Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyse microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods cannot be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes) to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches.

A gene expression signature for insulin resistance

Insulin resistance is a heterogeneous disorder caused by a range of genetic and environmental factors, and we hypothesize that its aetiology varies considerably between individuals. This heterogeneity provides significant challenges to the development of effective therapeutic regimes for long-term management of type 2 diabetes. We describe a novel strategy, using large-scale gene expression profiling, to develop a Gene Expression Signature (GES) that reflects the overall state of insulin resistance in cells and patients. The GES was developed from 3T3-L1 adipocytes that were made ‘insulin resistant’ by treatment with tumour necrosis factor-alpha (TNFα) and then reversed with aspirin and troglitazone (‘re-sensitized’). The GES consisted of five genes whose expression levels best discriminated between the insulin resistant and insulin re-sensitized states. We then used this GES to screen a compound library for agents that affected the GES genes in 3T3- L1 adipocytes in a way that most closely resembled the changes seen when insulin resistance was successfully reversed using aspirin and troglitazone. This screen identified both known and new insulin sensitizing compounds including non-steroidal anti inflammatory agents, β-adrenergic antagonists, beta-lactams and sodium channel blockers. We tested the biological relevance of this GES in participants in the San Antonio Family Heart Study (n = 1,240) and showed that patients with the lowest GES scores were more insulin resistant (according to HOMA_IR and fasting plasma insulin levels, P < 0.001). These findings show that GES technology can be used for both the discovery of insulin sensitizing compounds and the characterization of patients into subtypes of insulin resistance according to GES scores, opening the possibility of developing a personalized medicine approach to type 2 diabetes.

Docosapentaenoic acid : its metabolism and effect on lipogenic gene expression

This thesis found that the omega-3 fatty acid, docosapentaenoic acid (DPA) down-regulates the expression levels of key lipogenic genes and proteins in vitro. In vivo studies with labelled DPA showed that, like docosahexaenoic acid, DPA is more conserved from oxidation compared with eicosapentaenoic acid.

Lactation related gene expression data

RNA sequencing and gene expression data related to lactation (mammary gland, milk and their sub compartments) obtained in a number of species (buffalo, mice, human, seal, wallaby, platypus).

Conservation of the ST6Gal I gene and its expression in the mammary gland

Milk sialoglycoconjugates can protect the gastrointestinal tract of the suckling neonate by competitively binding to invading pathogens and promoting growth of beneficial flora, and their potential role in postnatal brain development is of particular interest in human infant nutrition. Although the concentration and the distribution of sialoglycoconjugates have been extensively studied in the milk of various species, the investigation of sialyltransferase gene expression in the mammary gland, in the context of lactation, has been limited. The sialyltransferase enzyme ST6Gal I transfers sialic acid from CMP-sialic acid to type 2 (Galβ1,4GlcNAc) free disaccharides or the termini of N- or O-linked oligosaccharides using an α2,6-linkage. Expression of the ST6Gal I gene is primarily regulated at the level of transcription through the use of several cell and development- specific promoters, producing transcripts with divergent 5′ untranslated regions (UTR). In the mouse mammary gland, the novel 5′UTR exon (L) appears to be associated with a drastic increase in ST6Gal I gene expression during lactation. We find that rats also possess an exon (L), suggesting conservation of this regulatory mechanism in rodents. In contrast, an exon (L)-containing transcript was not detected in the lactating bovine or human mammary gland. We also observed a trend of increasing ST6Gal I gene expression in the bovine mammary gland, culminating in involution. This is in contrast to species such as mice where the greatest change in ST6Gal I gene expression occurs between pregnancy and lactation, suggesting different roles in rodents vs. other mammals for α2,6-sialylated oligosaccharides present in milk.

Histological and global gene expression analysis of the ‘lactating’ pigeon crop

Background: Both male and female pigeons have the ability to produce a nutrient solution in their crop for the nourishment of their young. The production of the nutrient solution has been likened to lactation in mammals, and hence the product has been called pigeon ‘milk’. It has been shown that pigeon ‘milk’ is essential for growth and development of the pigeon squab, and without it they fail to thrive. Studies have investigated the nutritional value of pigeon ‘milk’ but very little else is known about what it is or how it is produced. This study aimed to gain insight into the process by studying gene expression in the ‘lactating’ crop.
Results: Macroscopic comparison of ‘lactating’ and non-’lactating’ crop reveals that the ‘lactating’ crop is enlarged and thickened with two very obvious lateral lobes that contain discrete rice-shaped pellets of pigeon ‘milk’. This was characterised histologically by an increase in the number and depth of rete pegs extending from the basal layer of the epithelium to the lamina propria, and extensive proliferation and folding of the germinal layer into the superficial epithelium. A global gene expression profile comparison between ‘lactating’ crop and non-’lactating’ crop showed that 542 genes are up-regulated in the ‘lactating’ crop, and 639 genes are down-regulated. Pathway analysis revealed that genes up-regulated in ‘lactating’ crop were involved in the proliferation of melanocytes, extracellular matrix-receptor interaction, the adherens junction and the wingless (wnt) signalling pathway. Gene ontology analysis showed that antioxidant response and microtubule transport were enriched in ‘lactating’ crop.
Conclusions: There is a hyperplastic response in the pigeon crop epithelium during ‘lactation’ that leads to localised cellular stress and expression of antioxidant protein-encoding genes. The differentiated, cornified cells that form the pigeon ‘milk’ are of keratinocyte lineage and contain triglycerides that are likely endocytosed as very low density lipoprotein (VLDL) and repackaged as triglyceride in vesicles that are transported intracellularly by microtubules. This mechanism is an interesting example of the evolution of a system with analogies to mammalian lactation, as pigeon ‘milk’ fulfils a similar function to mammalian milk, but is produced by a different mechanism.

Simplifying gene expression microarray comparative analysis.

Gene Expression Comparative Analysis allows bioinformatics researchers to discover the conserved or specific functional regulation of genes. This is achieved through comparisons between quantitative gene expression measurements obtained in different species on different platforms to address a particular biological system. Comparisons are made more difficult due to the need to map orthologous genes between species, pre-processing of data (normalization) and post-analysis (statistical and correlation analysis). In this paper we introduce a web-based software package called EXP-PAC which provides on line interfaces for database construction and query of data, and makes use of a high performance computing platform of computer clusters to run gene sequence mapping and normalization methods in parallel. Thus, EXP-PAC facilitates the integration of gene expression data for comparative analysis and the online sharing, retrieval and visualization of complex multi-specific and multi-platform gene expression results.

Expression of the male reproduction-related gene (Mar-Mrr) in the spermatic duct of the giant freshwater prawn, Macrobrachium rosenbergii

Phosphorylated sperm proteins are crucial for sperm maturation and capacitation as a priori to their fertilization with eggs. In the freshwater prawn, Macrobrachium rosenbergii, a male reproduction-related protein (Mar-Mrr) was known to be expressed only in the spermatic ducts as a protein with putative phosphorylation and may be involved in sperm capacitation in this species. We investigated further the temporal and spatial expression of the Mar-Mrr gene using RT-PCR and in situ hybridization and the characteristics and fate of the protein using immunblotting and immunocytochemistry. The Mar-Mrr gene was first expressed in 4-week-old post larvae and the protein was produced in epithelial cells lining the spermatic ducts, at the highest level in the proximal region and decreased in the middle and distal parts. The native protein had a MW of 17 kDa and a high degree of serine/threonine phosphorylation. It was transferred from the epithelial cells to become a major protein at the anterior region of the sperm. We suggest that it is involved in sperm capacitation and fertilization in this open thelycal species and this is being investigated.