Orthologous gene-expression profiling in multi-species models: search for candidate genes

Abstract

Microarray-driven gene-expression profiles are generally produced and analyzed for a single specific experimental model. We have assessed an analytical approach that simultaneously evaluates multi-species experimental models within a particular biological condition using orthologous genes as linkers for the various Affymetrix microarray platforms on multi-species models of ventilator-associated lung injury. The results suggest that this approach may be a useful tool in the evaluation of biological processes of interest and selection of process-related candidate genes.

Figure 1

Overlaps between rat (U34A GeneChip), mouse (U74A GeneChip) and human (U95A GeneChip) Affymetrix array platforms based on the human (U133A GeneChip) ortholog assignments. The sum of numbers inside each circle represents the total number of ortholog pairs formed with reference genes on the U133A GeneChip by corresponding arrays (see also Table 1). The reference genes formed 3,077 pairs with corresponding orthologs that were represented on all depicted arrays.

Figure 2

Schema of the centric approach in ortholog-linked database building and putative ortholog detection. (a) An example of putative ortholog creation for the ornithine decarboxylase 1 (ODC-1) gene. U74A and U34A probe IDs were EGO orthologs (solid line) for the U133A and U95A ODC-1 gene but were not directly linked (dashed line) either in EGO or in the Affymetrix ortholog table. (b) The reference genes common to all arrays (see Figure 1) and their corresponding orthologs for U95A-U74A, U95A-U34A, and U74A-U34A pairs were permutated and all possible combinations counted (dashed lines). EGO combinations were retrieved from RESOURCERER-generated tables for these paired arrays and counted (solid lines). The difference in the predicted and existing pairs represents the number of putative orthologs to be created, based on homology to the common reference gene.

Figure 3

Experimental data used for populating the ortholog-link database. (a) Using Affymetrix MAS 5.0 software, absent (black), marginal (white) and present (gray) transcript-abundance calls were counted for each experimental dataset and the values obtained expressed as a percentage of all calls. (b) By masking poorly performing probes for U95A, U74A and U34A, the present call ratio for these GeneChips was increased by 25%. As dog mRNA was hybridized to the human U133A chip, the present call ratio for this hetero-hybridization was much lower than that in other experiments. We therefore corrected U133A probe sets for differences in gene sequence between human and canine, which increased the present call ratio by more than 50%.

Figure 4

Overall distribution of orthologs among reference genes. Most of the reference genes (1,088) had only one ortholog on each of the U95A, U74A and U34A arrays used in these studies. The first bar shown here represents the number of reference genes that had three orthologs. The majority of remaining reference genes had two orthologs on one of the studied arrays. Overall, about 62% of reference genes had at least one multiple ortholog set.

Figure 5

Distribution of co-regulated and inversely regulated biological bioprocesses identified by linkage to GO. (a) Genes involved in a co-regulated bioprocess (inflammatory response; GO 6954) and (b) an inversely regulated bioprocess (DNA-dependent regulation of transcription; GO 6355). Solid areas under the curve represent upregulated genes and gray areas under the curve represent downregulated genes. (c) A summary of all co-regulated (top curve) and inversely regulated (bottom curve) GO bioprocesses identified by MAPPFinder corresponding to the increment in the fold-change cutoff.