Evidence map›Paper›PMID 25349913›Full record

ReviewNature neuroscience2014

Decoding neural transcriptomes and epigenomes via high-throughput sequencing.

Jaehoon Shin, Guo-li Ming, Hongjun Song

Abstract readReview
In one paragraph

Review in Nature neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Recent advances in tissue stem cells.Science China. Life sciences · 2021
    Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Opening up the DNA methylome of dementia.Molecular psychiatry · 2017
    Review
  16. Article
  17. Contribution of Neuroepigenetics to Huntington's Disease.Frontiers in human neuroscience · 2017
    Review
  18. Review
  19. The Role of Epigenetic Mechanisms in the Regulation of Gene Expression in the Nervous System.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2016
    Review
  20. Epigenetic mechanisms in neurogenesis.Nature reviews. Neuroscience · 2016
    Review
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

3 authors.

Jaehoon Shin1] Graduate Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [2] Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Guo-li Ming1] Graduate Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [2] Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [3] Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [4] The Solomon Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Hongjun Song1] Graduate Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [2] Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [3] Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. [4] The Solomon Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Funding

Modeling Zika virus pathogenesis and potential intervention during neural development using a human brain organoid systemU19AI131130 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI MING, GUO-LI · 2017 to 2021
$7.7M
Translational models of neurodevelopmental epigenetics and disease using human iPSCsP01NS097206 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI HE, CHUAN · 2016 to 2020
$4.3M
Neurobiology of MeCP2 in adult neurogenesisR01HD069184 · NICHD · JOHNS HOPKINS UNIVERSITY · PI MING, GUO-LI · 2010 to 2012
$734k
Deconstructing the hypothalmic ontogeny and plasticity via clonal analysisR21MH110160 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI MING, GUO-LI · 2016 to 2017
$444k
Development of forebrain organoid platform for modelling human cortical neurogenesisR21NS095348 · NINDS · JOHNS HOPKINS UNIVERSITY · PI MING, GUO-LI · 2015 to 2016
$294k
NIAID NIH HHS U19 AI131130NICHD NIH HHS R01 HD069184NIMH NIH HHS R21 MH110160NINDS NIH HHS P01 NS097206NINDS NIH HHS R21 NS095348
6 · The paper itself

Abstract

The mammalian brain is an evolutionary marvel in which engraving and re-engraving of cellular states enable complex information processing and lifelong maintenance. Understanding the mechanisms by which neurons alter and maintain their molecular signatures during information processing is a fundamental goal of neuroscience. Next-generation sequencing (NGS) technology is rapidly transforming the ability to probe the molecular basis of neuronal function. NGS can define not only the complete molecular signatures of cells by transcriptome analyses but also the cascade of events that induce or maintain such signatures by epigenetic analyses. Here we offer some general and practical information to demystify NGS technology and highlight its potential to the neuroscience field. We start with discussion of the complexity of the nervous system, then introduce various applications of NGS with practical considerations and describe basic principles underlying various NGS technologies. Finally, we discuss emerging NGS-related technologies for the neuroscience field.

Indexed as

Epigenesis, GeneticGene Expression ProfilingHigh-Throughput Nucleotide SequencingTranscriptomeAnimalsComputational BiologyHumansNeurons

Identifiers

PMID25349913
PMCPMC6195198

What OpenQuestion holds

Textmetadata
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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.