Single-cell multi-omics defines the cell-type specific impact of splicing aberrations in human hematopoietic clonal outgrowths

scRNAseq CH01-02, CH04, MDS01-06 and AML01A-B (See Table S1), raw (FASTQ) and processed (gene matrix counts, barcodes, features, and isoform junction counts) samples.

Description: RNA splicing factors are recurrently affected by alteration-of-function mutations in clonal blood disorders, highlighting the importance of splicing regulation in hematopoiesis. However, our understanding of the impact of dysregulated RNA splicing has been hampered by the inability to distinguish mutant and wildtype cells in primary patient samples, the cell-type complexity of the hematopoietic system, and the sparse coverage of splice junctions by short-read sequencing typically used in single-cell RNA sequencing. To overcome these limitations, we developed GoT-Splice by integrating Genotyping of Transcriptomes (GoT) with enhanced efficiency long-read single-cell transcriptome profiling, as well as proteogenomics (with CITE-seq). This allowed for the simultaneous single-cell profiling of gene expression, cell surface protein markers, somatic mutation status, and RNA splicing. We applied GoT-Splice to bone marrow progenitors from patients with myelodysplastic syndrome (MDS) affected by mutations in the most prevalent mutated RNA splicing factor – the core RNA splicing factor SF3B1. High-resolution mapping of SF3B1mut vs. SF3B1wt hematopoietic progenitors revealed increased fitness advantage of SF3B1mut cells in the megakaryocytic-erythroid lineage, resulting in an expansion of SF3B1mut erythroid progenitor (EP) cells. SF3B1mut EP cells exhibited upregulation of genes involved in regulation of cell cycle and mRNA translation. Long-read single-cell transcriptomes revealed the previously reported increase of aberrant 3’ splicing site usage in SF3B1mut cells. However, the ability to profile splicing within individual cell populations uncovered distinct cryptic 3’ splice site usage across different progenitor populations, as well as stage-specific aberrant splicing during erythroid maturation. Lastly, as splice factor mutations occur in clonal hematopoiesis (CH) with increased risk of neoplastic transformation, we applied GoT-Splice to CH samples. These data revealed that the erythroid lineage bias, as well as cell-type specific cryptic 3’ splice site usage in SF3B1mut cells, precede overt MDS. Collectively, we present an expanded multi-omics single-cell toolkit to define the cell-type specific impact of somatic mutations on RNA splicing, from the earliest phases of clonal outgrowths to overt neoplasia, directly in human samples.
Authors:
Mariela Cortés-López, Paulina Chamely, Allegra G. Hawkins, Robert F. Stanley, Ariel D. Swett, Saravanan Ganesan, Tarek H. Mouhieddine, Xiaoguang Dai, Lloyd Kluegel, Celine Chen, Kiran Batta, Nili Furer, Rahul S. Vedula, John Beaulaurier, Alexander W. Drong, Scott Hickey, Neville Dusaj, Gavriel Mullokandov, Adam M. Stasiw, Jiayu Su, Ronan Chaligné, Sissel Juul, Eoghan Harrington, David A. Knowles, Catherine J. Potenski, Daniel H. Wiseman, Amos Tanay, Liran Shlush, Robert C. Lindsley, Irene M. Ghobrial, Justin Taylor, Omar Abdel-Wahab, Federico Gaiti, Dan A. Landau
Lab: Gaiti
Year: 2022
Keywords:

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39 samples

Sample Type:N/A
Species:Human
Datatype:scRNAseq
Technology:Illumina HiSeq 4000, MinION, Illumina NovaSeq 6000, PromethION

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This dataset is public.

Contact: Dan Landau

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