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Deep indel mutagenesis reveals the regulatory and modulatory architecture of alternative exon splicing

ABSTRACT: Deep indel mutagenesis reveals the regulatory and modulatory architecture of alternative exon splicing

PROVIDER: PRJNA1021605 | ENA |

REPOSITORIES: ENA

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Deep indel mutagenesis reveals the regulatory and modulatory architecture of alternative exon splicing

Project description:Altered splicing is a frequent mechanism by which genetic variants cause disease. However, the regulatory architecture of human exons remains poorly understood, making the therapeutic modulation of splicing in disease challenging. Here we show that deep indel mutagenesis (DIM) provides an efficient strategy to chart the regulatory landscape of human exons and to rapidly identify effective splice-modulating oligonucleotides. DIM defines a minimal exon length, uncovers a mechanism for the evolutionary birth of unusually short microexons and the repression of transmembrane domain-encoding exons, and reveals a checkerboard architecture of sequential enhancers and silencers in a model alternatively spliced exon. Accurate prediction of the effects of deletions using deep learning provides a resource, DANGO, that maps the splicing regulatory landscape of all human exons and predicts effective splice-altering antisense oligonucleotides genome-wide.

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Deep indel mutagenesis reveals the impact of insertions and deletions on protein stability and function

Project description:Amino acid insertions and deletions (indels) are an abundant class of genetic variants. However, compared to substitutions, the effects of indels are not well understood and poorly predicted. Here we address this shortcoming by performing deep indel mutagenesis (DIM) of structurally diverse proteins. Indel tolerance is strikingly different to substitution tolerance and varies extensively both between different proteins and within different regions of the same protein. Although state of the art variant effect predictors perform poorly on indels, we show that both experimentally-measured and computationally-predicted substitution scores can be repurposed as good indel variant effect predictors by incorporating information on protein secondary structures. Quantifying the effects of indels on protein-protein interactions reveals that insertions can be an important class of gain-of-function variants. Our results provide an overview of the impact of indels on proteins and a method to predict their effects genome-wide.

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Saturation mutagenesis reveals manifold determinants of exon definition

Project description:To illuminate the extent and roles of exonic sequences in the splicing of human RNA transcripts we conducted saturation mutagenesis of a 51 nt internal exon in a 3-exon minigene. All possible single and tandem dinucleotide substitutions were surveyed. Using high throughput genetics, 5560 minigene molecules were assayed for splicing in HEK293 cells. Over 70% of mutations produced substantial (>2X) phenotypes of either increased or decreased splicing. Of all predicted secondary structural elements only a single 15 nt stem-loop, showed a strong correlation with splicing, acting negatively. The in vitro formation of exon-protein complexes between the mutant molecules and proteins associated with spliceosome formation (U2AF35, U2AF65, U1Aa, and U1-70K) correlated with splicing efficiencies, suggesting exon definition as the step affected by most mutations. The measured relative binding affinities of dozens of human RNA binding protein domains as reported in the CISBP-RNA database were found to correlate either positively or negatively with splicing efficiency, more than could fit on the 51 nt test exon simultaneously. Surprisingly, such correlations extended to weak relative protein-sequence affinities. These myriad protein binding correlations point to a dynamic and heterogeneous population of pre-mRNA molecules, each responding to a particular collection of binding proteins.

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