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单细胞 RNA 测序图谱揭示了调控玉米根系真菌入侵的细胞类型特异性转录调控网络。

Single-cell RNA sequencing profiles reveal cell type-specific transcriptional regulation networks conditioning fungal invasion in maize roots.

机构信息

Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.

Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China.

出版信息

Plant Biotechnol J. 2023 Sep;21(9):1839-1859. doi: 10.1111/pbi.14097. Epub 2023 Jun 22.

DOI:10.1111/pbi.14097
PMID:37349934
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10440994/
Abstract

Stalk rot caused by Fusarium verticillioides (Fv) is one of the most destructive diseases in maize production. The defence response of root system to Fv invasion is important for plant growth and development. Dissection of root cell type-specific response to Fv infection and its underlying transcription regulatory networks will aid in understanding the defence mechanism of maize roots to Fv invasion. Here, we reported the transcriptomes of 29 217 single cells derived from root tips of two maize inbred lines inoculated with Fv and mock condition, and identified seven major cell types with 21 transcriptionally distinct cell clusters. Through the weighted gene co-expression network analysis, we identified 12 Fv-responsive regulatory modules from 4049 differentially expressed genes (DEGs) that were activated or repressed by Fv infection in these seven cell types. Using a machining-learning approach, we constructed six cell type-specific immune regulatory networks by integrating Fv-induced DEGs from the cell type-specific transcriptomes, 16 known maize disease-resistant genes, five experimentally validated genes (ZmWOX5b, ZmPIN1a, ZmPAL6, ZmCCoAOMT2, and ZmCOMT), and 42 QTL or QTN predicted genes that are associated with Fv resistance. Taken together, this study provides not only a global view of maize cell fate determination during root development but also insights into the immune regulatory networks in major cell types of maize root tips at single-cell resolution, thus laying the foundation for dissecting molecular mechanisms underlying disease resistance in maize.

摘要

由轮枝镰孢菌(Fusarium verticillioides,Fv)引起的茎腐病是玉米生产中最具破坏性的病害之一。根系对 Fv 入侵的防御反应对于植物的生长和发育至关重要。解析根系细胞类型对 Fv 感染的特异性反应及其潜在的转录调控网络将有助于理解玉米根系对 Fv 入侵的防御机制。在这里,我们报告了来自接种 Fv 和模拟条件的两个玉米自交系根尖的 29217 个单细胞的转录组,鉴定出了 7 种主要的细胞类型和 21 个转录上不同的细胞簇。通过加权基因共表达网络分析,我们从这 7 种细胞类型中 4049 个差异表达基因(DEGs)中鉴定出 12 个 Fv 响应调控模块,这些基因在 Fv 感染时被激活或抑制。通过整合来自细胞类型特异性转录组、16 个已知的玉米抗病基因、5 个实验验证的基因(ZmWOX5b、ZmPIN1a、ZmPAL6、ZmCCoAOMT2 和 ZmCOMT)和 42 个与 Fv 抗性相关的 QTL 或 QTN 预测基因的 Fv 诱导的 DEGs,我们使用机器学习方法构建了 6 个细胞类型特异性免疫调控网络。综上所述,本研究不仅提供了玉米根系发育过程中细胞命运决定的全局视图,还深入了解了玉米根尖主要细胞类型在单细胞分辨率下的免疫调控网络,为解析玉米抗病的分子机制奠定了基础。

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