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Record W4402906306 · doi:10.1101/2024.09.25.615083

Development of multi-species qPCR assays for a stress transcriptional profiling (STP) Chip to assess the resilience of salmonids to changing environments

2024· preprint· en· W4402906306 on OpenAlexafffundabout
Shahinur S. Islam, Daniel D. Heath, Brian Dixon, Phillip Karpowicz, Kelvin Vuu, Jonathon LeBlanc, Nicholas J. Bernier, Kenneth M. Jeffries

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversity of GuelphUniversity of WaterlooUniversity of ManitobaUniversity of Windsor
FundersGenome Canada
KeywordsProfiling (computer programming)Computational biologyBiologyData scienceComputer science

Abstract

fetched live from OpenAlex

Abstract Ecologically and socio-economically important salmonid fishes in Canada are threatened by diverse environmental stressors. However, predicting species’ responses to environmental change requires understanding the underlying molecular mechanisms governing environmental stress tolerance. Developing advanced molecular genetic tools will provide opportunities to predict how salmonid fishes will respond to environmental stressors and assess their adaptive potential and vulnerability into the future. Here, we developed a panel of Taqman quantitative PCR (qPCR) assays designed to measure mRNA transcript abundance at selected candidate loci for use across salmonids. We designed and applied those assays for use in a high-throughput nanofluidic OpenArray Stress Transcriptional Profiling Chip (STP-Chip) capable of 2688 simultaneous qPCR at multiple gene loci (112 targets for 12 samples in duplicate). Using the nanofluidic STP-Chip, we tested these 112 multi-species qPCR assays using gill, liver and muscle tissue from eight species of salmonids across four genera. Of the selected 112 assays, 69 assays showed amplification in gill, 64 in liver, and 67 in muscle across all eight salmonid species. The percentage of assays that showed amplification across three tissues varied between genera: In general, Salmo , Oncorhynchus , and Salvelinus species showed a higher success rate than Coregonus species. Stress, circadian rhythm, apoptosis, growth-metabolism, and detoxification-relevant assays showed high success rates for amplification across all salmonid species for all three tissues. In contrast, neural plasticity, appetite regulation, osmoregulation, immune function, endocrine disruption, and hypoxia-relevant assays showed low success. Not surprisingly, we observed tissue-specific variation among qPCR amplification patterns. There were significant differences in mRNA transcript abundance among species across the four genera, but we did not see variation between species from the same genus. These qPCR assays can be used to design custom STP-Chips that can be used for quantifying stress in salmonid fish, improving health through more accurate diagnostic tests for disease, and monitoring adaptation to accelerated climate change regionally and globally.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.032
GPT teacher head0.272
Teacher spread0.241 · 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.

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

Citations7
Published2024
Admission routes3
Has abstractyes

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