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Programmable transcript-specific enrichment for single-cell sequencing enables profiling of rare cell states

ABSTRACT: The widespread application of single-cell genomics technologies has accelerated our understanding of the breadth and depth of heterogeneity of cell states across diverse contexts. As single-cell RNA sequencing (scRNA-seq) has been the most popular modality used for profiling, many populations have been described primarily based on specific marker transcript profiles compared to classical cytometry approaches relying on protein expression. Additionally, many single cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address this limitation, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables single cell and single nuclei RNA-seq profiling from subpopulations of complex cellular mixtures solely defined by the abundance of RNA transcripts. Across vignettes of immune cell populations as well as nuclei from fresh frozen and formalin-fixed paraffin-embedded brain tissue, we demonstrate the enrichment of cell populations via RNA-based cytometry upstream of high-throughput scRNA-seq. Together, our approach provides a rational, programmable method for studying cell identities and transcriptional heterogeneity of rare populations identifiable by as few as one marker transcript, advancing the rational study of cellular diversity across fresh and archived tissue materials.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE262355 | GEO | 2024/03/26

REPOSITORIES: GEO

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Project description:Genomic analysis of many cancers has led to the identification of novel targets and the development of personalized, targeted therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. Clinical specimens typically contain variable degrees of non-tumor cells that can mask a potentially critical genomic signature, leaving important clinically relevant events undetected. When analysis is limited to a smaller number of specimens, the effects of heterogeneity within each sample is magnified. In light of these challenges, we used DNA content based flow cytometry to isolate clonal tumor populations from a series of rare cancers for genomic analysis: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. These purified clonal populations are then subject to high definition measurement of copy number aberrations by objectively measuring the height and boundaries of amplicons and by discriminating homozygous from partial deletions. Ranking of these events by copy number facilitates the identification of highly selected aberrations. This approach can garner useful information from a single biopsy. In the cases we describe, several potential therapeutic targets were identified and genomic aberrations correlated with the phenotypic behavior. We propose that clonal genomic analysis can generate unique hypotheses and guide the development of clinical advances for these and other rare tumors. We applied DNA content based flow sorting to isolate the nuclei of clonal populations from tumor biopsies. We coupled this strategy with oligonucleotide array CGH (aCGH) thereby obtaining high definition genomic profiles of clonal populations from different rare tumors including pancreatic neuroendocrine cancers, adrenal leiomyosarcoma, anal carcinoma, and cholangiocarcinoma.

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Programmable transcript-specific enrichment for single-cell sequencing enables profiling of rare cell states

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