Evidence map›Paper›PMID 24058748›Full record

ReviewJAK-STAT2012

Comparative evolutionary genomics of the STAT family of transcription factors.

Yaming Wang, David E Levy

Open access · bronzeAbstract readReview
In one paragraph

Review in JAK-STAT, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

42 citing papers in PubMed, 62 citations in OpenAlex.

  1. Article
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  16. Targeting fibrosis, mechanisms and cilinical trials.Signal transduction and targeted therapy · 2022
    Review
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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

2 authors at 2 institutions in 1 country.

Yaming WangDepartments of Pathology and Microbiology and NYU Cancer Institute; New York University School of Medicine; New York, NY USA.
David E Levy
New York Proton Center · USUniversity School · US

Funding

Viral Pathogenesis and TherapeuticsU54AI057158 · NIAID · WADSWORTH CENTER · PI LEVY, DAVID E · 2003 to 2014
$100.8M
SIGNAL TRANSDUCTION PATHWAY IN IFN INDUCED TRANSCRIPTIONR01AI028900 · NIAID · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI LEVY, DAVID E · 1990 to 2010
$5.6M
NIAID NIH HHS R01 AI028900NIAID NIH HHS U54 AI057158
6 · The paper itself

Abstract

The STAT signaling pathway is one of the seven common pathways that govern cell fate decisions during animal development. Comparative genomics revealed multiple incidences of stat gene duplications throughout metazoan evolutionary history. While pseudogenization is a frequent fate of duplicated genes, many of these STAT duplications evolved into novel genes through rapid sequence diversification and neofunctionalization. Additionally, the core of STAT gene regulatory networks, comprising stat1 through 4, stat5 and stat6, arose early in vertebrate evolution, probably through the two whole genome duplication events that occurred after the split of Cephalochordates but before the rise of Chondrichthyes. While another complete genome duplication event took place during the evolution of bony fish after their separation from the tetrapods about 450 million years ago (Mya), modern fish have only one set of these core stats, suggesting the rapid loss of most duplicated stat genes. The two stat5 genes in mammals likely arose from a duplication event in early Eutherian evolution, a period from about 310 Mya at the avian-mammal divergence to the separation of marsupials from other mammals about 130 Mya. These analyses indicate that whole genome duplications and gene duplications by unequal chromosomal crossing over were likely the major mechanisms underlying the evolution of STATs.

Indexed as

domain accretionevolutiongene duplicationgenome sequencingSTAT

Identifiers

PMID24058748
PMCPMC3670131
OpenAlexW2050197806

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.