Integrated gene expression and alternative splicing analysis in human and mouse models of Rett Syndrome

Background Mutations of the MeCP2 gene lead to Rett syndrome (RTT), a rareX-linked developmental disease causing severe intellectual and physical disability. How the loss or defective function of MeCP2 mediates RTT is still poorly understood. MeCP2 is a global gene expression regulator, acting at transcriptional and post-transcriptional levels. Although several transcriptomic studies have been performed in human RTT biosamples and Mecp2mutant mouse models, few genes or pathways have been consistently associated with MeCP2 mutations. Despite the known regulatory role of MeCP2 in splicing mechanisms, the contribution of alternative splicing dysregulation to RTT pathophysiology has received little attention. To gain insight into common molecular pathways that might be dysregulated in RTT, we explore and integrate publicly available RNA sequencing (RNA-seq) data from human RTT patients and Mecp2 - mutant mouse models, processing data for gene expression and alternative splicing. Methods We downloaded from the Sequence Read Archive 100 samples (SRA-experiments) from 5 independent BioProjects on human Rett Syndrome patients, and 130 samples from 9 independent BioProjects on MeCP2 mutant mouse models. We performed a massive bioinformatics re-analysis of raw data, applying single, standardized pipelines for differential gene expression and alternative splicing analysis. Results Our comparative study across datasets indicates common differentially expressed genes (DEGs) and differentially alternatively spliced (DAS) genes shared by human or mouse datasets. We observed that genes dysregulated either in their expression or splicing are involved in two main functional categories: cell-extracellular matrix adhesion regulation and synaptic functions, the first category more significantly enriched in human datasets. A low overlap between human and mouse DEGs and DAS genes was observed. Limitations The main limitation of our analysis is the inclusion in the study of highly heterogeneous RNA-seq datasets, deriving from various RTT tissues and cells, and carrying different MeCP2 mutations. Conclusions Our massive bioinformatics study indicates for the first time a significant dysregulation of alternative splicing in human RTT datasets, suggesting the crucial contribution of altered RNA processing to the pathophysiology of Rett syndrome. Additionally, we observed that human and mouse DEGs and DAS genes converge into common functional categories related to cell-extracellular matrix adhesion and synaptic signaling.