Stochastic delay differential equations for genetic regulatory networks

Time delay is an important aspect in the modelling of genetic regulation due to slow biochemical reactions such as gene transcription and translation, and protein diffusion between the cytosol and nucleus. In this paper we introduce a general mathematical formalism via stochastic delay differential equations for describing time delays in genetic regulatory networks. Based on recent developments with the delay stochastic simulation algorithm, the delay chemical masterequation and the delay reaction rate equation are developed for describing biological reactions with time delay, which leads to stochastic delay differential equations derived from the Langevin approach. Two simple genetic regulatory networks are used to study the impact of' intrinsic noise on the system dynamics where there are delays. (c) 2006 Elsevier B.V. All rights reserved.

Polymorphisms in the 5 '-untranslated region of the human serotonin receptor 1B (HTR1B) gene affect gene expression

We present evidence of complex balancing regulation of HTR1B transcription by common polymorphisms in its promoter. Computational analysis of the HTR1B gene predicted that a 50 segment, spanning common DNA sequence variations, T-261G, A-161T, and -182INS/DEL-181, contained a putative functional promoter. Using a secreted alkaline phosphatase (SEAP) reporter gene system, we found that the haplotype -261G_-182INS-181_A-161 enhanced transcriptional activity 2.3-fold compared with the haplotype T-261_-182INS-181_A-161. Conversely, -161T reversed this, and the net effect when -261G and -161T were in the same haplotype (-261G_-182INS-181_-161T) was equivalent to the major haplotype (T-261_-182INS-181_A-161). Electrophoretic mobility shift experiments showed that -261G and -161T modify the binding of transcription factors (TFs): -261G generates a new AP2 binding site, while alleles A-161 and -161T exhibit different binding characteristics to AP1. T-261G and A-161T were found to be in linkage disequilibrium (LD) with G861C in a European ancestry population. Interestingly, G861C has been reported to be associated with several psychiatric disorders. Our results indicate that HTR1B is the target of substantial transcriptional genetic regulation by common haplotypes, which are in LD with the HTR1B single-nucleotide polymorphism (SNP) most commonly used in association studies.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge–Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work.

Accelerated leap methods for simulating discrete stochastic chemical kinetics

Biologists are increasingly conscious of the critical role that noise plays in cellular functions such as genetic regulation, often in connection with fluctuations in small numbers of key regulatory molecules. This has inspired the development of models that capture this fundamentally discrete and stochastic nature of cellular biology - most notably the Gillespie stochastic simulation algorithm (SSA). The SSA simulates a temporally homogeneous, discrete-state, continuous-time Markov process, and of course the corresponding probabilities and numbers of each molecular species must all remain positive. While accurately serving this purpose, the SSA can be computationally inefficient due to very small time stepping so faster approximations such as the Poisson and Binomial τ-leap methods have been suggested. This work places these leap methods in the context of numerical methods for the solution of stochastic differential equations (SDEs) driven by Poisson noise. This allows analogues of Euler-Maruyuma, Milstein and even higher order methods to be developed through the Itô-Taylor expansions as well as similar derivative-free Runge-Kutta approaches. Numerical results demonstrate that these novel methods compare favourably with existing techniques for simulating biochemical reactions by more accurately capturing crucial properties such as the mean and variance than existing methods.

RNA regulation: a new genetics?

Do non-coding RNAs that are derived from the introns and exons of protein-coding and non-protein-coding genes represent a fundamental advance in the genetic operating system of higher organisms? Recent evidence from comparative genomics and molecular genetics indicates that this might be the case. If so, there will be profound consequences for our understanding of the genetics of these organisms, and in particular how the trajectories of differentiation and development and the differences among individuals and species are genomically programmed. But how might this hypothesis be tested?

Factors underlying support or opposition to biotechnology among Australian food consumers and implications for retailer-led food regulation

Despite current findings that consumers, on average, have negative attitudes to biotechnologies such as cloning and genetic engineering, considerable variability can be found in the direction and strength of these attitudes. This paper presents a path analysis of attitudinal, motivational, demographic and behavioural variables that influence consumer dispositions towards biotechnology. Among these variables, those found to be most important were: consumers' level of motivation to find natural foods; the extent to which they were motivated by convenience; whether they did the shopping for their household on a regular basis; and their sex. In terms of direct effects on dispositions to biotechnology, motivation to find natural foods had a very strong negative effect while convenience had a very strong positive effect. Sex had a moderate direct effect with women less likely to be positively disposed towards biotechnology than men. In an apparent contradiction, taking responsibility for household shopping had an equally strong positive effect on both naturalness and convenience. However, sex also played a crucial role here with a very strong effect on motivation to find natural foods (women more motivated), a minor effect on convenience (women less motivated) and a strong effect on responsibility for household shopping (women more likely to shop). The policy implications of these findings are important, given the apparent oppositional trends of some sections of the food industry to endorse biotechnology, and of the supermarkets to deliver `clean and green' non-GM foods to consumers. (c) 2005 Elsevier Ltd. All rights reserved.

Molecular analysis reveals tighter social regulation of immigration in patrilocal populations than in matrilocal populations

Human social organization can deeply affect levels of genetic diversity. This fact implies that genetic information can be used to study social structures, which is the basis of ethnogenetics. Recently, methods have been developed to extract this information from genetic data gathered from subdivided populations that have gone through recent spatial expansions, which is typical of most human populations. Here, we perform a Bayesian analysis of mitochondrial and Y chromosome diversity in three matrilocal and three patrilocal groups from northern Thailand to infer the number of males and females arriving in these populations each generation and to estimate the age of their range expansion. We find that the number of male immigrants is 8 times smaller in patrilocal populations than in matrilocal populations, whereas women move 2.5 times more in patrilocal populations than in matrilocal populations. In addition to providing genetic quantification of sex-specific dispersal rates in human populations, we show that although men and women are exchanged at a similar rate between matrilocal populations, there are far fewer men than women moving into patrilocal populations. This finding is compatible with the hypothesis that men are strictly controlling male immigration and promoting female immigration in patrilocal populations and that immigration is much less regulated in matrilocal populations.

A Genetic Marker to Separate Emiliania Huxleyi (Prymnesiophyceae) Morphotypes

Emiliania huxleyi (Lohm.) Hay and Mohler is a ubiquitous unicellular marine alga surrounded by an elaborate covering of calcite platelets called coccoliths. It is an important primary producer involved in oceanic biogeochemistry and climate regulation. Currently, E. huxleyi is separated into five morphotypes based on morphometric, physiological, biochemical, and immunological differences. However, a genetic marker has yet to be found to characterize these morphotypes. With the use of sequence analysis and denaturing gradient gel electrophoresis, we discovered a genetic marker that correlates significantly with the separation of the most widely recognized A and B morphotypes. Furthermore, we reveal that the A morphotype is composed of a number of distinct genotypes. This marker lies within the 3' untranslated region of a coccolith associated protein mRNA, which is implicated in regulating coccolith calcification. Consequently, we tentatively termed this marker the coccolith morphology motif.