The base populations used in most forest tree
genetic improvement programs usually lack
detailed pedigree information. Molecular
markers, such as microsatellites (SSR), can be
used to estimate individuals’ pairwise
relatedness, which is based on the probabilities’
ratios of the identity in state between the
individuals compared and the reference
unrelated population These estimates can be
very useful to infer the level of relationship
among sub-populations of elite material and/or
for the design of controlled crosses between
putatively unrelated parents.
Using 113 putatively unrelated individuals -
genotyped with 18 SSR - self, full-sib, half-sib
and unrelated were simulated, and four pairwise
similarity coefficients were tested: Queller &
Goodnight 1989; Li et al. 1993; Ritland 1996,
and Lynch & Ritland 1999. The Lynch & Ritland
(1999) coefficient was selected (Figure 1), for it
displayed a better adjustment with the expected
level of relatedness and narrower standard
errors (SE). SE were calculated through Monte-
Carlo techniques, to avoid unequal sample size
bias, by using 105 simulations for each
relatedness group.
To illustrate the usefulness of molecular
estimates of similarity in genetic improvement
programs, a clustering (UPGMA) based on the
pairwise Lynch & Ritland (1999) coefficient (LR)
values was performed to infer about the putative
relationship among individuals of the subgroups
of E. globulus elite individuals. From that
analysis at least two pairs might be related and a
PCA analysis confirmed the clustering results
