Assessment of identity disequilibrium and its relation to empirical heterozygosity fitness correlations: a meta-analysis



Heterozygosity fitness correlations (HFCs) have frequently been used to detect inbreeding depression, under the assumption that genome-wide heterozygosity is a good proxy for inbreeding. However, meta-analyses of the association between fitness measures and individual heterozygosity have shown that often either no correlations are observed or the effect sizes are small. One of the reasons for this may be the absence of variance in inbreeding, a requisite for generating general-effect HFCs. Recent work has highlighted identity disequilibrium (ID) as a measure that may capture variance in the level of inbreeding within a population; however, no thorough assessment of ID in natural populations has been conducted. In this meta-analysis, we assess the magnitude of ID (as measured by the g2 statistic) from 50 previously published HFC studies and its relationship to the observed effect sizes of those studies. We then assess how much power the studies had to detect general-effect HFCs, and the number of markers that would have been needed to generate a high expected correlation (r2 = 0.9) between observed heterozygosity and inbreeding. Across the majority of studies, g2 values were not significantly different than zero. Despite this, we found that the magnitude of g2 was associated with the average effect sizes observed in a population, even when point estimates were nonsignificant. These low values of g2 translated into low expected correlations between heterozygosity and inbreeding and suggest that many more markers than typically used are needed to robustly detect HFCs.