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Record W2057318661 · doi:10.1111/gbb.12150

Methyl CpG Binding Domain Ultra‐Sequencing: a novel method for identifying inter‐individual and cell‐type‐specific variation in <scp>DNA</scp> methylation

2014· article· en· W2057318661 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGenes Brain & Behavior · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsnot available
FundersMedical Research CouncilNational Health and Medical Research CouncilNatural Sciences and Engineering Research Council of CanadaAustralian Research CouncilUniversity of Queensland
KeywordsDNA methylationCpG siteDNAMethylationVariation (astronomy)Computational biologyBiologyDNA sequencingGeneticsGenePhysicsGene expression

Abstract

fetched live from OpenAlex

Experience-dependent changes in DNA methylation can exert profound effects on neuronal function and behaviour. A single learning event can induce a variety of DNA modifications within the neuronal genome, some of which may be common to all individuals experiencing the event, whereas others may occur in a subset of individuals. Variations in experience-induced DNA methylation may subsequently confer increased vulnerability or resilience to the development of neuropsychiatric disorders. However, the detection of experience-dependent changes in DNA methylation in the brain has been hindered by the interrogation of heterogeneous cell populations, regional differences in epigenetic states and the use of pooled tissue obtained from multiple individuals. Methyl CpG Binding Domain Ultra-Sequencing (MBD Ultra-Seq) overcomes current limitations on genome-wide epigenetic profiling by incorporating fluorescence-activated cell sorting and sample-specific barcoding to examine cell-type-specific CpG methylation in discrete brain regions of individuals. We demonstrate the value of this method by characterizing differences in 5-methylcytosine (5mC) in neurons and non-neurons of the ventromedial prefrontal cortex of individual adult C57BL/6 mice, using as little as 50 ng of genomic DNA per sample. We find that the neuronal methylome is characterized by greater CpG methylation as well as the enrichment of 5mC within intergenic loci. In conclusion, MBD Ultra-Seq is a robust method for detecting DNA methylation in neurons derived from discrete brain regions of individual animals. This protocol will facilitate the detection of experience-dependent changes in DNA methylation in a variety of behavioural paradigms and help identify aberrant experience-induced DNA methylation that may underlie risk and resiliency to neuropsychiatric disease.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.048
GPT teacher head0.317
Teacher spread0.269 · 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