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Record W2346013961 · doi:10.1186/s12977-016-0267-8

Characterization of novel Bovine Leukemia Virus (BLV) antisense transcripts by deep sequencing reveals constitutive expression in tumors and transcriptional interaction with viral microRNAs

2016· article· en· W2346013961 on OpenAlexaff
Keith Durkin, Nicolas Rosewick, Maria Artesi, Vincent Hahaut, Philip Griebel, Natasa Arsic, Arsène Burny, Michel Georges, Anne Van den Broeke

Bibliographic record

VenueRetrovirology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and Retrovirus Studies
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health Authority
FundersAmis de l'Institut BordetFonds De La Recherche Scientifique - FNRS
KeywordsBovine leukemia virusmicroRNAVirologyBiologyLeukemiaVirusGeneComputational biologyMolecular biologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Bovine Leukemia Virus (BLV) is a deltaretrovirus closely related to the Human T cell leukemia virus-1 (HTLV-1). Cattle are the natural host of BLV where it integrates into B-cells, producing a lifelong infection. Most infected animals remain asymptomatic but following a protracted latency period about 5 % develop an aggressive leukemia/lymphoma, mirroring the disease trajectory of HTLV-1. The mechanisms by which these viruses provoke cellular transformation remain opaque. In both viruses little or no transcription is observed from the 5'LTR in tumors, however the proviruses are not transcriptionally silent. In the case of BLV a cluster of RNA polymerase III transcribed microRNAs are highly expressed, while the HTLV-1 antisense transcript HBZ is consistently found in all tumors examined. RESULTS: Here, using RNA-seq, we demonstrate that the BLV provirus also constitutively expresses antisense transcripts in all leukemic and asymptomatic samples examined. The first transcript (AS1) can be alternately polyadenylated, generating a transcript of ~600 bp (AS1-S) and a less abundant transcript of ~2200 bp (AS1-L). Alternative splicing creates a second transcript of ~400 bp (AS2). The coding potential of AS1-S/L is ambiguous, with a small open reading frame of 264 bp, however the transcripts are primarily retained in the nucleus, hinting at a lncRNA-like role. The AS1-L transcript overlaps the BLV microRNAs and using high throughput sequencing of RNA-ligase-mediated (RLM) 5'RACE, we show that the RNA-induced silencing complex (RISC) cleaves AS1-L. Furthermore, experiments using altered BLV proviruses with the microRNAs either deleted or inverted point to additional transcriptional interference between the two viral RNA species. CONCLUSIONS: The identification of novel viral antisense transcripts shows the BLV provirus to be far from silent in tumors. Furthermore, the consistent expression of these transcripts in both leukemic and nonmalignant clones points to a vital role in the life cycle of the virus and its tumorigenic potential. Additionally, the cleavage of the AS1-L transcript by the BLV encoded microRNAs and the transcriptional interference between the two viral RNA species suggest a shared role in the regulation of BLV.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.212
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations82
Published2016
Admission routes1
Has abstractyes

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