Rett syndrome (RTT) is a pediatric neurological disorder that results from dysfunction of X-linked Methyl-CpG-binding protein 2 (MECP2). Treatment strategies that are under-development for RTT either target MECP2 itself or target pathways downstream of MeCP2. In the first category, the goal is to normalize MECP2 expression through molecular techniques such as gene therapy. Targeting MECP2 is particularly attractive because it may lead to curing RTT yet special attention must be paid to MECP2 dosage. The brain is highly sensitive to perturbation of MECP2 as over-expression causes MECP2 Duplication syndrome and even subtle fluctuations are associated with a spectrum of neurological disorders, such as autism. We are taking advantage of genetically diverse mouse populations to integrate genetic, genomic (mRNA), proteomic (protein) and epigenetic (X inactivation) level data to address questions: (1) how are MECP2 transcript and protein levels controlled in the brain? And (2) how does genetic background influence the spectrum and severity of RTT-related phenotypes?
We have quantified Mecp2 transcript levels in the brain from three different but genetically related mouse populations: 65 Collaborative Cross (CC) strains, 27 F1 hybrid crosses of two different CC strains, and 223 Diversity Outbred (DO) mice. In all three populations, heritability is well over 0.50, demonstrating that expression is under genetic control and is segregating within our reference populations. Mecp2 expression in the inbred CC strains far exceeds the range of levels quantified between the three most diverse founders of the CC (CAST/EiJ, PWK/PhJ, and WSB/EiJ), demonstrating that Mecp2 expression is under the control of trans acting factor(s). Using the 223 Diversity Outbred mice, we have mapped trans eQTL. To establish Mecp2 expression thresholds in the brain, we are quantifying the correlation between steady-state transcript levels and protein abundance. And, we describe here strategies that we will employ to test how outlier levels are associated with clinical features. This work will produce new mouse lines and molecular and behavioral datasets will be valuable tools to map modifiers of phenotypes, inform on the molecular mechanisms that define transcript and protein levels, and develop and test more effective treatment strategies.