Abstract:Histone H3K4 demethylase LSD1 plays an important role in stem cell biology, especially in the maintenance of the silencing of differentiation genes. However, how the function of LSD1 is regulated and the differentiation genes are derepressed are not understood. Here, we report that elimination of LSD1 promotes embryonic stem cell (ESC) differentiation toward neural lineage. We showed that the destabilization of LSD1 occurs posttranscriptionally via the ubiquitin-proteasome pathway by an E3 ubiquitin ligase, Ja… Show more
“…14). Notably, the protein product of JADE2 has been found to act as a ubiquitin-ligase to regulate the activity of the histone demethylase LSD1 in neuronal differentiation [76], suggesting that it may play a role in shifting the immune-related epigenetic landscape in TNBC samples. Interactive figures for these two differential correlation networks are available online (see “Availability and requirements”).Fig.…”
BackgroundDissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition.ResultsIn this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC).ConclusionsDGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0349-1) contains supplementary material, which is available to authorized users.
“…14). Notably, the protein product of JADE2 has been found to act as a ubiquitin-ligase to regulate the activity of the histone demethylase LSD1 in neuronal differentiation [76], suggesting that it may play a role in shifting the immune-related epigenetic landscape in TNBC samples. Interactive figures for these two differential correlation networks are available online (see “Availability and requirements”).Fig.…”
BackgroundDissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition.ResultsIn this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC).ConclusionsDGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0349-1) contains supplementary material, which is available to authorized users.
“…In order to gain insight into the regulation of LSD1 function after AIE exposure, we measured mRNA transcripts of selected proteins known to interact with LSD1 in the amygdala of adult rats after AIE (Figure 5A). Jade-2 was recently reported to degrade the LSD1 protein and target it for proteasomal degradation (Han et al, 2014). However, our results show that Jade2 mRNA is unaltered in the amygdala after AIE in adulthood.…”
Alcohol exposure in adolescence is an important risk factor for the development of alcoholism in adulthood. Epigenetic processes are implicated in the persistence of adolescent alcohol exposure-related changes, specifically in the amygdala. We investigated the role of histone methylation mechanisms in the persistent effects of adolescent intermittent ethanol (AIE) exposure in adulthood. Adolescent rats were exposed to 2g/kg ethanol (2 days on/off) or intermittent n-saline (AIS) during post-natal days (PND) 28-41 and used for behavioral and epigenetic studies. We found that AIE exposure caused a long-lasting decrease in mRNA and protein levels of lysine demethylase 1(Lsd1) and mRNA levels of Lsd1+8a (a neuron-specific splice variant) in specific amygdaloid structures compared to AIS-exposed rats when measured at adulthood. Interestingly, AIE increased histone H3 lysine 9 dimethylation (H3K9me2) levels in the central nucleus of the amygdala (CeA) and medial nucleus of the amygdala (MeA) in adulthood without producing any change in H3K4me2 protein levels. Acute ethanol challenge (2g/kg) in adulthood attenuated anxiety-like behaviors and the decrease in Lsd1+8a mRNA levels in the amygdala induced by AIE. AIE caused an increase in H3K9me2 occupancy at the Bdnf exon IV promoter in the amygdala that returned to baseline after acute ethanol challenge in adulthood. These results indicate that AIE specifically modulates epizymes involved in H3K9 dimethylation in the amygdala in adulthood, which are possibly responsible for AIE-induced chromatin remodeling and adult psychopathology such as anxiety.
“…A checkpoint based on normal follicle size at stage 6 is unlikely, since our experiments showed that the M-E transition can be accelerated and take place in undersized follicles. However, regulated changes in Lsd1 protein stability may play a role, since a specific ubiquitin ligase, Jade 2, targets Lsd1 for degradation via the proteasome pathway in mammalian neural progenitors (Han et al 2014), while Lsd1 turnover is attenuated by expression of the ubiquitin-specific protease Usp28 in breast cancer cells (Wu et al 2013). Perhaps the most interesting possibility is that gradual changes in the cellular chromatin state mediated by Lsd1/CoREST activity act as a ''differentiation clock.''…”
Progenitors are early lineage cells that proliferate before the onset of terminal differentiation. Although widespread, the epigenetic mechanisms that control the progenitor state and the onset of differentiation remain elusive. By studying Drosophila ovarian follicle cell progenitors, we identified lysine-specific demethylase 1 (lsd1) and CoRest as differentiation regulators using a GAL4TGFP variegation assay. The follicle cell progenitors in lsd1 or CoRest heterozygotes prematurely lose epigenetic plasticity, undergo the Notch-dependent mitotic-endocycle transition, and stop dividing before a normal number of follicle cells can be produced. Simultaneously reducing the dosage of the histone H3K4 methyltransferase Trithorax reverses these effects, suggesting that an Lsd1/CoRest complex times progenitor differentiation by controlling the stability of H3K4 methylation levels. Individual cells or small clones initially respond to Notch; hence, a critical level of epigenetic stabilization is acquired cellautonomously and initiates differentiation by making progenitors responsive to pre-existing external signals.
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