transcriptomewide

The term transcriptomewide is used to describe analyses or measurements that cover the entire transcriptome, the complete set of RNA transcripts produced by the genome in a given cell, tissue, or condition. It is typically based on high-throughput sequencing technologies such as RNA sequencing (RNA-seq) and can be conducted at gene, transcript, or isoform resolution. The term is sometimes written as transcriptome-wide.

Common goals of transcriptomewide studies include quantifying expression levels across many transcripts, identifying differential expression between conditions, and characterizing alternative splicing and transcript usage. Data processing involves alignment, transcript quantification, normalization, and methods to account for technical and biological variation. Analyses are subject to challenges such as multiple testing, annotation uncertainty, and transcript-level ambiguity, particularly for isoform resolution.

A notable application is transcriptomewide association studies (TWAS), which integrate transcriptome and genetic data to associate transcript expression with traits or diseases, often leveraging expression quantitative trait loci (eQTL) resources. Other approaches include differential expression analysis, co-expression network construction, and isoform-level investigations to explore regulatory programs across the transcriptome.

Limitations and considerations include the need for robust reference annotations, careful handling of batch effects, and interpretation when transcripts map ambiguously to genes. The transcriptomewide perspective contrasts with genome-wide approaches by emphasizing expression, regulation, and function across all transcripts rather than just genomic loci.