Depletion of 16S ribosomal RNA improves single-cell RNA-seq of planarians by DASH
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ABSTRACT:
PROVIDER: PRJNA966898 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24415969.fastq.gz | Fastqsanger.gz | |||
| SRR24415970.fastq.gz | Fastqsanger.gz | |||
| SRR24415971.fastq.gz | Fastqsanger.gz | |||
| SRR24415972.fastq.gz | Fastqsanger.gz | |||
| SRR24415973.fastq.gz | Fastqsanger.gz |
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Project description:Single-cell transcriptomics (scRNA-seq) has revolutionized our understanding of cell types and states in various contexts, such as development and disease. Most methodology relies on poly(A) enrichment to selectively capture protein-coding polyadenylated transcripts, intending to exclude ribosomal transcripts that constitute >80% of the transcriptome. However, it is common for ribosomal transcripts to sneak into the library, which can add significant background by flooding libraries with irrelevant sequences. The challenge of amplifying all RNA transcripts from a single cell has motivated the development of new technologies to optimize retrieval of transcripts of interest. This problem is notable in planarians, where we find that 16S ribosomal transcripts were widely enriched (20-80%) across single-cell methods. Therefore, we adapted the Depletion of Abundant Sequences by Hybridization (DASH) to the standard 10X scRNA-seq protocol. We designed single-guide RNAs tiling the 16S sequence for CRISPR-mediated degradation, and subsequently generated untreated and DASH-treated datasets from the same libraries to enable a side-by-side comparison of the effects of DASH. DASH specifically removes 16S sequences without off-target removal of other genes. By assessing the cell barcodes shared by both libraries, DASH-treated cells have consistently higher complexity given the same amount of reads, which allows the detection of a rare cell cluster and more differentially expressed genes. In conclusion, DASH can be easily integrated into existing sequencing protocols and customized to deplete any unwanted transcripts.
2023-08-07 | GSE231548 | GEO
Project description:A major challenge for RNA-seq analysis of gene expression is to achieve sufficient coverage of informative non-ribosomal transcripts. In eukaryotic samples, this is typically achieved by selective oligo(dT)-priming of messenger RNAs to exclude ribosomal RNA (rRNA) during cDNA synthesis. However, this strategy is not compatible with prokaryotes in which functional transcripts are generally not polyadenylated. To overcome this, we adopted DASH (Depletion of Abundant Sequences by Hybridization), initially developed for eukaryotic cells, to improve both the sensitivity and depth of bacterial RNA-seq. DASH employs the Cas9 nuclease to remove unwanted cDNA sequences prior to library amplification. We report the design, evaluation, and optimization of DASH experiments for standard bacterial short-read sequencing approaches, including software for automated guide RNA (gRNA) design for Cas9-mediated cleavage in bacterial rDNA sequences. Using these gRNA pools, we effectively removed rRNA reads (56-86%) in RNA-seq libraries from two different model bacteria, the Gram-negative pathogen Salmonella enterica and the anaerobic gut commensal Bacteroides thetaiotaomicron. DASH works robustly, even with sub-nanogram amounts of input cDNA. Its efficiency, high sensitivity, ease of implementation, and low cost (~$5 per sample) render DASH an attractive alternative to rRNA removal protocols, in particular for material-constrained studies where conventional ribodepletion techniques fail.
2020-05-11 | GSE147155 | GEO
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:Time-course RNA-Seq of X-ray irradiated planarians Dugesia japonica.
2023-10-02 | GSE223928 | GEO
Project description:RNA-Seq of X-ray irradiated planarians
| PRJNA929052 | ENA
Project description:BackgroundSingle-cell RNA-sequencing (scRNA-seq) relies on PCR amplification to retrieve information from vanishingly small amounts of starting material. To selectively enrich mRNA from abundant non-polyadenylated transcripts, poly(A) selection is a key step during library preparation. However, some transcripts, such as mitochondrial genes, can escape this elimination and overwhelm libraries. Often, these transcripts are removed in silico, but whether physical depletion improves detection of rare transcripts in single cells is unclear.ResultsWe find that a single 16S ribosomal RNA is widely enriched in planarian scRNA-seq datasets, independent of the library preparation method. To deplete this transcript from scRNA-seq libraries, we design 30 single-guide RNAs spanning its length. To evaluate the effects of depletion, we perform a side-by-side comparison of the effects of eliminating the 16S transcript and find a substantial increase in the number of genes detected per cell, coupled with virtually complete loss of the 16S RNA. Moreover, we systematically determine that library complexity increases with a limited number of PCR cycles following CRISPR treatment. When compared to in silico depletion of 16S, physically removing it reduces dropout rates, retrieves more clusters, and reveals more differentially expressed genes.ConclusionsOur results show that abundant transcripts reduce the retrieval of informative transcripts in scRNA-seq and distort the analysis. Physical removal of these contaminants enables the detection of rare transcripts at lower sequencing depth, and also outperforms in silico depletion. Importantly, this method can be easily customized to deplete any abundant transcript from scRNA-seq libraries.
| S-EPMC10588366 | biostudies-literature
Project description:BACKGROUND:The astounding regenerative abilities of planarian flatworms prompt steadily growing interest in examining their molecular foundation. Planarian regeneration was found to require hundreds of genes and is hence a complex process. Thus, RNA interference followed by transcriptome-wide gene expression analysis by RNA-seq is a popular technique to study the impact of any particular planarian gene on regeneration. Typically, the removal of ribosomal RNA (rRNA) is the first step of all RNA-seq library preparation protocols. To date, rRNA removal in planarians was primarily achieved by the enrichment of polyadenylated (poly(A)) transcripts. However, to better reflect transcriptome dynamics and to cover also non-poly(A) transcripts, a procedure for the targeted removal of rRNA in planarians is needed. RESULTS:In this study, we describe a workflow for the efficient depletion of rRNA in the planarian model species S. mediterranea. Our protocol is based on subtractive hybridization using organism-specific probes. Importantly, the designed probes also deplete rRNA of other freshwater triclad families, a fact that considerably broadens the applicability of our protocol. We tested our approach on total RNA isolated from stem cells (termed neoblasts) of S. mediterranea and compared ribodepleted libraries with publicly available poly(A)-enriched ones. Overall, mRNA levels after ribodepletion were consistent with poly(A) libraries. However, ribodepleted libraries revealed higher transcript levels for transposable elements and histone mRNAs that remained underrepresented in poly(A) libraries. As neoblasts experience high transposon activity this suggests that ribodepleted libraries better reflect the transcriptional dynamics of planarian stem cells. Furthermore, the presented ribodepletion procedure was successfully expanded to the removal of ribosomal RNA from the gram-negative bacterium Salmonella typhimurium. CONCLUSIONS:The ribodepletion protocol presented here ensures the efficient rRNA removal from low input total planarian RNA, which can be further processed for RNA-seq applications. Resulting libraries contain less than 2% rRNA. Moreover, for a cost-effective and efficient removal of rRNA prior to sequencing applications our procedure might be adapted to any prokaryotic or eukaryotic species of choice.
| S-EPMC6884822 | biostudies-literature
Project description:Nkx2.2 is an intestine-enriched transcription factor required for regeneration in planarians. The goal of this study was to identify differentially expressed transcripts in uninjured nkx2.2(RNAi) planarians.
2022-05-24 | GSE174228 | GEO
Project description:We performed RNA-seq of whole starved cct3A(RNAi) planarians and controls at 72hR.
2021-04-26 | GSE134013 | GEO
Project description:The planarian Dugesia japonica has amazing ability to regenerate a head from the anterior ends of the amputated stump with maintenance of the original anterior-posterior polarity. Although planarians present an attractive system for molecular investigation of regeneration and research has focused on clarifying the molecular mechanism of regeneration initiation in planarians, but proteomic studies are still in the early stages. Here, a global proteomics analysis of regenerating head fragments in planarians at 0h, 2h and 6h after amputation was performed using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics coupled with LC-MS/MS strategy. Then the significantly changed proteins were identified. The correlation betwwen protein expression profiles and signaling pathways/biological processes was analyzed by bioinformatics and systems biology.
2015-07-07 | PXD002100 | Pride