On the estimation of inbreeding depression using different measures of inbreeding from molecular markers

The inbreeding coefficient (F) of individuals can be estimated from molecular marker data, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. These different measures of F can then be used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some recent simulation studies have investigated the accuracy of this estimation with contradictory results. Whereas some studies suggest that estimates of inbreeding from ROH account more accurately for ID, others suggest that inbreeding measures from SNP-by-SNP homozygosity giving a large weight to rare alleles are more accurate. Here, we try to give more light on this issue by carrying out a set of computer simulations considering a range of population genetic parameters and population sizes. Our results show that the previous studies are indeed not contradictory. In populations with low effective size, where relationships are more tight and selection is relatively less intense, F measures based on ROH provide very accurate estimates of ID whereas SNP-by-SNP-based F measures with high weight to rare alleles can show substantial upwardly biased estimates of ID. However, in populations of large effective size, with more intense selection and trait allele frequencies expected to be low if they are deleterious for fitness because of purifying selection, average estimates of ID from SNP-by-SNP-based F values become unbiased or slightly downwardly biased and those from ROH-based F values become slightly downwardly biased. The noise attached to all these estimates, nevertheless, can be very high in large-sized populations. We also investigate the relationship between the different F measures and the homozygous mutation load, which has been suggested as a proxy of inbreeding depression.

Estimation of Inbreeding Depression From Overdominant Loci Using Molecular Markers

Inbreeding depression is a highly relevant universal phenomenon in population and conservation genetics since it leads to a decline in the fitness of individuals. This phenomenon is due to the homozygous expression of alleles whose effects are hidden in heterozygotes (inbreeding load). The rate of inbreeding depression for quantitative traits can be quantified if the coefficient of inbreeding (F) of individuals is known. This coefficient can be estimated from pedigrees or from the information of molecular markers, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. Several studies have investigated the accuracy of different F measures to estimate inbreeding depression, but always assuming that this is only due to recessive or partially recessive deleterious mutations. It is possible, though, that part of the inbreeding depression is due to variants with overdominant gene action (heterozygote advantage). In this study, we carried out computer simulations to assess the impact of overdominance on the estimation of inbreeding depression based on different measures of F. The results indicate that the estimators based on ROH provide the most robust estimates of inbreeding depression when this is due to overdominant loci. The estimators that use measures of homozygosity from individual markers may provide estimates with substantial biases, depending on whether or not low-frequency alleles are discarded in the analyses; but among these SNP-by-SNP measures, those based on the correlation between uniting gametes are generally the most reliable.