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Record W2594320986 · doi:10.1093/dnares/dsx005

Evidence of translation efficiency adaptation of the coding regions of the bacteriophage lambda

2017· article· en· W2594320986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDNA Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsnot available
FundersAzrieli Foundation
KeywordsBiologyBacteriophageGeneGeneticsGenomeGenetic codeCoding regionTranslation (biology)Computational biologyTransfer RNAEscherichia coliMessenger RNARNA

Abstract

fetched live from OpenAlex

Deciphering the way gene expression regulatory aspects are encoded in viral genomes is a challenging mission with ramifications related to all biomedical disciplines. Here, we aimed to understand how the evolution shapes the bacteriophage lambda genes by performing a high resolution analysis of ribosomal profiling data and gene expression related synonymous/silent information encoded in bacteriophage coding regions.We demonstrated evidence of selection for distinct compositions of synonymous codons in early and late viral genes related to the adaptation of translation efficiency to different bacteriophage developmental stages. Specifically, we showed that evolution of viral coding regions is driven, among others, by selection for codons with higher decoding rates; during the initial/progressive stages of infection the decoding rates in early/late genes were found to be superior to those in late/early genes, respectively. Moreover, we argued that selection for translation efficiency could be partially explained by adaptation to Escherichia coli tRNA pool and the fact that it can change during the bacteriophage life cycle.An analysis of additional aspects related to the expression of viral genes, such as mRNA folding and more complex/longer regulatory signals in the coding regions, is also reported. The reported conclusions are likely to be relevant also to additional viruses.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.184
GPT teacher head0.377
Teacher spread0.193 · 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