MétaCan
Menu
Back to cohort
Record W3138996175 · doi:10.1101/2021.03.16.435708

DNA Methylation Networks Underlying Mammalian Traits

2021· preprint· en· W3138996175 on OpenAlexaff
Amin Haghani, Aimei Lu, Chengzhang Li, Todd R. Robeck, Katherine Belov, Charles E. Breeze, Robert T. Brooke, Shannon Clarke, Christopher G. Faulkes, Zhe Fei, Steven H. Ferguson, Carrie J. Finno, Vadim N. Gladyshev, Vera Gorbunova, Rodolfo G. Goya, Andrew N. Hogan, Carolyn J. Hogg, T.A. Hore, Hippokratis Kiaris, Paweł Kordowitzki, Gareth Banks, William R. Koski, Khyobeni Mozhui, Asieh Naderi, Elaine A. Ostrander, Kim M. Parsons, Jocelyn Plassais, Jooke Robbins, Karen E. Sears, Andrei Seluanov, Karen J. Steinman, Balázs Szladovits, Michael J. Thompson, Diego Villar, Nan Wang, Gerald S. Wilkinson, B. G. Young, Joshua Zhang, Joseph A. Zoller, Jason Ernst, X. William Yang, Ken Raj, Steve Horvath

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsLGL (Canada)University of ManitobaFisheries and Oceans Canada
FundersPaul G. Allen Frontiers Group
KeywordsBiologyPhylogenetic treeEpigeneticsDNA methylationEvolutionary biologyGeneticsMethylationDNAComputational biologyGeneGene expression

Abstract

fetched live from OpenAlex

Summary Epigenetics has hitherto been studied and understood largely at the level of individual organisms. Here, we report a multi-faceted investigation of DNA methylation across 11,117 samples from 176 different species. We performed an unbiased clustering of individual cytosines into 55 modules and identified 31 modules related to primary traits including age, species lifespan, sex, adult species weight, tissue type and phylogenetic order. Analysis of the correlation between DNA methylation and species allowed us to construct phyloepigenetic trees for different tissues that parallel the phylogenetic tree. In addition, while some stable cytosines reflect phylogenetic signatures, others relate to age and lifespan, and in many cases responding to anti-aging interventions in mice such as caloric restriction and ablation of growth hormone receptors. Insights uncovered by this investigation have important implications for our understanding of the role of epigenetics in mammalian evolution, aging and lifespan.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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

Citations30
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicEpigenetics and DNA MethylationFrench-language works237,207