, Kaufmann K, Raissig MT, Palfalvi G, Greb T, Libault M, De Rybel B. Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics. THE PLANT CELL 2024; 36:812-828. [PMID: 38231860 PMCID: PMC10980355 DOI: 10.1093/plcell/koae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/17/2023] [Accepted: 10/24/2023] [Indexed: 01/19/2024]
Abstract
Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.
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Affiliation(s)
- Carolin Grones
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Thomas Eekhout
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
- VIB Single Cell Core Facility, Ghent 9052, Belgium
| | - Dongbo Shi
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
- Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany
| | - Manuel Neumann
- Institute of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Lea S Berg
- Institute of Plant Sciences, University of Bern, 3012 Bern, Switzerland
| | - Yuji Ke
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Rachel Shahan
- Department of Biology, Duke University, Durham, NC 27708, USA
- Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA
| | - Kevin L Cox
- Donald Danforth Plant Science Center, St. Louis, MO 63132, USA
| | - Fabio Gomez-Cano
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hilde Nelissen
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Jan U Lohmann
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
| | - Stefania Giacomello
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Solna, Sweden
| | - Olivier C Martin
- Universities of Paris-Saclay, Paris-Cité and Evry, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay, Gif-sur-Yvette 91192, France
| | - Benjamin Cole
- DOE-Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Jia-Wei Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS), Shanghai 200032, China
| | - Kerstin Kaufmann
- Institute of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Michael T Raissig
- Institute of Plant Sciences, University of Bern, 3012 Bern, Switzerland
| | - Gergo Palfalvi
- Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany
| | - Thomas Greb
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
| | - Marc Libault
- Division of Plant Science and Technology, Interdisciplinary Plant Group, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65201, USA
| | - Bert De Rybel
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
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Kaur H, Jha P, Ochatt SJ, Kumar V. Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities. Crit Rev Biotechnol 2024; 44:202-217. [PMID: 36775666 DOI: 10.1080/07388551.2023.2165900] [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: 08/07/2022] [Revised: 11/04/2022] [Accepted: 12/08/2022] [Indexed: 02/14/2023]
Abstract
Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.
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Affiliation(s)
- Harmeet Kaur
- Division of Research and Development, Plant Biotechnology Lab, Lovely Professional University, Phagwara, Punjab, India
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
| | - Priyanka Jha
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
- Department of Research Facilitation, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, India
| | - Sergio J Ochatt
- Agroécologie, InstitutAgro Dijon, INRAE, Univ. Bourgogne Franche-Comté, Dijon, France
| | - Vijay Kumar
- Division of Research and Development, Plant Biotechnology Lab, Lovely Professional University, Phagwara, Punjab, India
- Department of Biotechnology, Lovely Faculty of Technology and Sciences, Lovely Professional University, Phagwara, Punjab, India
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30
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Ali M, Yang T, He H, Zhang Y. Plant biotechnology research with single-cell transcriptome: recent advancements and prospects. PLANT CELL REPORTS 2024; 43:75. [PMID: 38381195 DOI: 10.1007/s00299-024-03168-0] [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: 09/12/2023] [Accepted: 02/05/2024] [Indexed: 02/22/2024]
Abstract
KEY MESSAGE Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.
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Affiliation(s)
- Muhammad Ali
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
- Peking University-Institute of Advanced Agricultural Sciences, Weifang, China
| | - Tianxia Yang
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
- State Key Laboratory of Maize Bio-breeding, National Maize Improvement Center, Frontiers Science Center for Molecular Design Breeding (MOE), China Agricultural University, Beijing, China
| | - Hai He
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China
| | - Yu Zhang
- School of Agriculture, Sun Yat-Sen University, Shenzhen, 518107, China.
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31
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Bawa G, Liu Z, Yu X, Tran LSP, Sun X. Introducing single cell stereo-sequencing technology to transform the plant transcriptome landscape. TRENDS IN PLANT SCIENCE 2024; 29:249-265. [PMID: 37914553 DOI: 10.1016/j.tplants.2023.10.002] [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: 11/10/2022] [Revised: 10/01/2023] [Accepted: 10/02/2023] [Indexed: 11/03/2023]
Abstract
Single cell RNA-sequencing (scRNA-seq) advancements have helped detect transcriptional heterogeneities in biological samples. However, scRNA-seq cannot currently provide high-resolution spatial transcriptome information or identify subcellular organs in biological samples. These limitations have led to the development of spatially enhanced-resolution omics-sequencing (Stereo-seq), which combines spatial information with single cell transcriptomics to address the challenges of scRNA-seq alone. In this review, we discuss the advantages of Stereo-seq technology. We anticipate that the application of such an integrated approach in plant research will advance our understanding of biological process in the plant transcriptomics era. We conclude with an outlook of how such integration will enhance crop improvement.
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Affiliation(s)
- George Bawa
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Zhixin Liu
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Xiaole Yu
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China
| | - Lam-Son Phan Tran
- Institute of Genomics for Crop Abiotic Stress Tolerance, Department of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA.
| | - Xuwu Sun
- National Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Key Laboratory of Plant Stress Biology, School of Life Sciences, Henan University, 85 Minglun Street, Kaifeng 475001, PR China.
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32
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Xu Z, Wang W, Yang T, Li L, Ma X, Chen J, Wang J, Huang Y, Gould J, Lu H, Du W, Sahu SK, Yang F, Li Z, Hu Q, Hua C, Hu S, Liu Y, Cai J, You L, Zhang Y, Li Y, Zeng W, Chen A, Wang B, Liu L, Chen F, Ma K, Xu X, Wei X. STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization. Nucleic Acids Res 2024; 52:D1053-D1061. [PMID: 37953328 PMCID: PMC10767841 DOI: 10.1093/nar/gkad933] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/20/2023] [Accepted: 10/10/2023] [Indexed: 11/14/2023] Open
Abstract
Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.
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Affiliation(s)
- Zhicheng Xu
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Weiwen Wang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Tao Yang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Ling Li
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Xizheng Ma
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Jing Chen
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Jieyu Wang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Yan Huang
- BGI Research, Shenzhen 518083, China
| | - Joshua Gould
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Wensi Du
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | | | - Fan Yang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | | | - Qingjiang Hu
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Cong Hua
- BGI Research, Wuhan 430074, China
| | - Shoujie Hu
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Yiqun Liu
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Jia Cai
- BGI Research, Wuhan 430074, China
| | - Lijin You
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | | | | | - Wenjun Zeng
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Ao Chen
- BGI Research, Shenzhen 518083, China
| | - Bo Wang
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | | | | | - Kailong Ma
- China National GeneBank, BGI Research, Shenzhen 518120, China
| | - Xun Xu
- BGI Research, Shenzhen 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI research, Shenzhen 518120, China
| | - Xiaofeng Wei
- China National GeneBank, BGI Research, Shenzhen 518120, China
- Guangdong Provincial Genomics Data Center, BGI research, Shenzhen 518120, China
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33
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Liu H, Guo Z, Gangurde SS, Garg V, Deng Q, Du P, Lu Q, Chitikineni A, Xiao Y, Wang W, Hong Y, Varshney RK, Chen X. A Single-Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves. Adv Biol (Weinh) 2024; 8:e2300410. [PMID: 37828417 DOI: 10.1002/adbi.202300410] [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: 08/09/2023] [Revised: 09/02/2023] [Indexed: 10/14/2023]
Abstract
The peanut is an important worldwide cash-crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single-cell resolution. Here, a single-nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual-cell using fluorescence-activated sorted single-nuclei. In total, 5930 cells with 50 890 expressed genes are classified into 18 cell-clusters, and 5315 chromatin fragments are enriched with 26 083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene-AP2 module in leaf cell differentiation, and cell-cycle analysis demonstrated that genome replication featured in distinct cell-types with circadian rhythms transcription factors (TFs). Furthermore, dual-omics illustrates that the fatty acid pathway modulates epidermal-guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT-hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC-seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.
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Affiliation(s)
- Hao Liu
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Zenhua Guo
- Rice Research Institute of Heilongjiang Academy of Agriculture Sciences, Heilongjiang Province, Jiamusi, 154026, China
| | - Sunil S Gangurde
- USDA-ARS, Crop Genetics and Breeding Research Unit, Department of Plant Pathology, University of Georgia, Tifton, GA, 31793, USA
| | - Vanika Garg
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Quanqing Deng
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Puxuan Du
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Qing Lu
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Annapurna Chitikineni
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Yuan Xiao
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Wenyi Wang
- College of Agriculture, South China Agriculture University, Guangzhou, Guangdong Province, 510642, China
| | - Yanbin Hong
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
| | - Rajeev K Varshney
- State Agricultural Biotechnology Centre, Centre for Crop and Food Innovation, Food Futures Institute, Murdoch University (MU), Murdoch, Western Australia, 6150, Australia
| | - Xiaoping Chen
- Guangdong Provincial Key Laboratory of Crop Genetic Improvement, South China Peanut Sub-Center of National Center of Oilseed Crops Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou, Guangdong Province, 510640, China
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Song YC, Das D, Zhang Y, Chen MX, Fernie AR, Zhu FY, Han J. Proteogenomics-based functional genome research: approaches, applications, and perspectives in plants. Trends Biotechnol 2023; 41:1532-1548. [PMID: 37365082 DOI: 10.1016/j.tibtech.2023.05.010] [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: 03/17/2023] [Revised: 05/17/2023] [Accepted: 05/30/2023] [Indexed: 06/28/2023]
Abstract
Proteogenomics (PG) integrates the proteome with the genome and transcriptome to refine gene models and annotation. Coupled with single-cell (SC) assays, PG effectively distinguishes heterogeneity among cell groups. Affiliating spatial information to PG reveals the high-resolution circuitry within SC atlases. Additionally, PG can investigate dynamic changes in protein-coding genes in plants across growth and development as well as stress and external stimulation, significantly contributing to the functional genome. Here we summarize existing PG research in plants and introduce the technical features of various methods. Combining PG with other omics, such as metabolomics and peptidomics, can offer even deeper insights into gene functions. We argue that the application of PG will represent an important font of foundational knowledge for plants.
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Affiliation(s)
- Yu-Chen Song
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of Tree Genetics and Biotechnology of Educational Department of China, Key Laboratory of State Forestry and Grassland Administration on Subtropical Forest Biodiversity Conservation, College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China; College of Biology and Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Debatosh Das
- College of Agriculture, Food and Natural Resources (CAFNR), Division of Plant Sciences and Technology, 52 Agricultural Building, University of Missouri-Columbia, MO 65201, USA
| | - Youjun Zhang
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| | - Mo-Xian Chen
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of Tree Genetics and Biotechnology of Educational Department of China, Key Laboratory of State Forestry and Grassland Administration on Subtropical Forest Biodiversity Conservation, College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China; College of Biology and Environment, Nanjing Forestry University, Nanjing 210037, China.
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany; Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria.
| | - Fu-Yuan Zhu
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of Tree Genetics and Biotechnology of Educational Department of China, Key Laboratory of State Forestry and Grassland Administration on Subtropical Forest Biodiversity Conservation, College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China; College of Biology and Environment, Nanjing Forestry University, Nanjing 210037, China.
| | - Jiangang Han
- State Key Laboratory of Tree Genetics and Breeding, Co-Innovation Center for Sustainable Forestry in Southern China, Key Laboratory of Tree Genetics and Biotechnology of Educational Department of China, Key Laboratory of State Forestry and Grassland Administration on Subtropical Forest Biodiversity Conservation, College of Life Sciences, Nanjing Forestry University, Nanjing 210037, China; College of Biology and Environment, Nanjing Forestry University, Nanjing 210037, China.
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35
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Nolan TM, Shahan R. Resolving plant development in space and time with single-cell genomics. CURRENT OPINION IN PLANT BIOLOGY 2023; 76:102444. [PMID: 37696725 DOI: 10.1016/j.pbi.2023.102444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 09/13/2023]
Abstract
Single-cell genomics technologies are ushering in a new research era. In this review, we summarize the benefits and current challenges of using these technologies to probe the transcriptional regulation of plant development. In addition to profiling cells at a single snapshot in time, researchers have recently produced time-resolved datasets to map cell responses to stimuli. Live-imaging and spatial transcriptomic techniques are rapidly being adopted to link a cell's transcriptional profile with its spatial location within a tissue. Combining these technologies is a powerful spatiotemporal approach to investigate cell plasticity and developmental responses that contribute to plant resilience. Although there are hurdles to overcome, we conclude by discussing how single-cell genomics is poised to address developmental questions in the coming years.
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Affiliation(s)
- Trevor M Nolan
- Department of Biology, Duke University, Durham, NC 27708, USA; Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA
| | - Rachel Shahan
- Department of Biology, Duke University, Durham, NC 27708, USA; Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA.
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36
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Minow MAA, Marand AP, Schmitz RJ. Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits. Annu Rev Genet 2023; 57:297-319. [PMID: 37562412 PMCID: PMC10775913 DOI: 10.1146/annurev-genet-022123-110824] [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] [Indexed: 08/12/2023]
Abstract
The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.
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Affiliation(s)
- Mark A A Minow
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
| | | | - Robert J Schmitz
- Department of Genetics, University of Georgia, Athens, Georgia, USA;
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37
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Huang T, Guillotin B, Rahni R, Birnbaum KD, Wagner D. A rapid and sensitive, multiplex, whole mount RNA fluorescence in situ hybridization and immunohistochemistry protocol. PLANT METHODS 2023; 19:131. [PMID: 37993896 PMCID: PMC10666358 DOI: 10.1186/s13007-023-01108-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 11/10/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND In the past few years, there has been an explosion in single-cell transcriptomics datasets, yet in vivo confirmation of these datasets is hampered in plants due to lack of robust validation methods. Likewise, modeling of plant development is hampered by paucity of spatial gene expression data. RNA fluorescence in situ hybridization (FISH) enables investigation of gene expression in the context of tissue type. Despite development of FISH methods for plants, easy and reliable whole mount FISH protocols have not yet been reported. RESULTS We adapt a 3-day whole mount RNA-FISH method for plant species based on a combination of prior protocols that employs hybridization chain reaction (HCR), which amplifies the probe signal in an antibody-free manner. Our whole mount HCR RNA-FISH method shows expected spatial signals with low background for gene transcripts with known spatial expression patterns in Arabidopsis inflorescences and monocot roots. It allows simultaneous detection of three transcripts in 3D. We also show that HCR RNA-FISH can be combined with endogenous fluorescent protein detection and with our improved immunohistochemistry (IHC) protocol. CONCLUSIONS The whole mount HCR RNA-FISH and IHC methods allow easy investigation of 3D spatial gene expression patterns in entire plant tissues.
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Affiliation(s)
- Tian Huang
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Bruno Guillotin
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, 10003, USA
| | - Ramin Rahni
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, 10003, USA
| | - Kenneth D Birnbaum
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, NY, 10003, USA
| | - Doris Wagner
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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38
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Hao F, Liu X, Zhou B, Tian Z, Zhou L, Zong H, Qi J, He J, Zhang Y, Zeng P, Li Q, Wang K, Xia K, Guo X, Li L, Shao W, Zhang B, Li S, Yang H, Hui L, Chen W, Peng L, Liu F, Rong ZQ, Peng Y, Zhu W, McCallum JA, Li Z, Xu X, Yang H, Macknight RC, Wang W, Cai J. Chromosome-level genomes of three key Allium crops and their trait evolution. Nat Genet 2023; 55:1976-1986. [PMID: 37932434 DOI: 10.1038/s41588-023-01546-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 09/20/2023] [Indexed: 11/08/2023]
Abstract
Allium crop breeding remains severely hindered due to the lack of high-quality reference genomes. Here we report high-quality chromosome-level genome assemblies for three key Allium crops (Welsh onion, garlic and onion), which are 11.17 Gb, 15.52 Gb and 15.78 Gb in size with the highest recorded contig N50 of 507.27 Mb, 109.82 Mb and 81.66 Mb, respectively. Beyond revealing the genome evolutionary process of Allium species, our pathogen infection experiments and comparative metabolomic and genomic analyses showed that genes encoding enzymes involved in the metabolic pathway of Allium-specific flavor compounds may have evolved from an ancient uncharacterized plant defense system widely existing in many plant lineages but extensively boosted in alliums. Using in situ hybridization and spatial RNA sequencing, we obtained an overview of cell-type categorization and gene expression changes associated with spongy mesophyll cell expansion during onion bulb formation, thus indicating the functional roles of bulb formation genes.
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Affiliation(s)
- Fei Hao
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
- Center of Special Environmental Biomechanics & Biomedical Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi'an, China
| | - Xue Liu
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Botong Zhou
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Zunzhe Tian
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Lina Zhou
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Hang Zong
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Jiyan Qi
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Juan He
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Yongting Zhang
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Peng Zeng
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Qiong Li
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Kai Wang
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Keke Xia
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China
| | - Xing Guo
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China
- BGI Research, Wuhan, China
| | - Li Li
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China
| | - Wenwen Shao
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China
| | | | - Shengkang Li
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China
| | - Haifeng Yang
- Lianyungang Academy of Agricultural Sciences, Lianyungang, China
| | - Linchong Hui
- Lianyungang Academy of Agricultural Sciences, Lianyungang, China
| | - Wei Chen
- Lianyungang Academy of Agricultural Sciences, Lianyungang, China
| | - Lixin Peng
- National Engineering Research Center for Non-Food Biorefinery, Guangxi Academy of Sciences, Nanning, China
| | - Feipeng Liu
- Frontiers Science Center for Flexible Electronics (FSCFE), Shaanxi Institute of Flexible Electronics (SIFE) & Shaanxi Institute of Biomedical Materials and Engineering (SIBME), Northwestern Polytechnical University, Xi'an, China
| | - Zi-Qiang Rong
- Frontiers Science Center for Flexible Electronics (FSCFE), Shaanxi Institute of Flexible Electronics (SIFE) & Shaanxi Institute of Biomedical Materials and Engineering (SIBME), Northwestern Polytechnical University, Xi'an, China
| | - Yingmei Peng
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - Wenbo Zhu
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China
| | - John A McCallum
- The New Zealand Institute for Plant and Food Research, Christchurch, New Zealand
| | - Zhen Li
- Department of Plant Biotechnology and Bioinformatics, Ghent University and VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Xun Xu
- State Key Laboratory of Agricultural Genomics, BGI, Shenzhen, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, China.
| | - Hui Yang
- Center of Special Environmental Biomechanics & Biomedical Engineering, School of Life Sciences, Northwestern Polytechnical University, Xi'an, China.
| | | | - Wen Wang
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China.
| | - Jing Cai
- School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, China.
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Luo X, Yang Y, Lin X, Xiao J. Deciphering spike architecture formation towards yield improvement in wheat. J Genet Genomics 2023; 50:835-845. [PMID: 36907353 DOI: 10.1016/j.jgg.2023.02.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/28/2023] [Accepted: 02/28/2023] [Indexed: 03/12/2023]
Abstract
Wheat is the most widely grown crop globally, providing 20% of the daily consumed calories and protein content around the world. With the growing global population and frequent occurrence of extreme weather caused by climate change, ensuring adequate wheat production is essential for food security. The architecture of the inflorescence plays a crucial role in determining the grain number and size, which is a key trait for improving yield. Recent advances in wheat genomics and gene cloning techniques have improved our understanding of wheat spike development and its applications in breeding practices. Here, we summarize the genetic regulation network governing wheat spike formation, the strategies used for identifying and studying the key factors affecting spike architecture, and the progress made in breeding applications. Additionally, we highlight future directions that will aid in the regulatory mechanistic study of wheat spike determination and targeted breeding for grain yield improvement.
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Affiliation(s)
- Xumei Luo
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiman Yang
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; Nanjing Agricultural University, Nanjing, Jiangsu 210095, China
| | - Xuelei Lin
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Jun Xiao
- Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
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40
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Wong C, Alabadí D, Blázquez MA. Spatial regulation of plant hormone action. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:6089-6103. [PMID: 37401809 PMCID: PMC10575700 DOI: 10.1093/jxb/erad244] [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: 04/04/2023] [Accepted: 06/30/2023] [Indexed: 07/05/2023]
Abstract
Although many plant cell types are capable of producing hormones, and plant hormones can in most cases act in the same cells in which they are produced, they also act as signaling molecules that coordinate physiological responses between different parts of the plant, indicating that their action is subject to spatial regulation. Numerous publications have reported that all levels of plant hormonal pathways, namely metabolism, transport, and perception/signal transduction, can help determine the spatial ranges of hormone action. For example, polar auxin transport or localized auxin biosynthesis contribute to creating a differential hormone accumulation across tissues that is instrumental for specific growth and developmental responses. On the other hand, tissue specificity of cytokinin actions has been proposed to be regulated by mechanisms operating at the signaling stages. Here, we review and discuss current knowledge about the contribution of the three levels mentioned above in providing spatial specificity to plant hormone action. We also explore how new technological developments, such as plant hormone sensors based on FRET (fluorescence resonance energy transfer) or single-cell RNA-seq, can provide an unprecedented level of resolution in defining the spatial domains of plant hormone action and its dynamics.
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Affiliation(s)
- Cynthia Wong
- Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV), 46022-Valencia, Spain
| | - David Alabadí
- Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV), 46022-Valencia, Spain
| | - Miguel A Blázquez
- Instituto de Biología Molecular y Celular de Plantas (CSIC-UPV), 46022-Valencia, Spain
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41
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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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42
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Robertson SM, Wilkins O. Spatially resolved gene regulatory networks in Asian rice (Oryza sativa cv. Nipponbare) leaves. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 116:269-281. [PMID: 37390084 DOI: 10.1111/tpj.16375] [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: 01/27/2023] [Revised: 06/25/2023] [Accepted: 06/28/2023] [Indexed: 07/02/2023]
Abstract
Transcriptome profiles in plants are heterogenous at every level of morphological organization. Even within organs, cells of the same type can have different patterns of gene expression depending on where they are positioned within tissues. This heterogeneity is associated with non-uniform distribution of biological processes within organs. The regulatory mechanisms that establish and sustain the spatial heterogeneity are unknown. Here, we identify regulatory modules that support functional specialization of different parts of Oryza sativa cv. Nipponbare leaves by leveraging transcriptome data, transcription factor binding motifs and global gene regulatory network prediction algorithms. We generated a global gene regulatory network in which we identified six regulatory modules that were active in different parts of the leaf. The regulatory modules were enriched for genes involved in spatially relevant biological processes, such as cell wall deposition, environmental sensing and photosynthesis. Strikingly, more than 86.9% of genes in the network were regulated by members of only five transcription factor families. We also generated targeted regulatory networks for the large MYB and bZIP/bHLH families to identify interactions that were masked in the global prediction. This analysis will provide a baseline for future single cell and array-based spatial transcriptome studies and for studying responses to environmental stress and demonstrates the extent to which seven coarse spatial transcriptome analysis can provide insight into the regulatory mechanisms supporting functional specialization within leaves.
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Affiliation(s)
- Sean M Robertson
- Department of Biological Sciences, University of Manitoba, 50 Sifton Road, Winnipeg, R3T 2N2, Canada
| | - Olivia Wilkins
- Department of Biological Sciences, University of Manitoba, 50 Sifton Road, Winnipeg, R3T 2N2, Canada
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43
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Yuan Z, Yao J. Harnessing computational spatial omics to explore the spatial biology intricacies. Semin Cancer Biol 2023; 95:25-41. [PMID: 37400044 DOI: 10.1016/j.semcancer.2023.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 05/09/2023] [Accepted: 06/19/2023] [Indexed: 07/05/2023]
Abstract
Spatially resolved transcriptomics (SRT) has unlocked new dimensions in our understanding of intricate tissue architectures. However, this rapidly expanding field produces a wealth of diverse and voluminous data, necessitating the evolution of sophisticated computational strategies to unravel inherent patterns. Two distinct methodologies, gene spatial pattern recognition (GSPR) and tissue spatial pattern recognition (TSPR), have emerged as vital tools in this process. GSPR methodologies are designed to identify and classify genes exhibiting noteworthy spatial patterns, while TSPR strategies aim to understand intercellular interactions and recognize tissue domains with molecular and spatial coherence. In this review, we provide a comprehensive exploration of SRT, highlighting crucial data modalities and resources that are instrumental for the development of methods and biological insights. We address the complexities and challenges posed by the use of heterogeneous data in developing GSPR and TSPR methodologies and propose an optimal workflow for both. We delve into the latest advancements in GSPR and TSPR, examining their interrelationships. Lastly, we peer into the future, envisaging the potential directions and perspectives in this dynamic field.
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Affiliation(s)
- Zhiyuan Yuan
- Center for Medical Research and Innovation, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
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44
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Oliva M, Lister R. Exploring the identity of individual plant cells in space and time. THE NEW PHYTOLOGIST 2023; 240:61-67. [PMID: 37483019 PMCID: PMC10952157 DOI: 10.1111/nph.19153] [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: 02/02/2023] [Accepted: 06/17/2023] [Indexed: 07/25/2023]
Abstract
In recent years, single-cell genomics, coupled to imaging techniques, have become the state-of-the-art approach for characterising biological systems. In plant sciences, a variety of tissues and species have been profiled, providing an enormous quantity of data on cell identity at an unprecedented resolution, but what biological insights can be gained from such data sets? Using recently published studies in plant sciences, we will highlight how single-cell technologies have enabled a better comprehension of tissue organisation, cell fate dynamics in development or in response to various stimuli, as well as identifying key transcriptional regulators of cell identity. We discuss the limitations and technical hurdles to overcome, as well as future directions, and the promising use of single-cell omics to understand, predict, and manipulate plant development and physiology.
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Affiliation(s)
- Marina Oliva
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular SciencesUniversity of Western AustraliaPerthWA6009Australia
| | - Ryan Lister
- ARC Centre of Excellence in Plant Energy Biology, School of Molecular SciencesUniversity of Western AustraliaPerthWA6009Australia
- The Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical ResearchThe University of Western AustraliaPerthWA6009Australia
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45
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Zhang J, Ahmad M, Gao H. Application of single-cell multi-omics approaches in horticulture research. MOLECULAR HORTICULTURE 2023; 3:18. [PMID: 37789394 PMCID: PMC10521458 DOI: 10.1186/s43897-023-00067-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023]
Abstract
Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.
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Affiliation(s)
- Jun Zhang
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Mayra Ahmad
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hongbo Gao
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
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46
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Liu S, Zenda T, Tian Z, Huang Z. Metabolic pathways engineering for drought or/and heat tolerance in cereals. FRONTIERS IN PLANT SCIENCE 2023; 14:1111875. [PMID: 37810398 PMCID: PMC10557149 DOI: 10.3389/fpls.2023.1111875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 09/04/2023] [Indexed: 10/10/2023]
Abstract
Drought (D) and heat (H) are the two major abiotic stresses hindering cereal crop growth and productivity, either singly or in combination (D/+H), by imposing various negative impacts on plant physiological and biochemical processes. Consequently, this decreases overall cereal crop production and impacts global food availability and human nutrition. To achieve global food and nutrition security vis-a-vis global climate change, deployment of new strategies for enhancing crop D/+H stress tolerance and higher nutritive value in cereals is imperative. This depends on first gaining a mechanistic understanding of the mechanisms underlying D/+H stress response. Meanwhile, functional genomics has revealed several stress-related genes that have been successfully used in target-gene approach to generate stress-tolerant cultivars and sustain crop productivity over the past decades. However, the fast-changing climate, coupled with the complexity and multigenic nature of D/+H tolerance suggest that single-gene/trait targeting may not suffice in improving such traits. Hence, in this review-cum-perspective, we advance that targeted multiple-gene or metabolic pathway manipulation could represent the most effective approach for improving D/+H stress tolerance. First, we highlight the impact of D/+H stress on cereal crops, and the elaborate plant physiological and molecular responses. We then discuss how key primary metabolism- and secondary metabolism-related metabolic pathways, including carbon metabolism, starch metabolism, phenylpropanoid biosynthesis, γ-aminobutyric acid (GABA) biosynthesis, and phytohormone biosynthesis and signaling can be modified using modern molecular biotechnology approaches such as CRISPR-Cas9 system and synthetic biology (Synbio) to enhance D/+H tolerance in cereal crops. Understandably, several bottlenecks hinder metabolic pathway modification, including those related to feedback regulation, gene functional annotation, complex crosstalk between pathways, and metabolomics data and spatiotemporal gene expressions analyses. Nonetheless, recent advances in molecular biotechnology, genome-editing, single-cell metabolomics, and data annotation and analysis approaches, when integrated, offer unprecedented opportunities for pathway engineering for enhancing crop D/+H stress tolerance and improved yield. Especially, Synbio-based strategies will accelerate the development of climate resilient and nutrient-dense cereals, critical for achieving global food security and combating malnutrition.
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Affiliation(s)
- Songtao Liu
- Hebei Key Laboratory of Quality & Safety Analysis-Testing for Agro-Products and Food, Hebei North University, Zhangjiakou, China
| | - Tinashe Zenda
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding, China
| | - Zaimin Tian
- Hebei Key Laboratory of Quality & Safety Analysis-Testing for Agro-Products and Food, Hebei North University, Zhangjiakou, China
| | - Zhihong Huang
- Hebei Key Laboratory of Quality & Safety Analysis-Testing for Agro-Products and Food, Hebei North University, Zhangjiakou, China
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47
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Jing K, Xu Y, Yang Y, Yin P, Ning D, Huang G, Deng Y, Chen G, Li G, Tian SZ, Zheng M. ScSmOP: a universal computational pipeline for single-cell single-molecule multiomics data analysis. Brief Bioinform 2023; 24:bbad343. [PMID: 37779245 DOI: 10.1093/bib/bbad343] [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: 04/27/2023] [Revised: 06/24/2023] [Accepted: 09/10/2023] [Indexed: 10/03/2023] Open
Abstract
Single-cell multiomics techniques have been widely applied to detect the key signature of cells. These methods have achieved a single-molecule resolution and can even reveal spatial localization. These emerging methods provide insights elucidating the features of genomic, epigenomic and transcriptomic heterogeneity in individual cells. However, they have given rise to new computational challenges in data processing. Here, we describe Single-cell Single-molecule multiple Omics Pipeline (ScSmOP), a universal pipeline for barcode-indexed single-cell single-molecule multiomics data analysis. Essentially, the C language is utilized in ScSmOP to set up spaced-seed hash table-based algorithms for barcode identification according to ligation-based barcoding data and synthesis-based barcoding data, followed by data mapping and deconvolution. We demonstrate high reproducibility of data processing between ScSmOP and published pipelines in comprehensive analyses of single-cell omics data (scRNA-seq, scATAC-seq, scARC-seq), single-molecule chromatin interaction data (ChIA-Drop, SPRITE, RD-SPRITE), single-cell single-molecule chromatin interaction data (scSPRITE) and spatial transcriptomic data from various cell types and species. Additionally, ScSmOP shows more rapid performance and is a versatile, efficient, easy-to-use and robust pipeline for single-cell single-molecule multiomics data analysis.
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Affiliation(s)
- Kai Jing
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yewen Xu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yang Yang
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Pengfei Yin
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Duo Ning
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Guangyu Huang
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yuqing Deng
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Gengzhan Chen
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
- Agricultural Bioinformatics Key Laboratory of Hubei Province, Hubei Engineering Technology Research Center of Agricultural Big Data, 3D Genomics Research Center, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Simon Zhongyuan Tian
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
| | - Meizhen Zheng
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China
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48
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Song X, Guo P, Xia K, Wang M, Liu Y, Chen L, Zhang J, Xu M, Liu N, Yue Z, Xu X, Gu Y, Li G, Liu M, Fang L, Deng XW, Li B. Spatial transcriptomics reveals light-induced chlorenchyma cells involved in promoting shoot regeneration in tomato callus. Proc Natl Acad Sci U S A 2023; 120:e2310163120. [PMID: 37703282 PMCID: PMC10515167 DOI: 10.1073/pnas.2310163120] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 08/09/2023] [Indexed: 09/15/2023] Open
Abstract
Callus is a reprogrammed cell mass involved in plant regeneration and gene transformation in crop engineering. Pluripotent callus cells develop into fertile shoots through shoot regeneration. The molecular basis of the shoot regeneration process in crop callus remains largely elusive. This study pioneers the exploration of the spatial transcriptome of tomato callus during shoot regeneration. The findings reveal the presence of highly heterogeneous cell populations within the callus, including epidermis, vascular tissue, shoot primordia, inner callus, and outgrowth shoots. By characterizing the spatially resolved molecular features of shoot primordia and surrounding cells, specific factors essential for shoot primordia formation are identified. Notably, chlorenchyma cells, enriched in photosynthesis-related processes, play a crucial role in promoting shoot primordia formation and subsequent shoot regeneration. Light is shown to promote shoot regeneration by inducing chlorenchyma cell development and coordinating sugar signaling. These findings significantly advance our understanding of the cellular and molecular aspects of shoot regeneration in tomato callus and demonstrate the immense potential of spatial transcriptomics in plant biology.
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Affiliation(s)
- Xiehai Song
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Pengru Guo
- Beijing Genomics Institute Research, Beijing102601, China
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Keke Xia
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Meiling Wang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Yongqi Liu
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Lichuan Chen
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Jinhui Zhang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Mengyuan Xu
- Beijing Genomics Institute Research, Beijing102601, China
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Naixu Liu
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Zhiliang Yue
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Xun Xu
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Ying Gu
- Beijing Genomics Institute Research, Shenzhen518083, China
| | - Gang Li
- State Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University, Tai'an, Shandong271018, China
| | - Min Liu
- Baimaike Intelligent Manufacturing, Qingdao, Shandong266500, China
| | - Liang Fang
- Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, Guangdong518005, China
| | - Xing Wang Deng
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
| | - Bosheng Li
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong261325, China
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Li R, Wang Z, Wang JW, Li L. Combining single-cell RNA sequencing with spatial transcriptome analysis reveals dynamic molecular maps of cambium differentiation in the primary and secondary growth of trees. PLANT COMMUNICATIONS 2023; 4:100665. [PMID: 37491818 PMCID: PMC10504605 DOI: 10.1016/j.xplc.2023.100665] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/04/2023] [Accepted: 07/24/2023] [Indexed: 07/27/2023]
Abstract
Primary and secondary growth of the tree stem are responsible for corresponding increases in trunk height and diameter. However, our molecular understanding of the biological processes that underlie these two types of growth is incomplete. In this study, we used single-cell RNA sequencing and spatial transcriptome sequencing to reveal the transcriptional landscapes of primary and secondary growth tissues in the Populus stem. Comparison between the cell atlas and differentiation trajectory of primary and secondary growth revealed different regulatory networks involved in cell differentiation from cambium to xylem precursors and phloem precursors. These regulatory networks may be controlled by auxin accumulation and distribution. Analysis of cell differentiation trajectories suggested that vessel and fiber development followed a sequential pattern of progressive transcriptional regulation. This research provides new insights into the processes of cell identity and differentiation that occur throughout primary and secondary growth of tree stems, increasing our understanding of the cellular differentiation dynamics that occur during stem growth in trees.
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Affiliation(s)
- Renhui Li
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Zhifeng Wang
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Jia-Wei Wang
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Laigeng Li
- National Key Laboratory of Plant Molecular Genetics and CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China.
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Tu W, Ling G, Liu F, Hu F, Song X. GCSTI: A Single-Cell Pseudotemporal Trajectory Inference Method Based on Graph Compression. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:2945-2958. [PMID: 37037234 DOI: 10.1109/tcbb.2023.3266109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The single-cell pseudotemporal trajectory inference is an important way to explore the process of developmental changes within a cell. Due to the uneven rate of cell growth, changes in gene expression depend less on the time of data collection and more on a cell's "internal clock". To overcome the challenges of gene analysis, and replicate biological developmental processes, several strategies have been put forth. However, due to the size of single-cell datasets, locating relevant signposts usually necessitate clustering analysis or a sizable amount of priori information. To this end, we propose a novel single-cell pseudotemporal trajectory inference technique: GCSTI method, which is based on graph compression and doesn't rely on a priori knowledge or clustering procedures, can handle the trajectory inference problem for a large network in a stable and efficient manner. Additionally, we simultaneously improve the pseudotime defining method currently employed in this study in order to obtain more trustworthy and beneficial outcomes for trajectory inference. Finally, we validate the efficacy and stability of the GCSTI method using datasets from human skeletal muscle myogenic cells and four simulated datasets.
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