Targeted proteomics enables hypothesis-driven research by measuring the expression of protein cohorts related by function or disease in systems biology. Here, I highlight a strategy, termed GoDig, for targeting entire pathways of up to 200 proteins selected from among >10,000 expressed proteins, exploiting sample multiplexing to increase throughput. GoDig requires only a single-shot LC-MS analysis (equivalent to 7.5-min per sample), ~1 µg peptide material, and real-time analytics to simultaneously quantify hundreds of analytes across up to 18 samples. Importantly, MS3 scans are triggered without MS1 detection. We have applied the GoDig assay to study pathways in yeast, human, and mouse. For example, we have applied GoDig to investigate the impact of genetic variation on protein expression across 480 fully-genotyped diversity outbred (DO) mice fed a high-fat diet. We identified previously unknown quantitative trait loci and established potential linkages between specific proteins and lipid homeostasis.