Evidence map›Paper›PMID 31879761›Full record

ArticleNucleic acids research2020

Scalable and cost-effective ribonuclease-based rRNA depletion for transcriptomics.

Yiming Huang, Ravi U Sheth, Andrew Kaufman, Harris H Wang

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
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  5. Impact of expression systems on the transcriptome ofApplied and environmental microbiology · 2025
    Article
  6. Article
  7. Article
  8. Article
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  11. A practical introduction to holo-omics.Cell reports methods · 2024
    Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Small RNA MTS1338 Configures a Stress Resistance Signature inInternational journal of molecular sciences · 2023
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yiming HuangDepartment of Systems Biology, Columbia University, New York, NY 10032, USA.
Ravi U ShethDepartment of Systems Biology, Columbia University, New York, NY 10032, USA.
Andrew KaufmanDepartment of Systems Biology, Columbia University, New York, NY 10032, USA.
Harris H WangDepartment of Systems Biology, Columbia University, New York, NY 10032, USA.

Funding

A minimally invasive synthetic bio-driven approach for natural products discoveryU01GM110714 · NIGMS · ROCKEFELLER UNIVERSITY · PI BRADY, SEAN F · 2015 to 2019
$11.1M
Micron-scale Spatial Metagenomic Mapping of Microbial Biogeography in the Gastrointestinal TractR01AI132403 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Harris H Wang · 2017 to 2026
$6.0M
Ecological dynamics and metabolic interactions in thegut microbiome across space and timeR01DK118044 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI VITKUP, DENNIS, WANG, HARRIS H · 2018 to 2022
$3.4M
NIAID NIH HHS R01 AI132403NIDDK NIH HHS R01 DK118044NIGMS NIH HHS U01 GM110714
6 · The paper itself

Abstract

Bacterial RNA sequencing (RNA-seq) is a powerful approach for quantitatively delineating the global transcriptional profiles of microbes in order to gain deeper understanding of their physiology and function. Cost-effective bacterial RNA-seq requires efficient physical removal of ribosomal RNA (rRNA), which otherwise dominates transcriptomic reads. However, current methods to effectively deplete rRNA of diverse non-model bacterial species are lacking. Here, we describe a probe and ribonuclease based strategy for bacterial rRNA removal. We implemented the method using either chemically synthesized oligonucleotides or amplicon-based single-stranded DNA probes and validated the technique on three novel gut microbiota isolates from three distinct phyla. We further showed that different probe sets can be used on closely related species. We provide a detailed methods protocol, probe sets for >5000 common microbes from RefSeq, and an online tool to generate custom probe libraries. This approach lays the groundwork for large-scale and cost-effective bacterial transcriptomics studies.

Indexed as

BacteriaGene Expression ProfilingRibonucleasesRNA, BacterialRNA, RibosomalRNA-SeqTranscriptomeRibonucleasesRNA, BacterialRNA, Ribosomal

Identifiers

PMID31879761
PMCPMC7038938

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.