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Record W2951626485 · doi:10.1038/s41598-019-40361-8

miRNA analysis with Prost! reveals evolutionary conservation of organ-enriched expression and post-transcriptional modifications in three-spined stickleback and zebrafish

2019· article· en· W2951626485 on OpenAlexaff
Thomas Desvignes, Peter Batzel, Jason Sydes, B. Frank Eames, John H. Postlethwait

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversity of Saskatchewan
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Dental and Craniofacial ResearchNational Institute of General Medical SciencesUniversity of OregonNational Science FoundationNational Institutes of HealthU.S. Department of Health and Human ServicesNational Institute on Aging
KeywordsSticklebackZebrafishBiologyDaniomicroRNAGeneGasterosteusGeneticsConserved sequenceTranscriptomeRegulation of gene expressionGene expressionComputational biologyEvolutionary biologyFish <Actinopterygii>FisheryBase sequence

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) can have organ-specific expression and functions; they can originate from dedicated miRNA genes, from non-canonical miRNA genes, or from mirror-miRNA genes and can also experience post-transcriptional variation. It remains unclear, however, which mechanisms of miRNA production or modification are organ-specific and the extent of their evolutionary conservation. To address these issues, we developed the software Prost! (PRocessing Of Short Transcripts), which, among other features, helps quantify mature miRNAs, accounts for post-transcriptional processing, such as nucleotide editing, and identifies mirror-miRNAs. Here, we applied Prost! to annotate and analyze miRNAs in three-spined stickleback (Gasterosteus aculeatus), a model fish for evolutionary biology reported to have a miRNome larger than most teleost fish. Zebrafish (Danio rerio), a distantly related teleost with a well-known miRNome, served as comparator. Our results provided evidence for the existence of 286 miRNA genes and 382 unique mature miRNAs (excluding mir430 gene duplicates and the vaultRNA-derived mir733), which doesn't represent a miRNAome larger than other teleost miRNomes. In addition, small RNA sequencing data from brain, heart, testis, and ovary in both stickleback and zebrafish identified suites of mature miRNAs that display organ-specific enrichment, many of which are evolutionarily-conserved in the brain and heart in both species. These data also supported the hypothesis that evolutionarily-conserved, organ-specific mechanisms may regulate post-transcriptional variations in miRNA sequence. In both stickleback and zebrafish, miR2188-5p was edited frequently with similar nucleotide changes in the seed sequence with organ specific editing rates, highest in the brain. In summary, Prost! is a new tool to identify and understand small RNAs, to help clarify a species' miRNA biology as shown here for an important model for the evolution of developmental mechanisms, and to provide insight into organ-enriched expression and the evolutionary conservation of miRNA post-transcriptional modifications.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.348

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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 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

Citations63
Published2019
Admission routes1
Has abstractyes

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