Evidence map›Paper›PMID 24676093›Full record

ArticleGenome research2014

Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.

Hideya Kawaji, Marina Lizio, Masayoshi Itoh, Mutsumi Kanamori-Katayama, Ai Kaiho, Hiromi Nishiyori-Sueki, Jay W Shin, Miki Kojima-Ishiyama, Mitsuoki Kawano, Mitsuyoshi Murata and 8 more

Abstract read
In one paragraph

Article in Genome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Core promoterome of barley embryo.Computational and structural biotechnology journal · 2024
    Article
  8. Article
  9. Article
  10. Nanopore Guided Annotation of Transcriptome Architectures.bioRxiv : the preprint server for biology · 2024
    Article
  11. Review
  12. Article
  13. Article
  14. Current Status of Next-Generation Sequencing in Bone Genetic Diseases.International journal of molecular sciences · 2023
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

12 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

18 authors.

Hideya KawajiRIKEN Preventive Medicine and Diagnosis Innovation Program, Saitama 351-0198, Japan;
Marina Lizio
Masayoshi Itoh
Mutsumi Kanamori-Katayama
Ai Kaiho
Hiromi Nishiyori-Sueki
Jay W Shin
Miki Kojima-Ishiyama
Mitsuoki Kawano
Mitsuyoshi Murata
Noriko Ninomiya-Fukuda
Sachi Ishikawa-Kato
Sayaka Nagao-Sato
Shohei Noma
Yoshihide Hayashizaki
Alistair R R Forrest
Piero Carninci
FANTOM Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CAGE (cap analysis gene expression) and RNA-seq are two major technologies used to identify transcript abundances as well as structures. They measure expression by sequencing from either the 5' end of capped molecules (CAGE) or tags randomly distributed along the length of a transcript (RNA-seq). Library protocols for clonally amplified (Illumina, SOLiD, 454 Life Sciences [Roche], Ion Torrent), second-generation sequencing platforms typically employ PCR preamplification prior to clonal amplification, while third-generation, single-molecule sequencers can sequence unamplified libraries. Although these transcriptome profiling platforms have been demonstrated to be individually reproducible, no systematic comparison has been carried out between them. Here we compare CAGE, using both second- and third-generation sequencers, and RNA-seq, using a second-generation sequencer based on a panel of RNA mixtures from two human cell lines to examine power in the discrimination of biological states, detection of differentially expressed genes, linearity of measurements, and quantification reproducibility. We found that the quantified levels of gene expression are largely comparable across platforms and conclude that CAGE and RNA-seq are complementary technologies that can be used to improve incomplete gene models. We also found systematic bias in the second- and third-generation platforms, which is likely due to steps such as linker ligation, cleavage by restriction enzymes, and PCR amplification. This study provides a perspective on the performance of these platforms, which will be a baseline in the design of further experiments to tackle complex transcriptomes uncovered in a wide range of cell types.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansRNASequence Analysis, RNATranscriptomeRNA

Identifiers

PMID24676093
PMCPMC3975069

What OpenQuestion holds

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Registered trials

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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.