Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche (CNR), Cagliari, Italy.
CRS4-Next Generation Sequencing (NGS) Core, Parco POLARIS, Cagliari, Italy.
Front Immunol. 2024 Apr 2;15:1350111. doi: 10.3389/fimmu.2024.1350111. eCollection 2024.
Gene co-expression network analysis enables identification of biologically meaningful clusters of co-regulated genes (modules) in an unsupervised manner. We present here the largest study conducted thus far of co-expression networks in white blood cells (WBC) based on RNA-seq data from 624 individuals. We identify 41 modules, 13 of them related to specific immune-related functions and cell types (e.g. neutrophils, B and T cells, NK cells, and plasmacytoid dendritic cells); we highlight biologically relevant lncRNAs for each annotated module of co-expressed genes. We further characterize with unprecedented resolution the modules in T cell sub-types, through the availability of 95 immune phenotypes obtained by flow cytometry in the same individuals. This study provides novel insights into the transcriptional architecture of human leukocytes, showing how network analysis can advance our understanding of coding and non-coding gene interactions in immune system cells.
基因共表达网络分析能够以非监督的方式识别生物上有意义的共调控基因(模块)簇。我们在此介绍迄今为止基于 624 个人的 RNA-seq 数据对白血细胞(WBC)共表达网络进行的最大研究。我们鉴定出 41 个模块,其中 13 个与特定的免疫相关功能和细胞类型有关(例如中性粒细胞、B 和 T 细胞、自然杀伤细胞和浆细胞样树突状细胞);我们为每个注释的共表达基因模块突出了生物学上相关的 lncRNA。我们通过在相同个体中获得的 95 种流式细胞术免疫表型,以前所未有的分辨率进一步描述了 T 细胞亚型中的模块。这项研究为人类白细胞的转录结构提供了新的见解,展示了网络分析如何促进我们对免疫系统细胞中编码和非编码基因相互作用的理解。