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Record W3132662652 · doi:10.1186/s12864-021-07421-8

Genome-wide identification and functional prediction of long non-coding RNAs in Sprague-Dawley rats during heat stress

2021· article· en· W3132662652 on OpenAlexaff
Jinhuan Dou, Flávio S. Schenkel, Lirong Hu, Adnan Khan, Muhammad Zahoor Khan, Ying Yu, Yajing Wang, Yachun Wang

Bibliographic record

VenueBMC Genomics · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsUniversity of Guelph
FundersChina Scholarship Council
KeywordsBiologyGeneLong non-coding RNATranscriptomeExonRNAGene expressionGeneticsEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Heat stress (HS) is a major stress event in the life of an animal, with detrimental upshots in production and health. Long-non-coding RNAs (lncRNAs) play an important role in many biological processes by transcriptional regulation. However, no research has been reported on the characterization and functionality of lncRNAs in heat-stressed rats. RESULTS: We studied expression levels of lncRNAs in rats during HS, using strand-specific RNA sequencing. Six rats, three in each of Control (22 ± 1 °C) and H120 (42 °C for 120 min) experimental groups, were used to screen for lncRNAs in their liver and adrenal glands. Totally, 4498 and 7627 putative lncRNAs were identified in liver and adrenal glands of the Control and H120 groups, respectively. The majority of lncRNAs were relatively shorter and contained fewer exons than protein-coding transcripts. In total, 482 (174 up-regulated and 308 down-regulated) and 271 (126 up-regulated and 145 down-regulated) differentially-expressed lncRNAs (DElncRNAs, P < 0.05) were identified in the liver and adrenal glands of the Control and H120 groups, respectively. Furthermore, 1274, 121, and 73 target differentially-expressed genes (DEGs) in the liver were predicted to interact with DElncRNAs based on trans-/cis- and sequence similarity regulatory modes. Functional annotation analyses indicated that these DEGs were mostly significantly enriched in insulin signalling, myeloid leukaemia, and glucagon signalling pathways. Similarly, 437, 73 and 41 target DEGs in the adrenal glands were mostly significantly enriched in the cell cycle (trans-prediction) and lysosome pathways (cis-prediction). The DElncRNAs interacting with DEGs that encode heat shock proteins (HSPs) may play an important role in HS response, which include Hsf4, Dnaja1, Dnajb4, Hsph1 and Hspb1 in the liver, and Dnajb13 and Hspb8 in the adrenal glands. The strand-specific RNA sequencing findings were also further verified through RT-qPCR. CONCLUSIONS: This study is the first to provide a detailed characterization and functional analysis of expression levels of lncRNAs in liver and adrenal glands of heat-stressed rats, which provides basis for further studies on the biological functions of lncRNAs under heat stress in rats and other mammalian species.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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 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

Citations14
Published2021
Admission routes1
Has abstractyes

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