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.
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.
Project description:Stranded RNA-seq were performed on total RNA following ribosomal RNAs depletion (Ribo-zero removal kit, illumina) for glioblastoma stem cell
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.