Evidence map›Paper›PMID 20852648›Full record

ArticleNature methods2010

Validation of two ribosomal RNA removal methods for microbial metatranscriptomics.

Shaomei He, Omri Wurtzel, Kanwar Singh, Jeff L Froula, Suzan Yilmaz, Susannah G Tringe, Zhong Wang, Feng Chen, Erika A Lindquist, Rotem Sorek and 1 more

Abstract read
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In one paragraph

Article in Nature methods, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
–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

100 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
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  13. Dual RNA-seq in filarial nematodes andFrontiers in microbiology · 2024
    Article
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  16. Article
  17. Gut Microbiome Activity Contributes to Prediction of Individual Variation in Glycemic Response in Adults.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2022
    Article
  18. Review
  19. Review
  20. Article

40 more citing papers are in PubMed but not listed here.

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

11 authors.

Shaomei HeDepartment of Energy Joint Genome Institute, Walnut Creek, California, USA.
Omri Wurtzel
Kanwar Singh
Jeff L Froula
Suzan Yilmaz
Susannah G Tringe
Zhong Wang
Feng Chen
Erika A Lindquist
Rotem Sorek
Philip Hugenholtz

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The predominance of rRNAs in the transcriptome is a major technical challenge in sequence-based analysis of cDNAs from microbial isolates and communities. Several approaches have been applied to deplete rRNAs from (meta)transcriptomes, but no systematic investigation of potential biases introduced by any of these approaches has been reported. Here we validated the effectiveness and fidelity of the two most commonly used approaches, subtractive hybridization and exonuclease digestion, as well as combinations of these treatments, on two synthetic five-microorganism metatranscriptomes using massively parallel sequencing. We found that the effectiveness of rRNA removal was a function of community composition and RNA integrity for these treatments. Subtractive hybridization alone introduced the least bias in relative transcript abundance, whereas exonuclease and in particular combined treatments greatly compromised mRNA abundance fidelity. Illumina sequencing itself also can compromise quantitative data analysis by introducing a G+C bias between runs.

Indexed as

BacteriaDNA, ArchaealDNA, BacterialEuryarchaeotaExonucleasesGene Expression ProfilingIn Situ HybridizationReproducibility of ResultsRNA, ArchaealRNA, BacterialRNA, MessengerRNA, RibosomalRNA, Ribosomal, 16SRNA, Ribosomal, 23SSequence AlignmentSequence Analysis, RNADNA, ArchaealDNA, BacterialExonucleasesRNA, ArchaealRNA, BacterialRNA, MessengerRNA, RibosomalRNA, Ribosomal, 16SRNA, Ribosomal, 23S

Identifiers

PMID20852648

What OpenQuestion holds

Textmetadata
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.