Evidence map›Paper›PMID 30616562›Full record

ArticleBMC genomics2019

A comparison between whole transcript and 3' RNA sequencing methods using Kapa and Lexogen library preparation methods.

Feiyang Ma, Brie K Fuqua, Yehudit Hasin, Clara Yukhtman, Chris D Vulpe, Aldons J Lusis, Matteo Pellegrini

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Whole-genome sequence ofMicrobiology resource announcements · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Review

1 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.

Feiyang MaMolecular Biology Institute, University of California, Los Angeles, California, USA.
Brie K FuquaDepartment of Medicine, Cardiology, University of California, Los Angeles, California, USA.
Yehudit HasinDepartment of Medicine, Cardiology, University of California, Los Angeles, California, USA.
Clara YukhtmanDepartment of Medicine, Cardiology, University of California, Los Angeles, California, USA.
Chris D VulpeDepartment of Physiological Sciences, University of Florida, Gainesville, Florida, USA.
Aldons J LusisDepartment of Medicine, Cardiology, University of California, Los Angeles, California, USA. JLusis@mednet.ucla.edu.
Matteo PellegriniMolecular Biology Institute, University of California, Los Angeles, California, USA. matteope@gmail.com.

Funding

Systems genomics of metabolic syndrome traitsP01HL028481 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUSIS, ALDONS JAKE · 1985 to 2019
$50.2M
Vascular Biology Training GrantT32HL069766 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LUSIS, ALDONS JAKE · 2002 to 2022
$7.4M
An integrated molecular approach to understand variation in iron metabolismR01GM083198 · NIGMS · UNIVERSITY OF FLORIDA · PI VULPE, CHRISTOPHER D · 2012 to 2015
$2.7M
NHLBI NIH HHS P01 HL028481NHLBI NIH HHS T32 HL069766NIGMS NIH HHS R01 GM083198NIH HHS R01GM083198
6 · The paper itself

Abstract

background3' RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3' mRNA-Seq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches.

resultsWe found that the traditional whole transcript method and the 3' RNA-Seq method had similar levels of reproducibility. As expected, the whole transcript method assigned more reads to longer transcripts, while the 3' method assigned roughly equal numbers of reads to transcripts regardless of their lengths. We found that the 3' RNA-Seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth.

conclusionsThe 3' RNA-Seq method was better able to detect short transcripts, while the whole transcript RNA-Seq was able to detect more differentially expressed genes. Thus, both approaches have relative advantages and should be selected based on the goals of the experiment.

Indexed as

High-Throughput Nucleotide Sequencing3' Untranslated RegionsAnimalsExome SequencingGene Expression ProfilingMiceRNA, MessengerSequence Analysis, RNATranscriptome3' Untranslated RegionsRNA, Messenger3’ RNA-SeqGene expressionIron metabolismTraditional RNA-Seq

Identifiers

PMID30616562
PMCPMC6323698

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.