Single-cell RNA-seq data of Arabidopsis root
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA640389 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12046100.fastq.gz | Fastqsanger.gz | |||
| SRR12046101.fastq.gz | Fastqsanger.gz | |||
| SRR12046102.fastq.gz | Fastqsanger.gz | |||
| SRR12046103.fastq.gz | Fastqsanger.gz | |||
| SRR12046104.fastq.gz | Fastqsanger.gz |
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Project description:We report both raw and processed scRNA-seq data that are used to build transcriptomic atlas of Arabidopsis root.
2020-07-02 | GSE152766 | GEO
Project description:Here we explore the feasibility of single-cell proteomics on plant samples. We focus on Arabidopsis thaliana, examining isolated single cells from the cortex and endodermis, which are two adjacent root cell-types derived from a common stem cell.
2024-04-17 | MSV000094558 | MassIVE
Project description:A single cell RNA sequencing atlas of the Arabidopsis root distinguishes cells both by developmental fate and time, revealing defining expression features that depict a complex cascade of developmental progressions from stem cell through differentiation supported by mirroring waves of transcription factor expression. Methods: mRNA profiles of 6-day-old wild-type (WT) and shortroot-knockout Arabidopsis thaliana roots were generated by deep sequencing of single cell (all) and bulk RNA libraries (wild type only), in duplicate (bulk & wild-type single cell) and singlicate (shr-3), using Illumina NextSeq. The sequence reads that passed quality filters were analyzed at the transcript level. Single Cell libraries were processed and analysed using Cell Ranger, STAR, Seurat. Bulk libraries were processed using Trimmomatic, STAR, HTSeq and DEseq2. Results: For Single Cell - Using an optimized data analysis workflow, we mapped ~87k sequence reads per wild-type cell to the Arabidopsis genome (TAIR10) and identified a median of 4,276 genes and 14,758 transcripts per cell. In total, transcripts for 16,975 genes were detected (RPM ≥1) from wild-type cells. After correction for read depth, this represents ~90% of genes detected by bulk RNA-seq of protoplasted root tissue. Bulk RNA-seq data identified genes induced by protplasting of the Arabidopsis root which could be discounted from single cell analysis. The global gene expression profiles of pooled scRNA-seq and bulk RNA-seq are highly correlated (r = 0.9) indicating that plant scRNA-seq is highly sensitive. Conclusions: Our high-resolution single cell RNA sequencing atlas of the Arabidopsis root captures precise temporal information for all major cell types, revealing new regulators and defining features foreach. Developmental trajectories derived from pseudotime analysis depict a finely resolved cascade of developmental progressions between stem cell and final differentiation supported by mirroring waves of transcription factor expression.
2019-03-25 | GSE123818 | GEO
Project description:The definition of cell identity is a central problem in biology. Single-cell RNA-seq provides a wealth of information regarding the developmental state of individual cells. However, better methods are needed to map the identity of single cells, especially during identity transitions. We have developed a quantitative classification method that is robust to expression noise and can detect primary and chimeric identities from single-cell RNA sequencing profiles. The method uses existing transcriptome repositories of grouped cell-types to define a set of optimal cell-identity markers, which are then used to define a cell identity metric. This metric accurately classified diverse cell identities in Arabidopsis root tips and human glioblastoma cells. We demonstrate the strength of the approach to resolve a dynamic developmental process by analyzing the identity of single cells captured from regenerating Arabidopsis roots following removal of their stem-cell-niche. We discover that, apart from new niche formation at the vicinity of the cut site, cells that are distant from the injury site also undergo a transient, partial collapse of identity during the regeneration and reorganization of the root, demonstrating the usefulness of a quantitative cell identity metric. Overall design: 4 Technical replicates (pooled-and-split single QC cells), 23 cells from the QC, 3 cells from the Stele, and 4 cells from the stele, 16h following root tip decapitation
2015-03-12 | E-MTAB-4125 | biostudies-arrayexpress
Project description:The root epidermis of Arabidopsis provides a simple and experimentally useful model for studying the molecular basis of cell fate and differentiation. The goal of this study was to define the transcript changes in the root epidermis of mutants associated with root epidermis cell specification, including mutants that lack a visible phenotypic alteration (try, egl3, myb23, and ttg2). Transcript levels were assessed by purifying populations of root epidermal cells using fluorescence-based cell-sorting with the WER::GFP transgene. These microarray results were used to compare the effects of single and double mutants on the gene regulatory network that controls root epidermal cell fate and differentiation in Arabidopsis.
2013-11-21 | GSE47632 | GEO
Project description:We report both raw and processed scRNA-seq data that were used to construct a reference atlas of the cell cycle in the Arabidopsis root and profile opsopl2 mutant roots.
2025-01-26 | GSE262840 | GEO
Project description:The root epidermis of Arabidopsis provides a simple and experimentally useful model for studying the molecular basis of cell fate and differentiation. The goal of this study was to define the larger gene regulatory network that governs the differentiation of the root hair and non-hair cell types of the Arabidopsis root epidermis. Transcript levels in the root epidermis of wild-type and mutant lines were assessed by purifying populations of root epidermal cells using fluorescence-based cell-sorting. Further, the role of the plant hormones auxin and ethylene on root epidermis development was assessed by defining transcript levels in the root epidermis of plants grown on media containing IAA or ACC. These microarray results were used to construct a comprehensive gene regulatory network that depicts the transcriptional control of root epidermal cell fate and differentiation in Arabidopsis.
2011-12-01 | GSE30547 | GEO
Project description:The nuclei of Arabidopsis root seedlings were isolated then use to establish a single cell level resolution transcriptome (sNucRNA-seq) and profile of chromatin accessibility (sNucATAC-seq) applying 10X Genomics technologies.
2021-01-11 | GSE155304 | GEO
Project description:The definition of cell identity is a central problem in biology. Single-cell RNA-seq provides a wealth of information regarding the developmental state of individual cells. However, better methods are needed to map the identity of single cells, especially during identity transitions. We have developed a quantitative classification method that is robust to expression noise and can detect primary and chimeric identities from single-cell RNA sequencing profiles. The method uses existing transcriptome repositories of grouped cell-types to define a set of optimal cell-identity markers, which are then used to define a cell identity metric. This metric accurately classified diverse cell identities in Arabidopsis root tips and human glioblastoma cells. We demonstrate the strength of the approach to resolve a dynamic developmental process by analyzing the identity of single cells captured from regenerating Arabidopsis roots following removal of their stem-cell-niche. We discover that, apart from new niche formation at the vicinity of the cut site, cells that are distant from the injury site also undergo a transient, partial collapse of identity during the regeneration and reorganization of the root, demonstrating the usefulness of a quantitative cell identity metric.
2014-12-30 | GSE46226 | GEO
Project description:There are two main types of root systems in flowering plants, which are taproot systems in dicot and fibrous root systems in monocot. The cellular and molecular mechanism involved in root development are mainly from the study of dicot model Arabidopsis thaliana. However, mechanisms of root development and their conservation and divergence in monocot, which including the major crops, remain largely elusive. Here we profile the transcriptomes of more than 20,000 single cells in the root tips of two rice cultivars, Nipponbare (Nip; Japonica) and 93-11 (Indica). Single-cell analysis coupled with in situ hybridization identify the cell type-specific marker genes and annotate all the clusters. Comparison of single-cell transcriptome and analysis of mark gene expression suggest well-conserved molecular landscape between rice Nip and 93-11. Moreover, our analysis suggests specific functions gene expression patterns for each cell type cluster, including the hormone genes. Comparison to Arabidopsis single-cell RNA-sequencing dataset reveals extensive differences between Arabidopsis and rice cell types, and species-specific features emphasize the importance of directly studying rice root. Our study reveals transcriptome landscape of major cell types of rice root in singe-cell resolution and provides molecular insight of the cell type morphology of cell type evolution in plants.
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