Predicting the impact of sequence motifs on gene regulation using single-cell data

Binding of transcription factors (TFs) at proximal promoters and distal enhancers is central to gene regulation. Yet, identification of TF binding sites, also known as regulatory motifs, and quantification of their impact remains challenging. Here we present scover, a convolutional neural network model that can discover putative regulatory motifs along with their cell type-specific importance from single-cell data. Analysis of scRNA-seq data from human kidney shows that ETS, YY1 and NRF1 are the most important motif families for proximal promoters. Using multiple mouse tissues we obtain for the first time a model with cell type resolution which explains 34% of the variance in gene expression. Finally, by applying scover to distal enhancers identified using scATAC-seq from the mouse cerebral cortex we highlight the emergence of layer specific regulatory patterns during development.

Fibrinogen gene regulation

SummaryThe Aα, Bβ and γ polypeptide chains of fibrinogen are encoded by a three gene cluster on human chromosome four. The fibrinogen genes (FGB-FGA-FGG) are expressed almost exclusively in hepatocytes where their output is coordinated to ensure a sufficient mRNA pool for each chain and maintain an abundant plasma fibrinogen protein level. Fibrinogen gene expression is controlled by the activity of proximal promoters which contain binding sites for hepatocyte transcription factors, including proteins which influence fibrinogen transcription in response to acute-phase inflammatory stimuli. The fibrinogen gene cluster also contains cis regulatory elements; enhancer sequences with liver activities identified by sequence conservation and functional genomics. While the transcriptional control of this gene cluster is fascinating biology, the medical impetus to understand fibrinogen gene regulation stems from the association of cardiovascular disease risk with high level circulating fibrinogen. In the general population this level varies from about 1.5 to 3.5 g/l. This variation between individuals is influenced by genotype, suggesting there are genetic variants contributing to fibrinogen levels which reside in fibrinogen regulatory loci. A complete picture of how fibrinogen genes are regulated will therefore point towards novel sources of regulatory variants. In this review we discuss regulation of the fibrinogen genes from proximal promoters and enhancers, the influence of acute-phase stimulation, post-transcriptional regulation by miRNAs and functional regulatory variants identified in genetic studies. Finally, we discuss the fibrinogen locus in light of recent advances in understanding chromosomal architecture and suggest future directions for researching the mechanisms that control fibrinogen expression.