We describe a systems biology approach for the genetic dissection of complex traits based on applying gene network theory to the results from genome-wide associations. The associations of singlenucleotide polymorphisms (SNP) that were individually associated with a primary phenotype of interest, age at puberty in our study, were explored across 22 related traits. Genomic regions were surveyed for genes harboring the selected SNP. As a result, an association weight matrix (AWM) was constructed with as many rows as genes and as many columns as traits. Each {i, j} cell value in the AWM corresponds to the z-score normalized additive effect of the ith gene (via its neighboring SNP) on the jth trait. Columnwise, the AWM recovered the genetic correlations estimated via pedigree-based restricted maximum-likelihood methods. Rowwise, a combination of hierarchical clustering, gene network, and pathway analyses identified genetic drivers that would have been missed by standard genome-wide association studies. Finally, the promoter regions of the AWM-predicted targets of three key transcription factors (TFs), estrogen-related receptor γ (ESRRG), Pal3 motif, bound by a PPAR-γ homodimer, IR3 sites (PPARG), and Prophet of Pit 1, PROP paired-like homeobox 1 (PROP1), were surveyed to identify binding sites corresponding to those TFs. Applied to our case, the AWM results recapitulate the known biology of puberty, captured experimentally validated binding sites, and identified candidate genes and genegene interactions for further investigation.bovine | complex traits | fertility | reproduction | systems biology T he analysis of genome-wide association studies (GWASs) applied to complex traits remains a challenge (1). Addressing a complex trait by a single, often binary, phenotypic measure is common practice but is limiting. It is not easy to find the right balance between applying a conservative significance threshold that gives rise to a small number of strong and hopefully biologically meaningful associations and applying a relaxed threshold yielding numerous associations, many of which are new but potentially false. In addition, an increase in sample size coupled with a denser chip results in a larger number of associations that, on average, have a much smaller effect (2). Accepting a large number of associations while simultaneously reducing the number of false positives would be ideal. It is reasonable to propose that a holistic approach applied to a relaxed significance threshold could be the solution. Such a strategy would be particularly useful when investigating the genetic basis of complex traits that, by definition, are influenced by numerous genes and pathways.In our study, age at puberty was the complex phenotype considered. Puberty, or the progression to sexual maturity, is a developmental process with genetic drivers conserved among species (3). It is an important phenotype for the beef industry because late puberty has negative effects on reproduction rates and profitability (4). Age at puberty is moderately heritab...