Multiple myeloma (MM) is a cancer of plasma cells with approximately 200,000 new cases/year and a 54% 5-year overall survival rate. Myeloma arises from expansion of pre-existing clonal populations, referred to as either monoclonal gammopathy of uncertain significance (MGUS) or smoldering multiple myeloma (SMM), but only ~1% of individuals with these precursors will develop fulminant MM. As myeloma cells expand, clonal genetic differences lead to relapse due to acquired resistance in nearly 100% of patients, suggesting that initial therapy is inadequate to eradicate the entire disease burden and mandating regular, long-term surveillance. Being able to more comprehensively identify low-frequency subclones that may result in frank disease or resistance would enable a more direct application of precision therapies. Here, we present proof of concept single-cell, multiomic data identifying the clonal populations that progress to frank myeloma or resistant disease.