Bmal1 KO mouse lung versus WT under three ribosomal depletion methods
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ABSTRACT:
PROVIDER: PRJNA1217798 | ENA |
REPOSITORIES: ENA
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Project description:Embryonic Bmal1 knock-out (KO) mouse lungs were compared to wildtype (WT) mouse lungs. Three different library preparations were done on each sample in order to assess the impact of ribosomal depletion on differential expression.
2025-02-06 | GSE288461 | GEO
Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues. mRNA profile of 11 breast tumors were assayed by Agilent microarray, and by RNA-sequencing on libraries including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN, using Illunia HiSeq2000 2x50bp. RNA-Seq raw data is to be made available through dbGaP (controlled access) due to patient privacy concerns: http://www.ncbi.nlm.nih.gov/gap/?term=phs000676
2014-08-20 | E-GEOD-51783 | biostudies-arrayexpress
Project description:The measurement of RNA abundance derived from massively parallel sequencing experiments is an essential technique. Methods that reduce ribosomal RNA levels are usually required prior to sequencing library construction because ribosomal RNA typically comprises >90% of the total RNA molecules in a sample. For some experiments, ribosomal RNA depletion is favored over poly(A) selection because it offers a more inclusive representation of the transcriptome. However, methods to deplete ribosomal RNA are generally proprietary, complex, inefficient, applicable to only specific species, or compatible with only a narrow range of RNA input levels. Here, we describe Ribo-Pop (ribosomal RNA depletion for popular use), a simple workflow and antisense oligo design strategy that we demonstrate works over a wide input range and can be easily adapted to any organism with a sequenced genome. We provide a computational pipeline for probe selection, a streamlined 20-minute protocol, and ready-to-use oligo sequences for several organisms. We anticipate that our simple and generalizable “open source” design strategy would enable virtually any lab to pursue full transcriptome sequencing in their organism of interest with minimal time and resources.
2020-08-12 | GSE150332 | GEO
Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues.
2014-08-20 | GSE51783 | GEO
Project description:In a cross-site study we evaluated the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. We found that all of the kits were capable of performing significant ribosomal depletion, though there were differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify ~14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes among kits suggested that transcript length may be a key factor in library production efficiency. These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.
2018-02-01 | GSE100127 | GEO
Project description:The transcription factor BMAL1 is a core element of the circadian clock that contributes to cyclic control of genes transcribed by RNA polymerase II. By using biochemical cellular fractionation and immunofluorescence analyses we reveal a previously uncharacterized nucleolar localization for BMAL1. We used an unbiased approach to determine the BMAL1 interactome by mass spectrometry and identified NOP58 as a prominent nucleolar interactor. NOP58, a core component of the box C/D small nucleolar ribonucleoprotein complex, associates with Snord118 to control specific pre-ribosomal RNA (rRNA) processing steps. These results suggest a non-canonical role of BMAL1 in rRNA regulation. Indeed, we show that BMAL1 controls NOP58-associated Snord118 nucleolar levels and cleavage of unique pre-rRNA intermediates. Our findings identify an unsuspected function of BMAL1 in the nucleolus that appears distinct from its canonical role in the circadian clock system
2020-08-25 | PXD018946 | Pride
Project description:A decade since its invention, single-cell RNA sequencing (scRNA-seq) has become a mainstay technology for profiling transcriptional heterogeneity in individual cells. Yet, most existing scRNA-seq methods capture only polyadenylated mRNA to avoid expending resources on profiling the types of transcripts that are usually not-of-interest, such as ribosomal RNA (rRNA). Hence, protocols that enable analysis of the whole transcriptome remain scarce. We adapted a method called DASH (Depletion of Abundant Sequences by Hybridisation) for rRNA depletion from single-cell total RNA-seq libraries. Our analyses show that with our single-cell DASH (scDASH), rRNAs are effectively depleted with minimal non-specificity. Importantly, the rest of the transcriptome is significantly enriched for detection as a result of liberated sequencing quota from depleted rRNA.
2020-10-31 | GSE158880 | GEO
Project description:TMT analysis of proteomic changes in the gastrocnemius skeletal muscles of WT and Bmal1-KO mice, and Bmal1-KO mice rescued with AAV-mediated muscle-specific expression of Bmal1.
2024-10-03 | PXD054406 | Pride
Project description:To investigate the effect of Bmal1 on poly(I:C) response, we isolate mRNA from PBS or poly(I:C)-injected WT and myeloid Bmal1 KO mice. We then compare the poly(I:C)-induced transcriptomic change between WT and Bmal1 KO peritoneal myeloid cells.
2024-01-31 | GSE222759 | GEO
Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues. mRNA profile of 11 breast tumors were assayed by Agilent microarray, and by RNA-sequencing on libraries including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN, using Illunia HiSeq2000 2x50bp. RNA-Seq raw data is to be made available through dbGaP (controlled access) due to patient privacy concerns: http://www.ncbi.nlm.nih.gov/gap/?term=phs000676
| S-ECPF-GEOD-51783 | biostudies-other