1. Overview 1 1 2 2. Tools, Techniques and Results for Porcine Transcriptome Analysis Porcine Expressed Sequence Tag Projects describe Significant Portions of the Swine Transcriptome 2 3 4 5 1 http://www.ncbi.nlm.nih.gov/UniGene/UGOrg.cgi?TAXID=9823 http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=pig 6 7 8 9 10 8 9 10 in vivo in vitro in vivo in vitro 8 11 12 13 13 Serial Analysis of Gene Expression in Porcine Tissues 14 15 15 Screening for Differentially Expressed Genes using Differential Display and Suppression Subtractive Hybridization Technology 1 16 16 17 17 18 18 19 19 20 20 21 21 22 23 23 24 24 25 Longissimus dorsi +2 25 Salmonella enterica 26 26 Quantitative PCR Methods as the “Gold” Standard in Confirming Differential Expression Results 27 28 http://www.ars.usda.gov/Services/docs.htm?docid=6065 29 30 33 34 35 36 26 29 37 38 39 in vitro 40 41 42 43 44 23 45 46 47 48 28 49 50 51 Microarray Hybridization Studies have Dramatically Expanded our Knowledge of the Porcine Transcriptome 52 3 53 2 http://www.ncbi.nlm.nih.gov/Entrez/query.fcgi?db=gene http://www.informatics.jax.org/ http://www. geneontology.org/ http://david.abcc.ncifcrf.gov/ 53 2 3. Current Expression Profiling Results in Porcine Tissues and Cells using Microarrays Muscle Expression Profiling 54 55 55 56 Longissimus dorsi 56 50 psoas psoas psoas 50 psoas 57 57 58 59 58 60 60 61 60 61 62 62 63 63 Reproductive Tissue Expression Profiling 20 20 64 64 65 9 65 66 23 7 8 7 14 15 66 67 in vivo in vitro in vivo in vivo in vitro in vitro in vivo 67 68 68 69 69 Immune Response Expression Profiling 70 in vitro 95 in vivo 71 72 72 73 73 74 Actinobacillis pleuropneumoniae 74 75 75 76 76 Escherichia coli S. enterica 77 78 in vivo E. coli 77 77 78 78 31 Salmonella ( 31 31 1 1 Toxoplasma gondii T. gondii 35 T. gondii 35 Using Microarrays to Determine Tissue-Selective Gene Expression Patterns and Microarray Applications in Other Research Areas 55 2 32 32 79 79 46 46 80 80 49 49 34 18 19 34 4. But What Does It All Mean? Pig Expression Bioinformatics and Databases At this juncture, available swine transcriptomic data, especially for microarray projects, is somewhat fragmented and sparse. Many different platforms are being used and the data is not always being submitted to a common repository. The recent public disclosure of nearly a million additional ESTs from 97 different non-normalized libraries by the Sino-Danish consortium (Gorodkin et al., submitted) will certainly improve the accuracy of EST frequency data as an estimate of expression level. To become more efficient at drawing biological meaning out of such data, more attention needs to be paid to public sharing of data and integration of that data so that an increase in power is possible. In this section, we discuss the available public resources for pig microarray and other transcriptomic data and discuss some of our efforts to integrate these platforms and data sources. Sus scrofa http://www.animalgenome.org/pigs/ http://www.ncbi.nlm.nih.gov http://www.ebi.ac.uk http://www.ncbi.nlm.nih.gov/UniGene/UGOrg.cgi?TAXID=9823 http://www.ncbi.nlm.nih.gov/geo/ http://www.ebi.ac.uk/arrayexpress/ http://compbio.dfci.harvard.edu/tgi/ http://pigest.kvl.dk/index.html http://gowhite.ans.msu.edu/public_php/showPage.php 12 46 79 http://pede.dna.affrc.go.jp/ 81 http://gnomix.ansci.umn.edu/bioinf.htm http://www.pigoligoarray.org/ http://www.afmnet.ca/index.php?fa=Research.myProject&project_id=77&page=1 A fourth database currently under construction is at Iowa State University (URL pending). Our focus is storage and analysis of data from the Affymetrix platform, although Qiagen-Operon-NRSP8 platform data is also curated. One specific interest is using expression data to help identify tissue-selective genes and across-species expression comparison of such genes to recognize evolutionarily conserved regulatory modules of interest to pig genome scientists. Here we describe some of our efforts in this area; integration and comparison of data from the two broad-coverage platforms that currently exist for the pig; the Qiagen-Operon-NRSP8 13K oligonucleotide array (hereafter abbreviated the Operon array) and the Affymetrix 23K Porcine GeneChip® (abbreviated the Affymetrix chip), both of which were discussed above. 2 2 2 2 32 32 2 2 2 2 2 2 2 2 Since Class 5 has the lowest agreement and correlations (equal to Class 3 for cross platform correlations, but with a lower within platform correlation), this result indicates that the Operon probes could cross-hybridize to either alternative splice variants or gene family members with close sequence homology that the Affymetrix platform was designed to assay separately. Further investigation is needed to see if the Operon probe is present, while the Affymetrix probe sets are absent, or if there are multiple Affymetrix probe sets present while the single Operon is absent. The results for Class 4, which have the highest agreement and the best correlation, lends support to the proposal that multiple Operon probes target the same gene product—likely by the clustering of sequences from the time the Operon chip was developed to the time the Affymetrix chip was developed. While these results already show good agreement between platforms, it will be important to update the sequence comparisons on a regular basis, especially with the Sino-Danish data, as well as the genome sequence, coming online. As part of our database we plan to develop the means to regularly develop a consensus sequence for each gene from all available sequences to map the various probes and probe sets to each other. http://www.ba.ars.usda.gov/nrfl/nutri-immun-db/nrfl_query1.html 29 31 32 82 82 5. Conclusions Functional genomics data, primarily at the RNA level currently, is accumulating rapidly for the pig species. Excellent, sensitive and broadly useful tools are already available and more will be become available within the next year. Annotation of the draft porcine genome sequence, expected in late 2007 and into 2008, will allow rapid integration of the gene expression data discussed above with gene sequences, potential splice sites, and gene families within the draft sequence. Advances in other areas of investigation in pig genetics and genomics can be anticipated. One such area would be the ability to find common regulatory sites within flanking DNA of co-expressed/co-regulated genes; leading to the identification of critical regulatory proteins in common with, or distinct from, those found in other species. Such information will reinforce the discovery of pathways through gene list annotations, improve pathway understanding through differentiation of direct targets from indirect targets of transcriptional signals, and would identify targets for manipulation of complete pathways and systems. We can also anticipate the comprehensive integration of linkage mapping and expression profiling of the same population, termed eQTL studies. Such integration of functional and structural genomic data will dramatically improve our understanding of the genetic architecture controlling quantitative traits in pigs. eQTL analyses may lead to the first application of “systems biology” to genetic improvement in the pig through the identification of cis-regulatory variation controlling an economically important phenotype. 83 Supplementary Material Supplementary Table 1 Click here for additional data file. Supplementary Table 2 Click here for additional data file.