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. 2020 Sep 24;136(13):1477-1486.
doi: 10.1182/blood.2020006868.

Single-cell genomics reveals the genetic and molecular bases for escape from mutational epistasis in myeloid neoplasms

Justin Taylor  1   2 , Xiaoli Mi  1 , Khrystyna North  3   4   5 , Moritz Binder  6 , Alexander Penson  1 , Terra Lasho  6 , Katherine Knorr  1 , Michael Haddadin  1 , Bo Liu  1 , Joseph Pangallo  3   4 , Salima Benbarche  1 , Daniel Wiseman  7 , Ayalew Tefferi  6 , Stephanie Halene  8   9 , Yang Liang  10 , Mrinal M Patnaik  6 , Robert K Bradley  3   4   5 , Omar Abdel-Wahab  1
Affiliations

Single-cell genomics reveals the genetic and molecular bases for escape from mutational epistasis in myeloid neoplasms

Justin Taylor et al. Blood. .

Abstract

Large-scale sequencing studies of hematologic malignancies have revealed notable epistasis among high-frequency mutations. One of the most striking examples of epistasis occurs for mutations in RNA splicing factors. These lesions are among the most common alterations in myeloid neoplasms and generally occur in a mutually exclusive manner, a finding attributed to their synthetic lethal interactions and/or convergent effects. Curiously, however, patients with multiple-concomitant splicing factor mutations have been observed, challenging our understanding of one of the most common examples of epistasis in hematologic malignancies. In this study, we performed bulk and single-cell analyses of patients with myeloid malignancy who were harboring ≥2 splicing factor mutations, to understand the frequency and basis for the coexistence of these mutations. Although mutations in splicing factors were strongly mutually exclusive across 4231 patients (q < .001), 0.85% harbored 2 concomitant bona fide splicing factor mutations, ∼50% of which were present in the same individual cells. However, the distribution of mutations in patients with double mutations deviated from that in those with single mutations, with selection against the most common alleles, SF3B1K700E and SRSF2P95H/L/R, and selection for less common alleles, such as SF3B1 non-K700E mutations, rare amino acid substitutions at SRSF2P95, and combined U2AF1S34/Q157 mutations. SF3B1 and SRSF2 alleles enriched in those with double-mutations had reduced effects on RNA splicing and/or binding compared with the most common alleles. Moreover, dual U2AF1 mutations occurred in cis with preservation of the wild-type allele. These data highlight allele-specific differences as critical in regulating the molecular effects of splicing factor mutations as well as their cooccurrences/exclusivities with one another.

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Conflict of interest statement

Conflict-of-interest disclosure: O.A.-W. has served as a consultant for H3B Biomedicine, Foundation Medicine Inc, Merck, and Janssen; is on the Scientific Advisory Board of Envisagenics Inc; and has received prior research funding from H3B Biomedicine that was unrelated to the current study. The remaining authors declare no competing financial interests.

Figures

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Graphical abstract
Figure 1.
Figure 1.
Genetic features of patients harboring 2 concomitant mutations in RNA splicing factors at the bulk and single-cell level. (A) Oncoprint of hotspot mutations in SF3B1, SRSF2, an U2AF1, as well as clearly deleterious mutations (nonsense or frameshift mutations) in ZRSR2 across 4231 patients. Each column represents 1 patient. The number of patients with 0, 1, or 2 splicing factor mutations is shown in yellow, orange, and red, respectively. Overall, mutations in each gene exhibited strong mutual exclusivity (q < .001; Fisher’s exact test). (B) CCF of each mutant splicing factor from genomic DNA sequencing of a cohort of 58 dual mutant splicing factor samples, including those from a single study. (C) CCF of mutations at SF3B1K700, other residues of SF3B1 (SF3B1 other), SRSF2P95/P96, U2AF1S34, and U2AF1Q157 as well as ZRSR2 truncation mutations (ZRSR2 trunc). (D) Percentage of patients with single or double splicing factor mutations (in black and red, respectively) with mutations in SRSF2, SF3B1, U2AF1, and ZRSR2. Error bars: 1 standard deviation, based on a binomial distribution. **P < .005; ***P < .0005 (Fisher’s exact test). (E) Plot describing the number of patients with coexisting mutant alleles in splicing factors. The expected number was based on the fraction of samples with exactly 2 mutations under the assumption of no mutual exclusivity and using a Poisson distribution. The distribution of the number of (F) total sequenced cells per patient and (G) reads per amplicon per cell from single-cell genomic DNA sequencing. Each point represents a sample from a unique patient. (H) Fraction of mutated cells with 1 or 2 mutations in RNA splicing factors within each patient with a dual splicing factor mutation. Red bar denotes fraction of individual cells where 2 splicing factor mutations were identified within the same cell. The number of cells containing each mutation is indicated.
Figure 2.
Figure 2.
Allele-specific mutational cooccurrences in RNA splicing factor mutations. (A) Oncoprint indicating cellular-level cooccurrence of mutations in select cases of double splicing factor mutations (the clinical diagnosis and sample ID is listed above each Oncoprint). Each column in the heat map (left) depicts an individual cell, with the genotype of each sequenced cell for each variant. Clustering is based on the genotypes of driver mutations, and the horizontal bar depicts the detected clones in each case. Mutant and wild-type cells are indicated in blue and white, respectively. The subclones located to the right of the red line comprised <1% of the total sequence cells, because such small subclones can represent false-positive or -negative genotypes as a result of allele dropout or multiplets. The figures on the right show the pairwise association of mutations. The color and size of each panel represent the degree of the logarithmic odds ratio (log OR). The vertical bar indicates the association of the colors with the log OR. Cooccurrence and mutual exclusivity are indicated by red and blue, respectively. The statistical significance of the associations based on the false discovery rate (FDR) is indicated by the asterisks. *FDR < 0.1; **FDR < 0.05; ***FDR < 0.001. (B) Fish plots showing the inferred clonal hierarchy based on the single-cell genotype data for the 3 patients in panel A. (C) Oncoprint, as in panel A, but evaluating cellular cooccurrence or mutual exclusivity of deleterious ZRSR2 mutations with mutations in other splicing factors (left) or with one another (right). CMML, chronic myelomonocytic leukemia; MDS-MLD, myelodysplastic syndrome with multilineage dysplasia; MDS/MPN-U with >15% RS, MDS/myeloproliferative neoplasm unclassified with >15% ring sideroblasts.
Figure 3.
Figure 3.
Allele-specific effects on RNA binding and splicing in splicing factor mutations seen in patients harboring 2 concomitant mutations in splicing factors. (A) Pie chart of SRSF2 P95 amino acid substitutions across the entire cohort. (B) Binding affinities of WT vs P95H/L/R/A mutant SRSF2 peptides to UCCAGU RNA oligonucleotides as absolute Kd values. The column labeled “change in affinity” provides the Kd ratio of the mutant:WT peptide. (C) Comparison of the quantitative effects of SF3B1K700E and SF3B1K666N mutations on splicing, stratified by mutant allele fraction. Each point illustrates the absolute change in isoform usage (ΔPSI) for 1 of the top 20 most misspliced events associated with each mutation. For each panel, the top 20 most misspliced events were computed using only samples with SF3B1K700E or SF3B1K666N mutations. Missplicing of those 20 events was then computed for all samples, irrespective of mutation, and plotted as illustrated. SF3B1K700E and SF3B1K666N mutations cause missplicing of similar sets of genes, but SF3B1K700E mutations cause more dramatic changes. Lines, shading, and equations indicate the best-fit linear regressions and corresponding 95% confidence intervals. (D) As in panel C, but computed using the top 5 most misspliced events for each mutation (SF3B1K700E; SF3B1K666N). (E) Box plot illustrating the data from panel C and associated P-value, computed using a 2-sided Wilcoxon rank-sum test. (F) Fraction of U2AF1S34F, U2AF1Q157R, or dual U2AF1S34F/Q157R mutated cells from a patient harboring both U2AF1S34F/WT and U2AF1Q157R/WT mutations. Red bar indicates fraction of U2AF1S34F/Q157R dual mutant cells. (G) Clonal hierarchy of mutations in the patient from panel E. Each column represents a cell at the indicated scale, as in panel A. Cells with mutations and WT cells are indicated in blue and white, respectively. (H) Fish plots showing the inferred clonal hierarchy based on the single-cell genotype data from panel G. (I) Sanger sequencing electropherograms from representative single cell clones from the patient in panel F. As enumerated on the right, all colonies were either U2AF1 dual WT or U2AF1S34F/Q157R dual mutant, indicating that these mutations always occur in cis with preservation of the WT allele. (J) Heat map of percentage spliced in values of cassette exons in patients with U2AF1S34, Q157, and U2AF1S34/Q157 dual mutations displaying cassette exon splicing events specific to the U2AF1S34 or Q157 single-mutant state. Standard deviation of <0.2 among single mutants and mean(U2AF1 S34) − mean (U2AF1 Q157) < 0.32. Each row is a unique patient, and each column is a single splicing event.
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