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Cytogenetics and molecular genetics

Complex landscape of alternative splicing in myeloid neoplasms

A Correction to this article was published on 13 March 2021

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Abstract

Myeloid neoplasms are characterized by frequent mutations in at least seven components of the spliceosome that have distinct roles in the process of pre-mRNA splicing. Hotspot mutations in SF3B1, SRSF2, U2AF1 and loss of function mutations in ZRSR2 have revealed widely different aberrant splicing signatures with little overlap. However, previous studies lacked the power necessary to identify commonly mis-spliced transcripts in heterogeneous patient cohorts. By performing RNA-Seq on bone marrow samples from 1258 myeloid neoplasm patients and 63 healthy bone marrow donors, we identified transcripts frequently mis-spliced by mutated splicing factors (SF), rare SF mutations with common alternative splicing (AS) signatures, and SF-dependent neojunctions. We characterized 17,300 dysregulated AS events using a pipeline designed to predict the impact of mis-splicing on protein function. Meta-splicing analysis revealed a pattern of reduced levels of retained introns among disease samples that was exacerbated in patients with splicing factor mutations. These introns share characteristics with “detained introns,” a class of introns that have been shown to promote differentiation by detaining pro-proliferative transcripts in the nucleus. In this study, we have functionally characterized 17,300 targets of mis-splicing by the SF mutations, identifying a common pathway by which AS may promote maintenance of a proliferative state.

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Fig. 1: Overview of splicing factor (SF) mutations and expression levels in the cohorts.
Fig. 2: Overview of alternative splicing (AS) events observed in patient and control samples and quantified by rMATS.
Fig. 3: Distribution of dysregulated alternative splicing events by disease and SF mutation or expression.
Fig. 4: Predicted impact of AS on biological and clinical outcomes.
Fig. 5: Enhanced exclusion of RIs in SF groups compared with healthy controls.
Fig. 6: Characterization of rare somatic mutations in SFs and identification of neojunctions.

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Acknowledgements

This work was supported by U.S. NIH grants R01HL123904, R01HL132071 and R35HL135795 and Torsten Haferlach Leukämiediagnostik Stiftung. CEH was supported by NIH F31HL131140. We thank the staff of MLL for sample preparation and sequencing, RC Dietrich for helpful discussions and comments regarding the paper, DM Rotroff for assistance with clustering analysis, and T Radivoyevitch for advice on statistics. The authors wish to acknowledge the Vera and Joseph Dresner Foundation as a funding source and thank them for their contributions to this work.

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CEH, RAP, JPM, and TH conceptualized the project. CEH, RAP, JPM, TH, and MAS prepared the paper, with contributions from all authors. CMK assisted in sample preparation. CEH, DCM, VA, CH, NN, ST, SH, MM, WW, CB, WK, and TH performed data curation. CEH performed formal analyses and DCM contributed to formal analyses for Figs. 4 and 6.

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Correspondence to Richard A. Padgett.

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TH, CH, and WK serve as the management board of the MLL Munich Leukemia Laboratory. NN, ST, SH, MM, WW, and CB are employed by the MLL Munich Leukemia Laboratory. The MLL offers diagnostic services for leukemias and lymphomas, including cytomorphology, cytochemistry, immunophenotyping, cytogenetics, FISH, and a broad spectrum of molecular assays. In addition, MLL runs several research studies based on a combination of methods for routine use and also including whole genome sequencing and whole transcriptome sequencing.

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Hershberger, C.E., Moyer, D.C., Adema, V. et al. Complex landscape of alternative splicing in myeloid neoplasms. Leukemia 35, 1108–1120 (2021). https://doi.org/10.1038/s41375-020-1002-y

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