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A method for estimating the effective number of loci affecting a quantitative character

Content Provider	PubMed Central
Author	Slatkin, Montgomery
Copyright Year	2013
Abstract	A likelihood method is introduced that jointly estimates the number of loci and the additive effect of alleles that account for the genetic variance of a normally distributed quantitative character in a randomly mating population. The method assumes that measurements of the character are available from one or both parents and an arbitrary number of full siblings. The method uses the fact, first recognized by Karl Pearson in 1904, that the variance of a character among offspring depends on both the parental phenotypes and on the number of loci. Simulations show that the method performs well provided that data from a sufficient number of families (on the order of thousands) are available. This method assumes that loci are in Hardy-Weinberg and linkage equilibrium but does not assume anything about linkage relationships. It performs equally well if all loci are on the same non-recombining chromosome provided they are in linkage equilibrium. The method can be adapted to take account of loci already identified as being associated with the character of interest. In that case, the method estimates the number of loci not already known to be affect the character. The method applied to measurements of crown-rump length in 281 family trios in a captive colony of African green monkeys (Chlorocebus aethiopus sabaeus) estimates the number of loci to be 112 and the additive effect to be 0.26 cm. A parametric bootstrap analysis shows that a rough confidence interval has a lower bound of 14 loci.
Related Links	http://dx.doi.org/10.1016/j.tpb.2013.08.002
Ending Page	54
Page Count	11
Starting Page	44
File Format	PDF
ISSN	00405809
e-ISSN	10960325
Journal	Theoretical population biology
Volume Number	0
Language	English
Publisher Date	2013-11-01
Access Restriction	Open
Subject Keyword	Ecology, Evolution, Behavior and Systematics Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Ecology, Evolution, Behavior and Systematics

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