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

Abstract

Background: The recent development within high-throughput technologies for expression profiling has allowed for parallel analysis of transcriptomes and proteomes in biological systems such as comparative analysis of transcript and protein levels of tissue regulated genes. Until now, such studies of have only included microarray or short length sequence tags for transcript profiling. Furthermore, most comparisons of transcript and protein levels have been based on absolute expression values from within the same tissue and not relative expression values based on tissue ratios.

Results: Presented here is a novel study of two porcine tissues based on integrative analysis of data from expression profiling of identical samples using cDNA microarray, 454-sequencing and iTRAQ-based proteomics. Sequence homology identified 2.541 unique transcripts that are detectable by both microarray hybridizations and 454-sequencing of 1.2 million cDNA tags. Both transcript-based technologies showed high reproducibility between sample replicates of the same tissue, but the correlation across these two technologies was modest. Thousands of genes being differentially expressed were identified with microarray. Out of the 306 differentially expressed genes, identified by 454-sequencing, 198 (65%) were also found by microarray. The relationship between the regulation of transcript and protein levels was analyzed by integrating iTRAQ-based proteomics data. Protein expression ratios were determined for 354 genes, of which 148 could be mapped to both microarray and 454-sequencing data. A comparison of the expression ratios from the three technologies revealed that differences in transcript and protein levels across heart and muscle tissues are positively correlated.

Conclusion: We show that the reproducibility within cDNA microarray and 454-sequencing is high, but that the agreement across these two technologies is modest. We demonstrate that the regulation of transcript and protein levels across identical tissue samples is positively correlated when the tissue expression ratios are used for comparison. The results presented are of interest in systems biology research in terms of integration and analysis of high-throughput expression data from mammalian tissues.

Figure 1

Overview of the experimental design. For microarray and iTRAQ, a common reference sample (REF) was constructed by combining the three samples from heart (HEA1, HEA2 and HEA3) and three samples from the skeletal muscle Longissimus dorsi (LDO1, LDO2, and LDO3). In the microarray experiment, three cDNA microarray slides were used per sample.

Figure 2

Reproducibility within and across transcript-based technologies. Average correlation between transcript RA profiles from heart and skeletal muscle tissues within and across the two transcript-based technologies 454-sequencing and cDNA microarray. Black vertical error bars indicate the minimum and maximum values of the Pearson's correlations used to calculate average correlation.

Figure 3

Comparison of differentially expressed genes across transcript-based technologies. Level of agreement between 454-sequencing and cDNA microarray in the direction of regulation for 198 genes identified as significantly (adj. P ≤ 0.05) regulated between heart and skeletal muscle by both technologies. The scatter plot shows the log2 of the ratios between heart and skeletal muscle obtained with 454-sequencing plotted against those obtained with cDNA microarray. Red spots: 113 genes being up-regulated in heart compared to skeletal muscle were identified with both 454-sequencing and cDNA microarray. Green spots: 47 genes being down-regulated in heart compared to skeletal muscle were identified with both 454-sequencing and cDNA microarray. Yellow spots: 6 genes being up-regulated in heart compared to skeletal muscle were identified with cDNA microarray but found to be down-regulated with 454-sequencing. Blue spots: 32 genes being up-regulated in heart compared to skeletal muscle were identified with 454 but found to be down-regulated with cDNA microarray.

Figure 4

Comparison of tissue expression ratios from transcriptomic and proteomic profiling. Pair-wise comparison of heart-muscle log2 expression ratios obtained by 454-sequencing, cDNA microarray and iTRAQ-based proteomics for 148 genes detectable by all three technologies. Thick lines represent fitted straight lines from the data points. The distances between the thick and thin lines are equal to one time the standard deviation of all distances from data points to the fitted lines. The black data points between the two thin lines were considered to represent genes where transcript and protein ratios are in concordance, whereas the outside red data points were considered to represent genes where transcript and protein ratios are not in concordance (red).