Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1997-3-31
pubmed:abstractText
When a population experiences a reduction of its effective size, it generally develops a heterozygosity excess at selectively neutral loci, i.e., the heterozygosity computed from a sample of genes is larger than the heterozygosity expected from the number of alleles found in the sample if the population were at mutation drift equilibrium. The heterozygosity excess persists only a certain number of generations until a new equilibrium is established. Two statistical tests for detecting a heterozygosity excess are described. They require measurements of the number of alleles and heterozygosity at each of several loci from a population sample. The first test determines if the proportion of loci with heterozygosity excess is significantly larger than expected at equilibrium. The second test establishes if the average of standardized differences between observed and expected heterozygosities is significantly different from zero. Type I and II errors have been evaluated by computer simulations, varying sample size, number of loci, bottleneck size, time elapsed since the beginning of the bottleneck and level of variability of loci. These analyses show that the most useful markers for bottleneck detection are those evolving under the infinite allele model (IAM) and they provide guidelines for selecting sample sizes of individuals and loci. The usefulness of these tests for conservation biology is discussed.
pubmed:commentsCorrections
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pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0016-6731
pubmed:author
pubmed:issnType
Print
pubmed:volume
144
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2001-14
pubmed:dateRevised
2010-9-13
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data.
pubmed:affiliation
Laboratoire Population, Génétique, Evolution, CNRS, Gif sur Yvette, France. cornuet@ensam.inra.fr
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't