Transcriptomic and proteomic profiling of two porcine tissues using high-throughput technologies.

Area of Science:

• Systems biology
• Genomics
• Proteomics

Background:

• High-throughput technologies enable parallel analysis of transcriptomes and proteomes.
• Previous studies primarily used microarray or short sequence tags for transcript profiling.
• Comparisons of transcript and protein levels often relied on absolute values within a single tissue.

Purpose of the Study:

• To conduct an integrative analysis of transcript and protein expression in porcine tissues.
• To compare data from cDNA microarray, 454-sequencing, and iTRAQ-based proteomics.
• To investigate the correlation between transcript and protein level regulation using relative tissue ratios.

Main Methods:

• Utilized cDNA microarray, 454-sequencing, and iTRAQ-based proteomics on identical porcine tissue samples.
• Analyzed sequence homology to identify common transcripts between microarray and 454-sequencing.
• Integrated proteomics data to determine protein expression ratios and compare with transcript data.

Main Results:

• Identified 2,541 unique transcripts detectable by both microarray and 454-sequencing.
• Transcript-based technologies demonstrated high reproducibility but modest correlation across platforms.
• Found a positive correlation between transcript and protein level regulation when using tissue expression ratios.

Conclusions:

• Reproducibility is high within cDNA microarray and 454-sequencing, but agreement across them is modest.
• Transcript and protein level regulation is positively correlated across identical tissue samples using relative ratios.
• Results are valuable for integrating and analyzing high-throughput expression data in mammalian systems biology.