Small Noncoding RNAome Changes during Human Bone Marrow Mesenchymal Stem Cells Senescence
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ABSTRACT:
PROVIDER: PRJNA792130 | ENA |
REPOSITORIES: ENA
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Project description:Noncoding RNAs include small transcripts, such as microRNAs and piwi-interacting RNAs, and a wide range of long noncoding RNAs (lncRNAs). Although many lncRNAs have been identified, only a small number of lncRNAs have been characterized functionally. Here, we sought to identify lncRNAs differentially expressed during replicative senescence. We compared lncRNAs expressed in proliferating, early-passage, 'young' human diploid WI-38 fibroblasts [population doubling (PDL) 20] with those expressed in senescent, late-passage, 'old' fibroblasts (PDL 52) by RNA sequencing (RNA-Seq). Numerous transcripts in all lncRNA groups (antisense lncRNAs, pseudogene-encoded lncRNAs, previously described lncRNAs and novel lncRNAs) were validated using reverse transcription (RT) and real-time, quantitative (q)PCR. Among the novel senescence-associated lncRNAs (SAL-RNAs) showing lower abundance in senescent cells, SAL-RNA1 (XLOC_023166) was found to delay senescence, because reducing SAL-RNA1 levels enhanced the appearance of phenotypic traits of senescence, including an enlarged morphology, positive β-galactosidase activity, and heightened p53 levels. Our results reveal that the expression of known and novel lncRNAs changes with senescence and suggests that SAL-RNAs play direct regulatory roles in this important cellular process.
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Project description:Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from ribosomal RNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods. 8 mouse embryonic stem cell samples, 4 control and 4 cisplatin treated, 4 replicates per group for Affymetrix arrays. Of these, 6 were used for sequencing and are reported in this Series.
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Project description:Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from ribosomal RNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.
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Project description:Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from ribosomal RNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods.
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