It is becoming increasingly clear that local adaptation can occur even in the face of high gene flow and limited overall genomic differentiation among populations (reviewed by Nosil et al. 2009). Thus, one important task for molecular ecologists is to sift through genomic data to identify the genes that matter for local adaptation (Hoffmann & Willi 2008; Stapley et al. 2010). Recent advances in high-throughput molecular technologies have facilitated this search, and a variety of approaches can be applied, including those grounded in population genetics [e.g. outlier analysis (Pavlidis et al. 2008)], classical and quantitative genetics [e.g. quantitative trait locus analysis (MacKay et al. 2009)], and cellular and molecular biology [e.g. transcriptomics (Larsen et al. 2011)]. However, applying these approaches in nonmodel organisms that lack extensive genetic and genomic resources has been a formidable challenge. In this issue, Papakostas et al. (2012). demonstrate how one such approach – high-throughput label-free proteomics (reviewed by Gstaiger & Aebersold 2009; Domon & Aebersold 2010) – can be applied to detect genes that may be involved in local adaptation in a species with limited genomic resources. Using this approach, they identified genes that may be implicated in local adaptation to salinity in European whitefish (Coregonus lavaretus L.) and provide insight into the mechanisms by which fish cope with changes in this critically important environmental parameter.