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Single-cell RNA-sequencing analysis of Arabidopsis roots

ABSTRACT: We report the use of high-throughput single-cell RNA sequencing (scRNA-seq) to analyze gene expression in wild-type and mutant Arabidopsis root cells. We demonstrate that using a commercially available platform for droplet-based scRNA-seq (10X Genomics Chromium) enables transcriptional profiling of individual protoplasts representing all of the major cell/tissue types of the root. Furthermore, rare cell types and subtypes have been identified. These single-cell transcriptomes were also used to generate a pseudotime series for the root hair and non-hair cell differentiation pathways. In addition, scRNA-seq was used to define and compare transcriptomes from root epidermis mutants, which enabled a detailed molecular analysis of the mutant phenotype. This study demonstrates the feasibility and usefulness of scRNA-seq in plants and provides a gene expression map at single-cell resolution for the Arabidopsis root.

ORGANISM(S): Arabidopsis thaliana

PROVIDER: GSE123013 | GEO | 2019/02/05

REPOSITORIES: GEO

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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.

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Single-cell RNA-sequencing analysis of Arabidopsis roots

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