Genomic and Epigenomic Responses to Chronic Stress Involve miRNA-Mediated Programming

Stress represents a critical influence on motor system function and has been shown to impair movement performance. We hypothesized that stress-induced motor impairments are due to brain-specific changes in miRNA and protein-encoding gene expression. Here we show a causal link between stress-induced motor impairment and associated genetic and epigenetic responses in relevant central motor areas in a rat model. Exposure to two weeks of mild restraint stress altered the expression of 39 genes and nine miRNAs in the cerebellum. In line with persistent behavioural impairments, some changes in gene and miRNA expression were resistant to recovery from stress. Interestingly, stress up-regulated the expression of Adipoq and prolactin receptor mRNAs in the cerebellum. Stress also altered the expression of Prlr, miR-186, and miR-709 in hippocampus and prefrontal cortex. In addition, our findings demonstrate that miR-186 targets the gene Eps15. Furthermore, we found an age-dependent increase in EphrinB3 and GabaA4 receptors. These data show that even mild stress results in substantial genomic and epigenomic changes involving miRNA expression and associated gene targets in the motor system. These findings suggest a central role of miRNA-regulated gene expression in the stress response and in associated neurological function

Population growth as a nonlinear process

The evolution of the probability density of a biological population is described using nonlinear stochastic differential equations for the growth process and the related Fokker-Planck equations for the time-dependent probability densities. It is shown that the effect of the initial conditions disappears rapidly from the evolution of the mean of the process. But the behaviour of the variance depends on the initial condition. It may monotonically increase, reaching its maximum in the steady state, or have a rather complicated evolution reaching the maximum near the point where growth rates (not population size) is maximal. The variance then decreases to its steady-state value. This observation has implications for risk assessments associated with growing populations, such as microbial populations, which cause food poisoning if the population size reaches a critical level.falsePublishe

The evolution of a truncated Gaussian probability density through time: Modelling animal liveweights after selection

The form of the probability density derived from the evolution in time of a previously truncated frequency distribution of animal Liveweights is of interest in animal husbandry. Truncated frequency distributions arise when the heavier animals are sold for slaughter and the lighter animals retained. The demands of modern quality assurance schemes require that, given information on animal growth, the farmer is able to estimate the number of animals that would meet the specifications at some time in the future after truncation. Assuming that animal growth can be described by a linear stochastic differential equation, we derive an explicit expression for the probability density of animal Liveweights at any time after the truncation of an initial Gaussian density. It is shown that this probability density converges rapidly to a Gaussian density, so that after about 20 days of typical growth rates for lambs, the resulting density is practically indistinguishable from Gaussian.falsePublishe

Mathematical modelling of anoestrus in dairy cows and the linkage to nutrition

Postpartum anoestrus is a major reproductive problem in New Zealand dairy cows and its duration is related to the nutrition levels both pre and post calving. However, the mechanistic details of this relationship are largely unknown. A better understanding of the interactions between nutritional status, and the levels of the reproductive hormones controlling follicle development and ovulation is needed. A mathematical model consisting of a set of interactive nonlinear differential equations and describing the dynamics of the interactions among luteinising hormone (LH), follicle stimulating hormone (FSH) and oestradiol was developed. The model depicts oestradiol profiles generated by individual follicles from the first follicular wave after calving until ovulation, and changes in LH pulsatility leading to the first pre-ovulatory surge are also produced. The robustness of the model was ascertained from iterative processes, and it was also checked against existing experimental data so as to mimic observed changes in hormone levels. It was shown that two mathematical parameters which control: i) the speed of changes in the feedback of LH activity to oestradiol; and, ii) the sensitivity of the ovarian response to LH, have the greatest effect on duration of anoestrus.falsePublishe

Population dynamics of engineered underdominance and killer-rescue gene drives in the control of disease vectors

A number of different genetics-based vector control methods have been proposed. Two approaches currently under development in Aedes aegypti mosquitoes are the two-locus engineered underdominance and killer-rescue gene drive systems. Each of these is theoretically capable of increasing in frequency within a population, thus spreading associated desirable genetic traits. Thus they have gained attention for their potential to aid in the fight against various mosquito-vectored diseases. In the case of engineered underdominance, introduced transgenes are theoretically capable of persisting indefinitely (i.e. it is self-sustaining) whilst in the killer-rescue system the rescue component should initially increase in frequency (while the lethal component (killer) is common) before eventually declining (when the killer is rare) and being eliminated (i.e. it is temporally self-limiting). The population genetics of both systems have been explored using discrete generation mathematical models. The effects of various ecological factors on these two systems have also been considered using alternative modelling methodologies. Here we formulate and analyse new mathematical models combining the population dynamics and population genetics of these two classes of gene drive that incorporate ecological factors not previously studied and are simple enough to allow the effects of each to be disentangled. In particular, we focus on the potential effects that may be obtained as a result of differing ecological factors such as strengths of larval competition; numbers of breeding sites; and the relative fitness of transgenic mosquitoes compared with their wild-type counterparts. We also extend our models to consider population dynamics in two demes in order to explore the effects of dispersal between neighbouring populations on the outcome of UD and KR gene drive systems