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Record W2400966377 · doi:10.5376/cgg.2016.07.0002

Comparative miRNAome Analysis Revealed Numerous Conserved and Novel Drought Responsive miRNAs in Cotton (<i>Gossypium spp.</i>)

2016· article· en· W2400966377 on OpenAlexvenueno aff
Boopathi M.N., Selvam Sathish, P. Kavitha, P. Dachinamoorthy, R. Ravikesavan

Bibliographic record

VenueCotton Genomics and Genetics · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBiologymicroRNAGeneGossypiumAbiotic stressGeneticsSmall RNAAbiotic componentRNAComputational biologyEcology

Abstract

fetched live from OpenAlex

Negative regulations of gene expression by endogenous, non-coding miRNAs have been shown to play important role in abiotic stress responses in plants. However, limited knowledge is available on water stress responsive miRNAs in cotton. In this study, differentially expressed drought responsive miRNAs and their targets were identified under natural field conditions through high-throughput small RNA sequencing by comparing leaf samples of drought tolerant Gossypium hirsutum cv. KC3 and drought susceptible G. barbadense cv. Suvin. Totally four small RNA libraries were constructed and sequenced by employing ion proton TM technology. Altogether, there were 39 407 089 reads with a mean read length of 22 nt. In KC3, there were 5 138 unique miRNA reads that were differentially expressed with at least two folds under water stressed conditions. In contrast, Suvin have shown 8 469 unique miRNA reads that were differentially expressed with minimum of two folds under water stressed conditions. Comparison of miRNAs expressed under water stressed conditions between KC3 and Suvin, have resulted 7 494 miRNA reads and interestingly majority of them were down regulated with at least two folds. Besides identifying large numbers of novel miRNAs, several abiotic stress responsive conserved miRNAs were also noticed. Of particular interest were miR750, miR2, miR14, miR276, miR279, miR-bantam and miR5176 that were highly down regulated in KC3 under water stress conditions. Strikingly, miR2 and miR-bantam were previously shown to target pre-apoptotic genes in biological systems. Further, the identified miRNAs were also targeting different classes of dehydrogenases, protein kinases and transcription factors. Our results revealed for the first time that there were large numbers of water stress related miRNAs that might be sequentially and/or complexly involved in gene regulation that confers drought tolerance in cotton under field conditions and they have enormous potential in elucidating the molecular mechanism of miRNA based gene regulation and more importantly in genetic improvement of drought tolerance in cotton. Further, this is the first report on experimentally identifying miRNAs in G. barbadense .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.252
Teacher spread0.224 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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