Neuronal activity triggers widespread changes in RNA stability.

Many extracellular signals trigger changes in gene expression by altering the steady-state level of target transcripts. This modulation of transcript levels is typically ascribed to changes in transcription of target genes; however, there are numerous examples of changes in mRNA processing and stability that contribute to the overall change in transcript levels following signalling pathway activation. The alpha-factor-stimulated mating pathway in Saccharomyces cerevisiae is a receptor-operated MAP kinase cascade that results in increased levels of a large number of target mRNA transcripts when stimulated acutely. A previous study identified many of the transcripts modulated in response to alpha-factor and argued, based on genetic studies, that the response occurred solely at the level of gene transcription (Roberts et al., 2000). We directly examined whether enhanced mRNA stability contributes to the increase in the steady-state level of alpha-factor target transcripts by exploiting a temperature-sensitive RNA Polymerase II mutant, a Ste12 transcription factor import mutant, and tet-regulated synthetic mating factor minigene reporters. Examination of a panel of alpha-factor-responsive transcripts reveals no change in mRNA stability in response to alpha-factor stimulation, providing direct evidence that this signal transduction pathway in S. cerevisiae does not function through modulating transcript stability.

Neurons are exceptionally sensitive to oxidative stress, which is the basis for many neurodegenerative disease pathophysiologies. The posttranscriptional basis for neuronal differentiation and behavior is not well characterized. The steady-state levels of mRNA are outcomes of an interplay between RNA transcription and decay. However, the correlation between mRNA transcription, translation, and stability remains elusive. We utilized a SH-SY5Y-based neural differentiation model that is widely used to study neurodegenerative diseases. After neuronal differentiation, we observed enhanced sensitivity of mature neurons to mitochondrial stresses and ferroptosis induction. We employed a newly developed simplified mRNA stability profiling technique to explore the role of mRNA stability in SH-SY5Y neuronal differentiation model. Transcriptome-wide mRNA stability analysis revealed neural-specific RNA stability kinetics. Our analysis revealed that mRNA stability could either exert the buffering effect on gene products or change in the same direction as transcription. Importantly, we observed that changes in mRNA stability corrected over or under transcription of mRNAs to maintain mRNA translation dynamics. Furthermore, we conducted integrative analysis of our mRNA stability data set, and a published CRISPR-i screen focused on neuronal oxidative stress responses. Our analysis unveiled novel neuronal stress response genes that were not evident at the transcriptional or translational levels. SEPHS2 emerged as an important neuronal stress regulator based on this integrative analysis. Motif analysis unveiled SAMD4A as a major regulator of the dynamic changes in mRNA stability observed during differentiation. Knockdown of SAMD4A impaired neuronal differentiation and influenced the response to oxidative stress. Mechanistically, SAMD4A was found to alter the stability of several mRNAs. The novel insights into the interplay between mRNA stability and cellular behaviors provide a foundation for understanding neurodevelopmental processes and neurodegenerative disorders and highlight dynamic mRNA stability as an important layer of gene expression.

Colorectal carcinoma RKO cells expressing reduced levels of the RNA-binding protein HuR (ASHuR) displayed markedly reduced growth. In synchronous RKO populations, HuR was almost exclusively nuclear during early G(1), increasing in the cytoplasm during late G(1), S and G(2). The expression and half-life of mRNAs encoding cyclins A and B1 similarly increased during S and G(2), then declined, indicating that mRNA stabilization contributed to their cell cycle-regulated expression. In gel-shift assays using radiolabeled cyclin RNA transcripts and RKO protein extracts, only those transcripts corresponding to the 3'-untranslated regions of cyclins A and B1 formed RNA-protein complexes in a cell cycle-dependent fashion. HuR directly bound mRNAs encoding cyclins A and B1, as anti-HuR antibodies supershifted such RNA-protein complexes. Importantly, the expression and half-life of mRNAs encoding cyclins A and B1 were reduced in ASHuR RKO cells. Our results indicate that HuR may play a critical role in cell proliferation, at least in part by mediating cell cycle-dependent stabilization of mRNAs encoding cyclins A and B1.

Levodopa (L-DOPA) treatment in Parkinson’s disease is limited by the emergence of L-DOPA-induced dyskinesia. Such dyskinesia is associated with aberrant gene regulation in neurons of the striatum, which is caused by abnormal dopamine release from serotonin terminals. Previous work showed that modulating the striatal serotonin innervation with selective serotonin reuptake inhibitors (SSRIs) or 5-HT1A receptor agonists could attenuate L-DOPA-induced dyskinesia. We investigated the effects of a novel serotonergic agent, vilazodone, which combines SSRI and 5-HT1A partial agonist properties, on L-DOPA-induced behavior and gene regulation in the striatum in an animal model of Parkinson’s disease. After unilateral dopamine depletion by 6-hydroxydopamine (6-OHDA), rats received repeated L-DOPA treatment (5 mg/kg) alone or in combination with vilazodone (10 mg/kg) for 3 weeks. Gene regulation was then mapped throughout the striatum using in situ hybridization histochemistry. Vilazodone suppressed the development of L-DOPA-induced dyskinesia and turning behavior but did not interfere with the prokinetic effects of L-DOPA (forelimb stepping). L-DOPA treatment drastically increased the expression of dynorphin (direct pathway), 5-HT1B, and zif268 mRNA in the striatum ipsilateral to the lesion. These effects were inhibited by vilazodone. In contrast, vilazodone had no effect on enkephalin expression (indirect pathway) or on gene expression in the intact striatum. Thus, vilazodone inhibited L-DOPA-induced gene regulation selectively in the direct pathway of the dopamine-depleted striatum, molecular changes that are considered critical for L-DOPA-induced dyskinesia. These findings position vilazodone, an approved antidepressant, as a potential adjunct medication for the treatment of L-DOPA-induced motor side effects.

Liver regeneration is accompanied by a series of profound changes in hepatocyte gene expression. Similar changes in gene expression occur when hepatocytes are placed in primary culture. In the present study, we wished to determine the in vitro patterns of gene expression for several different functional classes of hepatocyte genes, and whether the changes in gene expression depended on the extracellular matrix. We therefore examined the expression of several genes which are known to change during hepatocyte proliferation in vivo or which are known to participate in different aspects of differentiated hepatocyte function. Hepatocytes were plated on collagen Type I, a matrix which supports cellular proliferation, or on the basement membrane matrix Matrigel, which supports a non-proliferating, differentiated hepatocyte phenotype. Total cellular RNA was collected after various times in culture, and cellular mRNA levels were determined by northern blot analysis for the following: transcription factors liver regeneration factor-1 (LRF-1) and CCAAT/enhancer binding protein delta (CEBPδ), the microsomal enzyme cytochrome CYP2A3 (rat orthologue of mouse CYP2A5) and the cell surface heparan sulfate proteoglycan, syndecan-2 (syn-2). Marked and rapid increases in LRF-1 and CEBPδ expression were observed on both matrix types. However, the expression of LRF-1 decreased rapidly on both matrices at 24 h, whereas CEBPδ expression was more delayed and returned to baseline values after 48 h. Messenger RNA for CYP2A3 decreased over 24 h on both matrices, but returned to 46% of control after 48 h on Matrigel which was significantly higher than hepatocytes plated on collagen. Finally, the expression of syndecan-2 was markedly decreased when hepatocytes were cultured on collagen Type I, but remained higher for hepatocytes grown on Matrigel at 48 h. For syndecan-2 it was shown that the half-life of syndecan mRNA was 1.5 fold longer on Matrigel than on collagen for the 3.4 kb mRNA, but no differences were found for the 2.2 and 1.1 kb messenger RNAs. These studies suggest that many changes in gene expression which occur in vivo during liver regeneration also occur in vitro during the transition to culture, and that some of these changes are influenced by the matrix upon which the cells are grown. Furthermore, these studies demonstrate that matrix-dependent changes in mRNA stability contribute, at least in part, to the observed changes in gene expression.

BackgroundQuiescence, reversible exit from the cell division cycle, is characterized by large-scale changes in steady-state gene expression, yet mechanisms controlling these changes are in need of further elucidation. In order to characterize the effects of post-transcriptional control on the quiescent transcriptome in human fibroblasts, we determined mRNA decay rates for over 10,000 genes using a transcription shut-off time-course.ResultsWe found that ~500 of the genes monitored exhibited significant changes in decay rate upon quiescence induction. Genes involved in RNA processing and ribosome biogenesis were destabilized with quiescence, while genes involved in the developmental process were stabilized with quiescence. Moreover, extracellular matrix genes demonstrated an upregulation of gene expression that corresponded with a stabilization of these transcripts. Additionally, targets of a quiescence-associated microRNA (miR-29) were significantly enriched in the fraction of transcripts that were stabilized during quiescence.ConclusionCoordinated stability changes in clusters of genes with important functions in fibroblast quiescence maintenance are highly correlated with quiescence gene expression patterns. Analysis of miR-29 target decay rates suggests that microRNA-induced changes in RNA stability are important contributors to the quiescence gene expression program in fibroblasts. The identification of multiple stability-related gene clusters suggests that other posttranscriptional regulators of transcript stability may contribute to the coordination of quiescence gene expression. Such regulators may ultimately prove to be valuable targets for therapeutics that target proliferative cells, for instance, in cancer or fibrosis.

This article is part of a mini review series: "Synaptic Function and Dysfunction in Brain Diseases".

Phosphorylation of HuR by Chk2 Regulates SIRT1 Expression

DNA breaks regulate neuronal activity: NMDA-receptor andionizing radiation-mediated DNA double-strand breaks governactivity regulating early-response gene expression

Acute reduction of neuronal RNA binding Elavl2 protein and Gap43 mRNA in mouse hippocampus after kainic acid treatment

Managing insomnia in children with autism spectrum disorder

Neurodevelopmental disorders (NDDs) are a complex grouping of conditions arising in childhood relating to altered development and function of the brain. The primary conditions classified as NDDs include autism spectrum disorder (ASD), intellectual disability, attention deficit hyperactivity disorder, as well as motor, communication, and specific learning disorders. Many NDDs are known to have significant genetic risk, but the particular genes and molecular pathways controlling this genetic risk are still poorly understood. In addition to the genetic etiology of NDDs themselves, understanding the role of genetics in commonly associated comorbidities, such as sleep dysfunction or epilepsy in ASD, and how these insights might be leveraged to develop new therapeutics, remains a central goal of NDD genetic research. In ASD in particular, mutations in more than 100 genes have been significantly linked to increased risk for ASD. However, projections based on the frequency of mutations in these known risk genes has suggested that over 1000 genes may significantly increase risk for ASD when mutated. In response to this prediction, several machine learning approaches have been developed to use genome-wide data sources to predict which genes are the best candidates for ASD risk gene discovery. However, with different sources of data and training strategies used for each of these scores, there is not a clear consensus in the community on the most important predictors of genetic risk. My work develops a new ASD risk gene score that combines the benefits of all prior scores through a machine learning approach called ”ensemble learning”, unifying the previous scores while providing additional genome-wide data sources for model training. By comparing the previous scores with my work, I demonstrate the effectiveness of ensemble learning in this setting, and provide an ASD risk gene score that is enriched across a variety of ASD genetic data domains, such as common variant risk and gene expression data. While ASD as a whole has many known genetic associations, differences in medical issues experienced by those with ASD are highly variable, and the genetic factors underlying these comorbidities remain unclear. For instance, more than 70% of individuals with ASD have issues with sleep, but it is unknown whether genetic changes explain this difference seen between individuals with of ASD. Simply put, we know that genetics plays a large role in ASD, but we do not know the specifics of how genes map to subtypes of ASD. My work bridges this gap by studying the genetics of sleep dysfunction within individuals with ASD. To my knowledge, I am the first to be able to demonstrate and report that sleep dysfunction in ASD has a significant genetic component. Further, I find that genetic risk for ADHD, BMI, and several other conditions heightens an autistic individual’s risk for having issues with sleep. This work also uncovers associations between the type of sleep issue an individual has and the drugs that may be most effective for restoring normal sleep. Another major medical issue faced by individuals with ASD is epilepsy, with over 20% of individuals diagnosed with ASD having or going on to develop epilepsy later in life. Similar to sleep issues in ASD, treatment options in epilepsy are often effective but fall short in approximately 30% of cases. Finding treatments for these individuals who fail to find relief from the standard of care options is of critical importance. My work uses a bioinformatic technique called drug repositioning to computationally prioritize drugs that may be capable of reversing the transcriptional state induced by epilepsy. This approach yielded 184 potential therapeutic compounds, of which 4 were selected and tested in a zebrafish model of epilepsy. Three of the four compounds showed significant seizure suppression activity, including one with no previous literature surrounding its use in epilepsy (pyrantel tartrate). While a diverse set of work, the common thread is leveraging computational genetic techniques to better understand the causes, symptoms, and treatments of neurodevelopmental and associated disorders. By using ensemble learning, this work establishes a unified autism risk gene score that effectively summarizes a gene’s level of association with autism. Through studying sleep issues in ASD, I find a significant role for common variant risk and establish several genetic associations for poor sleep in ASD, such as ADHD and BMI genetic risk factors. Lastly, by using gene expression to model an effective therapeutic for epilepsy, this work reports on the first possible use of pyrantel tartrate in the treatment of epilepsy. Taken together, these findings demonstrate the power of leveraging big genetic datasets and innovative techniques in order to understand complex disease.

Schizophrenia candidate genes participate in common molecular pathways that are regulated by activity-dependent changes in neurons. One important next step is to further our understanding on the role of activity-dependent changes of gene expression in the etiopathogenesis of schizophrenia. To examine whether neuronal activity-dependent changes of gene expression are dysregulated in schizophrenia. Neurons differentiated from human-induced pluripotent stem cells derived from 4 individuals with schizophrenia and 4 unaffected control individuals were depolarized using potassium chloride. RNA was extracted followed by genome-wide profiling of the transcriptome. Neurons were planted on June 21, 2013, and harvested on August 2, 2013. We performed differential expression analysis and gene coexpression analysis to identify activity-dependent or disease-specific changes of the transcriptome. Gene expression differences were assessed with linear models. Furthermore, we used gene set analyses to identify coexpressed modules that are enriched for schizophrenia risk genes. We identified 1669 genes that were significantly different in schizophrenia-associated vs control human-induced pluripotent stem cell-derived neurons and 1199 genes that are altered in these cells in response to depolarization (linear models at false discovery rate ≤0.05). The effect of activity-dependent changes of gene expression in schizophrenia-associated neurons (59 significant genes at false discovery rate ≤0.05) was attenuated compared with control samples (594 significant genes at false discovery rate ≤0.05). Using gene coexpression analysis, we identified 2 modules (turquoise and brown) that were associated with diagnosis status and 2 modules (yellow and green) that were associated with depolarization at a false discovery rate of ≤0.05. For 3 of the 4 modules, we found enrichment with schizophrenia-associated variants: brown (χ2 = 20.68; P = .002), turquoise (χ2 = 12.95; P = .04), and yellow (χ2 = 15.34; P = .02). In this analysis, candidate genes clustered within gene networks that were associated with a blunted effect of activity-dependent changes of gene expression in schizophrenia-associated neurons. Overall, these findings link schizophrenia candidate genes with specific molecular functions in neurons, which could be used to examine underlying mechanisms and therapeutic interventions related to schizophrenia.

The promise of precision medicine in autism

BackgroundMBD5, encoding the methyl-CpG-binding domain 5 protein, has been proposed as a necessary and sufficient driver of the 2q23.1 microdeletion syndrome. De novo missense and protein-truncating variants from exome sequencing studies have directly implicated MBD5 in the etiology of autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDDs). However, little is known concerning the specific function(s) of MBD5.MethodsTo gain insight into the complex interactions associated with alteration of MBD5 in individuals with ASD and related NDDs, we explored the transcriptional landscape of MBD5 haploinsufficiency across multiple mouse brain regions of a heterozygous hypomorphic Mbd5+/GT mouse model, and compared these results to CRISPR-mediated mutations of MBD5 in human iPSC-derived neuronal models.ResultsGene expression analyses across three brain regions from Mbd5+/GT mice showed subtle transcriptional changes, with cortex displaying the most widespread changes following Mbd5 reduction, indicating context-dependent effects. Comparison with MBD5 reduction in human neuronal cells reinforced the context-dependence of gene expression changes due to MBD5 deficiency. Gene co-expression network analyses revealed gene clusters that were associated with reduced MBD5 expression and enriched for terms related to ciliary function.LimitationsThese analyses included a limited number of mouse brain regions and neuronal models, and the effects of the gene knockdown are subtle. As such, these results will not reflect the full extent of MBD5 disruption across human brain regions during early neurodevelopment in ASD, or capture the diverse spectrum of cell-type-specific changes associated with MBD5 alterations.ConclusionsOur study points to modest and context-dependent transcriptional consequences of Mbd5 disruption in the brain. It also suggests a possible link between MBD5 and perturbations in ciliary function, which is an established pathogenic mechanism in developmental disorders and syndromes.