Mapping the genes underlying ecologically-relevant traits in natural
populations is fundamental to develop a molecular understanding of
species adaptation. Current sequencing technologies enable the
characterisation of a species' genetic diversity across the landscape or
even over its whole range. The relevant capture of the genetic diversity
across the landscape is critical for a successful genetic mapping of
traits and there are no clear guidelines on how to achieve an optimal
sampling and which sequencing strategy to implement. Here we determine
through simulation, the sampling scheme that maximises the power to map
the genetic basis of a complex trait in an outbreeding species across an
idealised landscape and draw genomic predictions for the trait,
comparing individual and pool sequencing strategies. Our results show
that QTL detection power and prediction accuracy are higher when more
populations over the landscape are sampled and this is more
cost-effectively done with pool sequencing than with individual
sequencing. Additionally, we recommend sampling populations from areas
of high genetic diversity. As progress in sequencing enables the
integration of trait-based functional ecology into landscape genomics
studies, these findings will guide study designs allowing direct
measures of genetic effects in natural populations across the
environment.