Evidence map›Paper›PMID 28583074›Full record

ArticleBMC genomics2017

A comprehensive assessment of RNA-seq protocols for degraded and low-quantity samples.

Sven Schuierer, Walter Carbone, Judith Knehr, Virginie Petitjean, Anita Fernandez, Marc Sultan, Guglielmo Roma

Abstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 2 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

90 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Prolonged Sample Storage Reshapes the mInternational journal of molecular sciences · 2026
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  13. An Analytic Pipeline to Obtain Reliable Genetic Ancestry Estimates from Tumor-Derived RNA Sequencing Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
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30 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

7 authors.

Sven SchuiererNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland. sven.schuierer@novartis.com.ORCID 0000-0003-1659-0941
Walter CarboneNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
Judith KnehrNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
Virginie PetitjeanNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
Anita FernandezNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland.
Marc SultanNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland. marc.sultan@novartis.com.
Guglielmo RomaNovartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland. guglielmo.roma@novartis.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRNA-sequencing (RNA-seq) has emerged as one of the most sensitive tool for gene expression analysis. Among the library preparation methods available, the standard poly(A) + enrichment provides a comprehensive, detailed, and accurate view of polyadenylated RNAs. However, on samples of suboptimal quality ribosomal RNA depletion and exon capture methods have recently been reported as better alternatives.

methodsWe compared for the first time three commercial Illumina library preparation kits (TruSeq Stranded mRNA, TruSeq Ribo-Zero rRNA Removal, and TruSeq RNA Access) as representatives of these three different approaches using well-established human reference RNA samples from the MAQC/SEQC consortium on a wide range of input amounts (from 100 ng down to 1 ng) and degradation levels (intact, degraded, and highly degraded).

resultsWe assessed the accuracy of the generated expression values by comparison to gold standard TaqMan qPCR measurements and gained unprecedented insight into the limits of applicability in terms of input quantity and sample quality of each protocol. We found that each protocol generates highly reproducible results (R

conclusionsWe found that the ribosomal RNA depletion protocol from Illumina works very well at amounts far below recommendation and over a good range of intact and degraded material. We also infer that the exome-capture protocol (RNA Access, Illumina) performs better than other methods on highly degraded and low amount samples.

Indexed as

HumansQuality ControlRNA, MessengerRNA StabilitySequence AlignmentSequence Analysis, RNATaq PolymeraseRNA, MessengerTaq PolymeraseBenchmarkingDifferential expressionExpression profilingLow qualityLow quantityRNA-sequencing

Identifiers

PMID28583074
PMCPMC5460543

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.