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1.
Inconsistencies exist in the standard expansions used to approximate selection coefficients for alleles at a locus underlying a quantitative character. Allelic (marginal) fitnesses obtained from expansions based on average excesses differ from allelic fitnesses obtained from expansions based on genotypic values. Similarly, the mean population fitness based on summing over either allelic or genotypic fitnesses usually differs mean population fitness obtained by averaging over the unrestricted phenotypic distribution. A consistent value of requires no variation in genotypic values. If, as suggested by Nagylaki (1984), expansions are corrected for the decrease in phenotypic variance resulting from conditioning on the presence of a particular allele or genotype, inconsistencies still exist. Unless W(z)[V z p(z) + zp(z) + p(z)] dz = 0, where p(z) is the phenotypic probability density function, V z the phenotypic variance, W( z ) the fitness of phenotypic value z, the primes denote differentiation with respect to z, allelic fitnesses based on average effects differ from allelic fitnesses based on genotypic values. This condition must also be satisfied in order for either expansion to give a consistent , as first shown by Nagylaki. For arbitrary W(z), this is satisfied if and only if phenotypes are normally distributed.  相似文献   

2.
A simple theoretical model of a Darwinian system (a periodic system with a multiplication phase and a selection phase) of entities (initial form of polymer strand, primary mutant and satellite mutants) is given. First case: one mutant is considered. One individual of the mutant appears in the multiplication phase of the first generation. The probabilities to find N mutants WnM(N) after the multiplication phase M of the n-th generation (with probability δ of an error in the replication, where all possible errors are fatal errors) and WnS(N) after the following selection phase S (with probability β that one individual survives) are given iteratively. The evolutionary tree is evaluated. Averages from the distributions and the probability of extinction WS(0) are obtained. Second case: two mutants are considered (primary mutant and new form). One individual of the primary mutant appears in the multiplication phase of the first generation. The probabilities to find Np primary mutants and Nm of the new form WnM(Np, Nm) after the multiplication phase M of the n-th generation (probability ε of an error in the replication of the primary mutant giving the new form) and WnS(Np, Nm) after the following selection phase S (probabilities βp and βm that one individual each of the primary mutant and of the new form survives) are given iteratively. Again the evolutionary tree is evaluated. Averages from the distributions are obtained.  相似文献   

3.
The Chinese rice cultivar Duokang #1 carries a single dominant gene Gm-6(t) that confers resistance to the four biotypes of Asian rice gall midge (Orseolia oryzae Wood-Mason) known in China. Bulked segregant analysis was performed on progeny of a cross between Duokang #1 and the gall midge-susceptible cultivar Feng Yin Zhan using the RAPD method. The RAPD marker OPM06(1400) amplified a locus linked to Gm-6(t). The locus was subsequently mapped to rice chromosome 4 in a region flanked by cloned RFLP markers RG214 and RG163. Fine mapping of Gm-6(t) revealed that markers RG214 and RG476 flanked the gene at distances of 1.0 and 2.3 cM, respectively. Another gall midge resistance gene, Gm-2, mapped previously to chromosome 4, is located about 16 cM from Gm-6(t), to judge by data from a segregating population derived from a cross between Duokang #1 and the Indian cultivar Phalguna that carries Gm-2. We developed a PCR-based marker-assisted selection kit for transfer of the Gm-6(t) gene into Ming Hui 63 and IR50404, two parental lines commonly used in hybrid rice production in China. The kit contains PCR primer pairs based on the terminal sequences of the RG214 and RG476 clones. Polymorphism between Duokang #1 and the hybrid parental lines was found at these markers after digestion of the PCR products with specific restriction endonucleases. The kit will accelerate introduction of gall midge resistance into hybrid rice in China. Received: 18 May 2000 / Accepted: 9 March 2001  相似文献   

4.
SIMtoEXP is a software package designed to facilitate the comparison of biomembrane simulations with experimental X-ray and neutron scattering data. It has the following features: (1) Accepts number density profiles from simulations in a standard but flexible format. (2) Calculates the electron density ε(z) and neutron scattering length density ν(z) profiles along the z direction (i.e., normal to the membrane) and their respective Fourier transforms (i.e., F ε [q z ] and F ν [q z ]). The resultant four functions are then displayed graphically. (3) Accepts experimental F ε (q z ) and F ν (q z ) data for graphical comparison with simulations. (4) Allows for lipids and other large molecules to be parsed into component groups by the user and calculates the component volumes following Petrache et al. (Biophys J 72:2237–2242, 1997). The software then calculates and displays the contributions of each component group as volume probability profiles, ρ(z), as well as the contributions of each component to ε(z) and ν(z).  相似文献   

5.
The method of minimum evolution reconstructs a phylogenetic tree T for n taxa given dissimilarity data d. In principle, for every tree W with these n leaves an estimate for the total length of W is made, and T is selected as the W that yields the minimum total length. Suppose that the ordinary least-squares formula S W (d) is used to estimate the total length of W. A theorem of Rzhetsky and Nei shows that when d is positively additive on a completely resolved tree T, then for all WT it will be true that S W (d) > S T (d). The same will be true if d is merely sufficiently close to an additive dissimilarity function. This paper proves that as n grows large, even if the shortest branch length in the true tree T remains constant and d is additive on T, then the difference S W (d)-S T (d) can go to zero. It is also proved that, as n grows large, there is a tree T with n leaves, an additive distance function d T on T with shortest edge ε, a distance function d, and a tree W with the same n leaves such that d differs from d T by only approximately ε/4, yet minimum evolution incorrectly selects the tree W over the tree T. This result contrasts with the method of neighbor-joining, for which Atteson showed that incorrect selection of W required a deviation at least ε/2. It follows that, for large n, minimum evolution with ordinary least-squares can be only half as robust as neighbor-joining.  相似文献   

6.
Cell cycle is controlled at two restriction points, R 1 and R 2. At both points the cell will commit apoptosis if it detects irreparable damage. But at R 1 an undamaged cell also decides whether to proceed to the S phase or go into a quiescent mode, depending on the environmental conditions (e.g., overpopulation, hypoxia). We consider the effect of this decision at the population level in a spherical tissue {r < R(t)}. We prove that if the cells have full control at R 1, they can manipulate the size of R(t) to ensure that 0 < cR(t) ≤ C < ∞; simulations further show that R(t) can be made nearly stationary. In the absence of such control, R(t) will either increase to ∞ or decrease to 0. The mathematical model and analysis involve a system of PDEs in {r < R(t)}.  相似文献   

7.
The conditions under which the output,γ b (t), of a biological system is related to the input,γ a (t), by an integral equation of the typeγ b (t) = ∫ 0 t γ a (ω)w(t−ω)dω, where ω(t) is a transport functioncharacteristic of the system, are analyzed in detail. Methods of solving this type of integral equation are briefly discussed. The theory is then applied to problems in tracer kinetics in which input and output are sums of exponentials, and explicit formulae, which are applicable whether or not the pool is uniformly mixed, are derived for “turnover time” and “pool” size.  相似文献   

8.
A biological microbeam for precisely positioned single-ion/single cell irradiation is built in the Institute of Modern Physics in Fudan University, Shanghai, China, based on the tandem accelerator (2 × 3MV) in the laboratory. In this paper, the developing progress of the FUDAN microbeam is reported, including the newly constructed beam line, the microbeam collimator, the ion detection system, and the cell-imaging and targeting systems. Statistical models are proposed for evaluating the spatial resolution and dosage precision of the microbeam. By taking the collimated ions as a Gaussian beam, the spatial resolution can be evaluated by the full width at half maximum of the 2-D Gaussian distribution, which is determined by fitting the proportions of peripheral pits outside specific radii in the pit clusters etched on ion track detectors to a 2-D Gaussian distribution. In the preset hitting of defined ion number, by taking the real delivered number of ions as an independent identically distributed random variable (iidrv), according to the Law of Large Numbers and Central Limit Theorem, the expected value μ and standard deviation σ of the real delivered ion number in a preset N-ion hitting can be determined by approaching the normal distribution of N (μ, σ 2/n) with the proportions of the mean counts of pits in multiple pit clusters on ion track detectors. By the values of μ, σ and additional assumptions, statistical dosage precision evaluations can be made on the preset hitting. From the linear fit curve of μ(N) and the power function fit curve of σ(N) on different preset ion numbers, characteristic factors k, b, A, p can be extracted for a precision evaluation independent of the specific preset ion number.  相似文献   

9.
 A population with birth rate function B(N) N and linear death rate for the adult stage is assumed to have a maturation delay T>0. Thus the growth equation N′(t)=B(N(tT)) N(tT) e d 1 TdN(t) governs the adult population, with the death rate in previous life stages d 1≧0. Standard assumptions are made on B(N) so that a unique equilibrium N e exists. When B(N) N is not monotone, the delay T can qualitatively change the dynamics. For some fixed values of the parameters with d 1>0, as T increases the equilibrium N e can switch from being stable to unstable (with numerically observed periodic solutions) and then back to stable. When disease that does not cause death is introduced into the population, a threshold parameter R 0 is identified. When R 0<1, the disease dies out; when R 0>1, the disease remains endemic, either tending to an equilibrium value or oscillating about this value. Numerical simulations indicate that oscillations can also be induced by disease related death in a model with maturation delay. Received: 2 November 1998 / Revised version: 26 February 1999  相似文献   

10.
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