Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
Commun Biol. 2022 Aug 26;5(1):876. doi: 10.1038/s42003-022-03831-w.
Most human genes are co-expressed with a nearby gene. Previous studies have revealed this local gene co-expression to be widespread across chromosomes and across dozens of tissues. Yet, so far these studies used bulk RNA-seq, averaging gene expression measurements across millions of cells, thus being unclear if this co-expression stems from transcription events in single cells. Here, we leverage single cell datasets in >85 individuals to identify gene co-expression across cells, unbiased by cell-type heterogeneity and benefiting from the co-occurrence of transcription events in single cells. We discover >3800 co-expressed gene pairs in two human cell types, induced pluripotent stem cells (iPSCs) and lymphoblastoid cell lines (LCLs) and (i) compare single cell to bulk RNA-seq in identifying local gene co-expression, (ii) show that many co-expressed genes - but not the majority - are composed of functionally related genes and (iii) using proteomics data, provide evidence that their co-expression is maintained up to the protein level. Finally, using single cell RNA-sequencing (scRNA-seq) and single cell ATAC-sequencing (scATAC-seq) data for the same single cells, we identify gene-enhancer associations and reveal that >95% of co-expressed gene pairs share regulatory elements. These results elucidate the potential reasons for co-expression in single cell gene regulatory networks and warrant a deeper study of shared regulatory elements, in view of explaining disease comorbidity due to affecting several genes. Our in-depth view of local gene co-expression and regulatory element co-activity advances our understanding of the shared regulatory architecture between genes.
大多数人类基因与附近的基因共表达。先前的研究表明，这种局部基因共表达在染色体上和数十种组织中广泛存在。然而，到目前为止，这些研究使用的是批量 RNA-seq，对数百万个细胞的基因表达进行平均测量，因此不清楚这种共表达是否源于单细胞中的转录事件。在这里，我们利用 >85 个人的单细胞数据集来识别细胞间的基因共表达，不受细胞类型异质性的影响，并受益于单细胞中转录事件的共同发生。我们在两种人类细胞类型——诱导多能干细胞 (iPSC) 和淋巴母细胞系 (LCL) 中发现了 >3800 对共表达的基因对，（i）比较单细胞和批量 RNA-seq 识别局部基因共表达，（ii）表明许多共表达的基因——但不是大多数——由功能相关的基因组成，（iii）使用蛋白质组学数据，提供证据表明它们的共表达在蛋白质水平上得以维持。最后，使用相同单细胞的单细胞 RNA-seq (scRNA-seq) 和单细胞 ATAC-seq (scATAC-seq) 数据，我们确定了基因-增强子的关联，并揭示了 >95%的共表达基因对共享调节元件。这些结果阐明了单细胞基因调控网络中基因共表达的潜在原因，并需要更深入地研究共享调节元件，以解释由于影响多个基因而导致的疾病共病现象。我们对局部基因共表达和调节元件共活性的深入了解，推进了我们对基因之间共享调节结构的理解。
