Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques.

Integrative genomics and genetics approaches have proven to be a useful tool in elucidating the complex relationships often found in gene regulatory networks. More importantly, a number of studies have provided the necessary experimental evidence confirming the validity of the causal relationships inferred using such an approach. By integrating messenger RNA (mRNA) expression data with microRNA (miRNA) (i.e. small non-coding RNA with well-established regulatory roles in a myriad of biological processes) expression data, we show how integrative genomics approaches can be used to characterize the role played by approximately a third of registered mouse miRNAs within the context of a liver gene regulatory network. Our analysis reveals that the transcript abundances of miRNAs are subject to regulatory control by many more loci than previously observed for mRNA expression. Moreover, our results indicate that miRNAs exist as highly connected hub-nodes and function as key sensors within the transcriptional network. We also provide evidence supporting the hypothesis that miRNAs can act cooperatively or redundantly to regulate a given pathway and that miRNAs play a subtle role by dampening expression of their target gene through the use of feedback loops.

Assessing the prospects of genome-wide association studies performed in inbred mice.

The remarkable success in mapping genes linked to a number of disease traits using genome-wide association studies (GWAS) in human cohorts has renewed interest in applying this same technique in model organisms such as inbred laboratory mice. Unlike humans, however, the limited genetic diversity in the ancestry of laboratory mice combined with selection pressure over the past decades have yielded an intricate population genetic structure that can complicate the results obtained from association studies. This problem is further exacerbated by the small number of strains typically used in such studies where multiple spurious associations arise as a result of random chance. We sought to empirically assess the viability of GWAS in inbred mice using hundreds of expression traits for which the true location of the expression quantitative trait locus was known a priori. We then measured transcript abundance levels for these expression traits in 16 classical and 3 wild-derived inbred strains and carried out a genome-wide association scan, demonstrating the low statistical power of such studies and empirically estimating the large extent to which allelic association of transcripts gives rise to spurious associations. We provide evidence illustrating that in a large fraction of cases, the marker with the most significant p values fails to map to the location of the true eQTL. Finally, we provide experimental support for hundreds of traits, and that combining linkage analysis with association mapping provides significant increases in statistical power over a stand-alone GWAS as well as significantly higher mapping resolution than either study alone.

Regulation of gene expression by lithium and depletion of inositol in slices of adult rat cortex.

Lithium inhibits inositol monophosphatase at therapeutically effective concentrations, and it has been hypothesized that depletion of brain inositol levels is an important chemical alteration for lithium's therapeutic efficacy in bipolar disorder. We have employed adult rat cortical slices as a model to investigate the gene regulatory consequences of inositol depletion effected by lithium using cytidine diphosphoryl-diacylglycerol as a functionally relevant biochemical marker to define treatment conditions. Genes coding for the neuropeptide hormone pituitary adenylate cyclase activating polypeptide (PACAP) and the enzyme that processes PACAP's precursor to the mature form, peptidylglycine alpha-amidating monooxygenase, were upregulated by inositol depletion. Previous work has shown that PACAP can increase tyrosine hydroxylase (TH) activity and dopamine release, and we found that the gene for GTP cyclohydrolase, which effectively regulates TH through synthesis of tetrahydrobiopterin, was also upregulated by inositol depletion. We propose that modulation of brain PACAP signaling might represent a new opportunity in the treatment of bipolar disorder.

Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.