Single-Cell Multi-omics to Link Clonal Mosaicism (CM) Genotypes with Chromatin, Epigenomic, Transcriptomic and Protein Phenotypes - SUMMARY Clonal outgrowths are observed across a wide range of normal human tissues. Clones harbor somatic mutations in known cancer and other driver genes, and show evidence of positive selection. Nevertheless, how these driver mutations alter the cellular states of cells to allow clones to outcompete wildtype counterparts remains poorly understood. To date, efforts to chart clonal outgrowths in normal tissues have been largely limited to genotyping. This is due to the fact that clones often affect a minority of cells in a sample, without distinguishing cell surface markers or morphological features. To address this challenge, we developed an array of multi-omic single-cell technologies that are capable of capturing multiple layers of information (e.g., genotypes, transcriptomes, methylomes, protein expression) from the same single cells. Moreover, we addressed the specific challenge of genotyping in scRNA-seq in single cells at high throughput by developing genotyping of transcriptomes. Importantly, this technology turns the admixture of mutant and wildtype cell from a limitation to an advantage, enabling the direct comparison of mutant (“winner”) and wildtype (“loser”) cells within the same individual. Capitalizing on our experience with single-cell technology development, we aim to extend the multi-omics single-cell GoT (Genotyping of Targeted loci) toolkit to allow to interrogate how somatic mutations lead to clonal growth advantage. First, we will develop and enhance our targeted single-cell genotyping in the context of chromatin accessibility (GoT-ChA). This technology critically performs genotyping from DNA directly, obviating limiting dependencies on mutated loci gene expression. Thus, it can be applied to extracted nuclei, critical for the SMaHT initiative. We will build on GoT-ChA using nanobody tethered transposases to jointly profile somatic mutations and histone modifications in single nuclei (GoT-EpiM). To capture transcriptional changes together with somatic mutation genotyping and chromatin accessibility, we will further use transposition of mRNA:cDNA hybrid in GoT-ChA-RNA. Finally, we will leverage recent advances that use antibodies tagged with oligonucleotides to capture mutated loci, chromatin and intra-nuclear proteins such as transcription factors (GoT-ChA-Pro). In aim 2, we will collaborate with genomic characterization centers to apply these technologies to primary human samples to define how clonal mutations in normal tissues alter chromatin, histone modifications, transcriptomes and protein abundance profiles to yield clonal outgrowth. Our overarching goal is to invoke multi-omic comparisons at the single-cell level between wildtype and mutant cells to comprehensively identify the underpinnings of fitness advantage in clonal outgrowth. The proposed comprehensive GoT toolkit will enable to link, at high throughout single-cell genotypes with transcriptional, protein, and epigenetic, with important implication in the study of clonal mosaicism as a harbinger of cancer, as well as other human health outcomes.
