Efficient and cost-effective bacterial mRNA sequencing from low input samples through ribosomal RNA depletion
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA629575 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11657250_1.fastq.gz | Fastqsanger.gz | |||
| SRR11657250_2.fastq.gz | Fastqsanger.gz | |||
| SRR11657251_1.fastq.gz | Fastqsanger.gz | |||
| SRR11657251_2.fastq.gz | Fastqsanger.gz | |||
| SRR11657252_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 56 |
Similar Datasets
Project description:RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species which are often present in low abundance. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification. EMBR-seq results in greater than 80% of the sequenced RNA molecules deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq employs a single oligonucleotide per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA. Thus, EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.
2020-10-22 | GSE149666 | GEO
Project description:Despite the precipitous decline in the cost of genome sequencing over the last few years, library preparation for RNA-seq is still laborious and expensive for high throughput screening for drug discovery. Limited availability of RNA generated by some experimental workflows poses an additional challenge and typically adds to the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that also maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies – Swift and Swift Rapid – using the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics, as our reference. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark differential gene expression in these kits, at input quantities ranging between 10 ng to 500 ng. Read quality and alignment metrics revealed high mapping efficiency and uniform read coverage through genes for all samples across all three kits. Normalized read counts between all treatment groups were in high agreement, with pairwise Pearson correlation coefficients >0.97. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits are cost effective and offer shorter workflow times enabled by their patented Adaptase technology. Furthermore, the Swift RNA kit allows for a relatively broader (and lower) input range, producing consistent results across diverse samples. The Swift Rapid RNA method is the fastest and most cost effective NGS workflow that is best suited for higher RNA yields, with the exact same RNA input range as the Illumina TruSeq kit. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways attributable to input mRNA concentration.
2021-02-23 | GSE167300 | GEO
Project description:Ribo-Pop: Simple, cost-effective, and widely applicable ribosomal RNA depletion
| PRJNA631775 | ENA
Project description:BACKGROUND:RNA sequencing is a powerful approach to quantify the genome-wide distribution of mRNA molecules in a population to gain deeper understanding of cellular functions and phenotypes. However, unlike eukaryotic cells, mRNA sequencing of bacterial samples is more challenging due to the absence of a poly-A tail that typically enables efficient capture and enrichment of mRNA from the abundant rRNA molecules in a cell. Moreover, bacterial cells frequently contain 100-fold lower quantities of RNA compared to mammalian cells, which further complicates mRNA sequencing from non-cultivable and non-model bacterial species. To overcome these limitations, we report EMBR-seq (Enrichment of mRNA by Blocked rRNA), a method that efficiently depletes 5S, 16S and 23S rRNA using blocking primers to prevent their amplification. RESULTS:EMBR-seq results in 90% of the sequenced RNA molecules from an E. coli culture deriving from mRNA. We demonstrate that this increased efficiency provides a deeper view of the transcriptome without introducing technical amplification-induced biases. Moreover, compared to recent methods that employ a large array of oligonucleotides to deplete rRNA, EMBR-seq uses a single or a few oligonucleotides per rRNA, thereby making this new technology significantly more cost-effective, especially when applied to varied bacterial species. Finally, compared to existing commercial kits for bacterial rRNA depletion, we show that EMBR-seq can be used to successfully quantify the transcriptome from more than 500-fold lower starting total RNA. CONCLUSIONS:EMBR-seq provides an efficient and cost-effective approach to quantify global gene expression profiles from low input bacterial samples.
| S-EPMC7565789 | biostudies-literature
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:Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing based methods for cell lineage analysis depend on low resolution bulk analysis or rely on extensive single cell sequencing which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way towards large-scale human cell lineage discovery.
2016-04-18 | E-MTAB-4553 | biostudies-arrayexpress
Project description:Systematic comparative analysis of strand-specific, cost-effective, RNA-seq library preparation methods for low input samples
| PRJNA704106 | ENA
Project description:Single-cell RNA -seq can precisely resolve cellular states, but applying this method to low-input samples is challenging. Here, we present Seq-Well, a portable, low-cost platform for massively parallel single-cell RNA -seq. Barcoded mRNA capture beads and single cells are sealed in an array of subnanoliter wells using a semipermeable membrane, enabling efficient cell lysis and transcript capture. We characterize Seq-Well extensively and use it to profile thousands of primary human macrophages exposed to tuberculosis.
2017-02-17 | GSE92495 | GEO
Project description:We developed FLIE (Fast Low-Input Efficient) Hi-C, a highly optimized and simplified version of Hi-C. Our method shortens the duration of Hi-C from five days to two days and decreases key reagent amounts 5-20 fold, while maintaining experimental controls and data quality. Importantly, the method also reduces the required input material by 100-1000 fold, as we demonstrate by generating detailed high complexity interaction maps from low-input sorted mouse frozen neuron nuclei and from 5,000-10,000 human Hap1 cells.
2024-09-06 | GSE276553 | GEO
Project description:A generic, cost-effective and scalable cell lineage analysis platform
| PRJEB13000 | ENA