Spatiotemporal Developmental Trajectories in the Arabidopsis Root Revealed Using High-Throughput Single Cell RNA Sequencing

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.

本数据集为拟南芥（Arabidopsis thaliana）根部的单细胞RNA测序（single cell RNA sequencing, scRNA-seq）图谱，可依据细胞发育命运与发育时间对细胞进行区分，揭示了核心基因表达特征：该特征刻画了从干细胞至终末分化状态的复杂发育级联过程，该过程由转录因子的镜像式表达波动所支撑。

方法：通过Illumina NextSeq测序平台，对6日龄野生型（wild-type, WT）及短根敲除（shortroot-knockout, shr-3）拟南芥根部样本进行深度测序，构建单细胞（全部样本）与批量RNA文库（仅野生型样本）：其中批量文库与野生型单细胞文库设置2次生物学重复，shr-3样本仅开展单次生物学重复。对通过质量控制过滤的测序reads进行转录本层面分析。单细胞文库采用Cell Ranger、STAR、Seurat工具完成处理与分析；批量文库则采用Trimmomatic、STAR、HTSeq及DESeq2工具进行处理。

结果：针对单细胞测序数据——通过优化后的数据分析流程，我们将每个野生型细胞的约8.7万条测序reads比对至拟南芥参考基因组TAIR10，最终每个细胞可检测到的基因数与转录本数的中位数分别为4276与14758。野生型细胞中共检测到16975个基因的转录本（每百万转录本读数Reads Per Million, RPM≥1）。经测序深度校正后，该检测覆盖度约为原生质体化根部组织批量RNA-seq所检测基因总数的90%。批量RNA-seq数据鉴定出拟南芥根部原生质体分离诱导的基因，此类基因可在单细胞分析中予以排除。合并后的scRNA-seq与批量RNA-seq全局基因表达谱相关性极高（Pearson相关系数r=0.9），表明植物单细胞RNA测序具有极高的灵敏度。

结论：本研究构建的高分辨率拟南芥根部单细胞RNA测序图谱，可捕获所有主要细胞类型的精准时间信息，揭示了全新的调控因子及各细胞类型的核心特征。基于拟时间分析得到的发育轨迹，刻画了从干细胞至终末分化状态的精细解析发育级联过程，该过程同样由转录因子的镜像式表达波动所支撑。