Evidence map›Paper›PMID 25121584›Full record

ArticlePLoS genetics2014

Inference of transposable element ancestry.

Aaron C Wacholder, Corey Cox, Thomas J Meyer, Robert P Ruggiero, Vijetha Vemulapalli, Annette Damert, Lucia Carbone, David D Pollock

Abstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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

8 authors.

Aaron C WacholderDepartment of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
Corey CoxDepartment of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
Thomas J MeyerDepartment of Behavioural Neuroscience, Oregon Health Sciences University, Portland, Oregon, United States of America; Division of Neuroscience, Oregon National Primate Research Center, Beaverton, Oregon, United States of America.
Robert P RuggieroDepartment of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
Vijetha VemulapalliDepartment of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.
Annette DamertMolecular Biology Centre, Institute for Interdisciplinary Research in Bio-Nano Sciences, Babes-Bolyai-University, Cluj-Napoca, Romania.
Lucia CarboneDepartment of Behavioural Neuroscience, Oregon Health Sciences University, Portland, Oregon, United States of America; Division of Neuroscience, Oregon National Primate Research Center, Beaverton, Oregon, United States of America.
David D PollockDepartment of Biochemistry & Molecular Genetics, University of Colorado School of Medicine, Aurora, Colorado, United States of America.

Funding

Modeling evolution of functional context in proteinsR01GM083127 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI POLLOCK, DAVID D · 2009 to 2019
$2.7M
Genome-wide mutation models to decipher functionR01GM097251 · NIGMS · UNIVERSITY OF COLORADO DENVER · PI POLLOCK, DAVID D · 2012 to 2015
$1.2M
NIGMS NIH HHS GM083127NIGMS NIH HHS R01 GM083127NIGMS NIH HHS R01 GM097251
6 · The paper itself

Abstract

Most common methods for inferring transposable element (TE) evolutionary relationships are based on dividing TEs into subfamilies using shared diagnostic nucleotides. Although originally justified based on the "master gene" model of TE evolution, computational and experimental work indicates that many of the subfamilies generated by these methods contain multiple source elements. This implies that subfamily-based methods give an incomplete picture of TE relationships. Studies on selection, functional exaptation, and predictions of horizontal transfer may all be affected. Here, we develop a Bayesian method for inferring TE ancestry that gives the probability that each sequence was replicative, its frequency of replication, and the probability that each extant TE sequence came from each possible ancestral sequence. Applying our method to 986 members of the newly-discovered LAVA family of TEs, we show that there were far more source elements in the history of LAVA expansion than subfamilies identified using the CoSeg subfamily-classification program. We also identify multiple replicative elements in the AluSc subfamily in humans. Our results strongly indicate that a reassessment of subfamily structures is necessary to obtain accurate estimates of mutation processes, phylogenetic relationships and historical times of activity.

Indexed as

Evolution, MolecularPhylogenyBayes TheoremDNA Transposable ElementsGene Transfer, HorizontalHumansMutationDNA Transposable Elements

Identifiers

PMID25121584
PMCPMC4133154

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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.