Profiling of cis-regulatory elements (CREs) in single cells allows the interrogation of the cell-type specific contexts of gene regulation and genetic predisposition to diseases. Here we demonstrated transcribed CREs (tCREs) are detectable from single-cell RNA-5′end-sequencing (sc-end5-seq) data, enabling simultaneous quantification of gene expression and enhancer activities in a single assay at no extra cost. As compared to CREs defined based on chromatin accessibility, we found tCREs are more accurate in predicting CRE interactions by co-activity, more sensitive in detecting shifts in alternative promoter usage and more enriched in disease heritability. We have developed a tool, SCAFE, for identification of genuine tCREs and applied it to sc-end5-seq data of >350,000 single cells, defining an atlas of 233,311 tCREs across 21 broad-cell-types and 180 narrow-cell-types in 23 human tissues. Using a novel tCRE module based heritability enrichment method, we were able to robustly estimate the enrichment of disease heritability at single-cell resolution across the tCRExCell atlas. This analysis framework allowed us to flexibly correlate disease heritability with a wide-range of single-cell-based properties, e.g. correlation of autoimmune disease heritability with T-cell effectorness and the tCREs driving such correlation. We have applied this analysis framework to the tCRExCell atlas with >100 diseases. While it recapitulated previous known distinct cell-type-to-disease associations (e.g. psychiatric diseases and neuron subtypes), it also revealed novel associations between various diseases and continuous cell-states driven by specific tCRE modules (e.g. hypertension and endothelial cell states). Finally, it allowed us to prioritize the disease associated variants based on the activity of their cognate tCREs, which is not feasible in gene-based single-cell expression analyses. In summary, this tCRE-based analysis framework provided an interface between disease heritability and single-cell expression data, enabling the interpretations of disease predispositions in the cell-type/state specific contexts of gene regulation as well as functional fine-mapping of disease associated variants.