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发表单位：加州大学戴维斯分校
发表日期：2023年6月20日
期 刊：Cell Reports（IF:8.8）
2023年6月20日加州大学戴维斯分校Gitta Coaker研究团队在期刊Cell Reports（IF:8.8）发表了题为“Single-cell profiling of Arabidopsis leaves to Pseudomonas syringae infection”的研究论文。作者以单细胞测序技术分析了植物对假单胞菌感染的反应，鉴定到叶肉处于免疫和易感两种对立状态的细胞群。整篇文章看下来逻辑顺畅，分析和实验穿插验证，看论文过程中的一些疑问也基本得到了解答。
背景
植物免疫响应异质性
病原体可以从不同的器官或组织（根，茎，叶，果实等）侵染植物产生不同的症状。即使在同一植物组织中， 我们也经常观察到不均一的病害症状。病原体在植物表面的不均匀分布，侵染的不同步性以及植物的免疫反应等都会影响病害症状的发展。传统的植物-病原体相互作用研究主要依赖于整体组织（即整叶或整根）的测定，这极大的提高了我们对植物免疫反应的理解。然而，植物-病原体相互作用的高度动态化的过程却难以体现出来，例如不同细胞类型和亚群之间的功能和基因表达差异，从而影响了我们对植物细胞反应异质性的理解。
单细胞测序解析细胞异质性
单细胞RNA测序（scRNA-seq）技术可以对成千上万个细胞进行高通量的转录组分析。scRNA-seq可以在基因组水平上，以单个细胞为单位，对不同细胞类型和状态的转录组进行分析。该技术在植物研究中的应用已经拓展了我们对细胞类型、功能和发育的理解。在植物-病原互作领域，寄主在单细胞水平如何应对侵染以及病原体距离对细胞反应的影响，目前尚不清楚。
拟南芥叶组织感染假单胞菌的scRNA-seq图谱分析
免疫和易感标记基因的空间表达模式分析
讨论
These data indicate that virulent bacteria are able to reprogram larger sections of the leaf toward susceptibility. 毒性细菌能够将叶片的较大部分重新编程为易感性 indicating asynchronous infection stages even early during infection. 表明在感染过程中，即使在早期也存在非同步感染阶段（进行单细胞转录组研究的意义） We identified two immune cell clusters, possibly due to waves of PTI transcriptional responses. 鉴定两个局部免疫亚群 Unlike the localized expression of immune markers, susceptibility markers exhibited more general expression, indicating more global reprogramming of the leaf to a susceptible state over time. Genes regulating plant immune perception and signaling have been well characterized over the past 30 years, but identification of susceptibility genes has lagged behind.67 Susceptibility genes are attractive targets to modify for developing disease resistant crops because of advances in genome editing technologies and decreased regulatory oversight. 研究易感基因的潜力
疑问
怎么富集的叶肉细胞
Protoplasts were isolated from Arabidopsis leaves infiltrated by bacteria and 10 mM MgCl2 (Mock) using Tape-Arabidopsis Sandwich method as described previously.
怎么进行QC的
The output from Cellranger was further processed using the Velocyto (v0.17.15) algorithm,72 using default parameters, to generate spliced and unspliced counts matrices. For each cell, the percentage of reads mapping to mitochondrial, and chloroplast genes was computed. Cells were then filtered for those having a spliced mitochondrial read percentage of less than 1%, as well as a total spliced Unique Molecular Identifier (UMI) count within a dataset dependent threshold, bounded at the high end by 50,000 counts, and at the low end by 10% of the UMI count of the 100th most spliced transcript-rich cell for that dataset.
样本和重复情况
Three biological replicates were performed for samples of Pst DC3000- or mock-infiltrated leaves, and one repeat was made for leaf protoplasts of each sample.
怎么排除的原生质体基因，如果不影响/影响不大还需要排除吗
Genes determined to be significantly altered by protoplasting were identified using a relatively liberal set of criteria, i.e. having log-fold change values > 0.5 and adjusted (BH) p-values less than 0.05, and were removed from dimension reduction and integration analyses.
Genes that were identified as being significantly influenced by protoplasting (see Bulk RNA-seq data analysis) were excluded from further analysis.
怎么做的鉴定
A recent Arabidopsis leaf single-cell RNA-seq dataset was used to annotate cell types for all cells in this dataset using the label transfer pipeline (Seurat) 直接用的label transfer, emmmmm...免疫/易感叶肉细胞亚群是否有特殊的空间定位——比如M1 M2应该细分为气孔及保卫细胞？
Pathogen signature基因集鉴定
Genes determined to be significantly affected by Pst DC3000 were those having log-fold change values >2 and adjusted (BH) p values less than 0.01, unless otherwise specified
使用处理的叶肉细胞做monocle3分析，是否展示了重新降维的结果
SCTransform-normalized expression values for spliced transcripts in mesophyll cells (excluding Seurat cluster 16, which seemed distinct from other mesophyll cells) were filtered from the Pst DC3000 dataset and re-embedded in a low-dimensional UMAP space using the Monocle 3 (v1.0.0) pipeline (using 5 principal components, the correlation distance metric, and a minimum distance of 0.01).
※标准分析|标准分析流程
※标准分析|Read10X源码拆解
标准分析|自动获得QC阈值
标准分析|污染处理SoupX
※细胞分化|轨迹分析基本概念1
※细胞分化|轨迹分析基本概念2
※细胞分化|monocle1原理
※细胞分化|monocle2原理
细胞分化|解决monocle2报错
细胞分化|Cytotrace分析
细胞分化|使用VECTOR进行无监督发育方向推断
※细胞分化|单细胞可变剪切分析全流程（基于velocyto.R）
细胞分化|不同scVelo模型
细胞分化|使用GeneTrajectory进行基因轨迹分析
细胞通讯|细胞通讯简介
※细胞通讯|CellPhoneDBv5安装及使用
※富集分析|基于TBtools&R语言进行富集分析及可视化
富集分析|更新clusterprofiler包
富集分析|基因ID格式转换
富集分析|水稻富集分析
※富集分析|植物组织特异性干细胞通路获取
※可视化|Featureplot函数进阶
※可视化|DotPlot函数进阶
※可视化|给你的Dotplot添加聚类及其它统计信息
※可视化|Cell级降维图绘制
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