scRNA-seq and single-cell TCR sequencing (scTCR-seq)

scRNA-seq and scTCR-seq libraries were prepared by the UCSF Core Immunology laboratory using the 10X Chromium Single Cell 5′ Gene Expression and V(D)J Profiling Solution kit, according to the manufacturer’s instructions (10X Genomics). 150 paired-end sequencing was performed on a Novaseq 6000 instrument.

The Cell Ranger analysis pipelines (version 3.0.2; 10X Genomics) were then used to process the generated sequencing data. Data were demultiplexed into FASTQ files, aligned to the GRCh38 human reference genome, and counted, and TCR library reads were assembled into single-cell V(D)J sequences and annotations. For gene expression analysis, the R package Seurat (version 3.0; Stuart et al., 2019) was used.

Filtered gene-barcode matrices were loaded and quality-control steps were performed (low-quality or dying cells and cell doublets/multiplets were excluded from subsequent analysis). Data were normalized and scaled, and then linear dimensional reduction using principal-component analysis was performed. Highly variable genes were used to perform unsupervised clustering, and nonlinear dimensional reduction with UMAP was used to visualize the data.

For scRNA-seq analysis, human melanoma single-cell datasets were integrated with the IntegrateData function of Seurat (Stuart et al., 2019). For differential gene expression analysis comparing LAYN-expressing cells to LAYN-nonexpressing cells, data were subsetted into LAYN negative (−) and LAYN positive (+) categories using LAYN expression > 0.1 as a threshold. Heatmaps were created using the R package Pretty Heatmaps (Kolde, 2015), and volcano plots were produced with ggplot2 (Wickham, 2016).

From the 10X cellranger “vdj” and “count” outputs, clones are defined as groups of 10X barcodes with perfect amino acid sequence homology of one or both of the TCR α or β chains. No two cells both having α and β chains exist where only one chain matches. All plots were generated using the R packages ggplot2 and cowplot. GEX LAYN data were generated using the R package Seurat version 3.0 and UMAP coordinates. To generate the coxcomb plots, the top 20 clones both expressing and not expressing a marker were dichotomized by majority consensus of binarized expression for said marker. Sequencing data have been uploaded to the National Center for Biotechnology Information Gene Expression Omnibus and can be accessed with the accession number GSE148190.