Biomaterial Database

Effective size of nonrandom mating populations. 1992

A Caballero, and W G Hill

Institute of Cell, Animal and Population Biology, University of Edinburgh, Scotland.

Nonrandom mating whereby parents are related is expected to cause a reduction in effective population size because their gene frequencies are correlated and this will increase the genetic drift. The published equation for the variance effective size, Ne, which includes the possibility of nonrandom mating, does not take into account such a correlation, however. Further, previous equations to predict effective sizes in populations with partial sib mating are shown to be different, but also incorrect. In this paper, a corrected form of these equations is derived and checked by stochastic simulation. For the case of stable census number, N, and equal progeny distributions for each sex, the equation is [formula: see text], where Sk2 is the variance of family size and alpha is the departure from Hardy-Weinberg proportions. For a Poisson distribution of family size (Sk2 = 2), it reduces to Ne = N/(1 + alpha), as when inbreeding is due to selfing. When nonrandom mating occurs because there is a specified system of partial inbreeding every generation, alpha can be substituted by Wright's FIS statistic, to give the effective size as a function of the proportion of inbred mates.

UI	MeSH Term	Description	Entries
D007178	Inbreeding	The mating of plants or non-human animals which are closely related genetically.	Backcrossing,Half-Sib Mating,Sib Mating,Genetic Inbreeding,Backcrossings,Genetic Inbreedings,Half Sib Mating,Half-Sib Matings,Inbreeding, Genetic,Mating, Half-Sib,Mating, Sib,Matings, Half-Sib,Matings, Sib,Sib Matings
D008957	Models, Genetic	Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.	Genetic Models,Genetic Model,Model, Genetic
D011156	Population Density	Number of individuals in a population relative to space.	Overpopulation,Population Size,Underpopulation,Densities, Population,Density, Population,Population Densities,Population Sizes
D012098	Reproduction	The total process by which organisms produce offspring. (Stedman, 25th ed)	Human Reproductive Index,Human Reproductive Indexes,Reproductive Period,Human Reproductive Indices,Index, Human Reproductive,Indexes, Human Reproductive,Indices, Human Reproductive,Period, Reproductive,Periods, Reproductive,Reproductive Index, Human,Reproductive Indices, Human,Reproductive Periods
D001947	Breeding	The production of offspring by selective mating or HYBRIDIZATION, GENETIC in animals or plants.	Breedings
D005787	Gene Frequency	The proportion of one particular in the total of all ALLELES for one genetic locus in a breeding POPULATION.	Allele Frequency,Genetic Equilibrium,Equilibrium, Genetic,Allele Frequencies,Frequencies, Allele,Frequencies, Gene,Frequency, Allele,Frequency, Gene,Gene Frequencies
D005828	Genetics, Population	The discipline studying genetic composition of populations and effects of factors such as GENETIC SELECTION, population size, MUTATION, migration, and GENETIC DRIFT on the frequencies of various GENOTYPES and PHENOTYPES using a variety of GENETIC TECHNIQUES.	Population Genetics
D014644	Genetic Variation	Genotypic differences observed among individuals in a population.	Genetic Diversity,Variation, Genetic,Diversity, Genetic,Diversities, Genetic,Genetic Diversities,Genetic Variations,Variations, Genetic
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model