Abstract 313: Benchmarking immune repertoire sequencing technologies

Abstract In the past decade, single cell gene expression technologies have transformed basic and translational research and are more frequently found in the toolbox of immunologists alongside the standard bulk B-cell receptor (BCR) sequencing and transcriptome profiling assays. While conventional bulk BCR assays capture the frequency of single chains, single-cell immune profiling reveals the frequency of paired heavy and light chains along with the cells transcriptional profile. Here we present the results of a single-blind benchmarking experiment conducted in collaboration with the U. S. Food and Drug Administration (FDA) that compares the performance of standard bulk DNA and RNA BCR repertoire sequencing assays, with the 10x Genomics Single Cell Immune Profiling solution. The FDA selected nine unambiguously monoclonal BCR-expressing cell lines to generate a reference mixture that was shared with each study participant, without revealing the input proportions. This reference cell line mixture was also diluted to 10% and 1% with B-cells sorted from peripheral blood mononuclear cells (PBMC) to further test the limits of clonotype detection. For each experiment, we targeted ~10, 000 cells and in aggregate generated a paired gene expression and V (D) J dataset from ~100, 000 cells. BCR clonotypes were detected in 78% of the captured cells across all samples profiled. Each of the 9 top unique clonotypes observed in our dataset corresponded to a cell line in the reference mixture, allowing us to decode the mixing percentages of each BCR-expression cell line. In addition, we were able to identify rare cell line clonotypes to as low as 0. 01% in the dilution experiments. Furthermore, the multimodal nature of the single cell data also resolved the transcriptional profile of each cell line into its own cluster thus enabling independent verification of clonotype proportions. In summary, we have generated a resource for the immunology community to evaluate and compare data generated with different repertoire sequencing technologies. Citation Format: Shamoni Maheshwari, Carolyn Morrison, Sarah Taylor, BCR-SEQC consortium. Benchmarking immune repertoire sequencing technologies abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 313.