Libraries corresponding to 7 animals (variable number of tissues per animal) were sequenced using Illumina NextSeq. Reads were aligned to the M. mulatta genome assembly 8.0.1 annotation version 102 and processed according to the Drop-Seq Computational Protocol v2.0 (https://github.com/broadinstitute/Drop-seq). Data was normalized and scaled using the Seurat R package v2.3.4 (https://satijalab.org/seurat/): transforming the data to loge(UMI+1) and applying a scale factor of 10,000. To identify major axes of variation within our data, we first examined only highly variable genes across all cells, yielding approximately 1,000-3,000 variable genes with average expression > 0.1 log-normalized UMI across all cells. An approximate principal component analysis was applied to the cells to generate 100 principal components (PCs). Using the JackStraw function within Seurat, we identified significant PCs to be used for subsequent clustering and further dimensionality reduction. For 2D visualization and cell type clustering, we used a Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction technique (https://github.com/lmcinnes/umap) with “min_dist” set to 0.5 and “n_neighbors” set to 30. To identify clusters of transcriptionally similar cells, we employed unsupervised clustering as described above using the FindClusters tool within the Seurat R package with default parameters and k.param set to 10 and resolution set to 0.5. Each cluster was sub-clustered to identify more granular cell types, requiring each cell type to express > 25 significantly upregulated genes by differential expression test (FindMarkers implemented in Seurat, setting “test.use” to “bimod,” Bonferroni-adjusted p value cutoff < 0.001). Differential expression tests between cells from ACE2 + versus ACE2 - Type II Pneumocytes were conducted using the SCDE R package with default parameters (Kharchenko et al., 2014). Expression data for epithelial cells and enterocytes included in this dataset can be visualized and downloaded here: https://singlecell.broadinstitute.org/single_cell/study/SCP807?scpbr=the-alexandria-project#study-summary.