Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA.
Center for Cancer and Immunology Research, Brain Tumor Institute, Children's National Medical Center, Washington, D.C. 20010, USA.
Cell Rep. 2019 Mar 12;26(11):3132-3144.e7. doi: 10.1016/j.celrep.2019.02.043.
Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis algorithm to identify both common and specific signature genes for obesity and T2D. We mapped both β-cell-specific genes and disease signature genes to the insulin regulatory network identified from a genome-wide CRISPR screen. Our integrative analysis discovered the previously unrecognized roles of the cohesin loading complex and the NuA4/Tip60 histone acetyltransferase complex in regulating insulin transcription and release. Our study demonstrated the power of combining single-cell heterogeneity analysis and functional genomics to dissect the etiology of complex diseases.
鉴定人类疾病特征基因通常需要从许多供体中获得样本以达到统计学意义。在这里，我们表明，通过显著提高检测灵敏度，单细胞异质性分析可能克服这一障碍。我们分析了来自 9 个供体的 39905 个单个胰岛细胞的转录组，观察到与肥胖或 2 型糖尿病 (T2D) 相关的不同β细胞异质性轨迹。因此，我们开发了 RePACT，一种敏感的单细胞分析算法，用于鉴定肥胖和 T2D 的常见和特异性特征基因。我们将β细胞特异性基因和疾病特征基因映射到从全基因组 CRISPR 筛选中鉴定出的胰岛素调控网络。我们的综合分析发现了黏合蛋白加载复合物和 NuA4/Tip60 组蛋白乙酰转移酶复合物在调节胰岛素转录和释放中的先前未被认识的作用。我们的研究表明，将单细胞异质性分析和功能基因组学相结合以剖析复杂疾病病因的强大功能。
