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1.
EMBO J ; 37(13)2018 07 02.
Artículo en Inglés | MEDLINE | ID: mdl-29880601

RESUMEN

Cytoplasmic mRNA degradation controls gene expression to help eliminate pathogens during infection. However, it has remained unclear whether such regulation also extends to nuclear RNA decay. Here, we show that 145 unstable nuclear RNAs, including enhancer RNAs (eRNAs) and long noncoding RNAs (lncRNAs) such as NEAT1v2, are stabilized upon Salmonella infection in HeLa cells. In uninfected cells, the RNA exosome, aided by the Nuclear EXosome Targeting (NEXT) complex, degrades these labile transcripts. Upon infection, the levels of the exosome/NEXT components, RRP6 and MTR4, dramatically decrease, resulting in transcript stabilization. Depletion of lncRNAs, NEAT1v2, or eRNA07573 in HeLa cells triggers increased susceptibility to Salmonella infection concomitant with the deregulated expression of a distinct class of immunity-related genes, indicating that the accumulation of unstable nuclear RNAs contributes to antibacterial defense. Our results highlight a fundamental role for regulated degradation of nuclear RNA in the response to pathogenic infection.


Asunto(s)
ARN Nuclear , ARN no Traducido , Infecciones por Salmonella/genética , Supervivencia Celular , Células HeLa , Humanos , Salmonella enterica/genética , Regulación hacia Arriba
2.
BMC Genomics ; 16: 154, 2015 Mar 06.
Artículo en Inglés | MEDLINE | ID: mdl-25879614

RESUMEN

BACKGROUND: Histone epigenome data determined by chromatin immunoprecipitation sequencing (ChIP-seq) is used in identifying transcript regions and estimating expression levels. However, this estimation does not always correlate with eventual RNA expression levels measured by RNA sequencing (RNA-seq). Part of the inconsistency may arise from the variance in RNA stability, where the transcripts that are more or less abundant than predicted RNA expression from histone epigenome data are inferred to be more or less stable. However, there is little systematic analysis to validate this assumption. Here, we used stability data of whole transcriptome measured by 5'-bromouridine immunoprecipitation chase sequencing (BRIC-seq), which enabled us to determine the half-lives of whole transcripts including lincRNAs, and we integrated BRIC-seq with ChIP-seq to achieve better estimation of the eventual transcript levels and to understand the importance of post-transcriptional regulation that determine the eventual transcript levels. RESULTS: We identified discrepancies between the RNA abundance estimated by ChIP-seq and measured RNA expression from RNA-seq; for number of genes and estimated that the expression level of 865 genes was controlled at the level of RNA stability in HeLa cells. ENCODE data analysis supported the idea that RNA stability control aids to determine transcript levels in multiple cell types. We identified UPF1, EXOSC5 and STAU1, well-studied RNA degradation factors, as controlling factors for 8% of cases. Computational simulations reasonably explained the changes of eventual mRNA levels attributable to the changes in the rates of mRNA half-lives. In addition, we propose a feedback circuit that includes the regulated degradation of mRNAs encoding transcription factors to maintain the steady state level of RNA abundance. Intriguingly, these regulatory mechanisms were distinct between mRNAs and lincRNAs. CONCLUSIONS: Integrative analysis of ChIP-seq, RNA-seq and our BRIC-seq showed that transcriptional regulation and RNA degradation are independently regulated. In addition, RNA stability is an important determinant of eventual transcript levels. RNA binding proteins, such as UPF1, STAU1 and EXOSC5 may play active roles in such controls.


Asunto(s)
Estabilidad del ARN , ARN/metabolismo , Antígenos de Neoplasias/metabolismo , Inmunoprecipitación de Cromatina , Proteínas del Citoesqueleto/metabolismo , Complejo Multienzimático de Ribonucleasas del Exosoma/metabolismo , Regulación de la Expresión Génica , Semivida , Células HeLa , Secuenciación de Nucleótidos de Alto Rendimiento , Histonas/metabolismo , Humanos , ARN/química , ARN Helicasas , ARN Largo no Codificante/química , ARN Largo no Codificante/metabolismo , ARN Mensajero/química , ARN Mensajero/metabolismo , Proteínas de Unión al ARN/metabolismo , Análisis de Secuencia de ARN , Transactivadores/metabolismo
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