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Record W4250406276 · doi:10.21203/rs.3.rs-50719/v1

Parallel analysis of global garlic gene expression and alliin content following leaf wounding

2020· preprint· en· W4250406276 on OpenAlexfundno aff
Xuqin Yang, Yiren Su, Jiaying Wu, Wen Wan, Huijian chen, Xiaoying Cao, Junjuan Wang, Zhong zhang, Youzhi wang, Deliang Ma, Gary Gloake, Jihong Jiang

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsnot available
FundersInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesShanghai Jiao Tong UniversityJiangsu Normal UniversityGovernment of Jiangsu ProvinceChinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of China
KeywordsAlliinGeneGene expressionContent (measure theory)Expression (computer science)BiologyComputational biologyGeneticsBotanyAllium sativumComputer scienceMathematics

Abstract

fetched live from OpenAlex

Abstract Background Allium sativum (garlic) is both an important food and medicinal plant of economic significance. This plant is rich in sulfides, especially alliin, which is a precursor for the synthesis of allicin. At present, there are few reports on the determination of alliin content in different parts of garlic under abiotic stress. Results Our data determining the accumulation of alliin in different organs showed that the content of alliin in garlic root was the lowest level recorded, while the content of alliin within a garlic bud was the highest level determined. Further, alliin levels decreased in mature leaves following wounding. Further, transcriptomic data generated over time following wounding of mature garlic leaves showed genes integral to the biosynthetic pathways of cysteine (CYS) and serine (SER) formation were significantly up-regulated. Conclusions This differential expression could underpin the accumulation of alliin and its precursors in garlic. Thus, our results provide a platform to help elucidate the biosynthetic pathway alliin biosynthesis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.215
GPT teacher head0.388
Teacher spread0.173 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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