Fibroblasts are non-hematopoietic structural cells that regulate tissue architecture, support homeostasis of tissue-resident cells and play pivotal roles in biological processes such as fibrosis, cancer, autoimmunity and wound-healing. While recent studies describe fibroblast heterogeneity across individual tissues, the field lacks a comprehensive, high resolution characterization of fibroblasts across tissues in healthy and diseased organs. Here, we applied state-of-the-art data integration methods to consolidate single-cell transcriptomics data into fibroblast atlases from 50 datasets, 17 tissues, 11 disease states and 2 species, leading us to propose paradigm of fibroblast lineage organization in health and disease. Mouse fibroblast atlases at steady- and perturbed-state coupled with lineage tracing methods led to the identification of two universal fibroblast transcriptional subtypes across multiple tissues along with specialized and disease-specific subsets. Computational predictions followed by experimental validation suggested that universal fibroblasts serve as a reservoir that can yield specialized fibroblasts across a broad range of steady-state tissues and activated fibroblasts across disease. Furthermore, comparison to an atlas of human fibroblasts from perturbed states showed that transcriptional states are conserved between mice and humans, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. We are now investigating spatial transcriptomics and chromatin dynamics to elucidate fundamental aspects of universal fibroblasts, their localization and cellular sphere of influence, gene regulatory network and transcription factors that orchestrate gene expression programs during diseased conditions. Taken together, our integrative analyses of fibroblasts represent an effort into implementing sophisticated single-cell methods towards the discovery of novel fundamental biology which will yield dividends for human medicine.