scholarly journals Evolution of Multigene Families by Gene Duplication: A Haploid Model

Genetics ◽  
1998 ◽  
Vol 149 (4) ◽  
pp. 2147-2158
Author(s):  
Hidenori Tachida ◽  
Tohru Kuboyama

Abstract Evolution of multigene families by gene duplication and subsequent diversification is analyzed assuming a haploid model without interchromosomal crossing over. Chromosomes with more different genes are assumed to have higher fitness. Advantageous and deleterious mutations and duplication/deletion also affect the evolution, as in previous studies. In addition, negative selection on the total number of genes (copy number selection) is incorporated in the model. First, a Markov chain approximation is used to obtain formulas for the average numbers of different alleles, genes without pseudogene mutations, and pseudogenes assuming that mutation rates and duplication/deletion rates are all very small. Computer simulation shows that the approximation works well if the products of population size with mutation and duplication/deletion rates are all small compared to 1. However, as they become large, the approximation underestimates gene numbers, especially the number of pseudogenes. Based on the approximation, the following was found: (1) Gene redundancy measured by the average number of redundant genes decreases as advantageous selection becomes stronger. (2) The number of different genes can be approximately described by a linear pure-birth process and thus has a coefficient of variation around 1. (3) The birth rate is an increasing function of population size without copy number selection, but not necessarily so otherwise. (4) Copy number selection drastically decreases the number of pseudogenes. Available data of mutation rates and duplication/deletion rates suggest much faster increases of gene numbers than those observed in the evolution of currently existing multigene families. Various explanations for this discrepancy are discussed based on our approximate analysis.

2021 ◽  
Vol 53 (2) ◽  
pp. 335-369
Author(s):  
Christian Meier ◽  
Lingfei Li ◽  
Gongqiu Zhang

AbstractWe develop a continuous-time Markov chain (CTMC) approximation of one-dimensional diffusions with sticky boundary or interior points. Approximate solutions to the action of the Feynman–Kac operator associated with a sticky diffusion and first passage probabilities are obtained using matrix exponentials. We show how to compute matrix exponentials efficiently and prove that a carefully designed scheme achieves second-order convergence. We also propose a scheme based on CTMC approximation for the simulation of sticky diffusions, for which the Euler scheme may completely fail. The efficiency of our method and its advantages over alternative approaches are illustrated in the context of bond pricing in a sticky short-rate model for a low-interest environment and option pricing under a geometric Brownian motion price model with a sticky interior point.


Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 853-867 ◽  
Author(s):  
Peter Donnelly ◽  
Magnus Nordborg ◽  
Paul Joyce

Abstract Methods for simulating samples and sample statistics, under mutation-selection-drift equilibrium for a class of nonneutral population genetics models, and for evaluating the likelihood surface, in selection and mutation parameters, are developed and applied for observed data. The methods apply to large populations in settings in which selection is weak, in the sense that selection intensities, like mutation rates, are of the order of the inverse of the population size. General diploid selection is allowed, but the approach is currently restricted to models, such as the infinite alleles model and certain K-models, in which the type of a mutant allele does not depend on the type of its progenitor allele. The simulation methods have considerable advantages over available alternatives. No other methods currently seem practicable for approximating likelihood surfaces.


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