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Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE232573 | GEO | 2024/02/06

REPOSITORIES: GEO

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Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_cosmic]

Project description:Understanding the function of rare non-coding genetic variants represents a significant challenge. Here, we developed MapUTR, a screen to identify rare 3’ UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated a further interrogation of 11,929 cancer somatic mutations, uncovering 3,928 (33%) functional mutations in well-established cancer driver genes, such as CDKN2A. Functional MapUTR variants were enriched in miRNA targets and protein-RNA interaction sites. Based on MapUTR, we define a new metric, untranslated tumor mutation burden (uTMB), reflecting the amount of somatic functional MapUTR variants of a tumor. We showed the potential of uTMB in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), illustrating their cancer-driving potential. Our study elucidates the function of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

2024-02-06 | GSE232572 | GEO

Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_3utr_gnomad.motif_activity]

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Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [prime_editing_3utr]

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Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes

Project description:Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes

| PRJNA972738 | ENA

Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [prime_editing_3utr]

Project description:Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [prime_editing_3utr]

| PRJNA972739 | ENA

Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_cosmic]

Project description:Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_cosmic]

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Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_3utr_gnomad.motif_activity]

Project description:Massively parallel screen uncovers many rare 3’ UTR variants regulating mRNA abundance of cancer driver genes [rare_3utr_gnomad.motif_activity]

| PRJNA972741 | ENA

A Massively Parallel Screen of 5′UTR Mutations Identifies Variants Impacting Translation and Protein Production in Neurodevelopmental Disorder Genes

Project description:De novo mutations cause a variety of neurodevelopmental disorders including autism. Recent whole genome sequencing has identified hundreds of mutations in untranslated regions (UTRs) of genes from individuals with autism, but it is impossible to predict from sequence alone which are functional, and thus might be causal. Therefore, we developed a high throughput assay to screen the consequence over 1,000 variants from 5'UTRs mutations on transcript abundance and translation efficiency. This assay successfully enriched for elements that alter reporter translation, identifying over 100 potentially functional mutations. Studies in patient-derived cell lines further confirmed these mutations alter protein production in individuals in autism, including for multiple genes known to cause of syndromic forms autism, suggesting a diagnosis for these individual patients. Since UTR function varies by cell type, we further optimized this high throughput assay to enable assessment of mutations in neurons of the living brain. Neurons demonstrate profoundly different principles of regulation by 5'UTRs, consistent with more robust mechanism for reducing impact of 5'UTR RNA structure. Overall our results highlight a new approach for assessing the impact of 5’UTR across cell types and suggest some cases of neurodevelopmental disorder may be caused by such variants.

2023-11-08 | GSE246381 | GEO

Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients

Project description:Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those that contribute to disease etiology remains a challenge. Here we address this challenge by experimentally profiling the functional consequences of rare noncoding variants detected in a cohort of undiagnosed rare disease patients at scale using a massively parallel reporter assay. We demonstrate that this approach successfully identifies rare noncoding variants that alter the regulatory capacity of genomic sequences. In addition, we describe an integrative analysis that utilizes genomic features alongside patient clinical data to further prioritize candidate variants with an increased likelihood of pathogenicity. This works represents an important step towards establishing a framework for the clinical interpretation of noncoding variants.

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Project description:Determining the pathogenicity of genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes requires generalizable, scalable assays. We describe variant abundance by massively parallel sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance simultaneously. We apply VAMP-seq to quantify the abundance of 7,801 single-amino-acid variants of PTEN and TPMT, proteins in which functional variants are clinically actionable. We identify 1,138 PTEN and 777 TPMT variants that result in low protein abundance, and may be pathogenic or alter drug metabolism, respectively. We observe selection for low-abundance PTEN variants in cancer, and show that p.Pro38Ser, which accounts for ~10% of PTEN missense variants in melanoma, functions via a dominant-negative mechanism. Finally, we demonstrate that VAMP-seq is applicable to other genes, highlighting its generalizability.

| S-EPMC5980760 | biostudies-literature

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