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

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

PROVIDER: PRJNA972738 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR24572600_1.fastq.gz	Fastqsanger.gz
	SRR24572600_2.fastq.gz	Fastqsanger.gz
	SRR24575000_1.fastq.gz	Fastqsanger.gz
	SRR24575000_2.fastq.gz	Fastqsanger.gz
	SRR24575400_1.fastq.gz	Fastqsanger.gz

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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]

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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]

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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.

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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]

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

Project description:This SuperSeries is composed of the SubSeries listed below.

2024-02-06 | GSE232573 | GEO

Massively parallel reporter assay of 3’UTR sequences identifies in vivo rules for mRNA degradation

Project description:The stability of mRNAs is regulated by signals within their sequences, but a systematic and predictive understanding of the underlying sequence rules remains elusive. Here, we introduce UTR-Seq, a combination of massively parallel reporter assays and regression models, to survey the dynamics of tens-of-thousands of 3’UTR sequences during early zebrafish embryogenesis. UTR-Seq revealed two temporal degradation programs: a maternally encoded early-onset program and a late-onset program that accelerated degradation after zygotic genome activation. Three signals regulated early-onset rates: stabilizing poly-U and UUAG sequences, and destabilizing GC-rich signals. Three signals explained late-onset degradation: miR-430 seeds, AU-rich sequences and Pumilio recognition sites. Sequence based regression models translated 3’UTRs into their unique decay patterns, and predicted the in vivo impact of sequence signals on mRNA stability. Their application led to the successful design of artificial 3’UTRs that conferred specific mRNA dynamics. UTR-Seq provides a general strategy to uncover the rules of RNA cis-regulation.

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