MétaCan
Menu
Back to cohort
Record W1558351807 · doi:10.1186/s12864-015-1551-z

Comparative transcriptomics analysis reveals difference of key gene expression between banana and plantain in response to cold stress

2015· article· en· W1558351807 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 · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBanana Cultivation and Research
Canadian institutionsMinistry of Agriculture
FundersNational High-tech Research and Development ProgramNational Natural Science Foundation of China
KeywordsBiologyTranscriptomeGeneCold stressGene expressionAbiotic stressDNA microarrayRNA-SeqBotanyAdaptation (eye)GeneticsAbiotic componentEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Banana and plantain (Musa spp.) comprise an important part of diets for millions of people around the globe. Low temperature is one of the key environmental stresses which greatly affects the global banana production. To understand the molecular mechanism of the cold-tolerance in plantain we used RNA-Seq based comparative transcriptomics analyses for both cold-sensitive banana and cold-tolerant plantain subjected to the cold stress for 0, 3 and 6 h. RESULTS: The cold-response genes at early stage are identified and grouped in both species by GO analysis. The results show that 10 and 68 differentially expressed genes (DEGs) are identified for 3 and 6 h of cold stress respectively in plantain, while 40 and 238 DEGs are identified respectively in banana. GO classification analyses show that the majority of DEGs identified in both banana and plantain belong to 11 categories including regulation of transcription, response to stress signal transduction, etc. A similar profile for 28 DEGs was found in both banana and plantain for 6 h of cold stress, suggesting both share some common adaptation processes in response to cold stress. There are 17 DEGs found uniquely in cold-tolerance plantain, which were involved in signal transduction, abiotic stress, copper ion equilibrium, photosynthesis and photorespiration, sugar stimulation, protein modifications etc. Twelve early responsive genes including ICE1 and MYBS3 were selected and further assessed and confirmed by qPCR in the extended time course experiments (0, 3, 6, 24 and 48 h), which revealed significant expression difference of key genes in response to cold stress, especially ICE1 and MYBS3 between cold-sensitive banana and cold-tolerant plantain. CONCLUSIONS: We found that the cold-tolerance pathway appears selectively activated by regulation of ICE1 and MYBS3 expression in plantain under different stages of cold stress. We conclude that the rapid activation and selective induction of ICE1 and MYBS3 cold tolerance pathways in plantain, along with expression of other cold-specific genes, may be one of the main reasons that plantain has higher cold resistance than banana.

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)0.001
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 score0.612
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.122
GPT teacher head0.305
Teacher spread0.184 · 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