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Record W2968206978 · doi:10.1139/gen-2019-0061

Genome-wide identification and expression analysis of aquaporin gene family related to abiotic stress in watermelon

2019· article· en· W2968206978 on OpenAlexvenueno aff
Yong Zhou, Junjie Tao, Golam Jalal Ahammed, Jingwen Li, Youxin Yang

Bibliographic record

VenueGenome · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant nutrient uptake and metabolism
Canadian institutionsnot available
FundersNatural Science Foundation of Jiangxi ProvinceNational Natural Science Foundation of China
KeywordsBiologyGeneAquaporinGenomeGeneticsAbiotic stressGene familyGene expressionPhylogenetic treeChromosomeCell biology

Abstract

fetched live from OpenAlex

The plant aquaporins (AQPs) are highly conserved integral membrane proteins that participate in multiple developmental processes and responses to various stresses. In this study, a total of 35 AQP genes were identified in the watermelon genome. The phylogenetic analysis showed that these AQPs can be divided into five types, including 16 plasma membrane intrinsic proteins (PIPs), eight tonoplast intrinsic proteins (TIPs), eight nodulin 26-like intrinsic proteins (NIPs), two small basic intrinsic proteins (SIPs), and one uncategorized X intrinsic protein (XIP). A number of cis-elements related to plant responses to hormones and stresses were detected in the promoter sequences of ClAQP genes. Chromosome distribution analysis revealed that the genes are unevenly distributed on eight chromosomes, with chromosomes 1 and 4 possessing the most genes. Expression analysis at different developmental stages in flesh and rind indicated that most of ClAQPs have tissue-specific expression. Meanwhile, some other AQP genes showed differential expression in response to cold, salt, and ABA treatments, which is consistent with the organization of the stress-responsive cis-elements detected in the promoter regions. Our results lay a foundation for understanding the specific functions of ClAQP genes to help the genetic improvement of watermelon.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

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