Systematic profiling of mRNA and miRNA expression in the pancreatic islets of spontaneously diabetic Goto-Kakizaki rats.

Type 2 diabetes (T2DM) is a complex multifactorial metabolic disorder that affects >100 million individuals worldwide, yet the mechanisms involved in the development and progression of the disease have not yet been fully elucidated. The present study examined the mRNA and micro (mi)RNA expression profiles by microarray analysis in the pancreas islets of spontaneously diabetic Goto-Kakizaki rats with the aim to identify regulatory mechanisms underlying the pathogenesis of T2DM. A total of 9 upregulated and 10 downregulated miRNAs were identified, including miR-150, miR-497, miR-344-3p and let-7f, which were independently validated by quantitative polymerase chain reaction assays. In addition, differential expression of 670 genes was detected by mRNA microarray analysis, including 370 upregulated and 247 downregulated genes. The differentially expressed genes were statistically associated with major cellular pathways, including the immune response pathway and the extracellular matrix (ECM)-receptor interaction pathway. Finally, a reverse regulatory association of differentially expressed miRNAs and their predicted target genes was constructed, supported by analysis of their mRNA and miRNA expression profiles. A number of key pairs of miRNA-mRNA was proposed to have significant roles in the pathogenesis of T2DM rats based on bioinformatics analysis, one example being the let-7f/collagen, type II, alpha 1 pair that may regulate ECM-receptor interactions.

Broad profiling of DNA-binding transcription factor activities improves regulatory network construction in adult mouse tissues.

Molecular systematics involves the description of the regulatory networks formed by the interconnections between active transcription factors and their target expressed genes. Here, we have determined the activities of 200 different transcription factors in six mouse tissues using an advanced mouse oligonucleotide array-based transcription factor assay (MOUSE OATFA). The transcription factor signatures from MOUSE OATFA were combined with public mRNA expression profiles to construct experimental transcriptional regulatory networks in each tissue. SRF-centered regulatory networks constructed for lung and skeletal muscle with OATFA data were confirmed by ChIP assays, and revealed examples of novel networks of expressed genes coregulated by sets of transcription factors. The combination of MOUSE OATFA with bioinformatics analysis of expressed genes provides a new paradigm for the comprehensive prediction of the transcriptional systems and their regulatory pathways in mouse.