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Record W3111055160 · doi:10.1002/ajb2.1579

Genetic insights into the evolution of genera with the eastern Asia–eastern North America floristic disjunction: a transcriptomics analysis

2020· article· en· W3111055160 on OpenAlexaff
Anthony E. Melton, Shichao Chen, Yunpeng Zhao, Chengxin Fu, Qiu‐Yun Xiang, Shifeng Cheng, Gane Ka‐Shu Wong, Pamela S. Soltis, Matthew A. Gitzendanner

Bibliographic record

VenueAmerican Journal of Botany · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of Alberta
FundersNational Science Foundation
KeywordsBiologyFloristicsEvolutionary biologyEast AsiaEcologyChinaArchaeologyGeography

Abstract

fetched live from OpenAlex

PREMISE: Large disjunctions in species distributions provide excellent opportunities to study processes that shape biogeographic patterns. One such disjunction is the eastern Asia-eastern North America (EA-ENA) floristic disjunction. For many genera with this disjunction, species richness is greater in EA than in ENA; this pattern has been attributed, in part, to higher rates of molecular evolution and speciation in EA. Longer branch lengths have been found in some EA clades, relative to their ENA sister clades, suggesting that the EA lineages have evolved at a higher rate, possibly due to environmental heterogeneity, potentially contributing to the species richness anomaly. METHODS: To evaluate whether rates of molecular evolution are elevated in EA relative to ENA, we used transcriptomes from species in 11 genera displaying this disjunction. Rates of molecular evolution were estimated for up to 385 orthologous nuclear loci per genus. RESULTS: No statistically significant differences were identified in pairwise comparisons between EA and ENA sister species, suggesting equal rates of molecular evolution for both species; the data also suggest similar selection pressures in both regions. For larger genera, evidence likewise argues against more species-rich clades having higher molecular evolutionary rates, regardless of region. Our results suggest that genes across multiple gene ontology categories are evolving at similar rates under purifying selection in species in both regions. CONCLUSIONS: Our data support the hypothesis that greater species richness in EA than ENA is due to factors other than an overall increase in rates of molecular evolution in EA.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.188
Teacher spread0.183 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

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