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Record W2469896511 · doi:10.3382/ps/pew194

Discovery of an expanded set of avian leukosis subgroup E proviruses in chickens using Vermillion, a novel sequence capture and analysis pipeline

2016· article· en· W2469896511 on OpenAlexafffund
Kim Rutherford, Conor J. Meehan, Morgan G. I. Langille, Scott G. Tyack, J. C. McKay, Nancy McLean, K. Benkel, Robert G. Beiko, Bernhard F. Benkel

Bibliographic record

VenuePoultry Science · 2016
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsDalhousie University
FundersMcGill UniversityCanadian Institutes of Health ResearchUniversity of California, Santa Cruz
KeywordsGenomeBiologyEndogenous retrovirusGeneticsDNA sequencingGeneVirology

Abstract

fetched live from OpenAlex

Transposable elements (TEs), such as endogenous retroviruses (ERVs), are common in the genomes of vertebrates. ERVs result from retroviral infections of germ-line cells, and once integrated into host DNA they become part of the host's heritable genetic material. ERVs have been ascribed positive effects on host physiology such as the generation of novel, adaptive genetic variation and resistance to infection, as well as negative effects as agents of tumorigenesis and disease. The avian leukosis virus subgroup E family (ALVE) of endogenous viruses of chickens has been used as a model system for studying the effects of ERVs on host physiology, and approximately 30 distinct ALVE proviruses have been described in the Gallus gallus genome. In this report we describe the development of a software tool, which we call Vermillion, and the use of this tool in combination with targeted next-generation sequencing (NGS) to increase the number of known proviruses belonging to the ALVE family of ERVs in the chicken genome by 4-fold, including expanding the number of known ALVE elements on chromosome 1 (Gga1) from the current 9 to a total of 40. Although we focused on the discovery of ALVE elements in chickens, with appropriate selection of target sequences Vermillion can be used to develop profiles of other families of ERVs and TEs in chickens as well as in species other than the chicken.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.339
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2016
Admission routes2
Has abstractyes

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