ArticleBMC genomics2023
CRISPR/Cas9-based depletion of 16S ribosomal RNA improves library complexity of single-cell RNA-sequencing in planarians.
Article in BMC genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- A practical guide to targeted single-cell RNA sequencing technologies.Communications biology · 2026Review
- RoboA reinforces planarian stem cell fate through FoxA and Anosmin1a.Nature communications · 2026Article
- CRISPR/Cas genome editing, functional genomics, and diagnostics for parasitic helminths.International journal for parasitology · 2025Review
- Pluripotent Stem Cell Plasticity is Sculpted by a Slit-Independent Robo Pathway in a Regenerative Animal.bioRxiv : the preprint server for biology · 2025Article
- Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotypes and phenotypes in chronic lymphocytic leukemia.Genome research · 2025Article
- Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotype and phenotype in chronic lymphocytic leukemia.bioRxiv : the preprint server for biology · 2024Article
- Purification of Planarian Stem Cells Using a Draq5-Based FACS Approach.Methods in molecular biology (Clifton, N.J.) · 2024Article
Corrections and comments
- Update of
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.