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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:S1534-5807(24)00334-4. [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] [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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Song J, Fan B, Shao X, Zang Y, Wang D, Min Y. Single-cell transcriptome sequencing atlas of cassava tuberous root. FRONTIERS IN PLANT SCIENCE 2023; 13:1053669. [PMID: 36684718 PMCID: PMC9848496 DOI: 10.3389/fpls.2022.1053669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
INTRODUCTION Single-cell transcriptome sequencing (ScRNA-seq) has emerged as an effective method for examining cell differentiation and development. In non-model plants, it hasn't been employed very much, especially in sink organs that are abundant in secondary metabolites. RESULTS In this study, we sequenced the single-cell transcriptomes at two developmental phases of cassava tuberous roots using the technology known as 10x Genomics (S1, S2). In total, 14,566 cells were grouped into 15 different cell types, primarily based on the marker genes of model plants known to exist. In the pseudotime study, the cell differentiation trajectory was defined, and the difference in gene expression between the two stages on the pseudotime axis was compared. The differentiation process of the vascular tissue and cerebral tissue was identified by the trajectory. We discovered the rare cell type known as the casparian strip via the use of up-regulated genes and pseudotime analysis, and we explained how it differentiates from endodermis. The successful creation of a protoplast isolation technique for organs rich in starch was also described in our study. DISCUSSION Together, we created the first high-resolution single-cell transcriptome atlas of cassava tuberous roots, which made significant advancements in our understanding of how these roots differentiate and develop.
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Affiliation(s)
- Jinjia Song
- Department of Biotechnology, School of Life Sciences, Hainan University, Haikou, Hainan, China
| | - Benji Fan
- Department of Biotechnology, School of Life Sciences, Hainan University, Haikou, Hainan, China
| | - Xiaodie Shao
- Department of Biotechnology, School of Life Sciences, Hainan University, Haikou, Hainan, China
| | - Yuwei Zang
- Department of Biotechnology, School of Life Sciences, Hainan University, Haikou, Hainan, China
| | - Dayong Wang
- Laboratory of Biopharmaceuticals and Molecular Pharmacology, School of Pharmaceutical Sciences, Hainan University, Haikou, Hainan, China
| | - Yi Min
- Department of Biotechnology, School of Life Sciences, Hainan University, Haikou, Hainan, China
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Guk J, Jang M, Choi J, Lee YM, Kim S. De novo phasing resolves haplotype sequences in complex plant genomes. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1031-1041. [PMID: 35332665 PMCID: PMC9129073 DOI: 10.1111/pbi.13815] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 02/07/2022] [Accepted: 03/20/2022] [Indexed: 05/12/2023]
Abstract
Genome phasing is a recently developed assembly method that separates heterozygous eukaryotic genomic regions and builds haplotype-resolved assemblies. Because differences between haplotypes are ignored in most published de novo genomes, assemblies are available as consensus genomes consisting of haplotype mixtures, thus increasing the need for genome phasing. Here, we review the operating principles and characteristics of several freely available and widely used phasing tools (TrioCanu, FALCON-Phase, and ALLHiC). An examination of downstream analyses using haplotype-resolved genome assemblies in plants indicated significant differences among haplotypes regarding chromosomal rearrangements, sequence insertions, and expression of specific alleles that contribute to the acquisition of the biological characteristics of plant species. Finally, we suggest directions to solve addressing limitations of current genome-phasing methods. This review provides insights into the current progress, limitations, and future directions of de novo genome phasing, which will enable researchers to easily access and utilize genome-phasing in studies involving highly heterozygous complex plant genomes.
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Affiliation(s)
- Ji‐Yoon Guk
- Department of Environmental HorticultureUniversity of SeoulSeoulKorea
| | - Min‐Jeong Jang
- Department of Environmental HorticultureUniversity of SeoulSeoulKorea
| | - Jin‐Wook Choi
- Department of Environmental HorticultureUniversity of SeoulSeoulKorea
| | - Yeon Mi Lee
- Department of Environmental HorticultureUniversity of SeoulSeoulKorea
| | - Seungill Kim
- Department of Environmental HorticultureUniversity of SeoulSeoulKorea
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Hatori MN, Modavi C, Xu P, Weisgerber D, Abate AR. Dual-layered hydrogels allow complete genome recovery with nucleic acid cytometry. Biotechnol J 2022; 17:e2100483. [PMID: 35088927 PMCID: PMC9208836 DOI: 10.1002/biot.202100483] [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: 09/06/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/09/2022]
Abstract
Targeting specific cells for sequencing is important for applications in cancer, microbiology, and infectious disease. Nucleic acid cytometry is a powerful approach for accomplishing this because it allows specific cells to be isolated based on sequence biomarkers that are otherwise impossible to detect. However, existing methods require specialized microfluidic devices, limiting adoption. Here, we describe a modified workflow that uses particle-templated emulsification and flow cytometry to conduct the essential steps of cell detection and sorting normally accomplished by microfluidics. Our microfluidic-free workflow allows facile isolation and sequencing of cells, viruses, and nucleic acids and thus provides a powerful enrichment approach for targeted sequencing applications. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Makiko N Hatori
- Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA
| | - Cyrus Modavi
- Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA
| | - Peng Xu
- Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA
| | - Daniel Weisgerber
- Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA
| | - Adam R Abate
- Department of Bioengineering and Therapeutic Sciences, California Institute for Quantitative Biosciences, University of California, San Francisco, CA, 94158, USA.,Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA
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Shojaee A, Saavedra M, Huang SSC. Potentials of single-cell genomics in deciphering cellular phenotypes. CURRENT OPINION IN PLANT BIOLOGY 2021; 63:102059. [PMID: 34116424 PMCID: PMC8545747 DOI: 10.1016/j.pbi.2021.102059] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/26/2021] [Accepted: 04/25/2021] [Indexed: 06/05/2023]
Abstract
Single-cell genomics, particularly single-cell transcriptome profiling by RNA sequencing have transformed the possibilities to relate genes to functions, structures, and eventually phenotypes. We can now observe changes in each cell's transcriptome and among its neighborhoods, interrogate the sequence of transcriptional events, and assess their influence on subsequent events. This paradigm shift in biology enables us to infer causal relationships in these events with high accuracy. Here we review the latest single-cell studies in plants that uncover how cellular phenotypes emerge as a result of the transcriptome process such as waves of expression, trajectories of development and responses to the environment, and spatial information. With an eye on the advances made in animal and human studies, we further highlight some of the needed areas for future research and development, including computational methods.
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Affiliation(s)
- Abbas Shojaee
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States
| | - Michelle Saavedra
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States
| | - Shao-Shan Carol Huang
- Center for Genomics and Systems Biology, Department of Biology, New York University, 12 Waverly Pl, New York, NY 10003, United States.
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Dorado G, Gálvez S, Rosales TE, Vásquez VF, Hernández P. Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review. Biomolecules 2021; 11:1111. [PMID: 34439777 PMCID: PMC8393538 DOI: 10.3390/biom11081111] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/12/2021] [Accepted: 07/23/2021] [Indexed: 02/06/2023] Open
Abstract
Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.
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Affiliation(s)
- Gabriel Dorado
- Dep. Bioquímica y Biología Molecular, Campus Rabanales C6-1-E17, Campus de Excelencia Internacional Agroalimentario (ceiA3), Universidad de Córdoba, 14071 Córdoba, Spain
| | - Sergio Gálvez
- Dep. Lenguajes y Ciencias de la Computación, Boulevard Louis Pasteur 35, Universidad de Málaga, 29071 Málaga, Spain;
| | - Teresa E. Rosales
- Laboratorio de Arqueobiología, Avda. Universitaria s/n, Universidad Nacional de Trujillo, 13011 Trujillo, Peru;
| | - Víctor F. Vásquez
- Centro de Investigaciones Arqueobiológicas y Paleoecológicas Andinas Arqueobios, Martínez de Companón 430-Bajo 100, Urbanización San Andres, 13088 Trujillo, Peru;
| | - Pilar Hernández
- Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo s/n, 14080 Córdoba, Spain;
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Tárnok A. STORM Under the Microscope. Cytometry A 2020; 97:1100-1101. [PMID: 33099863 DOI: 10.1002/cyto.a.24247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 11/11/2022]
Affiliation(s)
- Attila Tárnok
- Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany.,Department of Therapy Validation, Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig, Germany.,Department of Precision Instrument, Tsinghua University, Beijing, China
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