Comparative transcriptomic analyses provide insights into key genes involved in niche-associated functions of primary murine LEC and BEC in homeostasis

Purpose: The goal of this study is to compare the transcriptome profiles of freshly isolated primary murine endothelial populations, namely the lymph node-derived lymphatic endothelial cell (LN-LEC) and blood endothelial cell (LN-BEC), and the diaphragm-derived LEC (D-LEC) in homeostasis. Methods: LN-LEC and LN-BEC total RNA samples were prepared by pooling inguinal, axillary, brachial, cervical, and mesenteric LNs from wild-type C57BL/6 (B6) mice (6-8 weeks of age, purchased from NCI), followed by mechanical and enzymatic digestion, CD45- cell lineage enrichment using MACS beads (deplete S protocol in AUTOMACS), and sorted by flow cytometry based on CD45, CD31, and podoplanin expressions using Influx (BD) into RNA Protect (Qiagen). D-LEC total RNA samples were prepared by mechanical and enzymatic digestion of tissues, followed directly by flow cytometry sorting as described above. Total RNA extraction was performed using RNAeasy mini kit (Qiagen) as per manufacturer’s instructions. The cDNA library preparation and sequencing were performed by the Genomic Services Laboratory at Hudson Alpha, USA. Briefly, purified total RNAs (RIN score of 7.0 or higher) were prepared for sequencing using the Ovation RNA-seq System V2 kit (Nugen) followed by RNA-sequencing of 100 paired-end reads using the Illumina HiSeq 2500 v4 platform. Raw RNA-sequencing read quality was assessed using FastQC and low quality regions were trimmed using Fastx-trimmer. Cleaned reads were aligned to the mouse reference genome (build mm9) using STAR and read counts on known mouse genes were calculated using featureCounts, part of the Subread package. Next, uniquely aligned reads were analyzed using the DEseq2 package in the R statistical computing environment to obtain normalized counts, estimate dispersion, and determine a negative binomial model for each gene. Differentially expressed genes (DEG) were determined using DESeq2 and the Benjamini-Hochberg False Discovery Rate procedure was used to re-estimate the adjusted p-values. Differentially expressed genes (DEGs) were subsequently identified as those with an FPKM of 1 or greater, p-adjusted < 0.05, and additionally 5X-DEG subsets were identified as those with fold-change of 5 or greater. Results: Post-sort analyses of LN-LEC, LN-BEC, and D-LEC replicates showed 92.6-98.6% purity. RNAseq yielded 48-98 million reads per replicate, with an average length of 180 nucleotides, and an average of 85.7% uniquely mapped reads. These reads mapped a total of 23284 genes, of which 15331 were considered expressed based on an average FPKM of 1 or greater in at least one cell type. Of this number, 14718, 14893, and 14384 genes were considered expressed in LN-LEC, LN-BEC, and D-LEC, respectively. Principal component analysis revealed that the transcriptional profiles of sample replicates clustered tightly, and that those of LN-LEC, LN-BEC, and D-LEC differed from each other. Conclusions: Our study provides insights into key genes involved in niche-associated functions of primary murine LEC and BEC in homeostasis. The RNA-seq data reported here may provide a conceptual framework for future comparative investigations of LN-LEC, LN-BEC, and D-LEC phenotypic expression profiles, heterogeneity, and niche-specific functions in homeostasis as well as disease. mRNA profiles of 4 LN-LEC, 3 LN-BEC, and 3 D-LEC samples from wild-type C57BL/6 (B6) mice (6-8 weeks of age) were generated by RNA-sequencing using the Illumina HiSeq 2500 v4 platform.

## 研究目的
本研究旨在比较稳态条件下新鲜分离的原代小鼠内皮细胞群（primary murine endothelial populations）的转录组谱（transcriptome profiles），具体包括淋巴结来源的淋巴管内皮细胞（lymph node-derived lymphatic endothelial cell, LN-LEC）、淋巴结来源的血管内皮细胞（blood endothelial cell, LN-BEC），以及膈肌来源的淋巴管内皮细胞（diaphragm-derived LEC, D-LEC）。

## 实验方法
LN-LEC与LN-BEC的总RNA样本制备流程如下：合并6-8周龄、购自美国国家癌症研究所（National Cancer Institute, NCI）的野生型C57BL/6（B6）小鼠的腹股沟、腋下、臂部、颈部及肠系膜淋巴结，经机械联合酶解消化后，使用MACS磁珠（MACS beads）采用AUTOMACS的去除S方案富集CD45阴性细胞群，随后通过BD Influx流式细胞仪（BD Influx）根据CD45、CD31及podoplanin的表达水平进行分选，将细胞收集至Qiagen的RNA Protect试剂（RNA Protect, Qiagen）中。D-LEC的总RNA样本则通过对膈肌组织进行机械联合酶解消化后，直接按照上述方法进行流式细胞分选制备。总RNA提取采用Qiagen的RNAeasy mini kit（RNAeasy mini kit, Qiagen），并严格按照制造商说明书操作。cDNA文库构建及测序工作由美国哈德逊阿尔法的基因组服务实验室完成。简言之，先使用Nugen的Ovation RNA-seq System V2试剂盒（Ovation RNA-seq System V2 kit, Nugen）对纯化后的总RNA（RNA完整性数≥7.0）进行测序文库制备，随后采用Illumina HiSeq 2500 v4平台（Illumina HiSeq 2500 v4 platform）进行100bp双端读长的RNA测序。原始RNA测序读段的质量通过FastQC（FastQC）评估，并使用Fastx-trimmer（Fastx-trimmer）去除低质量区域；质控后的clean读段通过STAR（STAR）软件比对至小鼠参考基因组（mouse reference genome build mm9）（mm9版本），并利用Subread软件包（Subread package）中的featureCounts（featureCounts）工具计算已知小鼠基因的读段计数。随后在R统计计算环境（R statistical computing environment）中使用DEseq2软件包（DEseq2 package）对唯一比对的读段进行分析，以获得标准化计数、估算离散度，并为每个基因确定负二项分布模型（negative binomial model）；采用DESeq2鉴定差异表达基因（differentially expressed genes, DEG），并用Benjamini-Hochberg错误发现率（Benjamini-Hochberg False Discovery Rate）方法重新校正P值。最终将FPKM（FPKM）≥1且校正后P值<0.05的基因定义为差异表达基因，同时将折叠变化（fold-change）≥5的差异表达基因划分为5倍差异表达基因子集。

## 实验结果
分选后样本质量分析显示，LN-LEC、LN-BEC及D-LEC的生物学重复（replicates）样本纯度为92.6%~98.6%。每个生物学重复的RNA测序产出读段数为4800万~9800万，平均读长为180nt，平均唯一比对率为85.7%。这些读段共比对至23284个基因，其中至少在一种细胞类型中平均FPKM≥1的15331个基因被认定为表达基因，其中LN-LEC、LN-BEC及D-LEC中分别有14718、14893及14384个基因被认定为表达基因。主成分分析（principal component analysis）结果显示，各样本的生物学重复聚类紧密，且LN-LEC、LN-BEC与D-LEC的转录组谱彼此存在显著差异。

## 研究结论
本研究揭示了稳态条件下原代小鼠淋巴管内皮细胞与血管内皮细胞的微环境相关功能所涉及的关键基因。本研究报道的RNA测序数据可为未来开展LN-LEC、LN-BEC及D-LEC的表型表达谱、细胞异质性（heterogeneity）以及稳态与疾病状态下的微环境特异性功能（niche-specific functions）的比较研究提供理论框架。本研究共获取了来自6-8周龄野生型C57BL/6（B6）小鼠的4份LN-LEC、3份LN-BEC及3份D-LEC样本的mRNA表达谱，所有样本均通过Illumina HiSeq 2500 v4平台进行RNA测序。