In this study, we developed a novel approach by combining laser capture microdis-section (LCM) for isolating individual neuronal somas and the Smart-seq2 for generating full length RNA-seq libraries. We sequenced 1066 hDRG neurons with minimum satellite glial cell contamination from six lower thoracic and lumbar DRGs of three donors, detecting an average of >9,000 unique genes per neuron (~ 3-5 times or more than the previous single-nucleus RNA-seq results) and identifying 16 molecularly distinctive neuron types. Cross-species analysis revealed both similarities but considerable differences among human, macaque, and mouse DRG neurons. In addition, we uncovered a set of novel marker genes that can help to distinguish different types of sensory neurons and afferents in hDRG and skin tissues. Based on the molecular profiles, we also predicted novel response properties of human sensory afferents, which were tested and confirmed by single-cell in vivo recordings. These results support a close relationship between the molecular profiles uncovered by single-soma RNA-seq, histology, and functional properties of human sensory afferents, highlighting the precision and unique utility of this dataset in guiding functional studies of human somatosensory neurons. In short, we have established a novel approach to conduct single-soma deep RNA-seq of hDRG neurons, which revealed previously unknown neuronal types and functional properties. Given the high number of unique transcripts recovered from each neuron, our dataset is especially powerful for molec-ular discovery, such as identifying potential high value novel drug targets. We believe that this high-fidelity single-soma RNA-seq dataset will serve as a ground reference for homogenizing RNA-seq data of human DRG/TG neurons using different approaches and for translating animal studies into therapeutic applications.