Analyzing steady states of dynamics of bio-molecules from the structure of regulatory networks

Regulatory relations between biological molecules constitute complex network systems and realize diverse biological functions through the dynamics of molecular activities. However, we currently have very little understanding of the relationship between the structure of a regulatory network and its dynamical properties. In this paper we introduce a new method, named “linkage logic” to analyze the dynamics of network systems. By this method, we can restrict possible steady states of a given complex network system from the knowledge of regulatory linkages alone. The regulatory linkage simply specifies the list of variables that affect the dynamics of each variable. We formalize two aspects of the linkage logic: the “Principle of Compatibility” determines the upper limit of the diversity of possible steady states of the dynamics realized by a given network; the “Principle of Dependency” determines the possible combinations of states of the system. By combining these two aspects, (i) for a given network, we can identify a cluster of nodes that gives an alternative representation of the steady states of the whole system, (ii) we can reduce a given complex network into a simpler one without loss of the ability to generate the diversity of steady states, (iii) we can examine the consistency between the structure of network and observed set of steady states, and (iv) sometimes we can predict unknown states or unknown regulations from an observed set of steady states alone. We illustrate the method by several applications to an experimentally determined regulatory network for biological functions.     

Construction of a linkage map of Lentinula edodes (shiitake) with the HEGS (high-efficiency genome scanning) system: use of versatile AFLP and PCR-based gene markers

An improved linkage map of Lentinula edodes (shiitake) was constructed with an HEGS (high-efficiency genome scanning) system. Two hundred twenty-one HEGS-derived amplified fragment length polymorphism (AFLP-H) markers and 21 gene markers were developed and combined with 203 previously developed sequencer-derived AFLP markers (AFLP-S markers) and 3 mating factor loci (A, Bα, and Bβ) to construct a comprehensive linkage analysis. As a result, a novel linkage map with 166 markers including 2 mating factors (A and B), 10 HEGS-derived gene markers, 72 AFLP-H markers, and 82 AFLP-S markers was obtained. Of the total 448 markers, 273 could not be located on a linear map and thus were assigned to linkage groups as accessory markers. The map covers a total length of 1398.4 centimorgans (cM) with an average marker interval distance of 8.4 cM. The map consists of 11 linkage groups (LGs) in agreement with our previous map, and 7 LGs among them were found to contain branched linkages, which may be the result of reciprocal translocations representing dynamic reorganization of the shiitake genome. The previously reported linkage map was improved in terms of number of markers, marker density, linear order of markers, and total map length. Contribution no. 384 of the Tottori Mycological Institute     

Confirmation of linkage to chromosome 1q for spine bone mineral density in southern Chinese

Chromosome 1q has previously been linked to bone mineral density (BMD) variation in the general population in several genome-wide linkage studies in both humans and mouse model. The aim of present study is to replicate and fine map the QTL influencing BMD in chromosome 1q in southern Chinese. Twelve microsatellite markers were genotyped for a 57 cΜ region in the chromosome 1q in 306 southern Chinese families with 1,459 subjects. Each of these families was ascertained through a proband with BMD Z-scores less than −1.3 at the hip or spine. BMD (g/cm²) at the L1-4 lumbar spine, femoral neck (FN), trochanter and total hip was measured by dual-energy X-ray absortiometry. Linkage analyses were performed using the variance component linkage analysis method implemented in Merlin software. Four markers (D1S2878, D1S196, D1S452, and D1S218) achieved a LOD score greater than 1.0 with spine BMD, with the maximum multipoint LOD score of 2.36 at the marker D1S196. We did not detect a LOD score greater than 1.0 for BMD at the FN, trochanter, or total hip in multipoint linkage analyses. Our results present the first evidence for the presence of an osteoporosis susceptibility gene on chromosome 1q in non-Caucasian subjects. Further analyses of candidate genes are warranted to identify QTL genes and variants underlying the variations of BMD in this region.     

Linkage disequilibrium between alleles at highly polymorphic mini- and micro-satellite loci of Theileria parva isolated from cattle in three regions of Kenya

Theileria parva schizont-infected lymphocyte culture isolates from western, central and coastal Kenya were analysed for size polymorphism at 30 T. parva-specific variable number tandem repeat (VNTR) loci using a panel of mini- and micro-satellite markers. The mean number of alleles ranged from 3 to 11 at individual loci and 183 distinct alleles were observed in total, indicating high genetic diversity within the T. parva gene pool in Kenyan cattle. The frequency distribution of the length variation of specific alleles among isolates ranged from normal to markedly discontinuous. Genetic relationships between isolates were analysed using standard indices of genetic distance. Genetic distances and dendrograms derived from these using neighbour-joining algorithms did not indicate significant clustering on a geographical basis. Analysis of molecular variance demonstrated that the genetic variation between individual isolates was 72%, but only 2.3% when isolates from different regions were pooled. Both these observations suggest minimal genetic sub-structuring relative to geographical origin. Linkage disequilibrium was observed between pairs of loci within populations, as in certain Ugandan T. parva populations. A novel observation was that disequilibrium was also detected between alleles at three individual pairs of VNTR loci when isolates from the three regional meta-populations were pooled for analysis.     

Optimization of two-stage genetic designs where data are combined using an accurate and efficient approximation for Pearson's statistic

There is an increasing interest in the use of two-stage case-control studies to reduce genotyping costs in the search for genes underlying common disorders. Instead of analyzing the data from the second stage separately, a more powerful test can be performed by combining the data from both stages. However, standard tests cannot be used because only the markers that are significant in the first stage are selected for the second stage and the test statistics at both stages are dependent because they partly involve the same data. Theoretical approximations are not available for commonly used test statistics and in this specific context simulations can be problematic because of the computational burden. We therefore derived a cost-effective, that is, accurate but fast in terms of central processing unit (CPU) time, approximation for the distribution of Pearson's statistic on 2 xm contingency tables in two-stage design with combined data. We included this approximation in an iterative method for designing optimal two-stage studies. Simulations supported the accuracy of our approximation. Numerical results confirmed that the use of two-stage designs reduces the genotyping burden substantially. Compared to not combining data, combining the data decreases the required sample sizes on average by 15% and the genotyping burden by 5%.     

Addition of glycerol for improved methylation linkage analysis of polysaccharides

A presolubilization procedure with the use of glycerol is shown to be applicable for the structural analysis of polysaccharides. Neutral, acidic, high-molecular-weight and low-molecular-weight polysaccharides were solubilized in glycerol prior to methylation and subsequent linkage analysis by GC-MS. All four types of polysaccharides showed significant increases in derivatization following presolubilization as measured by recovery of partially methylated alditol acetates.     

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution.