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Record W2787175739

Use of random amplified microsatellites (RAMS) to discern genotypes of Saprolegnia parasitica isolates on the west coast of British Columbia

2014· dissertation· en· W2787175739 on OpenAlexaboutno aff
Cayla Naumann

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsSaprolegniaBiologyGenotypeWest coastVeterinary medicineMicrosatelliteFisheryGeographyBotanyFish <Actinopterygii>OceanographyGeneticsMedicineGeologyGene
DOInot available

Abstract

fetched live from OpenAlex

Several oomycete species of the genus Saprolegnia are recognized as devastating fish pathogens and are responsible for the loss of millions of fish annually for the aquaculture industry. Until recently, these pathogens were kept in check using malachite green; however, due to its toxicity, this chemical has now been banned from use. Saprolegnia parasitica is recognized as the major pathogen of aquaculture fish species. The industry is struggling to predict and control S. parasitica outbreaks in fish hatcheries and there is a need for new knowledge regarding the population genetic structure of this pathogen. Random amplified microsatellites were used to compare isolates of S. parasitica collected from a variety of hatchery locations during the period of November 2009 - August 2011, in order to determine the level of genetic variability and determine changes in genetic diversity over time. Allele frequencies of scored characters were graphically compared. Population genetic diversity was measured using Nei’s genetic distance, Shannon’s Information Index, number of polymorphic loci and phylogenetic trees. Due to the presence of Saprolegnia parasitica in the facilities tested, it appears to be ubiquitous in aquaculture facilities and treatment and prevention will be an ongoing concern in aquaculture management. Overall, genetic diversity of S. parasitica isolates was determined to be low with at least some sexual recombination occurring over time. There was a diversity of genotypes collected from the same hatchery on a single day, indicating there was not a single genotype present at a given time point. Genetic profiling, such as used here, could provide facility managers with a new approach to develop a series of best practices to control sporadic outbreaks of disease. Use of these genetic markers and close monitoring of S. parasitica genotypes will permit early detection and sanitation protocols.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.017
GPT teacher head0.213
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 designBench or experimental
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

Citations1
Published2014
Admission routes1
Has abstractno

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