Data from: Partitioning of genetic variation across the genome using multimarker methods in a wild bird population

The underlying basis of genetic variation in quantitative traits, in terms
of the number of causal variants and the size of their effects, is largely
unknown in natural populations. The expectation is that complex
quantitative trait variation is attributable to many, possibly
interacting, causal variants, whose effects may depend upon the sex, age
and the environment in which they are expressed. A recently developed
methodology in animal breeding derives a value of relatedness among
individuals from high-density genomic marker data, to estimate additive
genetic variance within livestock populations. Here, we adapt and test the
effectiveness of these methods to partition genetic variation for complex
traits across genomic regions within ecological study populations where
individuals have varying degrees of relatedness. We then apply this
approach for the first time to a natural population and demonstrate that
genetic variation in wing length in the great tit (Parus major) reflects
contributions from multiple genomic regions. We show that a polygenic
additive mode of gene action best describes the patterns observed, and we
find no evidence of dosage compensation for the sex chromosome. Our
results suggest that most of the genomic regions that influence wing
length have the same effects in both sexes. We found a limited amount of
genetic variance in males that is attributed to regions that have no
effects in females, which could facilitate the sexual dimorphism observed
for this trait. Although this exploratory work focuses on one complex
trait, the methodology is generally applicable to any trait for any
laboratory or wild population, paving the way for investigating sex-, age-
and environment-specific genetic effects and thus the underlying genetic
architecture of phenotype in biological study systems.