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Record W3152555201 · doi:10.1186/s12870-021-02972-0

Genome-wide identification and functional characterization of LEA genes during seed development process in linseed flax (Linum usitatissimum L.)

2021· article· en· W3152555201 on OpenAlexaff
Zhen Li, Hui Chi, Caiyue Liu, Tianbao Zhang, Lida Han, Liang Li, Xinwu Pei, Yan Long

Bibliographic record

VenueBMC Plant Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsBiotechnology Research Institute
FundersChinese Academy of Agricultural SciencesScience and Technology Department of Ningxia
KeywordsLinumBiologyGeneGenomeArabidopsisGene familyGeneticsPhylogenetic treeIntronBotanyMutant

Abstract

fetched live from OpenAlex

BACKGROUND: LEA proteins are widely distributed in the plant and animal kingdoms, as well as in micro-organisms. LEA genes make up a large family and function in plant protection against a variety of adverse conditions. RESULTS: Bioinformatics approaches were adopted to identify LEA genes in the flax genome. In total, we found 50 LEA genes in the genome. We also conducted analyses of the physicochemical parameters and subcellular location of the genes and generated a phylogenetic tree. LuLEA genes were unevenly mapped among 15 flax chromosomes and 90% of the genes had less than two introns. Expression profiles of LuLEA showed that most LuLEA genes were expressed at a late stage of seed development. Functionally, the LuLEA1 gene reduced seed size and fatty acid contents in LuLEA1-overexpressed transgenic Arabidopsis lines. CONCLUSION: Our study adds valuable knowledge about LEA genes in flax which can be used to improve related genes of seed development.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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 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

Citations34
Published2021
Admission routes1
Has abstractyes

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