Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from...

Area of Science:

• Genomics
• Transcriptomics
• Human Biology

Background:

• Understanding normal human tissue transcriptome profiles is crucial for disease state identification and marker discovery.
• Previous large-scale transcriptome data were generated using RNA-Sequencing (RNA-Seq) and Capped Analysis of Gene Expression (CAGE).

Purpose of the Study:

• To perform the first large-scale comparison of full-length mRNA sequencing (RNA-Seq) versus 5'-capped mRNA sequencing (CAGE) data across complex human tissues.
• To assess the concordance and complementarity of these two major transcriptome profiling methods.

Main Methods:

• Comparative analysis of transcriptome data from 22 human tissues.
• Utilized Illumina-sequenced RNA-Seq and Heliscope-sequenced CAGE data.
• Evaluated gene expression correlation, genome-wide agreement for ubiquitously expressed genes, and tissue-specific enrichment patterns.

Main Results:

• High overall gene expression correlation (R > 0.8) was observed between RNA-Seq and CAGE across 22 tissues.
• 91% agreement was found for ubiquitously expressed genes, with minor discrepancies suggesting gene model updates.
• Up to 75% of single-tissue enriched genes showed consensus enrichment, while 17% displayed varied enrichment patterns potentially due to sample composition.

Conclusions:

• RNA-Seq and CAGE transcriptome data are highly complementary for refining gene model annotations.
• These datasets reveal complexities within tissue transcriptomes, influenced by cell type proportions.
• Integrating transcriptome data with image-based protein expression enhances understanding of gene expression specificities.