in

Multi-species and multi-tissue methylation clocks for age estimation in toothed whales and dolphins

  • 1.

    Beal, A. P., Kiszka, J. J., Wells, R. S. & Eirin-Lopez, J. M. The Bottlenose dolphin Epigenetic Aging Tool (BEAT): a molecular age estimation tool for small cetaceans. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00561 (2019).

  • 2.

    Garde, E., Heide-Jørgensen, M. P., Hansen, S. H., Nachman, G. & Forchhammer, M. C. Age-specific growth and remarkable longevity in narwhals (Monodon monoceros) from West Greenland as estimated by aspartic acid racemization. J. Mammal. 88, 49–58 (2007).

    Article 

    Google Scholar 

  • 3.

    Matkin, C. O., Ward Testa, J., Ellis, G. M. & Saulitis, E. L. Life history and population dynamics of southern Alaska resident killer whales (Orcinus orca). Mar. Mammal. Sci. 30, 460–479 (2014).

    Article 

    Google Scholar 

  • 4.

    Olesiuk, P., Bigg, M. & Ellis, G. Life history and population dynamics of resident killer whales (Orcinus orca) in the coastal waters of British Columbia and Washington State. Report of the International Whaling Commission. Special 12, 209–243 (1990).

    Google Scholar 

  • 5.

    Wells, R. S. Primates and Cetaceans: Field Research and Conservation of Complex Mammalian Societies, Primatology Monographs (eds. J. Yamagiwa, & Karczmarski, L.) p. 149–172 (Springer, 2014).

  • 6.

    Robeck, T. R., Willis, K., Scarpuzzi, M. R. & O’Brien, J. K. Survivorship pattern inaccuracies and inappropriate anthropomorphism in scholarly pursuits of killer whale (Orcinus orca) life history: a response to Franks et al.(2016). J. Mammal. 97, 899–905 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 7.

    Ellis, S. et al. Analyses of ovarian activity reveal repeated evolution of post-reproductive lifespans in toothed whales. Sci. Rep. 8, 1–10 (2018).

    CAS 
    Article 

    Google Scholar 

  • 8.

    Croft, D. P., Brent, L. J., Franks, D. W. & Cant, M. A. The evolution of prolonged life after reproduction. Trends Ecol. Evol. 30, 407–416 (2015).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 9.

    Wursig, B. & Jefferson, T. A. Methods of photo-identification for small cetaceans. Rep. Int. Whal. Comm. 12, 43–52 (1990).

    Google Scholar 

  • 10.

    Perrin, W. F. & Myrick, A. C. Age Determination Of Toothed Whales And Sirenians (International Whaling Commission, 1980).

  • 11.

    Bryden, M. Research on Dolphins (eds. Bryden, M. M. & Harrison, R. J.) p. 211–224 (Clarendon Press Oxford, 1986).

  • 12.

    Myrick, A. C., Yochem, P. K. & Cornell, L. H. Toward calibrating dentinal layers in captive killer whales by use of tetracycline labels. Rit Fiskid. 11, 285–296 (1988).

    Google Scholar 

  • 13.

    Best, P., Meÿer, M. & Lockyer, C. Killer whales in South African waters—a review of their biology. Afr. J. Mar. Sci. 32, 171–186 (2010).

    Article 

    Google Scholar 

  • 14.

    Foote, A. D., Newton, J., Piertney, S. B., Willerslev, E. & Gilbert, M. T. P. Ecological, morphological and genetic divergence of sympatric North Atlantic killer whale populations. Mol. Ecol. 18, 5207–5217 (2009).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 15.

    Ford, J. K. et al. Shark predation and tooth wear in a population of northeastern Pacific killer whales. Aquat. Biol. 11, 213–224 (2011).

    Article 

    Google Scholar 

  • 16.

    Hohn, A. A. & Fernandez, S. Biases in dolphin age structure due to age estimation technique. Mar. Mammal. Sci. 15, 1124–1132 (1999).

    Article 

    Google Scholar 

  • 17.

    Lockyer, C. A report on patterns of deposition of dentine and cement in teeth of pilot whales, genus Globicephala. Rep. Int. Whal. Comm. 14, 137–161 (1993).

    Google Scholar 

  • 18.

    Waugh, D. A., Suydam, R. S., Ortiz, J. D. & Thewissen, J. Validation of Growth Layer Group (GLG) depositional rate using daily incremental growth lines in the dentin of beluga (Delphinapterus leucas (Pallas, 1776)) teeth. PLoS ONE 13, e0190498 (2018).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 19.

    Sergeant, D. E. Age Determination In Odontocete Whales From Dentinal Growth Layers (Norwegian Whaling Gazette, 1959).

  • 20.

    Brodie, P. F. Mandibular layering in Delphinapterus leucas and age determination. Nature 221, 956–958 (1969).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 21.

    Goren, A. D. et al. Growth layer groups (GLGs) in the teeth of an adult belukha whale (Delphinapterus leucas) of known age: evidence for two annual layers. Mar. Mammal. Sci. 3, 14–21 (1987).

    Article 

    Google Scholar 

  • 22.

    Brodie, P. & Haulena, M. Dentinal growth layer counts of captive, known-age, mother and daughter belugas (Delphinapterus leucas): confirming two growth layer groups (GLG/2) per year; consequences for recovery and management. J Cetacean. Res Manag. 18, 23–31 (2018).

    Google Scholar 

  • 23.

    Brodie, P., Ramirez, K. & Haulena, M. Growth and maturity of belugas (Delphinapterus leucas) in Cumberland Sound, Canada, and in captivity: evidence for two growth layer groups (GLGs) per year in teeth. J. Cetacean Res. Manag. 13, 1–18 (2013).

    Google Scholar 

  • 24.

    Lockyer, C., Hohn, A. A., Doidge, D. W., Heide-Jørgensen, M. P. & Suydam, R. Age determination in belugas (Delphinapterus leucas in Belugas): a quest for validation of dentinal layering. Aquat. Mamm. 33, 293–304 (2007).

    Article 

    Google Scholar 

  • 25.

    Stewart, R., Campana, S., Jones, C. & Stewart, B. Bomb radiocarbon dating calibrates beluga (Delphinapterus leucas) age estimates. Can. J. Zool. 84, 1840–1852 (2006).

    Article 

    Google Scholar 

  • 26.

    Brodie, P. A reconsideration of aspects of growth, reproduction, and behavior of the white whale (Delphinapterus leucas), with reference to the Cumberland Sound, Baffin Island, population. J. Fish. Board Can. 28, 1309–1318 (1971).

    Article 

    Google Scholar 

  • 27.

    Brodie, P. F., Parsons, J. L. & Sergeant, D. E. Present status of the white whale (Delphinapterus leucas) in Cumberland Sound, Baffin Island.Rep. Int. Whal. Comm. 31, 579–582 (1981).

    Google Scholar 

  • 28.

    Robeck, T. R. et al. Reproduction, growth and development in captive beluga (Delphinapterus leucas). Zoo Biol. 24, 29–49 (2005).

    Article 

    Google Scholar 

  • 29.

    Bada, J., Brown, S. & Masters, P. Age determination of marine mammals based on aspartic acid racemization in the teeth and lens nucleus. Age Determination of Toothed Whales and Sirenians. p. 113–118 (Report of the International Whaling Commission, Special, 1980).

  • 30.

    George, J. C. et al. Age and growth estimates of bowhead whales (Balaena mysticetus) via aspartic acid racemization. Can. J. Zool. 77, 571–580 (1999).

    Article 

    Google Scholar 

  • 31.

    Pleskach, K. et al. Use of mass spectrometry to measure aspartic acid racemization for ageing beluga whales. Mar. Mammal. Sci. 32, 1370–1380 (2016).

    CAS 
    Article 

    Google Scholar 

  • 32.

    Garde, E., Peter Heide-Jørgensen, M., Ditlevsen, S. & Hansen, S. H. Aspartic acid racemization rate in narwhal (Monodon monoceros) eye lens nuclei estimated by counting of growth layers in tusks. Polar Res. https://doi.org/10.3402/polar.v31i0.15865 (2012).

  • 33.

    Herman, D. P. et al. Assessing age distributions of killer whale Orcinus orca populations from the composition of endogenous fatty acids in their outer blubber layers. Mar. Ecol. Prog. Ser. 372, 289–302 (2008).

    CAS 
    Article 

    Google Scholar 

  • 34.

    Herman, D. P. et al. Age determination of humpback whales Megaptera novaeangliae through blubber fatty acid compositions of biopsy samples. Mar. Ecol. Prog. Ser. 392, 277–293 (2009).

    Article 

    Google Scholar 

  • 35.

    Marcoux, M., Lesage, V., Thiemann, G. W., Iverson, S. J. & Ferguson, S. H. Age estimation of belugas, Delphinapterus leucas, using fatty acid composition: a promising method. Mar. Mammal. Sci. 31, 944–962 (2015).

    Article 

    Google Scholar 

  • 36.

    Olsen, M. T., Berube, M., Robbins, J. & Palsboll, P. J. Empirical evaluation of humpback whale telomere length estimates; quality control and factors causing variability in the singleplex and multiplex qPCR methods. BMC Genet. 13, 77 (2012).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 37.

    Broer, L. et al. Meta-analysis of telomere length in 19 713 subjects reveals high heritability, stronger maternal inheritance and a paternal age effect. Eur. J. Hum. Genet. 21, 1163–1168 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 38.

    Dunshea, G. et al. Telomeres as age markers in vertebrate molecular ecology. Mol. Ecol. Resour. 11, 225–235 (2011).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 39.

    Polanowski, A. M., Robbins, J., Chandler, D. & Jarman, S. N. Epigenetic estimation of age in humpback whales. Mol. Ecol. Resour. 14, 976–987 (2014).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 40.

    Tanabe, A. et al. Age estimation by DNA methylation in the Antarctic minke whale. Fish. Sci. 86, 35–41 (2020).

    CAS 
    Article 

    Google Scholar 

  • 41.

    Smith, Z. D. & Meissner, A. DNA methylation: roles in mammalian development. Nat. Rev. Genet. 14, 204–220 (2013).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 42.

    Rakyan, V. K. et al. Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains. Genome Res. 20, 434–439 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 43.

    Teschendorff, A. E. et al. Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer. Genome Res. 20, 440–446 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 44.

    Horvath, S. & Raj, K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat. Rev. Genet. 19, 371–384 (2018).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 45.

    Field, A. E. et al. DNA methylation clocks in aging: categories, causes, and consequences. Mol. Cell 71, 882–895 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 46.

    Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 47.

    Bell, C. G. et al. DNA methylation aging clocks: challenges and recommendations. Genome Biol. 20, 1–24 (2019).

    Article 

    Google Scholar 

  • 48.

    Petkovich, D. A. et al. Using DNA methylation profiling to evaluate biological age and longevity interventions. Cell Metab. 25, 954–960.e956 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 49.

    Cole, J. J. et al. Diverse interventions that extend mouse lifespan suppress shared age-associated epigenetic changes at critical gene regulatory regions. Genome Biol. 18, 1–16 (2017).

    Article 
    CAS 

    Google Scholar 

  • 50.

    Wang, T. et al. Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment. Genome Biol. 18, 57 (2017).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 51.

    Stubbs, T. M. et al. Multi-tissue DNA methylation age predictor in mouse. Genome Biol. 18, 1–14 (2017).

    Article 
    CAS 

    Google Scholar 

  • 52.

    Thompson, M. J. et al. A multi-tissue full lifespan epigenetic clock for mice. Aging 10, 2832 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 53.

    Meer, M. V., Podolskiy, D. I., Tyshkovskiy, A. & Gladyshev, V. N. A whole lifespan mouse multi-tissue DNA methylation clock. Elife 7, e40675 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 54.

    Ito, T., Teo, T. V., Evans, S. A., Neretti, N. & Sedivy, J. Regulation of cellular senescence by polycomb chromatin modifiers through distinct DNA damage- and histone methylation-dependent pathways. Cell Rep. 22, 3480–3492 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 55.

    St Aubin, D., Deguise, S., Richard, P., Smith, T. & Geraci, J. Hematology and plasma chemistry as indicators of health and ecological status in beluga whales, Delphinapterus leucas. Arctic 54, 317–331 (2001).

  • 56.

    Norman, S. A. et al. Seasonal hematology and serum chemistry of wild beluga whales (Delphinapterus leucas) in Bristol Bay, Alaska, USA. J. Wildl. Dis. 48, 21–32 (2012).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 57.

    Frost, K. J. & Suydam, R. S. Subsistence harvest of beluga or white whales (Delphinapterus leucas) in northern and western Alaska 1987–2006. J. Cetacea. Res. Manag. 11, 293–299 (2010).

    Google Scholar 

  • 58.

    Rosen, A. D. et al. DNA methylation age is accelerated in alcohol dependence. Transl. Psychiatry 8, 182 (2018).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 59.

    Zhang, Q. et al. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing. Genome Med. 11, 54 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 60.

    Gronniger, E. et al. Aging and chronic sun exposure cause distinct epigenetic changes in human skin. PLoS Genet. 6, e1000971 (2010).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 61.

    Doi, A. et al. Differential methylation of tissue-and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat. Genet. 41, 1350–1353 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 62.

    Vandiver, A. R. et al. Age and sun exposure-related widespread genomic blocks of hypomethylation in nonmalignant skin. Genome Biol. 16, 1–15 (2015).

    CAS 
    Article 

    Google Scholar 

  • 63.

    Li, Q. S., Sun, Y. & Wang, T. Epigenome-wide association study of Alzheimer’s disease replicates 22 differentially methylated positions and 30 differentially methylated regions. Clin. Epigenet. 12, 1–14 (2020).

    Article 
    CAS 

    Google Scholar 

  • 64.

    Sun, L., Zhang, X., Wang, T., Chen, M. & Qiao, H. Association of ANK1 variants with new‑onset type 2 diabetes in a Han Chinese population from northeast China. Exp. Ther. Med. 14, 3184–3190 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 65.

    Luoma, L. M. & Berry, F. B. Molecular analysis of NPAS3 functional domains and variants. BMC Mol. Biol. 19, 1–19 (2018).

    Article 
    CAS 

    Google Scholar 

  • 66.

    Cosgrove, D. et al. Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons. bioRxiv https://doi.org/10.1101/2019.12.16.877837 (2019).

  • 67.

    Decourcelle, A. et al. O-GlcNAcylation links nutrition to the epigenetic downregulation of UNC5A during colon carcinogenesis. Cancers 12, 3168 (2020).

    CAS 
    PubMed Central 
    Article 

    Google Scholar 

  • 68.

    Yang, T., Zhang, X.-B., Li, X.-N., Sun, M.-Z. & Gao, P.-Z. Homeobox C4 promotes hepatocellular carcinoma progression by the transactivation of Snail. Neoplasma 68, 23–30 (2020).

  • 69.

    Yeung, B., Law, A. & Wong, C. K. Evolution and roles of stanniocalcin. Mol. Cell. Endocrinol. 349, 272–280 (2012).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 70.

    Chen, C., Jamaluddin, M. S., Yan, S., Sheikh-Hamad, D. & Yao, Q. Human stanniocalcin-1 blocks TNF-α–induced monolayer permeability in human coronary artery endothelial cells. Arterioscler. Thromb. Vasc. Biol. 28, 906–912 (2008).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 71.

    Jourdain, E. & Karoliussen, R. Identification catalogue of Norwegian killer whales: 2007–2018. Figshare https://doi.org/10.608/m9.figshare.4205226 (2018).

  • 72.

    Kuningas, S., Similä, T. & Hammond, P. S. Population size, survival and reproductive rates of northern Norwegian killer whales (Orcinus orca) in 1986-2003. J. Mar. Biol. Assoc. UK 94, 1277 (2014).

    Article 

    Google Scholar 

  • 73.

    Christensen, I. Growth and reproduction of killer whales, Orcinus orca, in Norwegian coastal waters. Rep. Int. Whal. Commn 6, 253–258 (1984).

    Google Scholar 

  • 74.

    Jourdain, E., Vongraven, D., Bisther, A. & Karoliussen, R. First longitudinal study of seal-feeding killer whales (Orcinus orca) in Norwegian coastal waters. PLoS ONE 12, e0180099 (2017).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 75.

    Arneson, A. et al. A mammalian methylation array for profiling methylation levels at conserved sequences. bioRxiv https://doi.org/10.1101/2021.01.07.425637 (2021).

  • 76.

    Zhou, W., Triche, T. J. Jr., Laird, P. W. & Shen, H. SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions. Nucleic Acids Res. 46, e123 (2018).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 77.

    Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1 (2010).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 78.

    Shao, J. Linear model selection by cross-validation. J. Am. Stat. Assoc. 88, 486–494 (1993).

    Article 

    Google Scholar 

  • 79.

    Zhang, P. Model selection via multifold cross validation. Ann. Statist. 21, 299–313 (1993).

  • 80.

    Team, R. C. R.: A language and environment for statistical computing (2020).


  • Source: Ecology - nature.com

    Taking an indirect path into a bright future

    Sex-biased genes and metabolites explain morphologically sexual dimorphism and reproductive costs in Salix paraplesia catkins