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Record W2905108074 · doi:10.1101/316711

Genome-wide sampling suggests island divergence accompanied by cryptic epigenetic plasticity in Canada lynx

2018· preprint· en· W2905108074 on OpenAlexafffundabout
Justin B. Johnson, Dennis L. Murray, Aaron B. A. Shafer

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyEpigeneticsEvolutionary biologyPopulationDNA methylationGene flowPhenotypic plasticityGeneticsLocal adaptationGenetic variationGeneGene expression

Abstract

fetched live from OpenAlex

ABSTRACT Determining the molecular signatures of adaptive differentiation is a fundamental component of evolutionary biology. A key challenge remains for identifying such signatures in wild organisms, particularly between populations of highly mobile species that undergo substantial gene flow. The Canada lynx ( Lynx canadensis ) is one species where mainland populations appear largely undifferentiated at traditional genetic markers, despite inhabiting diverse environments and displaying phenotypic variation. Here, we used high-throughput sequencing to investigate both neutral genetic structure and epigenetic differentiation across the distributional range of Canada lynx. Using a customized bioinformatics pipeline we scored both neutral SNPs and methylated nucleotides across the lynx genome. Newfoundland lynx were identified as the most differentiated population at neutral genetic markers, with diffusion approximations of allele frequencies indicating that divergence from the panmictic mainland occurred at the end of the last glaciation, with minimal contemporary admixture. In contrast, epigenetic structure revealed hidden levels of differentiation across the range coincident with environmental determinants including winter conditions, particularly in the peripheral Newfoundland and Alaskan populations. Several biological pathways related to morphology were differentially methylated between populations, with Newfoundland being disproportionately methylated for genes that could explain the observed island dwarfism. Our results indicate that epigenetic modifications, specifically DNA methylation, are powerful markers to investigate population differentiation and functional plasticity in wild and non-model systems. SIGNIFICANCE Populations experiencing high rates of gene flow often appear undifferentiated at neutral genetic markers, despite often extensive environmental and phenotypic variation. We examined genome-wide genetic differentiation and DNA methylation between three interconnected regions and one insular population of Canada lynx ( Lynx canadensis) to determine if epigenetic modifications characterized climatic associations and functional molecular plasticity. Demographic approximations indicated divergence of Newfoundland during the last glaciation, while cryptic epigenetic structure identified putatively functional differentiation that might explain island dwarfism. Our study suggests that DNA methylation is a useful marker for differentiating wild populations, particularly when faced with functional plasticity and low genetic differentiation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.613
Threshold uncertainty score0.770

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.207
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes3
Has abstractyes

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