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Record W4372204598 · doi:10.3791/65485

Soybean Hairy Root Transformation for the Analysis of Gene Function

2023· article· en· W4372204598 on OpenAlexaff
Jie Lin, Dasol Wi, Melissa Ly, Md Asraful Jahan, Sarah Pullano, Izabella Martirosyan, Nik Kovinich

Bibliographic record

VenueJournal of Visualized Experiments · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsYork University
Fundersnot available
KeywordsAgrobacteriumBiologyTransformation (genetics)GeneSymbiosisBiotechnologyGeneticsComputational biologyBotanyAgronomyBacteria

Abstract

fetched live from OpenAlex

Soybean (Glycine max) is a valuable crop in agriculture that has thousands of industrial uses. Soybean roots are the primary site of interaction with soil-borne microbes that form symbiosis to fix nitrogen and pathogens, which makes research involving soybean root genetics of prime importance to improve its agricultural production. The genetic transformation of soybean hairy roots (HRs) is mediated by the Agrobacterium rhizogenes strain NCPPB2659 (K599) and is an efficient tool for studying gene function in soybean roots, taking only 2 months from start to finish. Here, we provide a detailed protocol that outlines the method for overexpressing and silencing a gene of interest in soybean HRs. This methodology includes soybean seed sterilization, infection of cotyledons with K599, and the selection and harvesting of genetically transformed HRs for RNA isolation and, if warranted, metabolite analyses. The throughput of the approach is sufficient to simultaneously study several genes or networks and could determine the optimal engineering strategies prior to committing to long-term stable transformation approaches.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.067
Threshold uncertainty score0.158

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.031
GPT teacher head0.385
Teacher spread0.354 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

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