Abstract:Recent studies have suggested that genes longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in MeCP2-mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, here we re-evaluate the statistical significance of these results. We find that the apparent length-dependent trends previously observed in MeCP2 microarr… Show more
“…10.7554/eLife.38619.027Figure 7—figure supplement 2.Significant length differences using the test proposed by Raman et al (2018) evaluating length dependent differences by comparing expression ratios between groups to those within a single group.( A,B ) (Top panels) Mean and Std. Dev.…”
Understanding the principles governing neuronal diversity is a fundamental goal for neuroscience. Here, we provide an anatomical and transcriptomic database of nearly 200 genetically identified cell populations. By separately analyzing the robustness and pattern of expression differences across these cell populations, we identify two gene classes contributing distinctly to neuronal diversity. Short homeobox transcription factors distinguish neuronal populations combinatorially, and exhibit extremely low transcriptional noise, enabling highly robust expression differences. Long neuronal effector genes, such as channels and cell adhesion molecules, contribute disproportionately to neuronal diversity, based on their patterns rather than robustness of expression differences. By linking transcriptional identity to genetic strains and anatomical atlases, we provide an extensive resource for further investigation of mouse neuronal cell types.
“…10.7554/eLife.38619.027Figure 7—figure supplement 2.Significant length differences using the test proposed by Raman et al (2018) evaluating length dependent differences by comparing expression ratios between groups to those within a single group.( A,B ) (Top panels) Mean and Std. Dev.…”
Understanding the principles governing neuronal diversity is a fundamental goal for neuroscience. Here, we provide an anatomical and transcriptomic database of nearly 200 genetically identified cell populations. By separately analyzing the robustness and pattern of expression differences across these cell populations, we identify two gene classes contributing distinctly to neuronal diversity. Short homeobox transcription factors distinguish neuronal populations combinatorially, and exhibit extremely low transcriptional noise, enabling highly robust expression differences. Long neuronal effector genes, such as channels and cell adhesion molecules, contribute disproportionately to neuronal diversity, based on their patterns rather than robustness of expression differences. By linking transcriptional identity to genetic strains and anatomical atlases, we provide an extensive resource for further investigation of mouse neuronal cell types.
“…Data analysis approaches varied in stringency between experiments, with cut‐off values ranging from p < .05 to .005 and fold change (fc) from >1.2 (<0.67) to >2 (<0.5). These different methodologies are of great consequence to the interpretation of data as subtle changes caused by Mecp2 deficiency may be reported to be important in the less stringent tests which do not reflect the real function of Mecp2 (Raman et al, ). The opposite can also happen, as too few genes may be reported in more stringent tests, hence “loosing” critical data .…”
The discovery that Rett syndrome is caused by mutations in the MECP2 gene has provided a major breakthrough in our understanding of the disorder. However, despite this, there is still limited understanding of the underlying pathophysiology of the disorder hampering the development of curative treatments. Over the years, a number of animal models have been developed contributing to our knowledge of the role of MECP2 in development and improving our understanding of how subtle expression levels affect brain morphology and function. Transcriptomic and proteomic studies of animal models are useful in identifying perturbations in functional pathways and providing avenues for novel areas of research into disease.This review focuses on published transcriptomic and proteomic studies of mouse models of Rett syndrome with the aim of providing a summary of all the studies, the reported dysregulated genes and functional pathways that are found to be perturbed.The 36 articles identified highlighted a number of dysfunctional pathways as well as perturbed biological networks and cellular functions including synaptic dysfunction and neuronal transmission, inflammation, and mitochondrial dysfunction. These data reveal biological insights that contribute to the disease process which may be targeted to investigate curative treatments.
“…One hypothesis for the pathogenesis of Rett syndrome is that loss-of-function mutations in the MECP2 gene are detrimental because they result in the lack of MeCP2-mediated silencing of transcriptional noise (Bird and Tweedie 1995). It has also been suggested that MeCP2 controls the expression of long genes (more than 100 kb) in a length-dependent manner (Gabel et al 2015), although this view is controversial (Raman et al 2018). Regardless of the specific molecular mechanism(s) of MeCP2 regulation of gene expression (Guy et al 2011), there is ample consensus that MeCP2 is a critical component of the gene structure required for proper transcription.…”
Section: Molecular Mechanisms Of Mecp2 Functionmentioning
Gene transcription is a crucial step in the sequence of molecular, synaptic, cellular, and systems mechanisms underlying learning and memory. Here, we review the experimental evidence demonstrating that alterations in the levels and functionality of the methylated DNA-binding transcriptional regulator MeCP2 are implicated in the learning and memory deficits present in mouse models of Rett syndrome and MECP2 duplication syndrome. The significant impact that MeCP2 has on gene transcription through a variety of mechanisms, combined with well-defined models of learning and memory, make MeCP2 an excellent candidate to exemplify the role of gene transcription in learning and memory. Together, these studies have strengthened the concept that precise control of activity-dependent gene transcription is a fundamental mechanism that ensures long-term adaptive behaviors necessary for the survival of individuals interacting with their congeners in an ever-changing environment.
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