Evidence map›Paper›PMID 30944857›Full record

ArticleScience advances2019

Taiji: System-level identification of key transcription factors reveals transcriptional waves in mouse embryonic development.

Kai Zhang, Mengchi Wang, Ying Zhao, Wei Wang

Open access · goldAbstract read
In one paragraph

Article in Science advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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, 86 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Kai ZhangDepartment of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0003-3454-7357
Mengchi WangBioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, USA.
Ying ZhaoDepartment of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA.
Wei WangDepartment of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0003-4377-5060
University of California San Diego · US

Funding

Center for Mammalian Regulatory GenomicsU54HG006997 · NHGRI · LUDWIG INSTITUTE FOR CANCER RES LTD · PI REN, BING · 2012 to 2016
$14.3M
Integrated analysis of genetic variation and epigenomic dataR01HG009626 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WANG, WEI · 2017 to 2025
$4.5M
NHGRI NIH HHS R01 HG009626NHGRI NIH HHS U54 HG006997
6 · The paper itself

Abstract

Transcriptional regulation is pivotal to the specification of distinct cell types during embryonic development. However, it still lacks a systematic way to identify key transcription factors (TFs) orchestrating the temporal and tissue specificity of gene expression. Here, we integrated epigenomic and transcriptomic data to reveal key regulators from two cells to postnatal day 0 in mouse embryogenesis. We predicted three-dimensional chromatin interactions in 12 tissues across eight developmental stages, which facilitates linking TFs to their target genes for constructing transcriptional regulatory networks. To identify driver TFs, we developed a new algorithm, dubbed Taiji, to assess the global influence of each TF and systematically uncovered TFs critical for lineage-specific and stage-dependent tissue specification. We have also identified TF combinations that function in spatiotemporal order to form transcriptional waves regulating developmental progress. Furthermore, lacking stage-specific TF combinations suggests a distributed timing strategy to orchestrate the coordination between tissues during embryonic development.

Indexed as

AlgorithmsGene Expression Regulation, DevelopmentalGene Regulatory NetworksAnimalsEmbryonic DevelopmentEpigenomicsGene Expression ProfilingMiceOrgan SpecificityTranscription FactorsTranscription Factors

Identifiers

PMID30944857
PMCPMC6436936
OpenAlexW2923240451

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.