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Lateral Gene Transfer and the Origins of Prokaryotic Groups

2003· review· en· W2125194704 on OpenAlexaff
Christophe J. Douady, R. Thane Papke, David A. Walsh, Mary Ellen R. Boudreau, Camilla Nesbø, Rebecca J. Case, W. Ford Doolittle

Bibliographic record

VenueAnnual Review of Genetics · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsCanadian Institute for Advanced Research
Fundersnot available
KeywordsBiologyHorizontal gene transferGenomeGeneLineage (genetic)Taxonomic rankEvolutionary biologyPhylogeneticsNitrogen fixationGeneticsRibosomal RNAPhylumBacterial genome sizeBacteriaEcology

Abstract

fetched live from OpenAlex

Lateral gene transfer (LGT) is now known to be a major force in the evolution of prokaryotic genomes. To date, most analyses have focused on either (a) verifying phylogenies of individual genes thought to have been transferred, or (b) estimating the fraction of individual genomes likely to have been introduced by transfer. Neither approach does justice to the ability of LGT to effect massive and complex transformations in basic biology. In some cases, such transformation will be manifested as the patchy distribution of a seemingly fundamental property (such as aerobiosis or nitrogen fixation) among the members of a group classically defined by the sharing of other properties (metabolic, morphological, or molecular, such as small subunit ribosomal RNA sequence). In other cases, the lineage of recipients so transformed may be seen to comprise a new group of high taxonomic rank ("class" or even "phylum"). Here we review evidence for an important role of LGT in the evolution of photosynthesis, aerobic respiration, nitrogen fixation, sulfate reduction, methylotrophy, isoprenoid biosynthesis, quorum sensing, flotation (gas vesicles), thermophily, and halophily. Sometimes transfer of complex gene clusters may have been involved, whereas other times separate exchanges of many genes must be invoked.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations403
Published2003
Admission routes1
Has abstractyes

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