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Record W4366083582 · doi:10.1093/molbev/msad090

Dynamic Evolution of Retroviral Envelope Genes in Egg-Laying Mammalian Genomes

2023· article· en· W4366083582 on OpenAlexfundno aff
K. Kitao, Hiyori Shoji, Takayuki Miyazawa, So Nakagawa

Bibliographic record

VenueMolecular Biology and Evolution · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceHokkaido University
KeywordsBiologyORFSGenomeGeneEndogenous retrovirusPlatypusGeneticsOpen reading frameVirologyPeptide sequenceZoology

Abstract

fetched live from OpenAlex

Independently acquired envelope (env) genes from endogenous retroviruses have contributed to the placental trophoblast cell-cell fusion in therian mammals. Egg-laying mammals (monotremes) are an important sister clade for understanding mammalian placental evolution, but the env genes in their genomes have yet to be investigated. Here, env-derived open reading frames (env-ORFs) encoding more than 400 amino acid lengths were searched in the genomes of two monotremes: platypus and echidna. Only two env-ORFs were present in the platypus genome, whereas 121 env-ORFs were found in the echidna genome. The echidna env-ORFs were phylogenetically classified into seven groups named env-Tac1 to -Tac7. Among them, the env-Tac1 group contained only a single gene, and its amino acid sequence showed high similarity to those of the RD114/simian type D retroviruses. Using the pseudotyped virus assay, we demonstrated that the Env-Tac1 protein utilizes echidna sodium-dependent neutral amino acid transporter type 1 and 2 (ASCT1 and ASCT2) as entry receptors. Moreover, the Env-Tac1 protein caused cell-cell fusion in human 293T cells depending on the expression of ASCT1 and ASCT2. These results illustrate that fusogenic env genes are not restricted to placental mammals, providing insights into the evolution of retroviral genes and the placenta.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.230
Teacher spread0.222 · 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

Citations11
Published2023
Admission routes1
Has abstractyes

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