Dataset Information

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

ABSTRACT: In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model for investigating the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single-cell resolution. In addition to estimating developmental progressions in pseudotime, we employed the mathematical concept of optimal transport to infer developmental trajectories and identify their underlying regulators. To demonstrate the utility of the atlas to interpret new datasets, we profiled mutants for two key transcriptional regulators at single-cell resolution, shortroot and scarecrow. We report transcriptomic and in vivo evidence for tissue trans-differentiation underlying a mixed cell identity phenotype in scarecrow. Our results support the atlas as a rich community resource for unraveling the transcriptional programs that specify and maintain cell identity to regulate spatiotemporal organ development.

SUBMITTER: Shahan R

PROVIDER: S-EPMC9014886 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

Shahan Rachel R Hsu Che-Wei CW Nolan Trevor M TM Cole Benjamin J BJ Taylor Isaiah W IW Greenstreet Laura L Zhang Stephen S Afanassiev Anton A Vlot Anna Hendrika Cornelia AHC Schiebinger Geoffrey G Benfey Philip N PN Ohler Uwe U

Developmental cell 20220207 4

In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model for investigating the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single-cell resolution. In addition to estimating developmental progressions in pseudotime, ...[more]

PMID: 35134336

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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.

Dataset Information

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

Publications

A single-cell Arabidopsis root atlas reveals developmental trajectories in wild-type and cell identity mutants.

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