transcriptome
Definition
The transcriptome is the complete set of RNA transcripts produced by the genome under specific circumstances or in a specific cell type. Unlike the static genome, the transcriptome is highly dynamic, varying across cell types, developmental stages, and environmental conditions. It includes messenger RNA (mRNA), ribosomal RNA (rRNA), transfer RNA (tRNA), and various non-coding RNAs. Transcriptome analysis, typically performed through RNA sequencing (RNA-seq), reveals which genes are actively expressed, at what levels, and how expression patterns change in response to stimuli. This information is crucial for understanding cellular function, disease mechanisms, and identifying therapeutic targets, as gene expression levels often correlate more closely with phenotype than genome sequence alone.
Visualize transcriptome in Nodes Bio
Researchers can use Nodes Bio to visualize transcriptomic data as gene regulatory networks, mapping relationships between differentially expressed genes, transcription factors, and their targets. Network analysis reveals co-expression modules, identifies hub genes driving disease phenotypes, and integrates transcriptome data with protein-protein interactions or metabolic pathways. This enables discovery of key regulatory nodes and causal relationships between gene expression changes and biological outcomes.
Visualization Ideas:
- Gene co-expression networks showing modules of coordinately regulated genes
- Transcription factor-target gene regulatory networks from transcriptomic data
- Multi-omics integration networks connecting transcriptome with proteome and metabolome data
Example Use Case
A cancer research team performs RNA-seq on tumor samples versus healthy tissue to identify the transcriptomic signature of aggressive melanoma. They discover 2,000 differentially expressed genes but need to understand functional relationships. By visualizing these genes as a network in Nodes Bio, they identify a cluster of upregulated genes centered around the transcription factor MITF, revealing a melanocyte differentiation program gone awry. This network-based approach highlights MITF and its direct targets as potential therapeutic intervention points.