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Record W4385726857 · doi:10.1126/science.abq5693

DNA methylation networks underlying mammalian traits

2023· article· en· W4385726857 on OpenAlexaff
Amin Haghani, Caesar Z. Li, Todd R. Robeck, Joshua Zhang, Ake T. Lu, Julia Ablaeva, Victoria A. Acosta-Rodríguez, Danielle M. Adams, Abdulaziz N. Alagaili, Javier Almunia, Ajoy Aloysius, Nabil Amor, Reza Ardehali, A Arneson, C. Scott Baker, Gareth Banks, Katherine Belov, Nigel C. Bennett, Peter McL. Black, Daniel T. Blumstein, Eleanor K. Bors, Charles E. Breeze, Robert T. Brooke, Janine L. Brown, Gerald G. Carter, Alex Caulton, Julie M. Cavin, Lisa Chakrabarti, Ioulia Chatzistamou, Andreas S. Chavez, Hao Chen, Kaiyang Cheng, Priscila Chiavellini, Oi‐Wa Choi, Shannon Clarke, Joseph A. Cook, Lisa Noelle Cooper, Marie‐Laurence Cossette, Joanna Day, Joseph DeYoung, Stacy DiRocco, Christopher Dold, Jonathan L. Dunnum, Erin E. Ehmke, Candice K. Emmons, Stephan Emmrich, Ebru Erbay, Claire Erlacher‐Reid, Chris G. Faulkes, Zhe Fei, Steven H. Ferguson, Carrie J. Finno, Jennifer E. Flower, Jean‐Michel Gaillard, Eva Garde, Livia Gerber, Vadim N. Gladyshev, Rodolfo G. Goya, Matthew J. Grant, Carla B. Green, M. Bradley Hanson, Daniel W. Hart, Martin Haulena, Kelsey Herrick, Andrew N. Hogan, Carolyn J. Hogg, Timothy A. Hore, Taosheng Huang, Juan Carlos Izpisúa Belmonte, Anna J. Jasinska, Gareth Jones, Eve Jourdain, Olga Kashpur, Harold L. Katcher, Etsuko Katsumata, Vimala Kaza, Hippokratis Kiaris, Michael S. Kobor, Paweł Kordowitzki, William R. Koski, Michael Krützen, Soo Bin Kwon, Brenda Larison, Sang‐Goo Lee, Marianne Lehmann, Jean‐François Lemaître, Andrew J. Levine, Xinmin Li, Andrea R. Lim, David Lin, Dana M. Lindemann, Schuyler Liphardt, Thomas J. Little, Nicholas Macoretta, Dewey Maddox, Craig O. Matkin, Julie A. Mattison, Matthew McClure, June Mergl, Jennifer J. Meudt, Gisele Montano, Khyobeni Mozhui, Jason Munshi‐South, William J. Murphy, Asieh Naderi, Martina Nagy, Pritika Narayan, Peter W. Nathanielsz, Ngoc B. Nguyen, Christof Niehrs, Nyamsuren Batsaikhan, Justine K. O’Brien, Perrie O’Tierney-Ginn, Duncan T. Odom, Alexander G. Ophir, Steve Osborn, Elaine A. Ostrander, Kim M. Parsons, Kimberly C. Paul, Amy B. Pedersen, Matteo Pellegrini, Katharina J. Peters, Jessica L. Petersen, Darren W. Pietersen, Gabriela Medeiros de Pinho, Jocelyn Plassais, Jesse R. Poganik, Natalia A. Prado, Pradeep Reddy, Benjamin Rey, Beate Ritz, Jooke Robbins, Magdalena Rodríguez, Jennifer Russell, Elena Rydkina, Lindsay L. Sailer, Adam B. Salmon, Akshay Sanghavi, Kyle M. Schachtschneider, Dennis Schmitt, Todd L. Schmitt, Lars Schomacher, Lawrence B. Schook, Karen E. Sears, Ashley W. Seifert, Aaron B. A. Shafer, Anastasia V. Shindyapina, Melanie Simmons, Kavita Singh, Ishani Sinha, Jesse Slone, Russel G. Snell, Elham Soltanmohammadi, Matthew L Spangler, Maria Spriggs, Lydia Staggs, Nancy Stedman, Karen J. Steinman, Donald T. Stewart, Victoria J Sugrue, Balázs Szladovits, Joseph S. Takahashi, Masaki Takasugi, Emma C. Teeling, Michael J. Thompson, Sonja C. Vernes, Diego Villar, Harry V. Vinters, Ha Vu, Mary C. Wallingford, Nan Wang, Gerald S. Wilkinson, Robert W. Williams, Qi Yan, M. Yao, Brent G. Young, Bohan Zhang, Zhihui Zhang, Yang Zhao, Wanding Zhou, Joseph A. Zoller, Jason Ernst, Andrei Seluanov, Vera Gorbunova, X. William Yang, Ken Raj, Steve Horvath

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsBC Children's HospitalLGL (Canada)University of British ColumbiaAcadia UniversityVancouver AquariumUniversity of ManitobaFisheries and Oceans CanadaTrent University
FundersNational Institute on AgingUniversity of California, Los AngelesNational Institutes of HealthTaronga Conservation Society AustraliaUniversität ZürichA.H. Schultz-Stiftung zur Förderung Primatologischer ForschungKing Saud UniversityDepartment of Science and Technology, Ministry of Science and Technology, IndiaLeverhulme TrustSight Research UKBritish Heart FoundationWellcome TrustUniversity of MarylandNatural Environment Research CouncilScience Foundation IrelandUK Research and InnovationJonsson Comprehensive Cancer CenterNational Science FoundationOpen Philanthropy ProjectNational Geographic SocietyCancer Research UK
KeywordsBiologyDNA methylationGeneticsEpigenomeEpigeneticsMethylationGeneRetrotransposonPhylogenetic treeGenomeEvolutionary biologyGene expressionTransposable element

Abstract

fetched live from OpenAlex

Using DNA methylation profiles ( n = 15,456) from 348 mammalian species, we constructed phyloepigenetic trees that bear marked similarities to traditional phylogenetic ones. Using unsupervised clustering across all samples, we identified 55 distinct cytosine modules, of which 30 are related to traits such as maximum life span, adult weight, age, sex, and human mortality risk. Maximum life span is associated with methylation levels in HOXL subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.266

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 science0.0000.000
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 head0.039
GPT teacher head0.320
Teacher spread0.280 · 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

Citations132
Published2023
Admission routes1
Has abstractyes

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