M.H. Pool

Comparison of prenatal muscle tissue expression profiles of two pig breeds differing in muscle characteristics.

The objective of this study was to compare purebred Duroc and Pietrain prenatal muscle tissue transcriptome expression levels at different stages of prenatal development to gain insight into the differences in muscle tissue development in these pig breeds. Commercial western pig breeds have been selected for muscle growth for the past 2 decades. Pig breeds differ for their muscle phenotypes (i.e., myofiber numbers and myofiber types). Duroc and Pietrain pig breeds are extremes; Duroc pigs have redder muscle fiber types with more intramuscular fat, and Pietrain pigs have faster-growing and whiter muscle fiber types. Pietrain pigs are more muscular than Duroc pigs, whereas Duroc pigs are fatter than Pietrain pigs. The genomic background underlying these breed-specific differences is poorly known. Myogenesis is a complex exclusive prenatal process involving proliferation and differentiation (i.e., fusion) of precursor cells called myoblasts. We investigated the difference in the prenatal muscle-specific transcriptome profiles of Duroc and Pietrain pigs using microarray technology. The microarray contained more than 500 genes affecting myogenesis, energy metabolism, muscle structural genes, and other genes from a porcine muscle cDNA library. The results indicated that the expression of the myogenesis-related genes was greater in early Duroc embryos than in early Pietrain embryos (14 to 49 d of gestation), whereas the opposite was found in late embryos (63 to 91 d of gestation). These findings suggest that the myogenesis process is more intense in early Duroc embryos than in Pietrain embryos but that myogenesis is more intense in late Pietrain fetuses than in Duroc fetuses. Transcriptomes of muscle structural genes followed that pattern. The energy metabolism genes were expressed at a higher level in prenatal Pietrain pigs than in prenatal Duroc pigs, except for d 35, when the opposite situation was found. Fatty acid metabolism genes were expressed at a higher level in early (14 to 49 d of gestation) Duroc embryos than in Pietrain embryos. Better understanding of the genomic regulation of tissue formation leads to improved knowledge of the genome under selection and may lead to directed breed-specific changes in the future.

Biochemical pathways analysis of microarray results: regulation of myogenesis in pigs

BackgroundCombining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet.Mammalian muscle formation has been previously studied using microarray technology in pigs because these animals are an interesting animal model for muscle formation due to selection for increased muscle mass. Results indicated regulation of the expression of genes involved in proliferation and differentiation of myoblasts, and energy metabolism. The aim of the present study was to analyse microarrays studying myogenesis in pigs. It was necessary to develop methods to search biochemical pathways databases.ResultsPERL scripts were developed that used the names of the genes on the microarray to search databases. Synonyms of gene names were added to the list by searching the Gene Ontology database. The KEGG database was searched for pathway information using this updated gene list. The KEGG database returned 88 pathways. Most genes were found in a single pathway, but others were found in up to seven pathways. Combining the pathways and the microarray information 21 pathways showed sufficient information content for further analysis. These pathways were related to regulation of several steps in myogenesis and energy metabolism. Pathways regulating myoblast proliferation and muscle fibre formation were described. Furthermore, two networks of pathways describing the formation of the myoblast cytoskeleton and regulation of the energy metabolism during myogenesis were presented.ConclusionCombining microarray results and pathways information available through the internet provide biological insight in how the process of porcine myogenesis is regulated.

Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.

A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1) Add synonyms of gene names by searching the Gene Ontology (GO) database. (2) Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database for pathway information using this GO-enriched gene list. (3) Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example.

Analysis of the real EADGENE data set: Multivariate approaches and post analysis (Open Access publication)

The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.

The EADGENE Microarray Data Analysis Workshop (Open Access publication)

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.