Sus scrofa, the domestic pig, is a model organism relevant for food production and for human biomedical research. The availability of an increasingly large amount of public proteomics datasets in ProteomeXchange and in the PRIDE database (https://www.ebi.ac.uk/pride/) in particular, presents an opportunity for performing combined meta-analyses to generate comprehensive organism-wide protein expression maps across different organisms and biological conditions. To enable the access to proteomics data by the wider scientific community, the PRIDE team is developing data dissemination and integration pipelines with existing popular resources so that proteomics data is made more accessible. We have already performed combined analyses of baseline (without any perturbation) protein expression for human, mouse and rat tissues.

Here we reanalysed 14 public proteomics datasets from the PRIDE database coming from pig tissues to assess baseline (without any biological perturbation) protein abundance in 14 organs, encompassing a total of 20 healthy tissues from 128 samples. The analysis involved the quantification of protein abundance in 599 mass spectrometry runs.

We compared protein expression patterns among different pig organs and examined the distribution of proteins across these organs. The number of canonical proteins per dataset ranged from 789 (dataset PXD002918, biceps femoris) to 6,062 (dataset PXD012636, heart). Then, we studied how protein abundances compared across different datasets and studied the tissue specificity of the detected proteins. Of particular interest, we conducted a comparative analysis of protein expression between pig and human tissues (from a previous study performed following the same methodology), revealing a high degree of correlation in protein expression among orthologs, particularly in brain, kidney, heart, and liver samples. Additionally, we analysed the differences in quantitative expression of proteins across organs between human and pig organs.

We have integrated the protein expression results into EBI"s Expression Atlas resource (https://www.ebi.ac.uk/gxa/) for easy access and visualisation of the protein expression data individually or alongside gene expression data.