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Record W3165111345 · doi:10.1101/828780

Population structure of chum salmon and selection on the markers collected for stock identification

2019· preprint· en· W3165111345 on OpenAlexfundno aff
Shuichi Kitada, Hirohisa Kishino

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceFisheries and Oceans Canada
KeywordsMicrosatelliteBiologySingle-nucleotide polymorphismGeneticsLocus (genetics)PopulationAllele frequencyLoss of heterozygosityEvolutionary biologyAlleleGenotypeGeneDemography

Abstract

fetched live from OpenAlex

Abstract Genetic stock identification (GSI) is a major management tool of Pacific salmon ( Oncorhynchus Spp.) that has provided rich genetic baseline data of allozymes, microsatellites, and single nucleotide polymorphisms (SNPs) across the Pacific Rim. Here, we analyzed published data sets for adult chum salmon ( Oncorhynchus keta ), namely 10 microsatellites, 53 SNPs, and a mitochondrial DNA locus (mtDNA3, control region and NADH-3 combined) from 495 locations in the same distribution range ( n = 61,813). TreeMix analysis of the microsatellite loci identified the highest level of genetic drift towards Japanese/Korean populations and suggested two admixture events from Japan/Korea to Russia and the Alaskan Peninsula. The SNPs had been purposively collected from rapidly evolving genes to increase the power of GSI. The highest expected heterozygosity was observed in Japanese/Korean populations for microsatellites, whereas it was highest in Western Alaskan populations for SNPs, reflecting the SNP discovery process. By regressing the SNP population structures on those of the microsatellites, we estimated the selection on the SNP loci according to deviations from the predicted structures. Specifically, we matched the sampling locations of the SNPs with those of the microsatellites according to geographical information and performed regression analyses of SNP allele frequencies on the two coordinates of multi-dimensional scaling (MDS) of matched locations obtained from microsatellite pairwise F ST values. The MDS first axis indicated a latitudinal cline in American and Russian populations, whereas the second axis found a differentiation of Japanese/Korean populations. The top five outlier SNPs were mtDNA3 (combined locus of the control region and NADH-3), U502241 (unknown), GnRH373, ras1362, and TCP178, which were consistently identified by principal component analysis. We summarized the functions of the 53 nuclear SNPs and mtDNA3 locus by referring to a gene database system and discussed the functions of the outlier SNPs and fitness of chum salmon.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.213
Teacher spread0.203 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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