Using an exon microarray to identify a global profile of gene expression and alternative splicing in K562 cells exposed to sodium valproate

Transcriptional analysis of sodium valproate in a serotonergic cell line reveals gene regulation through both HDAC inhibition-dependent and independent mechanisms

Sodium valproate (VPA) is a histone deacetylase (HDAC) inhibitor, widely prescribed in the treatment of bipolar disorder, and yet the precise modes of therapeutic action for this drug are not fully understood. After exposure of the rat serotonergic cell line RN46A to VPA, RNA-sequencing (RNA-Seq) analysis showed widespread changes in gene expression. Analysis by four bioinformatic pipelines revealed as many as 230 genes were significantly upregulated and 72 genes were significantly downregulated. A subset of 23 differentially expressed genes was selected for validation using the nCounter® platform, and of these we obtained robust validation for ADAM23, LSP1, MAOB, MMP13, PAK3, SERPINB2, SNAP91, WNT6, and ZCCHC12. We investigated the effect of lithium on this subset and found four genes, CDKN1C, LSP1, SERPINB2, and WNT6 co-regulated by lithium and VPA. We also explored the effects of other HDAC inhibitors and the VPA analogue valpromide on the subset of 23 selected genes. Expression of eight of these genes, CDKN1C, MAOB, MMP13, NGFR, SHANK3, VGF, WNT6 and ZCCHC12, was modified by HDAC inhibition, whereas others did not appear to respond to several HDAC inhibitors tested. These results suggest VPA may regulate genes through both HDAC-dependent and independent mechanisms. Understanding the broader gene regulatory effects of VPA in this serotonergic cell model should provide insights into how this drug works and whether other HDAC inhibitor compounds may have similar gene regulatory effects, as well as highlighting molecular processes that may underlie regulation of mood.

Triple-layer dissection of the lung adenocarcinoma transcriptome: regulation at the gene, transcript, and exon levels

Lung adenocarcinoma is one of the most deadly human diseases. However, the molecular mechanisms underlying this disease, particularly RNA splicing, have remained underexplored. Here, we report a triple-level (gene-, transcript-, and exon-level) analysis of lung adenocarcinoma transcriptomes from 77 paired tumor and normal tissues, as well as an analysis pipeline to overcome genetic variability for accurate differentiation between tumor and normal tissues. We report three major results. First, more than 5,000 differentially expressed transcripts/exonic regions occur repeatedly in lung adenocarcinoma patients. These transcripts/exonic regions are enriched in nicotine metabolism and ribosomal functions in addition to the pathways enriched for differentially expressed genes (cell cycle, extracellular matrix receptor interaction, and axon guidance). Second, classification models based on rationally selected transcripts or exonic regions can reach accuracies of 0.93 to 1.00 in differentiating tumor from normal tissues. Of the 28 selected exonic regions, 26 regions correspond to alternative exons located in such regulators as tumor suppressor (GDF10), signal receptor (LYVE1), vascular-specific regulator (RASIP1), ubiquitination mediator (RNF5), and transcriptional repressor (TRIM27). Third, classification systems based on 13 to 14 differentially expressed genes yield accuracies near 100%. Genes selected by both detection methods include C16orf59, DAP3, ETV4, GABARAPL1, PPAR, RADIL, RSPO1, SERTM1, SRPK1, ST6GALNAC6, and TNXB. Our findings imply a multilayered lung adenocarcinoma regulome in which transcript-/exon-level regulation may be dissociated from gene-level regulation. Our described method may be used to identify potentially important genes/transcripts/exonic regions for the tumorigenesis of lung adenocarcinoma and to construct accurate tumor vs. normal classification systems for this disease.

Alternative splicing events is not a key event for gene expression regulation in uremia

Background

The control of gene expression in the course of chronic kidney disease (CKD) is not well addressed. Alternative splicing is a common way to increase complexity of proteins. More than 90% of human transcripts are alternatively spliced. We hypothesised that CKD can induce modification of the alternative splicing machinery.

Methods

During mutation screening in autosomal dominant polycystic kidney disease, we identified in mononuclear cells (PBMC), an alternative splicing event on the exon 30 of PKD1 gene, the gene implicated in this disease. This alternative splice variant was not correlated with the cystic disease but with CKD. To confirm the association between this variant and CKD, a monocentric clinical study was performed with 3 different groups according to their kidney function (CKD5D, CKD3-5 and normal kidney function). An exon microarray approach was used to highlight splicing events in whole human genome in a normal cell model (fibroblasts) incubated with uremic serum. Alternative splicing variants identified were confirmed by RT-PCR.

Results

The splicing variant of the exon 30 of PKD1 was more frequent in PBMCs from patients with CKD compared to control. With the microarray approach, despite the analysis of more than 230 000 probes, we identified 36 genes with an abnormal splicing index evocating splicing event in fibroblasts exposed to uremic serum. Only one abnormal splicing event in one gene, ADH1B, was confirmed by RT-PCR.

Conclusion

We observed two alternative spliced genes in two different cell types associated with CKD. Alternative splicing could play a role in the control of gene expression during CKD but it does not seem to be a major mechanism.

Analyzing gene expression profile in K562 cells exposed to sodium valproate using microarray combined with the connectivity map database

To explore the mechanism underlying antileukaemia effect of sodium valproate, the growth and survival of the K562 cell line were investigated. Global profiles of gene expression in K562 cells exposed to sodium valproate were assessed and validated. The differentially expressed genes identified were further used to query the connectivity map database to retrieve a ranked list of compounds that act on the same intracellular targets as sodium valproate. A significant increase in cell apoptosis and a change in gene expression profile were observed in valproate-exposed K562 cells. The significant enrichment analysis of gene ontology terms for the differentially expressed genes showed that these genes were involved in many important biological processes. Eight differentially expressed genes involved in apoptosis were verified by quantitative real-time PCR. The connectivity map analysis showed gene expression profile in K562 cells exposed to sodium valproate was most similar to that of HDACi and PI3K inhibitors, suggesting that sodium valproate might exert antileukaemic action by inhibiting HDAC as well as inhibiting PI3K pathway. In conclusion, our data might provide clues to elucidate the molecular and therapeutic potential of VPA in leukaemia treatment, and the connectivity map is a useful tool for exploring the molecular mechanism of drug action.