MétaCan
Menu
Back to cohort
Record W2176228213 · doi:10.1534/g3.115.020180

Long-Lasting Gene Conversion Shapes the Convergent Evolution of the Critical Methanogenesis Genes

2015· article· en· W2176228213 on OpenAlexaff
Sishuo Wang, Youhua Chen, Qinhong Cao, Huiqiang Lou

Bibliographic record

VenueG3 Genes Genomes Genetics · 2015
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersProgram for New Century Excellent Talents in UniversityNational Natural Science Foundation of China
KeywordsBiologyOperonMethanomicrobialesNeofunctionalizationGeneGeneticsGene duplicationMethanogenesisConvergent evolutionGene conversionArchaeaPhylogeneticsAlleleMethanosarcinaBacteria

Abstract

fetched live from OpenAlex

Methanogenesis and its key small-molecule methyltransferase Mtr complex are poorly understood despite their pivotal role in Earth's global carbon cycle. Mtr complex is encoded by a conserved mtrEDCBAFGH operon in most methanogens. Here we report that two discrete lineages, Methanococcales and Methanomicrobiales, have a noncanonical mtr operon carrying two copies of mtrA resulting from an ancient duplication. Compared to mtrA-1, mtrA-2 acquires a distinct transmembrane domain through domain shuffling and gene fusion. However, the nontransmembrane domains (MtrA domain) of mtrA-1 and mtrA-2 are homogenized by gene conversion events lasting throughout the long history of these extant methanogens (over 2410 million years). Furthermore, we identified a possible recruitment of ancient nonmethanogenic methyltransferase genes to establish the methanogenesis pathway. These results not only provide novel evolutionary insight into the methanogenesis pathway and methyltransferase superfamily but also suggest an unanticipated long-lasting effect of gene conversion on gene evolution in a convergent pattern.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score0.687

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 head0.025
GPT teacher head0.232
Teacher spread0.207 · 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 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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueG3 Genes Genomes GeneticsSame topicAnaerobic Digestion and Biogas ProductionFrench-language works237,207