Quantifying RNA-Protein Interactions Characterizes Recurrent Mutations in RNA Binding Proteins in Cancer
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ABSTRACT:
PROVIDER: PRJNA681609 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13169561_1.fastq.gz | Fastqsanger.gz | |||
| SRR13169561_2.fastq.gz | Fastqsanger.gz | |||
| SRR13169562_1.fastq.gz | Fastqsanger.gz | |||
| SRR13169562_2.fastq.gz | Fastqsanger.gz | |||
| SRR13169563_1.fastq.gz | Fastqsanger.gz |
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Project description:Quantifying RNA-Protein Interactions Characterizes Recurrent Mutationsin RNA Binding Proteins in Cancer
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Project description:Quantitative criteria to identify proteins as RNA-binding proteins (RBPs) are presently lacking, as are criteria to define RBP “target” RNAs. To address this, an ultraviolet (UV) cross-linking immunoprecipitation (CLIP)-sequencing method, easyCLIP, was developed. easyCLIP, provides absolute cross-link rates, as well as increased simplicity, efficiency, and capacity to visualize unamplified libraries. 213 cross-link measurements were performed and found that RBPs could be distinguished from non-RBPs by RNA cross-link rates and that target RNAs could be defined as those with a complex frequency unlikely for a random protein. easyCLIP was used to study the 33 most recurrent cancer mutations across 28 RBPs. This demonstrated increased RNA binding per RBP molecule for KHDRBS2 and A1CF cancer mutants, and showed that the PCBP1L100P/Q cancer mutation also dramatically increased RNA binding. Quantitating RBP-RNA interactions can thus categorize proteins as RBPs or not and define the impact of specific disease-associated RBP mutations on RNA binding.
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Project description:Quantitative criteria to identify proteins as RNA-binding proteins (RBPs) are presently lacking, as are criteria to define RBP target RNAs. Here, we develop an ultraviolet (UV) cross-linking immunoprecipitation (CLIP)-sequencing method, easyCLIP. easyCLIP provides absolute cross-link rates, as well as increased simplicity, efficiency, and capacity to visualize RNA libraries. Measurement of >200 independent cross-link experiments across >35 proteins identifies an RNA cross-link rate threshold that distinguishes RBPs from non-RBPs and defines target RNAs as those with a complex frequency unlikely for a random protein. We apply easyCLIP to the 33 most recurrent cancer mutations across 28 RBPs, finding increased RNA binding per RBP molecule for PCBP1 L100P/Q cancer mutations. Quantitating RBP-RNA interactions can thus nominate proteins as RBPs and define the impact of specific disease-associated RBP mutations on RNA association.
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Project description:easyCLIP Quantifies RNA-Protein Interactions and Characterizes Recurrent PCBP1 Mutations in Cancer
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Project description:RNA-protein interactions mediate a host of cellular processes, underscoring the need for methods to quantify their occurrence in living cells. RNA interaction frequencies for the average cellular protein are undefined, however, and there is no quantitative threshold to define a protein as an RNA-binding protein (RBP). Ultraviolet (UV) cross-linking immunoprecipitation (CLIP)-sequencing, an effective widely used means of characterizing RNA-protein interactions, would particularly benefit from the capacity to quantitate the number of RNA cross-links per protein per cell. In addition, CLIP-seq methods are difficult, have high experimental failure rates and many ambiguous analytical decisions. To address these issues, the easyCLIP method was developed and used to quantify RNA-protein interactions for a panel of known RBPs as well as a spectrum of random non-RBP proteins. easyCLIP provides the advantages of good efficiency compared to current standards, a simple protocol with a very low failure rate, troubleshooting information that includes direct visualization of prepared libraries without amplification, and a new form of analysis. easyCLIP, which uses sequential on-bead ligation of 5’ and 3’ adaptors tagged with different infrared dyes, classified non-RBPs as those with a per protein RNA cross-link rate of <0.1%, with most RBPs substantially above this threshold, including Rbfox1 (18%), hnRNPC (22%), CELF1 (11%), FBL (2%), and STAU1 (1%). easyCLIP with the PCBP1L100 RBP mutant recurrently seen in cancer quantified increased RNA binding compared to wild-type PCBP1 and suggested a potential mechanism for this RBP mutant in cancer. easyCLIP provides a simple, efficient and robust method to both obtain both traditional CLIP-seq information and to define actual RNA interaction frequencies for a given protein, enabling quantitative cross-RBP comparisons as well as insight into RBP mechanisms.
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Project description:ZC3H18 (Z18) is a component of multiple nuclear RNA surveillance complexes which detect and degrade aberrant nuclear RNAs. We found recurrent truncating mutations in Z18 (Z18trunc) enriched in many cancer types, and as these truncating forms lack the distal domain required for recruitment of RNA degradation machinery, we predicted that Z18’s target transcripts would be stabilized. Expression of Z18trunc expedited melanoma onset in a zebrafish melanoma model and caused a specific accumulation of endogenous retroviral (ERV) RNA. Z18 mutant human cell lines from the Cancer Cell Line Encyclopedia also had increased ERV expression. In engineered human melanoma cells, Z18trunc caused a more severe accumulation of ERV RNA than loss of one Z18 copy, showing dominant negative activity. Z18trunc was exported to the cytoplasm and failed to recruit RNA degradation machinery, while maintaining binding to two RNA stabilizing proteins. Z18trunc bound ERV RNA via aromatic amino acids in the zinc finger domain but failed to recruit the degradation machinery, so in lieu of destruction, ERV messages were stabilized. We find that Z18 normally specifically identifies ERV messages for destruction, while Z18trunc protects ERV RNA, contributing to oncogenesis. This work demonstrates that mutations in a second nuclear RNA surveillance component are oncogenic, supporting that deficient nuclear RNA surveillance is a broad tumor suppressive mechanism. Our work provides a specific mechanism that results in elevated ERV transcripts in cancer and reveals that nuclear RNA surveillance complexes play a complementary role in suppressing ERV expression.
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