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Record W4404666915 · doi:10.1111/nph.20293

Patterns of presence–absence variation of <scp>NLRs</scp> across populations of <i>Solanum chilense</i> are clade‐dependent and mainly shaped by past demographic history

2024· article· en· W4404666915 on OpenAlexaff
Gustavo A. Silva‐Arias, Edeline Gagnon, Surya Hembrom, Alexander Fastner, Muhammad Ramzan Khan, Remco Stam, Aurélien Tellier

Bibliographic record

VenueNew Phytologist · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Pathogenic Bacteria Studies
Canadian institutionsUniversity of Guelph
FundersUniversity of California, DavisH2020 Marie Skłodowska-Curie ActionsTechnische Universität MünchenDeutsche ForschungsgemeinschaftDeutscher Akademischer AustauschdienstEuropean Commission
KeywordsBiologyOutcrossingNucleotide diversityCladePopulationBalancing selectionEvolutionary biologyGenetic variationSingle-nucleotide polymorphismGeneticsDemographic historyGenomeGeneAlleleEcologyPhylogeneticsHaplotypeGenotypePollen

Abstract

fetched live from OpenAlex

Understanding the evolution of pathogen resistance genes (nucleotide-binding site-leucine-rich repeats, NLRs) within a species requires a comprehensive examination of factors that affect gene loss and gain. We present a new reference genome of Solanum chilense, which leads to an increased number and more accurate annotation of NLRs. Using a target capture approach, we quantify the presence-absence variation (PAV) of NLR loci across 20 populations from different habitats. We build a rigorous pipeline to validate the identification of PAV of NLRs and then show that PAV is larger within populations than between populations, suggesting that maintenance of NLR diversity is linked to population dynamics. The amount of PAV appears not to be correlated with the NLR presence in gene clusters in the genome, but rather with the past demographic history of the species, with loss of NLRs in diverging (smaller) populations at the distribution edges. Finally, using a redundancy analysis, we find limited evidence of PAV being linked to environmental gradients. Our results suggest that random processes (genetic drift and demography) and weak positive selection for local adaptation shape the evolution of NLRs at the single nucleotide polymorphism and PAV levels in an outcrossing plant with high nucleotide diversity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.328

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 head0.029
GPT teacher head0.234
Teacher spread0.205 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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