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显微切割肾小管中的深度测序鉴定肾单位节段特异性转录组。

Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment-Specific Transcriptomes.

作者信息

Lee Jae Wook, Chou Chung-Lin, Knepper Mark A

机构信息

Epithelial Systems Biology Laboratory, Systems Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland.

Epithelial Systems Biology Laboratory, Systems Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland

出版信息

J Am Soc Nephrol. 2015 Nov;26(11):2669-77. doi: 10.1681/ASN.2014111067. Epub 2015 Mar 27.

Abstract

The function of each renal tubule segment depends on the genes expressed therein. High-throughput methods used for global profiling of gene expression in unique cell types have shown low sensitivity and high false positivity, thereby limiting the usefulness of these methods in transcriptomic research. However, deep sequencing of RNA species (RNA-seq) achieves highly sensitive and quantitative transcriptomic profiling by sequencing RNAs in a massive, parallel manner. Here, we used RNA-seq coupled with classic renal tubule microdissection to comprehensively profile gene expression in each of 14 renal tubule segments from the proximal tubule through the inner medullary collecting duct of rat kidneys. Polyadenylated mRNAs were captured by oligo-dT primers and processed into adapter-ligated cDNA libraries that were sequenced using an Illumina platform. Transcriptomes were identified to a median depth of 8261 genes in microdissected renal tubule samples (105 replicates in total) and glomeruli (5 replicates). Manual microdissection allowed a high degree of sample purity, which was evidenced by the observed distributions of well established cell-specific markers. The main product of this work is an extensive database of gene expression along the nephron provided as a publicly accessible webpage (https://helixweb.nih.gov/ESBL/Database/NephronRNAseq/index.html). The data also provide genome-wide maps of alternative exon usage and polyadenylation sites in the kidney. We illustrate the use of the data by profiling transcription factor expression along the renal tubule and mapping metabolic pathways.

摘要

每个肾小管节段的功能取决于其中表达的基因。用于对独特细胞类型中的基因表达进行全局分析的高通量方法显示出低灵敏度和高假阳性率,从而限制了这些方法在转录组学研究中的实用性。然而,RNA 物种深度测序(RNA-seq)通过大规模并行测序 RNA 实现了高灵敏度和定量转录组分析。在这里,我们使用 RNA-seq 结合经典的肾小管显微切割技术,全面分析了大鼠肾脏从近端小管到髓质内集合管的 14 个肾小管节段中每个节段的基因表达。通过寡聚 dT 引物捕获多聚腺苷酸化的 mRNA,并将其处理成连接有接头的 cDNA 文库,使用 Illumina 平台进行测序。在显微切割的肾小管样本(总共 105 个重复样本)和肾小球(5 个重复样本)中,转录组鉴定到的基因中位数深度为 8261 个。手动显微切割保证了高度的样本纯度,这通过观察到的成熟细胞特异性标志物的分布得到了证明。这项工作的主要成果是一个广泛的沿肾单位基因表达数据库,可通过一个公开访问的网页获取(https://helixweb.nih.gov/ESBL/Database/NephronRNAseq/index.html)。这些数据还提供了肾脏中可变外显子使用和聚腺苷酸化位点的全基因组图谱。我们通过分析沿肾小管的转录因子表达和绘制代谢途径来说明这些数据的用途。

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本文引用的文献

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Atlas of gene expression in the mouse kidney: new features of glomerular parietal cells.小鼠肾脏基因表达图谱:壁细胞的新特征
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