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The post-mortem bipolar disorder (BD) gene expression dataset was created using RNA sequencing (RNAseq) data from post-mortem dorsolateral prefrontal cortex (DLPFC) samples obtained from BD patients and healthy controls (HC). This dataset was used to create gene regulatory networks, which were then compared to a list of genes related to melatonin synthesis, signalling, and degradation using gene set enrichment analysis (GSEA), and to gene regulatory networks for melatonin agonists. The <t>NT2-N</t> gene expression dataset was created using RNAseq libraries prepared from differentiated NT2-N neurons treated with various mood stabilisers for 24 hours. This dataset was then compared to a list of melatonin-related genes using GSEA. [Created by authors with biorender.com ]
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The post-mortem bipolar disorder (BD) gene expression dataset was created using RNA sequencing (RNAseq) data from post-mortem dorsolateral prefrontal cortex (DLPFC) samples obtained from BD patients and healthy controls (HC). This dataset was used to create gene regulatory networks, which were then compared to a list of genes related to melatonin synthesis, signalling, and degradation using gene set enrichment analysis (GSEA), and to gene regulatory networks for melatonin agonists. The NT2-N gene expression dataset was created using RNAseq libraries prepared from differentiated NT2-N neurons treated with various mood stabilisers for 24 hours. This dataset was then compared to a list of melatonin-related genes using GSEA. [Created by authors with biorender.com ]

Journal: bioRxiv

Article Title: Investigating the role of melatonin in bipolar disorder using transcriptomics

doi: 10.1101/2025.09.03.673928

Figure Lengend Snippet: The post-mortem bipolar disorder (BD) gene expression dataset was created using RNA sequencing (RNAseq) data from post-mortem dorsolateral prefrontal cortex (DLPFC) samples obtained from BD patients and healthy controls (HC). This dataset was used to create gene regulatory networks, which were then compared to a list of genes related to melatonin synthesis, signalling, and degradation using gene set enrichment analysis (GSEA), and to gene regulatory networks for melatonin agonists. The NT2-N gene expression dataset was created using RNAseq libraries prepared from differentiated NT2-N neurons treated with various mood stabilisers for 24 hours. This dataset was then compared to a list of melatonin-related genes using GSEA. [Created by authors with biorender.com ]

Article Snippet: This dataset consists of RNAseq data collected from human NT2 teratocarcinoma cells (ATCC, United States; RRID: CVCL_0034).

Techniques: Gene Expression, RNA Sequencing