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Record W6929822735 · doi:10.5061/dryad.hg600

Data from: Air-borne genotype by genotype indirect genetic effects are substantial in the filamentous fungus Aspergillus nidulans

2017· dataset· en· W6929822735 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2017
Typedataset
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsGenotypeAspergillus nidulansFungusMyceliumPhenotypeGenetic variationFilamentous fungusMutation

Abstract

fetched live from OpenAlex

Genotype by genotype indirect genetic effects (G × G IGEs) occur when the phenotype of an individual is influenced by an interaction between its own genotype and those of neighbour individuals. Little is known regarding the relative importance of G × G IGEs compared with other forms of direct and indirect genetic effects. We quantified the relative importance of IGEs in the filamentous fungus Aspergillus nidulans, a species in which IGEs are likely to be important as air-borne social interactions are known to affect growth. We used a collection of distantly related wild isolates, lab strains and a set of closely related mutation accumulation lines to estimate the contribution of direct and indirect genetic effects on mycelium growth rate, a key fitness component. We found that indirect genetic effects were dominated by G × G IGEs that occurred primarily between a focal genotype and its immediate neighbour within a vertical stack, and these accounted for 11% of phenotypic variation. These results indicate that G × G IGEs may be substantial, at least in some systems, and that the evolutionary importance of these interactions may be underappreciated, especially in microbes. We advocate for a wider use of the IGE framework in both applied (for example, choice of varietal mixtures in plant breeding) and evolutionary genetics (kin selection/kin competition studies).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0000.001
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 head0.030
GPT teacher head0.288
Teacher spread0.257 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2017
Admission routes1
Has abstractyes

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