BioTile, A Perl based tool for the identification of differentially enriched regions in tiling microarray data

BACKGROUND: Genome-wide tiling array experiments are increasingly used for the analysis of DNA methylation. Because DNA methylation patterns are tissue and cell type specific, the detection of differentially methylated regions (DMRs) with small effect size is a necessary feature of tiling microarray ‘peak’ finding algorithms, as cellular heterogeneity within a studied tissue may lead to a dilution of the phenotypically relevant effects. Additionally, the ability to detect short length DMRs is necessary as biologically relevant signal may occur in focused regions throughout the genome. RESULTS: We present a free open-source Perl application, Binding Intensity Only Tile array analysis or “BioTile”, for the identification of differentially enriched regions (DERs) in tiling array data. The application of BioTile to non-smoothed data allows for the identification of shorter length and smaller effect-size DERs, while correcting for probe specific variation by inversely weighting on probe variance through a permutation corrected meta-analysis procedure employed at identified regions. BioTile exhibits higher power to identify significant DERs of low effect size and across shorter genomic stretches as compared to other peak finding algorithms, while not sacrificing power to detect longer DERs. CONCLUSION: BioTile represents an easy to use analysis option applicable to multiple microarray platforms, allowing for its integration into the analysis workflow of array data analysis

Roman high and low avoidance rats differ in their response to chronic olanzapine treatment at the level of body weight regulation, glucose homeostasis, and cortico-mesolimbic gene expression

Olanzapine, an antipsychotic agent mainly used for treating schizophrenia, is frequently associated with body weight gain and diabetes mellitus. Nonetheless, studies have shown that not every individual is equally susceptible to olanzapine's weight-gaining effect. Therefore, Roman high and low avoidance rat strains were examined on their responsiveness to olanzapine treatment. The Roman high avoidance rat shares many behavioral and physiological characteristics with human schizophrenia, such as increased central dopaminergic sensitivity, whereas the Roman low avoidance rat has been shown to be prone to diet-induced obesity and insulin resistance. The data revealed that only the Roman high avoidance rats are susceptible to olanzapine-induced weight gain and attenuated glucose tolerance. Here it is suggested that the specific olanzapine-induced weight gain in Roman high avoidance rats could be related to augmented dopaminergic sensitivity at baseline through increased expression of prefrontal cortex dopamine receptor D1 mRNA and nucleus accumbens dopamine receptor D2 mRNA expression. Regression analyses revealed that olanzapine-induced weight gain in the Roman high avoidance rat is above all related to increased prolactin levels, whereas changes in glucose homeostasis is best explained by differences in central dopaminergic receptor expressions between strains and treatment. Our data indicates that individual differences in dopaminergic receptor expression in the cortico-mesolimbic system are related to susceptibility to olanzapine-induced weight gain