Integrative analysis of spatial transcriptome with single-cell transcriptome and single-cell epigenome in mouse lungs after immunization
Zhongli Xu, Xinjun Wang, Li Fan, Fujing Wang, Becky Lin, Jiebiao Wang, Giraldina Trevejo-Nuñez, Wei Chen, Kong Chen
Abstract
infection model. We built an optimized deconvolution pipeline to accurately decipher specific cell-type compositions by anatomic location. We discovered that combining scATAC-seq and scRNA-seq data may provide more robust cell-type identification, especially for lineage-specific T helper cells. Combining all three modalities, we observed a dynamic change in the location of T helper cells as well as their corresponding chemokines. In summary, our proof-of-principle study demonstrated the power and potential of single-cell multi-omics analysis to uncover spatial- and cell-type-dependent mechanisms of lung immunity.
Topics & Concepts
TranscriptomeEpigenomeSingle-cell analysisComputational biologyBiologyCellGenomicsRNA-SeqGenomeCell biologyGeneticsGeneGene expressionDNA methylationSingle-cell and spatial transcriptomicsImmune cells in cancerImmunotherapy and Immune Responses