MICROSATELLITE MEASURES OF INBREEDING: A META-ANALYSIS
Meta-analyses of published and unpublished correlations between phenotypic variation and two measures of genetic variation at microsatellite loci, multilocus heterozygosity (MLH) and mean d2, revealed that the strength of these associations are generally weak (mean r < 0.10). Effects on life-hist...
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Veröffentlicht in: | Evolution 2003-05, Vol.57 (5), p.971-983 |
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Sprache: | eng |
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Zusammenfassung: | Meta-analyses of published and unpublished correlations between phenotypic variation and two measures of genetic variation at microsatellite loci, multilocus heterozygosity (MLH) and mean d2, revealed that the strength of these associations are generally weak (mean r < 0.10). Effects on life-history trait variation were significantly greater than zero for both measures over all reported effect sizes (r = 0.0856 and 0.0479 for MLH and mean d2, respectively), whereas effects on morphometric traits were not (r = 0.0052 and r = 0.0038), which is consistent with the prediction that life-history traits exhibit greater inbreeding depression than morphometric traits. Effect sizes reported using mean d2 were smaller and more variable than those reported using MLH, suggesting that MLH may be a better metric for capturing inbreeding depression most of the time. However, analyses of paired effect sizes reported using both measures from the same data did not differ significantly. Several lines of evidence suggest that published effects sizes are upwardly biased. First, effect sizes from published studies were significantly higher than those reported in unpublished studies. Second, fail-safe numbers for reported effect sizes were generally quite low, with the exception of correlations between MLH and life-history traits. Finally, the slope of the regression of effect size on sample size was negative for most sets of traits. Taken together, these results suggest that studies designed to detect inbreeding depression on a life-history trait using microsatellites will need to sample in excess of 600 individuals to detect an average effect size (r = 0.10) with reasonable statistical power (0.80). Very few published studies have used samples sizes approaching this value. |
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ISSN: | 0014-3820 1558-5646 |
DOI: | 10.1554/0014-3820(2003)057[0971:MMOIAM]2.0.CO;2 |