Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles.
Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles.
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DOI：
10.1186/s13073-023-01179-2
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发表时间：
2023-05-01
期刊：
影响因子：
12.3
通讯作者：
中科院分区：
文献类型：
--
作者：
单细胞 RNA 测序 (scRNA-seq) 为了解人类胰岛细胞类型及其相应的稳定基因表达谱提供了宝贵的见解。然而，这种方法需要细胞解离，这使其在体内的应用变得复杂。另一方面，单核 RNA 测序 (snRNA-seq) 与冷冻样品兼容，消除解离诱导的转录应激反应，并提供内含子序列的增强信息，可用于识别前 mRNA 转录本。我们从新鲜的人胰岛细胞中获得核制剂并生成 snRNA-seq 数据集。我们将这些数据集与从同一供体的人类胰岛细胞获得的 scRNA-seq 输出进行了比较。我们采用 snRNA-seq 来获得移植到免疫缺陷小鼠体内的人类胰岛的转录组图谱。在这两项分析中，我们将内含子读数纳入了 GRCh38-2020-A 文库的 snRNA-seq 数据中。首先，snRNA-seq分析显示人胰岛内分泌细胞体外和体内差异性选择性表达最高的4个基因不是经典基因，而是一组新的非经典基因标记，包括ZNF385D、TRPM3、LRFN2、PLUT（β细胞）； PTPRT、FAP、PDK4、LOXL4（α 细胞）； LRFN5、ADARB2、ERBB4、KCNT2（δ 细胞）；和 CACNA2D3、THSD7A、CNTNAP5、RBFOX3（γ 细胞）。其次，通过整合来自人类胰岛细胞的 scRNA-seq 和 snRNA-seq 的信息，我们区分了三个 β 细胞亚簇：INS 前 mRNA 簇 (β3)、中间 INS mRNA 簇 (β2) 和富含 INS mRNA 的簇 (β1)。它们表现出不同的基因表达模式，代表体外和体内不同的生物动态状态。有趣的是，富含 INS mRNA 的簇 (β1) 成为体内的主要亚簇。总之，人胰岛细胞的 snRNA-seq 和 pre-mRNA 分析可以准确识别人胰岛细胞群体、亚群及其体内动态转录组谱。在线版本包含可在 10.1186/s13073-023-01179-2 获取的补充材料。
Single-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts. We obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library. First, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo. In summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo. The online version contains supplementary material available at 10.1186/s13073-023-01179-2.
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影响因子：
64.5
作者：
Enge M;Arda HE;Mignardi M;Beausang J;Bottino R;Kim SK;Quake SR
通讯作者：
Quake SR
影响因子：
9.3
作者：
Baron M;Veres A;Wolock SL;Faust AL;Gaujoux R;Vetere A;Ryu JH;Wagner BK;Shen-Orr SS;Klein AM;Melton DA;Yanai I
通讯作者：
Yanai I
影响因子：
7.7
作者：
Evans-Molina, Carmella;Garmey, James C.;Mirmira, Raghavendra G.
通讯作者：
Mirmira, Raghavendra G.
影响因子：
64.8
作者：
La Manno G;Soldatov R;Zeisel A;Braun E;Hochgerner H;Petukhov V;Lidschreiber K;Kastriti ME;Lönnerberg P;Furlan A;Fan J;Borm LE;Liu Z;van Bruggen D;Guo J;He X;Barker R;Sundström E;Castelo-Branco G;Cramer P;Adameyko I;Linnarsson S;Kharchenko PV
通讯作者：
Kharchenko PV
DOI：
10.1111/gbb.12085
发表时间：
2013-11
期刊：
Genes, brain, and behavior
影响因子：
--
作者：
Eicher JD;Powers NR;Miller LL;Akshoomoff N;Amaral DG;Bloss CS;Libiger O;Schork NJ;Darst BF;Casey BJ;Chang L;Ernst T;Frazier J;Kaufmann WE;Keating B;Kenet T;Kennedy D;Mostofsky S;Murray SS;Sowell ER;Bartsch H;Kuperman JM;Brown TT;Hagler DJ Jr;Dale AM;Jernigan TL;St Pourcain B;Davey Smith G;Ring SM;Gruen JR;Pediatric Imaging, Neurocognition, and Genetics Study
通讯作者：
Pediatric Imaging, Neurocognition, and Genetics Study