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Record W4292087083 · doi:10.1016/j.ygeno.2022.110449

Epigenomics of rats' liver and its cross-species functional annotation reveals key regulatory genes underlying short term heat-stress response

2022· article· en· W4292087083 on OpenAlexaff
Jinhuan Dou, Hanpeng Luo, Abdul Sammad, Wenqi Lou, Di Wang, Flávio S. Schenkel, Ying Yu, Lingzhao Fang, Yachun Wang

Bibliographic record

VenueGenomics · 2022
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyHeat stressGeneRNA-SeqEpigenomicsGeneticsEpigeneticsComputational biologyTranscriptomeGene expressionDNA methylation

Abstract

fetched live from OpenAlex

Molecular responses to heat stress are multifaceted and under a complex cellular post-transcriptional control. This study explores the epigenetic and transcriptional alterations induced by heat stress (42 °C for 120 min) in the liver of rats, by integrating ATAC-seq, RNA-Seq, and WGBS information. Out of 2586 differential ATAC-seq peaks induced by heat stress, 36 up-regulated and 22 down-regulated transcript factors (TFs) are predicted, such as Cebpα, Foxa2, Foxo4, Nfya and Sp3. Furthermore, 150,189 differentially methylated regions represent 2571 differentially expressed genes (DEGs). By integrating all data, 45 DEGs are concluded as potential heat stress response markers in rats. To comprehensively annotate and narrow down predicted markers, they are integrated with GWAS results of heat stress parameters in cows, and PheWAS data in humans. Besides better understanding of heat stress responses in mammals, INSR, MAPK8, RHPN2 and BTBD7 are proposed as candidate markers for heat stress in mammals.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.296
Teacher spread0.233 · 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 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

Citations9
Published2022
Admission routes1
Has abstractyes

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