Manzanillo, P. | bioRxiv Science

bioRxiv2026

High-resolution analysis of T cell subsets, clonality, and trajectories in psoriasis

Psoriasis is sustained by type 17 immunity, yet how transcriptionally defined T-cell states are clonally organized across lesions, clinically uninvolved skin, and the circulation remains incompletely understood. We performed paired single-cell RNA and T-cell receptor (TCR) sequencing of T cells isolated from two spatially separated lesions, non-lesional skin, and peripheral blood from 23 participants with psoriasis, together with healthy skin and blood comparators. We resolved 19 cutaneous T-cell populations and found that lesions were enriched for IL-17-associated CD4+ and CD8+ states and activated regulatory T-cell states. CD8+ Tc17 cells showed prominent clonal expansion, and expanded clonotypes contributed more prominently to skin than to blood. Clonotype sharing was greatest between paired lesions, while clonotypes detected in cutaneous IL-17-associated cells mapped to multiple circulating phenotypes, indicating that blood and skin capture complementary features of the disease-associated repertoire. At the sample level, T-cell composition separated 57 lesional samples into two recurrent compositional states that were largely concordant across paired body sites. HLA-C*06:02 status was associated with differences in pretreatment lesional CD8+ T-cell composition, clonotype overlap, and clonal-size distributions. Exploratory longitudinal analyses in eight treated participants showed heterogeneous remodeling of T-cell composition and clonotype detection after therapy. Together, these findings define tissue-restricted and tissue-shared features of the psoriatic T-cell repertoire and identify clonal architecture across skin sites and blood as an organizing feature of lesion heterogeneity.

immunology↗

bioRxiv2020

Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BackgroundElucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. ResultsHere, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluate methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5 v1 and 3 v3 methods. We demonstrate that these methods have fewer drop-out events which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. ConclusionOverall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

immunology↗