Using GeneReg to construct time delay gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes.</p> <p>Findings</p> <p>The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases.</p> <p>Conclusions</p> <p>GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.</p

Predictive value of multiple cytokines and chemokines for mortality in an admixed population: 15-year follow-up of the Bambui-Epigen (Brazil) cohort study of aging

Inflammation, particularly elevated IL-6 serum levels, has been associated with increased mortality risk, mostly in Caucasians. The influence of genetic ethno-racial background on this association is unknown. We examined associations between baseline serum levels of Interleukin-6 (IL-6) and other cytokines (IL1-2, TNF, IL-10, and IL1β) and chemokines (CCL2, CCL5, CXCL8, CXCL9 and CXCL10) with 15-year mortality in 1,191 admixed Brazilians aged 60 years and over. Elevated IL6 level (but not other biomarkers) was associated with increased risk of deaths with fully adjusted hazard ratios of 1.51 (95% CI = 1.15, 1.97), 1.54 (95% CI = 1.20, 1.96) and 1.79 (95% CI = 1.40, 2.29) for the 2nd, 3rd and the highest quartiles, respectively. Genomic African and Native American proportions did not modify the association (p > 0.05). The discriminatory ability to predict death of a model based on IL-6 alone was similar as that of a comprehensive morbidity score (C statistics = 0.59 and 0.60, respectively). The abilities of IL-6 and the morbidity score models to predict death remained stable for very long term after the baseline measurement. Our results indicate that genome-based African and Native American ancestries have no impact on the prognostic value of IL-6 for mortality

A case of polymicrogyria in macaque monkey: impact on anatomy and function of the motor system

Background: Polymicrogyria is a malformation of the cerebral cortex often resulting in epilepsy or mental retardation. It remains unclear whether this pathology affects the structure and function of the corticospinal (CS) system. The anatomy and histology of the brain of one macaque monkey exhibiting a spontaneous polymicrogyria (PMG monkey) were examined and compared to the brain of normal monkeys. The CS tract was labelled by injecting a neuronal tracer (BDA) unilaterally in a region where low intensity electrical microstimulation elicited contralateral hand movements (presumably the primary motor cortex in the PMG monkey). Results: The examination of the brain showed a large number of microgyri at macro- and microscopic levels, covering mainly the frontoparietal regions. The layered cortical organization was locally disrupted and the number of SMI-32 stained pyramidal neurons in the cortical layer III of the presumed motor cortex was reduced. We compared the distribution of labelled CS axons in the PMG monkey at spinal cervical level C5. The cumulated length of CS axon arbors in the spinal grey matter was not significantly different in the PMG monkey. In the red nucleus, numerous neurons presented large vesicles. We also assessed its motor performances by comparing its capacity to execute a complex reach and grasp behavioral task. The PMG monkey exhibited an increase of reaction time without any modification of other motor parameters, an observation in line with a normal CS tract organisation. Conclusion: In spite of substantial cortical malformations in the frontal and parietal lobes, the PMG monkey exhibits surprisingly normal structure and function of the corticospinal system