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The identification of retro-DNAs in primate genomes as DNA transposons mobilizing via retrotransposition

2023· preprint· en· W4323669555 on OpenAlexafffund
Wangxiangfu Tang, Ping Liang

Bibliographic record

VenueF1000Research · 2023
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsBrock University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaBrock UniversityCanada Research ChairsCompute CanadaCanada Foundation for InnovationOntario Research Foundation
KeywordsRetrotransposonTransposable elementGenomeBiologyGeneticsComputational biologyDNAGene

Abstract

fetched live from OpenAlex

<ns3:p> <ns3:bold>Background:</ns3:bold> Mobile elements (MEs) constitute a major portion of the genome in primates and other higher eukaryotes, and they play important role in genome evolution and gene function. MEs can be divided into two fundamentally different classes: DNA transposons which transpose in the genome in a “cut-and-paste” style, and retrotransposons which propagate in a “copy-and-paste” fashion via a process involving transcription and reverse-transcription. In primate genomes, DNA transposons are mostly dead, while many retrotransposons are still highly active. We report here the identification of a new type of MEs, which we call “retro-DNAs”, for their combined characteristics of these two fundamentally different ME classes. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> A comparative computational genomic approach was used to analyze the reference genome sequences of 10 primate species consisting of five apes, four monkeys, and marmoset. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> From our analysis, we identified a total of 1,750 retro-DNAs, representing 748 unique insertion events in the genomes of ten primate species including human. These retro-DNAs contain sequences of DNA transposons but lack the terminal inverted repeats (TIRs), the hallmark of DNA transposons. Instead, they show characteristics of retrotransposons, such as polyA tails, longer target-site duplications (TSDs), and the “TT/AAAA” insertion site motif, suggesting the use of the L1-based <ns3:underline>t</ns3:underline> arget- <ns3:underline>p</ns3:underline> rimed <ns3:underline>r</ns3:underline> everse <ns3:underline>t</ns3:underline> ranscription (TPRT) mechanism. At least 40% of these retro-DNAs locate into genic regions, presenting potentials for impacting gene function. More interestingly, some retro-DNAs, as well as their parent sites, show certain levels of expression, suggesting that they have the potential to create more retro-DNA copies in the present primate genomes. </ns3:p> <ns3:p> <ns3:bold>Conclusions:</ns3:bold> Although small in number, the identification of these retro-DNAs reveals a new mechanism for propagating DNA transposons in primate genomes without active canonical DNA transposon activity. Our data also suggest that the TPRT machinery may transpose a wider variety of DNA sequences in the genomes. </ns3:p>

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
models splitAgreement compares identical category sets and study designs across arms.

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 score0.880
Threshold uncertainty score0.281

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 science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.314
Teacher spread0.263 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Bench 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

Citations4
Published2023
Admission routes2
Has abstractyes

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