Charting the differentiation topology of SF3B1 mutated clonal hematopoiesis (CH) and myelodysplastic syndromes (MDS) via a multi-omics single-cell toolkit

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SUMMARY Genomic analyses of thousands of MDS patients has established that mutations in RNA splicing factors are the most common class of genetic alterations in patients with MDS. In parallel, functional studies have revealed that several of these genetic lesions appear to drive aberrant hematopoietic self-renewal and differentiation that is characteristic of MDS. Specifically, mutations in splicing factor 3b subunit 1(SF3B1), a core spliceosome component, are among the most common in patients with MDS and lead to incorrect intronic branch point recognition. Despite these advances, our knowledge of the effects of this genetic alteration on downstream gene expression programs within actual disease initiating cells has been hampered by the coexistence of normal wildtype hematopoiesis together with the aberrant clone harboring somatic driver mutations. While some of these limitations are now beginning to be addressed with single cell genomics, performing a layered genomic analysis to simultaneously capture somatic mutations, gene expression, RNA splicing, and chromatin state in single cells has never been performed. Expression of RNA-binding proteins is in turn cell type dependent, necessitating the simultaneously profiling of gene expression, full-length cDNA and SF3B1 mutational status at the single cell level, allowing splicing to be examined in the proper cellular context. 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 (GoT). Importantly, GoT turns the admixture of mutant and wildtype hematopoiesis from a limitation to an advantage, enabling the direct comparison of mutant and wildtype cells within the same individual. Capitalizing on a unique cohort of bone marrow samples from individuals with MDS and CH, we now aim to apply and extend the multi-omics single-cell toolkit to test define how SF3B1 somatic mutations lead to clonal growth advantage. First, we will perform GoT across MDS and CH samples with canonical SF3B1 driver mutations. We will integrate GoT with Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE- seq) (GoT-CITE), to add the critical layer of cell surface markers to single-cell whole transcriptomes. Second, mutations in splicing factors are specifically associated with greater risk of transformation in CH. Therefore, we will develop and implement GoT-Splice, where long-read sequencing will be used to define splicing variation as a function of cell identity. Third, given the high importance of epigenetic patterning to hematopoietic stem cell identity, we will develop and apply targeted single-cell genotyping in the context of chromatin accessibility (GoT-ChA). This will allow us to unravel the regulatory underpinnings of SF3B1-driven CH and MDS.