DNA methylation networks underlying mammalian traits

Haghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T. and 170 moreHaghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T., Bors, E. K., Breeze, C. E., Brooke, R. T., Brown, J. L., Carter, G., Caulton, A., Cavin, J. M., Chakrabarti, L., Chatzistamou, I., Chavez, A. S., Chen, H., Cheng, K., Chiavellini, P., Choi, O.-W., Clarke, S., Cook, J. A., Cooper, L. N., Cossette, M.-L., Day, J., DeYoung, J., Dirocco, S., Dold, C., Dunnum, J. L., Ehmke, E. E., Emmons, C. K., Emmrich, S., Erbay, E., Erlacher-Reid, C., Faulkes, C. G., Fei, Z., Ferguson, S. H., Finno, C. J., Flower, J. E., Gaillard, J.-M., Garde, E., Gerber, L., Gladyshev, V. N., Goya, R. G., Grant, M. J., Green, C. B., Hanson, M. B., Hart, D. W., Haulena, M., Herrick, K., Hogan, A. N., Hogg, C. J., Hore, T. A., Huang, T., Izpisua Belmonte, J. C., Jasinska, A. J., Jones, G., Jourdain, E., Kashpur, O., Katcher, H., Katsumata, E., Kaza, V., Kiaris, H., Kobor, M. S., Kordowitzki, P., Koski, W. R., Krützen, M., Kwon, S. B., Larison, B., Lee, S.-G., Lehmann, M., Lemaître, J.-F., Levine, A. J., Li, X., Li, C., Lim, A. R., Lin, D. T. S., Lindemann, D. M., Liphardt, S. W., Little, T. J., Macoretta, N., Maddox, D., Matkin, C. O., Mattison, J. A., McClure, M., Mergl, J., Meudt, J. J., Montano, G. A., Mozhui, K., Munshi-South, J., Murphy, W. J., Naderi, A., Nagy, M., Narayan, P., Nathanielsz, P. W., Nguyen, N. B., Niehrs, C., Nyamsuren, B., O’Brien, J. K., Ginn, P. O., Odom, D. T., Ophir, A. G., Osborn, S., Ostrander, E. A., Parsons, K. M., Paul, K. C., Pedersen, A. B., Pellegrini, M., Peters, K. J., Petersen, J. L., Pietersen, D. W., Pinho, G. M., Plassais, J., Poganik, J. R., Prado, N. A., Reddy, P., Rey, B., Ritz, B. R., Robbins, J., Rodriguez, M., Russell, J., Rydkina, E., Sailer, L. L., Salmon, A. B., Sanghavi, A., Schachtschneider, K. M., Schmitt, D., Schmitt, T., Schomacher, L., Schook, L. B., Sears, K. E., Seifert, A. W., Shafer, A. B. A., Shindyapina, A. V., Simmons, M., Singh, K., Sinha, I., Slone, J., Snell, R. G., Soltanmohammadi, E., Spangler, M. L., Spriggs, M., Staggs, L., Stedman, N., Steinman, K. J., Stewart, D. T., Sugrue, V. J., Szladovits, B., Takahashi, J. S., Takasugi, M., Teeling, E. C., Thompson, M. J., Van Bonn, B., Vernes, S. C., Villar, D., Vinters, H. V., Vu, H., Wallingford, M. C., Wang, N., Wilkinson, G. S., Williams, R. W., Yan, Q., Yao, M., Young, B. G., Zhang, B., Zhang, Z., Zhao, Y., Zhao, P., Zhou, W., Zoller, J. A., Ernst, J., Seluanov, A., Gorbunova, V., Yang, X. W., Raj, K., & Horvath, S. (2023). DNA methylation networks underlying mammalian traits. Science, 381(6658): eabq5693. doi:10.1126/science.abq5693.
INTRODUCTION
Comparative epigenomics is an emerging field that combines epigenetic signatures with phylogenetic relationships to elucidate species characteristics such as maximum life span. For this study, we generated cytosine DNA methylation (DNAm) profiles (n = 15,456) from 348 mammalian species using a methylation array platform that targets highly conserved cytosines.
RATIONALE
Nature has evolved mammalian species of greatly differing life spans. To resolve the relationship of DNAm with maximum life span and phylogeny, we performed a large-scale cross-species unsupervised analysis. Comparative studies in many species enables the identification of epigenetic correlates of maximum life span and other traits.
RESULTS
We first tested whether DNAm levels in highly conserved cytosines captured phylogenetic relationships among species. We constructed phyloepigenetic trees that paralleled the traditional phylogeny. To avoid potential confounding by different tissue types, we generated tissue-specific phyloepigenetic trees. The high phyloepigenetic-phylogenetic congruence is due to differences in methylation levels and is not confounded by sequence conservation.
We then interrogated the extent to which DNA methylation associates with specific biological traits. We used an unsupervised weighted correlation network analysis (WGCNA) to identify clusters of highly correlated CpGs (comethylation modules). WGCNA identified 55 distinct comethylation modules, of which 30 were significantly associated with traits including maximum life span, adult weight, age, sex, human mortality risk, or perturbations that modulate murine life span.
Both the epigenome-wide association analysis (EWAS) and eigengene-based analysis identified methylation signatures of maximum life span, and most of these were independent of aging, presumably set at birth, and could be stable predictors of life span at any point in life. Several CpGs that are more highly methylated in long-lived species are located near HOXL subclass homeoboxes and other genes that play a role in morphogenesis and development. Some of these life span–related CpGs are located next to genes that are also implicated in our analysis of upstream regulators (e.g., ASCL1 and SMAD6). CpGs with methylation levels that are inversely related to life span are enriched in transcriptional start site (TSS1) and promoter flanking (PromF4, PromF5) associated chromatin states. Genes located in chromatin state TSS1 are constitutively active and enriched for nucleic acid metabolic processes. This suggests that long-living species evolved mechanisms that maintain low methylation levels in these chromatin states that would favor higher expression levels of genes essential for an organism’s survival.
The upstream regulator analysis of the EWAS of life span identified the pluripotency transcription factors OCT4, SOX2, and NANOG. Other factors, such as POLII, CTCF, RAD21, YY1, and TAF1, showed the strongest enrichment for negatively life span–related CpGs.
CONCLUSION
The phyloepigenetic trees indicate that divergence of DNA methylation profiles closely parallels that of genetics through evolution. Our results demonstrate that DNA methylation is subjected to evolutionary pressures and selection. The publicly available data from our Mammalian Methylation Consortium are a rich source of information for different fields such as evolutionary biology, developmental biology, and aging.

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Publication type
Journal article
Publication date
2023
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