Document Detail

Effect of excluding sib matings on inbreeding coefficient and effective size of finite diploid populations.
MedLine Citation:
PMID:  9423254     Owner:  NLM     Status:  MEDLINE    
The effects of excluding full-sib matings, half-sib matings, or both under random selection or equal family size selection on the inbreeding coefficient and effective size in finite populations with unequal sex ratio have been studied. Recurrent equations for the inbreeding coefficient and approximate formulas for effective size are derived for different breeding systems. It is shown that avoidance of sib matings results in lower inbreeding coefficients in any generations under random selection. Under equal family size selection, however, excluding sib matings gives rise to lower inbreeding coefficients only in the first few generations and will eventually result in a higher inbreeding in later generations compared with random mating. Exclusion of sib matings increases effective size under random selection while it decreases effective size under equal family size selection. The relative effectiveness on effective size of different sib mating avoidance depends only on sex ratio of the population. The importance of full-sib mating decreases and that of half-sib mating increases with the increment of the value of sex ratio (r). When r = 3, full-sib mating has the same effect on effective size as half-sib mating.
J Wang
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biometrics     Volume:  53     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  1997 Dec 
Date Detail:
Created Date:  1998-02-04     Completed Date:  1998-02-04     Revised Date:  2003-11-14    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  1354-65     Citation Subset:  IM    
College of Animal Sciences, Zhejiang Agricultural University, Hangzhou, Peoples Republic of China.
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MeSH Terms
Biometry / methods
Crosses, Genetic
Models, Genetic*
Models, Statistical*
Population Density
Sex Ratio

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