A Massively Parallel Fluorescence Assay to Characterize the Effects of Synonymous Mutations on TP53 Expression

Abstract

Although synonymous mutations can affect gene expression, they have generally not been considered in genomic studies that focus on mutations that increase the risk of cancer. However, mounting evidence implicates some synonymous mutations as driver mutations in cancer. Here, a massively parallel assay, based on cell sorting of a reporter containing a segment of p53 fused to GFP, was used to measure the effects of nearly all synonymous mutations in exon 6 of TP53 In this reporter context, several mutations within the exon caused strong expression changes including mutations that may cause potential gain or loss of function. Further analysis indicates that these effects are largely attributed to errors in splicing, including exon skipping, intron inclusion, and exon truncation, resulting from mutations both at exon-intron junctions and within the body of the exon. These mutations are found at extremely low frequencies in healthy populations and are enriched a few-fold in cancer genomes, suggesting that some of them may be driver mutations in TP53 This assay provides a general framework to identify previously unknown detrimental synonymous mutations in cancer genes.Implications: Using a massively parallel assay, this study demonstrates that synonymous mutations in the TP53 gene affect protein expression, largely through their impact on splicing.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/15/10/1301/F1.large.jpg Mol Cancer Res; 15(10); 1301-7. ©2017 AACR.

Figure 1. A massively-parallel assay to measure the splicing effects of synonymous mutations in TP53

(A) Overview of the assay. A library of synonymous variants is created in a TP53 reporter construct. This library is integrated into the genome of Flp-In™-293 cells, a derivative of the human embryonic kidney cell line (HEK-293T) using Flp-mediated recombination. Cells are sorted into bins based on GFP intensity, and the exon library from each bin is sequenced and genotyped. S_GFP is calculated as a weighted sum based on the frequency of each variant in each sorted bin. (B) Library design. Positions in the mutagenized exon (bold) are numbered, and degenerate positions are annotated with the possible mutant bases above the wild type sequence. The known splice donor and acceptor sites are highlighted with gray boxes. (C) Flow cytometry of TP53 variant library. Cells were sorted based on GFP signal (x-axis); blue, cells expressing a wild type exon 6;red, negative control cells expressing the G113A variant of exon 6;green, TP53 exon 6 synonymous variant library. Bins are represented by lines at top, annotated with the percentage of sorted cells in each bin.

Figure 2. Synonymous mutations cause mis-splicing

(A) S_GFP scores for synonymous mutations in exon 6 of TP53 plotted as a heatmap. At each codon’s third position (x-axis), the base present in the exon variant (y-axis) is colored based on S_GFP. The wild type base at each position is hatched, non-synonymous mutations are light grey, and missing data is dark grey. Codon numbers for each in p53 are noted below the heatmap. (B) Model of the reporter construct. Amino acid residues in p53 are shown in italics above the model. Residue 188 spans the splice junction between exons 5 and 6. Lengths of relevant exonic and intronic fragments are below the model. (C) Polyacrylamide gel showing cDNA for clonal samples. TP53 exon 6 mutations are shown below each well. Cartoon representations of major fragments and their lengths, matching the model in (B), are shown between the two panels. Samples were split between two gels.

Figure 3