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Record W1911940415 · doi:10.1111/mec.13245

<scp>RAD</scp> genotyping reveals fine‐scale genetic structuring and provides powerful population assignment in a widely distributed marine species, the <scp>A</scp>merican lobster (<i><scp>H</scp>omarus americanus</i>)

2015· article· en· W1911940415 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Ecology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsUniversity of New BrunswickFisheries and Oceans CanadaUniversité Laval
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsBiologyPopulationGenetic structureRange (aeronautics)Evolutionary biologyPopulation geneticsEcologyGeneticsGenetic variationGene

Abstract

fetched live from OpenAlex

Deciphering genetic structure and inferring connectivity in marine species have been challenging due to weak genetic differentiation and limited resolution offered by traditional genotypic methods. The main goal of this study was to assess how a population genomics framework could help delineate the genetic structure of the American lobster (Homarus americanus) throughout much of the species' range and increase the assignment success of individuals to their location of origin. We genotyped 10 156 filtered SNPs using RAD sequencing to delineate genetic structure and perform population assignment for 586 American lobsters collected in 17 locations distributed across a large portion of the species' natural distribution range. Our results revealed the existence of a hierarchical genetic structure, first separating lobsters from the northern and southern part of the range (FCT = 0.0011; P-value = 0.0002) and then revealing a total of 11 genetically distinguishable populations (mean FST = 0.00185; CI: 0.0007-0.0021, P-value < 0.0002), providing strong evidence for weak, albeit fine-scale population structuring within each region. A resampling procedure showed that assignment success was highest with a subset of 3000 SNPs having the highest FST . Applying Anderson's (Molecular Ecology Resources, 2010, 10, 701) method to avoid 'high-grading bias', 94.2% and 80.8% of individuals were correctly assigned to their region and location of origin, respectively. Lastly, we showed that assignment success was positively associated with sample size. These results demonstrate that using a large number of SNPs improves fine-scale population structure delineation and population assignment success in a context of weak genetic structure. We discuss the implications of these findings for the conservation and management of highly connected marine species, particularly regarding the geographic scale of demographic independence.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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