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Record W2917181170 · doi:10.1186/s12864-018-5400-8

A dynamic degradome landscape on miRNAs and their predicted targets in sugarcane caused by Sporisorium scitamineum stress

2019· article· en· W2917181170 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Genomics · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSugarcane Cultivation and Processing
Canadian institutionsMinistry of Agriculture
FundersProgram for New Century Excellent Talents in UniversityFujian Agriculture and Forestry UniversityNatural Science Foundation of Fujian ProvinceNational Natural Science Foundation of China
KeywordsKEGGBiologyGeneMetabolic pathwaySmutGeneticsPhenylpropanoidComputational biologyBotanyGene expressionTranscriptomeBiosynthesis

Abstract

fetched live from OpenAlex

BACKGROUND: Sugarcane smut is a fungal disease caused by Sporisorium scitamineum. Cultivation of smut-resistant sugarcane varieties is the most effective way to control this disease. The interaction between sugarcane and S. scitamineum is a complex network system. However, to date, there is no report on the identification of microRNA (miRNA) target genes of sugarcane in response to smut pathogen infection by degradome technology. RESULTS: TaqMan qRT-PCR detection and enzyme activity determination showed that S. scitamineum rapidly proliferated and incurred significant enzyme activity changes in the reactive oxygen species metabolic pathway and phenylpropanoid metabolic pathway at 2 d and 5 d after inoculation, which was the best time points to study target gene degradation during sugarcane and S. scitamineum interaction. A total of 122.33 Mb of raw data was obtained from degradome sequencing analysis of YC05-179 (smut-resistant) and ROC22 (smut-susceptible) after inoculation. The Q30 of each sample was > 93%, and the sequence used for degradation site analysis exactly matched the sugarcane reference sequence. A total of 309 target genes were predicted in sugarcane, corresponding to 97 known miRNAs and 112 novel miRNAs, and 337 degradation sites, suggesting that miRNAs can efficiently direct cleavage at multiple sites in the predicted target mRNAs. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the predicted target genes were involved in various regulatory processes, such as signal transduction mechanisms, inorganic ion transport and metabolism, defense mechanisms, translation, posttranslational modifications, energy production and conversion, and glycerolipid metabolism. qRT-PCR analysis of the expression level of 13 predicted target genes and their corresponding miRNAs revealed that there was no obvious negative regulatory relationship between miRNAs and their target genes. In addition, a number of putative resistance-related target genes regulated by miRNA-mediated cleavage were accumulated in sugarcane during S. scitamineum infection, suggesting that feedback regulation of miRNAs may be involved in the response of sugarcane to S. scitamineum infection. CONCLUSIONS: This study elucidates the underlying response of sugarcane to S. scitamineum infection, and also provides a resource for miRNAs and their predicted target genes for smut resistance improvement in sugarcane.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.264

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 head0.012
GPT teacher head0.202
Teacher spread0.189 · 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