We are grateful to the Journal of Marriage and Family for this forum in which to discuss important issues in candidate Gene× Environment (cGxE) family research and to Drs. Salvatore and Dick (2015) for sharing their expertise and their thoughtful and balanced commentary on our article (Schlomer, Fosco, Cleveland, Vandenbergh, & Feinberg, 2015). We found many points of agreement in their commentary and believe that differences in our views are a matter of degree and emphasis rather than contrast.We agree with Salvatore and Dick that a major challenge in cGxE research is "which gene." We differ, however, with the suggestion that considering the "usual suspects" is necessarily problematic. Although this strategy should not be exclusively pursued, there is now a decades-old literature on these usual-suspect markers (e.g., SLC6A4, DRD4, MAOA, CHRNA5), including genomic function, neurological/hormonal correlates, endophenotypes, psychological/behavioral outcomes, and environmental moderation. It is because these markers have been well characterized, at multiple analytic levels, that they have been incorporated into family/developmental research. Given adequate sophistication and care (see Cleveland et al., in press), research with these genes can provide valuable insights into gene-environment interplay.Salvatore and Dick note that genome-wide association studies (GWAS) have shown inconsistent associations with psychiatric phenotypes and suggest we should be no better at "guessing" sensitivity genes. Our own skepticism (Schlomer et al., 2014) has been somewhat abated, however, by the growing number of studies that have found cGxE patterns consistent with plasticity theories (i.e., differential susceptibility theory, diathesis-stress, vantage sensitivity), including compelling evidence from experimental studies (e.g., van IJzendoorn & Bakermans-Kranenburg, in press) and prevention/intervention studies that use random assignment (e.g., Brody Beach, Philibert, Chen, & Murry, 2009). Two additional experimental studies of DRD4 and alcohol use (Creswell et al., 2012; Larsen et al., 2010) have made a particularly strong case that some genes deserve the status of a usual suspect.GWAS and cGxE approaches have unique strengths, and neither should be dismissed on the basis of their limitations. GWAS analyses are greatly important for discovering gene-phenotype links. However, the inconsistency noted by Salvatore and Dick may be the result of the search for population-level main effects. Because they require large samples, GWAS findings likely reflect a gene's average effect over the wide range of environments from which the samples were drawn. However, if a genetic effect is larger in one environment and smaller in others, the overall main effect may be small and thus difficult to detect statistically. The solution to this problem has been to increase power through sample size. Interaction-based work underscores a reality that in many cases (based on the shape of the interaction and the distribution of the environments sampled) a null main effect may hide an interaction, as exemplified in our findings (Schlomer et al., 2015). Thus, in conventional GWAS a null main effect overlooks the possibility that an allelic association may be environmentally contingent. The remedy for inconsistent GWAS findings may include more than increasing sample size, such as considering conditional associations (i.e., moderation).MOVING FORWARD IN CGXE RESEARCHOur view of the future of cGxE research is optimistic, tempered by the need for careful and critical evaluation of this work. To assist in this process, we emphasize five domains in which cGxE research should be evaluated: Design, Measurement, Theory, Biological Role, and Population Structure.DesignThere are substantial benefits of applying randomized designs to cGxE research. In epidemiological studies, causality is difficult to determine because experience-outcome associations may equally reflect causal environmental influences or self-selection into those environmental experiences. …