Abstract We analyzed whole genome–based transcriptional profiles of Mycobacterium tuberculosis subjected to prolonged hypoxia to guide the discovery of novel potential Ags, by a combined bioinformatic and empirical approach. We analyzed the fold induction of the 100 most highly induced genes at 7 d of hypoxia, as well as transcript abundance, peptide-binding prediction (ProPred) adjusted for population-specific MHC class II allele frequency, and by literature search. Twenty-six candidate genes were selected by this bioinformatic approach and evaluated empirically using IFN-γ and IL-2 ELISPOT using immunodominant Ags (Acr-1, CFP-10, ESAT-6) as references. Twenty-three of twenty-six proteins induced an IFN-γ response in PBMCs of persons with active or latent tuberculosis. Five novel immunodominant proteins—Rv1957, Rv1954c, Rv1955, Rv2022c, and Rv1471—were identified that induced responses similar to CFP-10 and ESAT-6 in both magnitude and frequency. IL-2 responses were of lower magnitude than were those of IFN-γ. Only moderate evidence of infection stage–specific recognition of Ags was observed. Reconciliation of bioinformatic and empirical hierarchies of immunodominance revealed that Ags could be predicted, providing transcriptomic data were combined with peptide-binding prediction adjusted by population-specific MHC class II allele frequency.