Hi Frederik,
You are comparing two different things which is understandable because they have similar names.
In your first plot, you are estimating individual inbreeding coefficients which is the probability that two alleles at any locus in an individual are identical by descent and it is estimated at the individual level. Here it is expected a negative correlation between heterozygosity and individual inbreeding coefficients.
In your second plot, you are estimating Wright's inbreeding coefficient (FIS) which is a measure of departure from Hardy–Weinberg proportions within populations, ie the deviation between observed heterozygosity and expected heterozygosity. FIS is calculated at the population level. If you want to estimate FIS using hierfstat, you could use the following code:
> library(dartR)
> library(hierfstat)
> t1 <-
platypus.gl> res <- fs.dosage(as.matrix(t1),pop=pop(t1))
Prof. Bill Sherwin commented:
" Every decade or so, starting with
Jaccard in the 1950s, good population geneticists have told us not to confuse:
Hardy-Weinberg expected
heterozygosity He (also called gene diversity). Eg for a 2-allele SNP, where p
and q are proportions of the two alleles, A1 and A2, Gene
diversity/Heterozygosity: He=2pq
With
Inbreeding coefficient (FIS, also
measures effect of other things such as selection for or against
heterozygotes). Inbreeding coefficient: FIS=1-(Ho/He) where Ho is the observed
proportion of heterozygotes.
You can see from the equations
that there will not be a simple linear relationship between FIS and He.
Or you can see the same thing from these two examples of different
populations, both with p=q=0.5:
EG1: if there is total
inbreeding, with 50% of families having only A1 homozygotes, and the other
families only having A2 homozygotes, so that He=0.5, Ho=1 then FIS =0.5.
EG2: Alternatively if all
individuals are heterozygotes, He=0.5, Ho=0 then FIS=1.
Those are extreme examples, but
they show that with the same He, you can get a very wide range of FIS values. So,
it is not reasonable to expect any tight relationship between the two measures
– they measure different things, so they behave independently.
MORAL: NEVER say that a
population with low He is ‘inbred’ – there may be zero consanguineous matings
occurring in this population; there is just low gene diversity – most of the A1
or A2 alleles have been lost by drift (which is NOT inbreeding)."
It is a bit strange that you see a correlation between heterozygosity and FIS in your dataset because it is not expected in "normal" circumstances, as Bill commented above. However, in clonal populations this pattern seems to be usual because these populations accumulate a lot of mutations which results in an accumulation of heterozygosity at all loci (observed
heterozygosity is higher than expected heterozygosity and therefore FIS
is negative). This accumulation of mutations in clonal populations occurs because once a homozygous site has experienced mutation, it becomes
heterozygous and has very little chance of becoming homozygous again (reverse mutation is
unlikely). Also in clonal populations, FIS directly reflects the size of the population. See for example:
Koffi, Mathurin, et al. "Population genetics and reproductive strategies of African trypanosomes: revisiting available published data." PLoS neglected tropical diseases 9.10 (2015): e0003985.
Cheers,
Luis