Abstract :
[en] 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.
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