MétaCan
Menu
Back to cohort
Record W2091221439 · doi:10.1186/1756-0500-7-534

In silico analysis identifies novel restriction enzyme combinations that expand reduced representation bisulfite sequencing CpG coverage

2014· article· en· W2091221439 on OpenAlexafffund
Daniel B. Martinez–Arguelles, Sunghoon Lee, Vassilios Papadopoulos

Bibliographic record

VenueBMC Research Notes · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill UniversityMontreal General HospitalMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsIn silicoComputational biologyCpG siteBisulfiteRestriction enzymeBiologyGeneticsBioinformaticsDNA methylationDNAGeneGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: Epigenetics is the study of gene expression changes that are not caused by changes in the deoxyribonucleic acid (DNA) sequence. DNA methylation is an epigenetic mark occurring in C-phosphate-G sites (CpGs) that leads to local or regional gene expression changes. Reduced-representation bisulfite sequencing (RRBS) is a technique that is used to ascertain the DNA methylation of millions of CpGs at single-nucleotide resolution. The genomic coverage of RRBS is given by the restriction enzyme combination used during the library preparation and the throughput capacity of the next-generation sequencer, which is used to read the generated libraries. The four-nucleotide cutters, MspI and TaqαI, are restriction enzymes commonly used in RRBS that, when combined, achieve ~12% genomic coverage. The increase in throughput of next-generation sequencers allows for novel combinations of restriction enzymes that provide higher CpG coverage. RESULTS: We performed a near-neighbor analysis of the four nucleotide sequences most frequently found within 50 nt of all genomic CpGs. This resulted in the identification of seven methylation-insensitive restriction enzymes (AluI, BfaI, HaeIII, HpyCH4V, MluCI, MseI, and MspI) that shared similar restriction conditions suitable for RRBS library preparation. We report that the use of two or three enzyme combinations increases the theoretical epigenome coverage to almost half of the human genome. CONCLUSIONS: We provide the enzyme combinations that are more likely to increase the CpG coverage in human, rat, and mouse genomes.

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)0.002
metaresearch head score (Gemma)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.151
GPT teacher head0.410
Teacher spread0.259 · 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

Citations16
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueBMC Research NotesSame topicEpigenetics and DNA MethylationFrench-language works237,207