FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Nat Commun / DNA methylation aging and transcriptomic studies in horses.
Nature communications2022; 13(1); 40; doi: 10.1038/s41467-021-27754-y

DNA methylation aging and transcriptomic studies in horses.

Abstract: Cytosine methylation patterns have not yet been thoroughly studied in horses. Here, we profile n = 333 samples from 42 horse tissue types at loci that are highly conserved between mammalian species using a custom array (HorvathMammalMethylChip40). Using the blood and liver tissues from horses, we develop five epigenetic aging clocks: a multi-tissue clock, a blood clock, a liver clock and two dual-species clocks that apply to both horses and humans. In addition, using blood methylation data from three additional equid species (plains zebra, Grevy's zebras and Somali asses), we develop another clock that applies across all equid species. Castration does not significantly impact the epigenetic aging rate of blood or liver samples from horses. Methylation and RNA data from the same tissues define the relationship between methylation and RNA expression across horse tissues. We expect that the multi-tissue atlas will become a valuable resource.
© 2022. The Author(s).
Get Full Text
Publication Date: 2022-01-10 PubMed ID: 35013267PubMed Central: PMC8748428DOI: 10.1038/s41467-021-27754-yGoogle Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article
  • Meta-Analysis
  • Research Support
  • N.I.H.
  • Extramural
  • Research Support
  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research investigates cytosine methylation patterns in horses with a focus on DNA methylation aging. The study produced five epigenetic aging clocks for various horse tissues and established that castration does not significantly impact the epigenetic aging rate. The research also explored the relationship between methylation and RNA expression within horse tissues.

Research Methodology

  • The researchers used a method of profiling called HorvathMammalMethylChip40 to study cytosine methylation patterns in samples from 42 horse tissue types.
  • The sample size used was 333 samples.
  • The team developed five epigenetic aging clocks. These were developed based on blood and liver tissues and ranged from a multi-tissue clock, a blood clock, a liver clock, and two dual-species clocks that apply to horses and humans.
  • The researchers also analyzed blood methylation data obtained from other equid species such as the plains zebra, Grevy’s zebras, and Somali asses forming an additional clock that applies to all equid species.

Findings of the Research

  • The study found that castration does not significantly impact the epigenetic aging rate of blood or liver samples in horses. This means that the process of castration does not alter the normal progression of epigenetic aging in these animals.
  • The research also highlighted the relationship between methylation and RNA expression in horse tissues. The methylation and RNA data gathered from the same tissues helped define this relationship.
  • Importantly, the research anticipates that the multi-tissue atlas developed from this study will turn into a valuable resource for further studies in this field of research.

Significance of the Research

  • This research is significant because it provides insights into the DNA methylation aging in horses, providing a tool for understanding and tracking the ageing process in these animals.
  • The development of the five epigenetic aging clocks in this study is also a significant contribution to the fields of genetics and veterinary science, potentially helping in diagnosing and treating age-related diseases in horses, and perhaps even other equid species.
  • The fact that the research was able to tie together methylation and RNA expression creates new ways of understanding genetic expressions and functionalities in relation to aging.

Cite This Article

APA
Horvath S, Haghani A, Peng S, Hales EN, Zoller JA, Raj K, Larison B, Robeck TR, Petersen JL, Bellone RR, Finno CJ. (2022). DNA methylation aging and transcriptomic studies in horses. Nat Commun, 13(1), 40. https://doi.org/10.1038/s41467-021-27754-y

Publication

Nature communications
ISSN: 2041-1723
NlmUniqueID: 101528555
Country: England
Language: English
Volume: 13
Issue: 1
Pages: 40
PII: 40

Researcher Affiliations

Horvath, Steve
  • Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. shorvath@mednet.ucla.edu.
  • Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA. shorvath@mednet.ucla.edu.
Haghani, Amin
  • Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Peng, Sichong
  • Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA.
Hales, Erin N
  • Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA.
Zoller, Joseph A
  • Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
Raj, Ken
  • Radiation Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Chilton, Didcot, UK.
Larison, Brenda
  • Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA.
  • Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA, USA.
Robeck, Todd R
  • Zoological Operations, SeaWorld Parks and Entertainment, 7007 SeaWorld Drive, Orlando, FL, USA.
Petersen, Jessica L
  • Department of Animal Science, University of Nebraska, Lincoln, NE, USA.
Bellone, Rebecca R
  • Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA.
  • Veterinary Genetics Laboratory, University of California, Davis School of Veterinary Medicine, Davis, CA, USA.
Finno, Carrie J
  • Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA. cjfinno@ucdavis.edu.

MeSH Terms

  • Aging / genetics
  • Animals
  • Blood
  • DNA Methylation
  • Epigenesis, Genetic
  • Epigenomics
  • Equidae / genetics
  • Genetic Techniques
  • Horses / genetics
  • Humans
  • Liver
  • Transcriptome

Grant Funding

  • K01 OD015134 / NIH HHS
  • L40 TR001136 / NCATS NIH HHS

Conflict of Interest Statement

S.H. is a founder of the non-profit Epigenetic Clock Development Foundation, which plans to license several patents from his employer UC Regents. These patents list S.H. as an inventor. The other authors declare no competing interests.

References

This article includes 68 references
  1. Rakyan VK, Down TA, Maslau S, Andrew T, Yang TP, Beyan H, Whittaker P, McCann OT, Finer S, Valdes AM, Leslie RD, Deloukas P, Spector TD. Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains.. Genome Res 2010 Apr;20(4):434-9.
    pmc: PMC2847746pubmed: 20219945doi: 10.1101/gr.103101.109google scholar: lookup
  2. Teschendorff AE, Menon U, Gentry-Maharaj A, Ramus SJ, Weisenberger DJ, Shen H, Campan M, Noushmehr H, Bell CG, Maxwell AP, Savage DA, Mueller-Holzner E, Marth C, Kocjan G, Gayther SA, Jones A, Beck S, Wagner W, Laird PW, Jacobs IJ, Widschwendter M. Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer.. Genome Res 2010 Apr;20(4):440-6.
    pmc: PMC2847747pubmed: 20219944doi: 10.1101/gr.103606.109google scholar: lookup
  3. Issa JP. Aging and epigenetic drift: a vicious cycle.. J Clin Invest 2014 Jan;124(1):24-9.
    pmc: PMC3871228pubmed: 24382386doi: 10.1172/jci69735google scholar: lookup
  4. Horvath S, Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing.. Nat Rev Genet 2018 Jun;19(6):371-384.
    pubmed: 29643443doi: 10.1038/s41576-018-0004-3google scholar: lookup
  5. Field AE, Robertson NA, Wang T, Havas A, Ideker T, Adams PD. DNA Methylation Clocks in Aging: Categories, Causes, and Consequences.. Mol Cell 2018 Sep 20;71(6):882-895.
    pmc: PMC6520108pubmed: 30241605doi: 10.1016/j.molcel.2018.08.008google scholar: lookup
  6. Bell CG, Lowe R, Adams PD, Baccarelli AA, Beck S, Bell JT, Christensen BC, Gladyshev VN, Heijmans BT, Horvath S, Ideker T, Issa JJ, Kelsey KT, Marioni RE, Reik W, Relton CL, Schalkwyk LC, Teschendorff AE, Wagner W, Zhang K, Rakyan VK. DNA methylation aging clocks: challenges and recommendations.. Genome Biol 2019 Nov 25;20(1):249.
    pmc: PMC6876109pubmed: 31767039doi: 10.1186/s13059-019-1824-ygoogle scholar: lookup
  7. Horvath S. DNA methylation age of human tissues and cell types.. Genome Biol 2013;14(10):R115.
    pmc: PMC4015143pubmed: 24138928doi: 10.1186/gb-2013-14-10-r115google scholar: lookup
  8. Petkovich DA, Podolskiy DI, Lobanov AV, Lee SG, Miller RA, Gladyshev VN. Using DNA Methylation Profiling to Evaluate Biological Age and Longevity Interventions.. Cell Metab 2017 Apr 4;25(4):954-960.e6.
    pmc: PMC5578459pubmed: 28380383doi: 10.1016/j.cmet.2017.03.016google scholar: lookup
  9. Cole JJ, Robertson NA, Rather MI, Thomson JP, McBryan T, Sproul D, Wang T, Brock C, Clark W, Ideker T, Meehan RR, Miller RA, Brown-Borg HM, Adams PD. Diverse interventions that extend mouse lifespan suppress shared age-associated epigenetic changes at critical gene regulatory regions.. Genome Biol 2017 Mar 28;18(1):58.
    pmc: PMC5370462pubmed: 28351383doi: 10.1186/s13059-017-1185-3google scholar: lookup
  10. Wang T, Tsui B, Kreisberg JF, Robertson NA, Gross AM, Yu MK, Carter H, Brown-Borg HM, Adams PD, Ideker T. Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment.. Genome Biol 2017 Mar 28;18(1):57.
    pmc: PMC5371228pubmed: 28351423doi: 10.1186/s13059-017-1186-2google scholar: lookup
  11. Stubbs TM, Bonder MJ, Stark AK, Krueger F, von Meyenn F, Stegle O, Reik W. Multi-tissue DNA methylation age predictor in mouse.. Genome Biol 2017 Apr 11;18(1):68.
    pmc: PMC5389178pubmed: 28399939doi: 10.1186/s13059-017-1203-5google scholar: lookup
  12. Thompson MJ, Chwiałkowska K, Rubbi L, Lusis AJ, Davis RC, Srivastava A, Korstanje R, Churchill GA, Horvath S, Pellegrini M. A multi-tissue full lifespan epigenetic clock for mice.. Aging (Albany NY) 2018 Oct 21;10(10):2832-2854.
    pmc: PMC6224226pubmed: 30348905doi: 10.18632/aging.101590google scholar: lookup
  13. Meer MV, Podolskiy DI, Tyshkovskiy A, Gladyshev VN. A whole lifespan mouse multi-tissue DNA methylation clock.. Elife 2018 Nov 14;7.
    pmc: PMC6287945pubmed: 30427307doi: 10.7554/elife.40675google scholar: lookup
  14. Marioni RE, Shah S, McRae AF, Chen BH, Colicino E, Harris SE, Gibson J, Henders AK, Redmond P, Cox SR, Pattie A, Corley J, Murphy L, Martin NG, Montgomery GW, Feinberg AP, Fallin MD, Multhaup ML, Jaffe AE, Joehanes R, Schwartz J, Just AC, Lunetta KL, Murabito JM, Starr JM, Horvath S, Baccarelli AA, Levy D, Visscher PM, Wray NR, Deary IJ. DNA methylation age of blood predicts all-cause mortality in later life.. Genome Biol 2015 Jan 30;16(1):25.
    pmc: PMC4350614pubmed: 25633388doi: 10.1186/s13059-015-0584-6google scholar: lookup
  15. Christiansen L, Lenart A, Tan Q, Vaupel JW, Aviv A, McGue M, Christensen K. DNA methylation age is associated with mortality in a longitudinal Danish twin study.. Aging Cell 2016 Feb;15(1):149-54.
    pmc: PMC4717264pubmed: 26594032doi: 10.1111/acel.12421google scholar: lookup
  16. Perna L, Zhang Y, Mons U, Holleczek B, Saum KU, Brenner H. Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort.. Clin Epigenetics 2016;8:64.
    pmc: PMC4891876pubmed: 27274774doi: 10.1186/s13148-016-0228-zgoogle scholar: lookup
  17. Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, Roetker NS, Just AC, Demerath EW, Guan W, Bressler J, Fornage M, Studenski S, Vandiver AR, Moore AZ, Tanaka T, Kiel DP, Liang L, Vokonas P, Schwartz J, Lunetta KL, Murabito JM, Bandinelli S, Hernandez DG, Melzer D, Nalls M, Pilling LC, Price TR, Singleton AB, Gieger C, Holle R, Kretschmer A, Kronenberg F, Kunze S, Linseisen J, Meisinger C, Rathmann W, Waldenberger M, Visscher PM, Shah S, Wray NR, McRae AF, Franco OH, Hofman A, Uitterlinden AG, Absher D, Assimes T, Levine ME, Lu AT, Tsao PS, Hou L, Manson JE, Carty CL, LaCroix AZ, Reiner AP, Spector TD, Feinberg AP, Levy D, Baccarelli A, van Meurs J, Bell JT, Peters A, Deary IJ, Pankow JS, Ferrucci L, Horvath S. DNA methylation-based measures of biological age: meta-analysis predicting time to death.. Aging (Albany NY) 2016 Sep 28;8(9):1844-1865.
    pmc: PMC5076441pubmed: 27690265doi: 10.18632/aging.101020google scholar: lookup
  18. Horvath S, Pirazzini C, Bacalini MG, Gentilini D, Di Blasio AM, Delledonne M, Mari D, Arosio B, Monti D, Passarino G, De Rango F, D'Aquila P, Giuliani C, Marasco E, Collino S, Descombes P, Garagnani P, Franceschi C. Decreased epigenetic age of PBMCs from Italian semi-supercentenarians and their offspring.. Aging (Albany NY) 2015 Dec;7(12):1159-70.
    pmc: PMC4712339pubmed: 26678252doi: 10.18632/aging.100861google scholar: lookup
  19. Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, Hou L, Baccarelli AA, Li Y, Stewart JD, Whitsel EA, Assimes TL, Ferrucci L, Horvath S. DNA methylation GrimAge strongly predicts lifespan and healthspan.. Aging (Albany NY) 2019 Jan 21;11(2):303-327.
    pmc: PMC6366976pubmed: 30669119doi: 10.18632/aging.101684google scholar: lookup
  20. Jylhävä J, Pedersen NL, Hägg S. Biological Age Predictors.. EBioMedicine 2017 Jul;21:29-36.
    pmc: PMC5514388pubmed: 28396265doi: 10.1016/j.ebiom.2017.03.046google scholar: lookup
  21. Li X, Ploner A, Wang Y, Magnusson PK, Reynolds C, Finkel D, Pedersen NL, Jylhävä J, Hägg S. Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up.. Elife 2020 Feb 11;9.
    pmc: PMC7012595pubmed: 32041686doi: 10.7554/elife.51507google scholar: lookup
  22. Ferrucci L, Gonzalez-Freire M, Fabbri E, Simonsick E, Tanaka T, Moore Z, Salimi S, Sierra F, de Cabo R. Measuring biological aging in humans: A quest.. Aging Cell 2020 Feb;19(2):e13080.
    pmc: PMC6996955pubmed: 31833194doi: 10.1111/acel.13080google scholar: lookup
  23. Raj K, Horvath S. Current perspectives on the cellular and molecular features of epigenetic ageing.. Exp Biol Med (Maywood) 2020 Nov;245(17):1532-1542.
    pmc: PMC7787550pubmed: 32276545doi: 10.1177/1535370220918329google scholar: lookup
  24. Fahy GM, Brooke RT, Watson JP, Good Z, Vasanawala SS, Maecker H, Leipold MD, Lin DTS, Kobor MS, Horvath S. Reversal of epigenetic aging and immunosenescent trends in humans.. Aging Cell 2019 Dec;18(6):e13028.
    pmc: PMC6826138pubmed: 31496122doi: 10.1111/acel.13028google scholar: lookup
  25. Burns EN, Bordbari MH, Mienaltowski MJ, Affolter VK, Barro MV, Gianino F, Gianino G, Giulotto E, Kalbfleisch TS, Katzman SA, Lassaline M, Leeb T, Mack M, Müller EJ, MacLeod JN, Ming-Whitfield B, Alanis CR, Raudsepp T, Scott E, Vig S, Zhou H, Petersen JL, Bellone RR, Finno CJ. Generation of an equine biobank to be used for Functional Annotation of Animal Genomes project.. Anim Genet 2018 Dec;49(6):564-570.
    pmc: PMC6264908pubmed: 30311254doi: 10.1111/age.12717google scholar: lookup
  26. McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, Wenger AM, Bejerano G. GREAT improves functional interpretation of cis-regulatory regions.. Nat Biotechnol 2010 May;28(5):495-501.
    pmc: PMC4840234pubmed: 20436461doi: 10.1038/nbt.1630google scholar: lookup
  27. Eppig JT, Blake JA, Bult CJ, Kadin JA, Richardson JE. The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease.. Nucleic Acids Res 2015 Jan;43(Database issue):D726-36.
    pmc: PMC4384027pubmed: 25348401doi: 10.1093/nar/gku967google scholar: lookup
  28. Robeck TR, Fei Z, Lu AT, Haghani A, Jourdain E, Zoller JA, Li CZ, Steinman KJ, DiRocco S, Schmitt T, Osborn S, Van Bonn B, Katsumata E, Mergl J, Almunia J, Rodriguez M, Haulena M, Dold C, Horvath S. Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins.. Commun Biol 2021 May 31;4(1):642.
    pmc: PMC8167141pubmed: 34059764doi: 10.1038/s42003-021-02179-xgoogle scholar: lookup
  29. Raj K, Szladovits B, Haghani A, Zoller JA, Li CZ, Black P, Maddox D, Robeck TR, Horvath S. Epigenetic clock and methylation studies in cats.. Geroscience 2021 Oct;43(5):2363-2378.
    pmc: PMC8599556pubmed: 34463900doi: 10.1007/s11357-021-00445-8google scholar: lookup
  30. Prado NA, Brown JL, Zoller JA, Haghani A, Yao M, Bagryanova LR, Campana MG, E Maldonado J, Raj K, Schmitt D, Robeck TR, Horvath S. Epigenetic clock and methylation studies in elephants.. Aging Cell 2021 Jul;20(7):e13414.
    pmc: PMC8282242pubmed: 34118182doi: 10.1111/acel.13414google scholar: lookup
  31. Lu AT. Universal DNA methylation age across mammalian tissues. bioRxiv 2021.
    doi: 10.1101/2021.01.18.426733google scholar: lookup
  32. Tallmadge RL, Wang M, Sun Q, Felippe MJB. Transcriptome analysis of immune genes in peripheral blood mononuclear cells of young foals and adult horses.. PLoS One 2018;13(9):e0202646.
    pmc: PMC6124769pubmed: 30183726doi: 10.1371/journal.pone.0202646google scholar: lookup
  33. Arighi, M., Bosu, W. & Raeside, J. In Proceedings of the 31st Annual Convention of the American Association of Equine Practitioners (ed. American Association of Equine Practioners) 591–602 (1985).
  34. Arighi M, Bosu WT. Comparison of hormonal methods for diagnosis of cryptorchidism in horses. J. Equine Vet. Sci. 1989;9:20–26.
  35. Cox JE. Testosterone concentrations in normal and cryptorchid horses. Response to human chorionic gonadotrophin. Anim. Reprod. Sci. 1989;18:43–50.
  36. Schaffer PA, Wobeser B, Martin LE, Dennis MM, Duncan CG. Cutaneous neoplastic lesions of equids in the central United States and Canada: 3,351 biopsy specimens from 3,272 equids (2000-2010).. J Am Vet Med Assoc 2013 Jan 1;242(1):99-104.
    pubmed: 23234288doi: 10.2460/javma.242.1.99google scholar: lookup
  37. Kafarnik C, Rawlings M, Dubielzig RR. Corneal stromal invasive squamous cell carcinoma: a retrospective morphological description in 10 horses.. Vet Ophthalmol 2009 Jan-Feb;12(1):6-12.
    pubmed: 19152592doi: 10.1111/j.1463-5224.2009.00666.xgoogle scholar: lookup
  38. Mosunic CB, Moore PA, Carmicheal KP, Chandler MJ, Vidyashankar A, Zhao Y, Roberts RE, Dietrich UM. Effects of treatment with and without adjuvant radiation therapy on recurrence of ocular and adnexal squamous cell carcinoma in horses: 157 cases (1985-2002).. J Am Vet Med Assoc 2004 Dec 1;225(11):1733-8.
    pubmed: 15626225doi: 10.2460/javma.2004.225.1733google scholar: lookup
  39. Michau TM, Davidson MG, Gilger BC. Carbon dioxide laser photoablation adjunctive therapy following superficial lamellar keratectomy and bulbar conjunctivectomy for the treatment of corneolimbal squamous cell carcinoma in horses: a review of 24 cases.. Vet Ophthalmol 2012 Jul;15(4):245-53.
    pubmed: 22151134doi: 10.1111/j.1463-5224.2011.00977.xgoogle scholar: lookup
  40. Sugrue VJ, Zoller JA, Narayan P, Lu AT, Ortega-Recalde OJ, Grant MJ, Bawden CS, Rudiger SR, Haghani A, Bond DM, Hore RR, Garratt M, Sears KE, Wang N, Yang XW, Snell RG, Hore TA, Horvath S. Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci.. Elife 2021 Jul 6;10.
    pmc: PMC8260231pubmed: 34227937doi: 10.7554/elife.64932google scholar: lookup
  41. Arneson A. A mammalian methylation array for profiling methylation levels at conserved sequences. bioRxiv 2021.
    doi: 10.1101/2021.01.07.425637google scholar: lookup
  42. Horvath S, Zoller JA, Haghani A, Lu AT, Raj K, Jasinska AJ, Mattison JA, Salmon AB. DNA methylation age analysis of rapamycin in common marmosets.. Geroscience 2021 Oct;43(5):2413-2425.
    pmc: PMC8599537pubmed: 34482522doi: 10.1007/s11357-021-00438-7google scholar: lookup
  43. Horvath S, Zoller JA, Haghani A, Jasinska AJ, Raj K, Breeze CE, Ernst J, Vaughan KL, Mattison JA. Epigenetic clock and methylation studies in the rhesus macaque.. Geroscience 2021 Oct;43(5):2441-2453.
    pmc: PMC8599607pubmed: 34487267doi: 10.1007/s11357-021-00429-8google scholar: lookup
  44. Schachtschneider KM, Schook LB, Meudt JJ, Shanmuganayagam D, Zoller JA, Haghani A, Li CZ, Zhang J, Yang A, Raj K, Horvath S. Epigenetic clock and DNA methylation analysis of porcine models of aging and obesity.. Geroscience 2021 Oct;43(5):2467-2483.
    pmc: PMC8599541pubmed: 34523051doi: 10.1007/s11357-021-00439-6google scholar: lookup
  45. de Magalhães JP, Costa J, Church GM. An analysis of the relationship between metabolism, developmental schedules, and longevity using phylogenetic independent contrasts.. J Gerontol A Biol Sci Med Sci 2007 Feb;62(2):149-60.
    pmc: PMC2288695pubmed: 17339640doi: 10.1093/gerona/62.2.149google scholar: lookup
  46. Thompson MJ, vonHoldt B, Horvath S, Pellegrini M. An epigenetic aging clock for dogs and wolves.. Aging (Albany NY) 2017 Mar 28;9(3):1055-1068.
    pmc: PMC5391218pubmed: 28373601doi: 10.18632/aging.101211google scholar: lookup
  47. Ząbek T, Semik-Gurgul E, Szmatoła T, Gurgul A, Fornal A, Bugno-Poniewierska M. Methylation Marks of Blood Leukocytes of Native Hucul Mares Differentiated in Age.. Int J Genomics 2019;2019:2839614.
    pmc: PMC6589255pubmed: 31281827doi: 10.1155/2019/2839614google scholar: lookup
  48. Dunican DS, Mjoseng HK, Duthie L, Flyamer IM, Bickmore WA, Meehan RR. Bivalent promoter hypermethylation in cancer is linked to the H327me3/H3K4me3 ratio in embryonic stem cells.. BMC Biol 2020 Mar 4;18(1):25.
    pmc: PMC7057567pubmed: 32131813doi: 10.1186/s12915-020-0752-3google scholar: lookup
  49. Bernhart SH, Kretzmer H, Holdt LM, Jühling F, Ammerpohl O, Bergmann AK, Northoff BH, Doose G, Siebert R, Stadler PF, Hoffmann S. Changes of bivalent chromatin coincide with increased expression of developmental genes in cancer.. Sci Rep 2016 Nov 23;6:37393.
    pmc: PMC5120258pubmed: 27876760doi: 10.1038/srep37393google scholar: lookup
  50. van Eijk KR, de Jong S, Boks MP, Langeveld T, Colas F, Veldink JH, de Kovel CG, Janson E, Strengman E, Langfelder P, Kahn RS, van den Berg LH, Horvath S, Ophoff RA. Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects.. BMC Genomics 2012 Nov 17;13:636.
    pmc: PMC3583143pubmed: 23157493doi: 10.1186/1471-2164-13-636google scholar: lookup
  51. Clark SJ, Lee HJ, Smallwood SA, Kelsey G, Reik W. Single-cell epigenomics: powerful new methods for understanding gene regulation and cell identity.. Genome Biol 2016 Apr 18;17:72.
    pmc: PMC4834828pubmed: 27091476doi: 10.1186/s13059-016-0944-xgoogle scholar: lookup
  52. Hu Y, Huang K, An Q, Du G, Hu G, Xue J, Zhu X, Wang CY, Xue Z, Fan G. Simultaneous profiling of transcriptome and DNA methylome from a single cell.. Genome Biol 2016 May 5;17:88.
    pmc: PMC4858893pubmed: 27150361doi: 10.1186/s13059-016-0950-zgoogle scholar: lookup
  53. Linker SM, Urban L, Clark SJ, Chhatriwala M, Amatya S, McCarthy DJ, Ebersberger I, Vallier L, Reik W, Stegle O, Bonder MJ. Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity.. Genome Biol 2019 Feb 11;20(1):30.
    pmc: PMC6371455pubmed: 30744673doi: 10.1186/s13059-019-1644-0google scholar: lookup
  54. Levine ME, Lu AT, Quach A, Chen BH, Assimes TL, Bandinelli S, Hou L, Baccarelli AA, Stewart JD, Li Y, Whitsel EA, Wilson JG, Reiner AP, Aviv A, Lohman K, Liu Y, Ferrucci L, Horvath S. An epigenetic biomarker of aging for lifespan and healthspan.. Aging (Albany NY) 2018 Apr 18;10(4):573-591.
    pmc: PMC5940111pubmed: 29676998doi: 10.18632/aging.101414google scholar: lookup
  55. Larison B, Pinho GM, Haghani A, Zoller JA, Li CZ, Finno CJ, Farrell C, Kaelin CB, Barsh GS, Wooding B, Robeck TR, Maddox D, Pellegrini M, Horvath S. Epigenetic models developed for plains zebras predict age in domestic horses and endangered equids.. Commun Biol 2021 Dec 17;4(1):1412.
    doi: 10.1038/s42003-021-02935-zpmc: PMC8683477pubmed: 34921240google scholar: lookup
  56. Harley EH, Knight MH, Lardner C, Wooding B, Gregor M. The Quagga project: progress over 20 years of selective breeding. Afr. J. Wildl. Res. 2009;39:155–163.
  57. Morgello S, Gelman BB, Kozlowski PB, Vinters HV, Masliah E, Cornford M, Cavert W, Marra C, Grant I, Singer EJ. The National NeuroAIDS Tissue Consortium: a new paradigm in brain banking with an emphasis on infectious disease.. Neuropathol Appl Neurobiol 2001 Aug;27(4):326-35.
    pubmed: 11532163doi: 10.1046/j.0305-1846.2001.00334.xgoogle scholar: lookup
  58. Horvath S, Stein DJ, Phillips N, Heany SJ, Kobor MS, Lin DTS, Myer L, Zar HJ, Levine AJ, Hoare J. Perinatally acquired HIV infection accelerates epigenetic aging in South African adolescents.. AIDS 2018 Jul 17;32(11):1465-1474.
    pmc: PMC6026068pubmed: 29746298doi: 10.1097/qad.0000000000001854google scholar: lookup
  59. Kabacik S, Horvath S, Cohen H, Raj K. Epigenetic ageing is distinct from senescence-mediated ageing and is not prevented by telomerase expression.. Aging (Albany NY) 2018 Oct 17;10(10):2800-2815.
    pmc: PMC6224244pubmed: 30332397doi: 10.18632/aging.101588google scholar: lookup
  60. Horvath S, Ritz BR. Increased epigenetic age and granulocyte counts in the blood of Parkinson's disease patients.. Aging (Albany NY) 2015 Dec;7(12):1130-42.
    pmc: PMC4712337pubmed: 26655927doi: 10.18632/aging.100859google scholar: lookup
  61. Horvath S, Haghani A. Mammalian Methylation Consortium Github. 2021.
    doi: 10.5281/zenodo.5711978google scholar: lookup
  62. Zhou W, Triche TJ Jr, Laird PW, Shen H. SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions.. Nucleic Acids Res 2018 Nov 16;46(20):e123.
    pmc: PMC6237738pubmed: 30085201doi: 10.1093/nar/gky691google scholar: lookup
  63. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression.. Nat Methods 2017 Apr;14(4):417-419.
    pmc: PMC5600148pubmed: 28263959doi: 10.1038/nmeth.4197google scholar: lookup
  64. Friedman J, Hastie T, Tibshirani R. Regularization Paths for Generalized Linear Models via Coordinate Descent.. J Stat Softw 2010;33(1):1-22.
    pmc: PMC2929880pubmed: 20808728
  65. de Magalhães JP, Costa J, Toussaint O. HAGR: the Human Ageing Genomic Resources.. Nucleic Acids Res 2005 Jan 1;33(Database issue):D537-43.
    pmc: PMC539971pubmed: 15608256doi: 10.1093/nar/gki017google scholar: lookup
  66. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis.. BMC Bioinformatics 2008 Dec 29;9:559.
    pmc: PMC2631488pubmed: 19114008doi: 10.1186/1471-2105-9-559google scholar: lookup
  67. Horvath S. Pan-primate DNA methylation clocks. bioRxiv 2021.
    doi: 10.1101/2020.11.29.402891google scholar: lookup
  68. Vu H, Ernst J. Universal annotation of the human genome through integration of over a thousand epigenomic datasets. bioRxiv 2021.
    doi: 10.1101/2020.11.17.387134google scholar: lookup

Citations

This article has been cited 29 times.
  1. Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. Nat Aging 2023 Aug 10;.
    doi: 10.1038/s43587-023-00462-6pubmed: 37563227google scholar: lookup
  2. Horvath S, Haghani A, Zoller JA, Lu AT, Ernst J, Pellegrini M, Jasinska AJ, Mattison JA, Salmon AB, Raj K, Horvath M, Paul KC, Ritz BR, Robeck TR, Spriggs M, Ehmke EE, Jenkins S, Li C, Nathanielsz PW. Pan-primate studies of age and sex. Geroscience 2023 Jul 26;.
    doi: 10.1007/s11357-023-00878-3pubmed: 37493860google scholar: lookup
  3. Wang X, Li W, Feng X, Li J, Liu GE, Fang L, Yu Y. Harnessing male germline epigenomics for the genetic improvement in cattle. J Anim Sci Biotechnol 2023 Jun 6;14(1):76.
    doi: 10.1186/s40104-023-00874-9pubmed: 37277852google scholar: lookup
  4. Naue J. Getting the chronological age out of DNA: using insights of age-dependent DNA methylation for forensic DNA applications. Genes Genomics 2023 May 30;.
    doi: 10.1007/s13258-023-01392-8pubmed: 37253906google scholar: lookup
  5. Doherty T, Dempster E, Hannon E, Mill J, Poulton R, Corcoran D, Sugden K, Williams B, Caspi A, Moffitt TE, Delany SJ, Murphy TM. A comparison of feature selection methodologies and learning algorithms in the development of a DNA methylation-based telomere length estimator. BMC Bioinformatics 2023 May 1;24(1):178.
    doi: 10.1186/s12859-023-05282-4pubmed: 37127563google scholar: lookup
  6. Li J, Han F, Yuan T, Li W, Li Y, Wu HX, Wei H, Niu S. The methylation landscape of giga-genome and the epigenetic timer of age in Chinese pine. Nat Commun 2023 Apr 7;14(1):1947.
    doi: 10.1038/s41467-023-37684-6pubmed: 37029142google scholar: lookup
  7. Robeck TR, Haghani A, Fei Z, Lindemann DM, Russell J, Herrick KES, Montano G, Steinman KJ, Katsumata E, Zoller JA, Horvath S. Multi-tissue DNA methylation aging clocks for sea lions, walruses and seals. Commun Biol 2023 Apr 1;6(1):359.
    doi: 10.1038/s42003-023-04734-0pubmed: 37005462google scholar: lookup
  8. Liu X, Seguin-Orlando A, Chauvey L, Tressières G, Schiavinato S, Tonasso-Calvière L, Aury JM, Perdereau A, Wagner S, Clavel P, Estrada O, Pan J, Ma Y, Enk J, Devault A, Klunk J, Lepetz S, Clavel B, Jiang L, Wincker P, Collin YRH, Sarkissian C, Orlando L. DNA methylation-based profiling of horse archaeological remains for age-at-death and castration. iScience 2023 Mar 17;26(3):106144.
    doi: 10.1016/j.isci.2023.106144pubmed: 36843848google scholar: lookup
  9. DeNotta S, McFarlane D. Immunosenescence and inflammaging in the aged horse. Immun Ageing 2023 Jan 6;20(1):2.
    doi: 10.1186/s12979-022-00325-5pubmed: 36609345google scholar: lookup
  10. Cai Y, Song W, Li J, Jing Y, Liang C, Zhang L, Zhang X, Zhang W, Liu B, An Y, Li J, Tang B, Pei S, Wu X, Liu Y, Zhuang CL, Ying Y, Dou X, Chen Y, Xiao FH, Li D, Yang R, Zhao Y, Wang Y, Wang L, Li Y, Ma S, Wang S, Song X, Ren J, Zhang L, Wang J, Zhang W, Xie Z, Qu J, Wang J, Xiao Y, Tian Y, Wang G, Hu P, Ye J, Sun Y, Mao Z, Kong QP, Liu Q, Zou W, Tian XL, Xiao ZX, Liu Y, Liu JP, Song M, Han JJ, Liu GH. The landscape of aging. Sci China Life Sci 2022 Dec;65(12):2354-2454.
    doi: 10.1007/s11427-022-2161-3pubmed: 36066811google scholar: lookup
  11. Ribeiro AMF, Sanglard LP, Wijesena HR, Ciobanu DC, Horvath S, Spangler ML. DNA methylation profile in beef cattle is influenced by additive genetics and age. Sci Rep 2022 Jul 14;12(1):12016.
    doi: 10.1038/s41598-022-16350-9pubmed: 35835812google scholar: lookup
  12. Seale K, Horvath S, Teschendorff A, Eynon N, Voisin S. Making sense of the ageing methylome. Nat Rev Genet 2022 Oct;23(10):585-605.
    doi: 10.1038/s41576-022-00477-6pubmed: 35501397google scholar: lookup
  13. Horvath S, Haghani A, Zoller JA, Raj K, Sinha I, Robeck TR, Black P, Couzens A, Lau C, Manoyan M, Ruiz YA, Talbott A, Belov K, Hogg CJ, Sears KE. Epigenetic clock and methylation studies in marsupials: opossums, Tasmanian devils, kangaroos, and wallabies. Geroscience 2022 Jun;44(3):1825-1845.
    doi: 10.1007/s11357-022-00569-5pubmed: 35449380google scholar: lookup
  14. Arneson A, Haghani A, Thompson MJ, Pellegrini M, Kwon SB, Vu H, Maciejewski E, Yao M, Li CZ, Lu AT, Morselli M, Rubbi L, Barnes B, Hansen KD, Zhou W, Breeze CE, Ernst J, Horvath S. A mammalian methylation array for profiling methylation levels at conserved sequences. Nat Commun 2022 Feb 10;13(1):783.
    doi: 10.1038/s41467-022-28355-zpubmed: 35145108google scholar: lookup
  15. Moqri M, Ying K, Poganik JR, Herzog C, Chen Q, Emamifar M, Tyshkovskiy A, Eames A, Mur J, Glubokov D, Matei-Dediu B, Goeminne L, Mitchell W, McCartney DL, Salas LA, Marioni RE, Lasky-Su JA, Snyder MP, Gladyshev VN. Integrative epigenetics and transcriptomics identify aging genes in human blood. Nat Commun 2026 Jan 19;17(1):725.
    doi: 10.1038/s41467-025-67369-1pubmed: 41554691google scholar: lookup
  16. Jafari H, Abebe BK, Cong L, Ahmed Z, Zhaofei W, Sun M, Muhatai G, Chuzhao L, Dang R. Review: Genomic insights into the adaptive traits and stress resistance in modern horses. Stress Biol 2026 Jan 12;6(1):5.
    doi: 10.1007/s44154-025-00274-1pubmed: 41521281google scholar: lookup
  17. Maciejewski E, Horvath S, Ernst J. CMImpute: cross-species and tissue imputation of species-level DNA methylation samples across mammalian species. Genome Biol 2025 May 20;26(1):133.
    doi: 10.1186/s13059-025-03561-2pubmed: 40394556google scholar: lookup
  18. Sugrue VJ, Prescott M, Glendining KA, Bond DM, Horvath S, Anderson GM, Garratt M, Campbell RE, Hore TA. The androgen clock is an epigenetic predictor of long-term male hormone exposure. Proc Natl Acad Sci U S A 2025 Jan 21;122(3):e2420087121.
    doi: 10.1073/pnas.2420087121pubmed: 39805019google scholar: lookup
  19. Nakamura M, Matsumoto Y, Yasuda K, Nagata M, Nakaki R, Okumura M, Yamazaki J. Unraveling the DNA methylation landscape in dog blood across breeds. BMC Genomics 2024 Nov 15;25(1):1089.
    doi: 10.1186/s12864-024-10963-2pubmed: 39548380google scholar: lookup
  20. Attree E, Griffiths B, Panchal K, Xia D, Werling D, Banos G, Oikonomou G, Psifidi A. Identification of DNA methylation markers for age and Bovine Respiratory Disease in dairy cattle: A pilot study based on Reduced Representation Bisulfite Sequencing. Commun Biol 2024 Oct 3;7(1):1251.
    doi: 10.1038/s42003-024-06925-9pubmed: 39363014google scholar: lookup
  21. Semik-Gurgul E, Pawlina-Tyszko K, Gurgul A, Szmatoła T, Rybińska J, Ząbek T. In search of epigenetic hallmarks of different tissues: an integrative omics study of horse liver, lung, and heart. Mamm Genome 2024 Dec;35(4):600-620.
    doi: 10.1007/s00335-024-10057-0pubmed: 39143382google scholar: lookup
  22. Dutta S, Goodrich JM, Dolinoy DC, Ruden DM. Biological Aging Acceleration Due to Environmental Exposures: An Exciting New Direction in Toxicogenomics Research. Genes (Basel) 2023 Dec 21;15(1).
    doi: 10.3390/genes15010016pubmed: 38275598google scholar: lookup
  23. Hu Z, Boschiero C, Li CJ, Connor EE, Baldwin RL 6th, Liu GE. Unraveling the Genetic Basis of Feed Efficiency in Cattle through Integrated DNA Methylation and CattleGTEx Analysis. Genes (Basel) 2023 Nov 24;14(12).
    doi: 10.3390/genes14122121pubmed: 38136943google scholar: lookup
  24. Maciejewski E, Horvath S, Ernst J. Cross-species and tissue imputation of species-level DNA methylation samples across mammalian species. bioRxiv 2023 Nov 27;.
    doi: 10.1101/2023.11.26.568769pubmed: 38076978google scholar: lookup
  25. Reißmann M, Rajavel A, Kokov ZA, Schmitt AO. Identification of Differentially Expressed Genes after Endurance Runs in Karbadian Horses to Determine Candidates for Stress Indicators and Performance Capability. Genes (Basel) 2023 Oct 24;14(11).
    doi: 10.3390/genes14111982pubmed: 38002925google scholar: lookup
  26. Cappelletti E, Piras FM, Sola L, Santagostino M, Petersen JL, Bellone RR, Finno CJ, Peng S, Kalbfleisch TS, Bailey E, Nergadze SG, Giulotto E. The localization of centromere protein A is conserved among tissues. Commun Biol 2023 Sep 21;6(1):963.
    doi: 10.1038/s42003-023-05335-7pubmed: 37735603google scholar: lookup
  27. Mozhui K, Kim H, Villani F, Haghani A, Sen S, Horvath S. Pleiotropic influence of DNA methylation QTLs on physiological and ageing traits. Epigenetics 2023 Dec;18(1):2252631.
    doi: 10.1080/15592294.2023.2252631pubmed: 37691384google scholar: lookup
  28. Haghani A, Li CZ, Robeck TR, Zhang J, Lu AT, Ablaeva J, Acosta-Rodríguez VA, Adams DM, Alagaili AN, Almunia J, Aloysius A, Amor NMS, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter G, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chavez AS, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke S, Cook JA, Cooper LN, Cossette ML, Day J, DeYoung J, Dirocco S, Dold C, Dunnum JL, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Fei Z, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Goya RG, Grant MJ, Green CB, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaître JF, Levine AJ, Li X, Li C, Lim AR, Lin DTS, Lindemann DM, Liphardt SW, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Murphy WJ, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, Nyamsuren B, O'Brien JK, Ginn PO, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pedersen AB, Pellegrini M, Peters KJ, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Shafer ABA, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmohammadi E, Spangler ML, Spriggs M, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Vu H, Wallingford MC, Wang N, Wilkinson GS, Williams RW, Yan Q, Yao M, Young BG, Zhang B, Zhang Z, Zhao Y, Zhao P, Zhou W, Zoller JA, Ernst J, Seluanov A, Gorbunova V, Yang XW, Raj K, Horvath S. DNA methylation networks underlying mammalian traits. Science 2023 Aug 11;381(6658):eabq5693.
    doi: 10.1126/science.abq5693pubmed: 37561875google scholar: lookup
  29. Vu H, Ernst J. Universal annotation of the human genome through integration of over a thousand epigenomic datasets. Genome Biol 2022 Jan 6;23(1):9.
    doi: 10.1186/s13059-021-02572-zpubmed: 34991667google scholar: lookup
Subscribe to our newsletter
Join 99,344 horse owners like you who receive our email updates on horse health and nutrition.