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Record W4290760139 · doi:10.3390/plants11152053

Comprehensive Analysis of Differentially Expressed Genes and Epigenetic Modification-Related Expression Variation Induced by Saline Stress at Seedling Stage in Fiber and Oil Flax, Linum usitatissimum L.

2022· article· en· W4290760139 on OpenAlexaff
Ningning Wang, Yujie Lin, Fan Qi, Chunxiao Xiaoyang, Zhanwu Peng, Ying Yu, Yingnan Liu, Jun Zhang, Xin Qi, Michael K. Deyholos, Jian Zhang

Bibliographic record

VenuePlants · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersJilin Agricultural UniversityNational Natural Science Foundation of China
KeywordsLinumBiologySalineGermplasmEpigeneticsSeedlingGeneBotanyHalophyteSalinityGenetics

Abstract

fetched live from OpenAlex

The ability of different germplasm to adapt to a saline-alkali environment is critical to learning about the tolerance mechanism of saline-alkali stress in plants. Flax is an important oil and fiber crop in many countries. However, its molecular tolerance mechanism under saline stress is still not clear. In this study, we studied morphological, physiological characteristics, and gene expression variation in the root and leaf in oil and fiber flax types under saline stress, respectively. Abundant differentially expressed genes (DEGs) induced by saline stress, tissue/organ specificity, and different genotypes involved in plant hormones synthesis and metabolism and transcription factors and epigenetic modifications were detected. The present report provides useful information about the mechanism of flax response to saline stress and could lead to the future elucidation of the specific functions of these genes and help to breed suitable flax varieties for saline/alkaline soil conditions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.285

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 head0.032
GPT teacher head0.259
Teacher spread0.228 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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