Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T13:10:36.537Z Has data issue: false hasContentIssue false

DNA methylation profile of liver of mice conceived by in vitro fertilization

Published online by Cambridge University Press:  14 June 2021

Saúl Lira-Albarrán
Affiliation:
Department of Obstetrics and Gynecology and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA94143, USA
Xiaowei Liu
Affiliation:
Department of Obstetrics and Gynecology and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA94143, USA
Seok Hee Lee
Affiliation:
Department of Obstetrics and Gynecology and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA94143, USA
Paolo Rinaudo*
Affiliation:
Department of Obstetrics and Gynecology and Reproductive Sciences, Center for Reproductive Sciences, University of California, San Francisco, CA94143, USA
*
Address for correspondence: Paolo Rinaudo, Department of Obstetrics and Gynecology and Reproductive Sciences, Center for Reproductive Sciences, University of California, 513 Parnassus Avenue, HSW1464E, San Francisco, CA94143, USA. Email: [email protected]

Abstract

Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Luke, B. Pregnancy and birth outcomes in couples with infertility with and without assisted reproductive technology: with an emphasis on US population-based studies. Am J Obstet Gynecol. 2017; 217(3), 270281.CrossRefGoogle ScholarPubMed
Feuer, SK, Camarano, L, Rinaudo, PF. ART and health: clinical outcomes and insights on molecular mechanisms from rodent studies. Mol Hum Reprod. 2013; 19(4), 189204.CrossRefGoogle ScholarPubMed
Chen, M, Heilbronn, LK. The health outcomes of human offspring conceived by assisted reproductive technologies (ART). J Dev Orig Health Dis. 2017; 8(4), 388402.CrossRefGoogle Scholar
Jiang, Z, Wang, Y, Lin, J, Xu, J, Ding, G, Huang, H. Genetic and epigenetic risks of assisted reproduction. Best Pract Res Clin Obstet Gynaecol. 2017; 44, 90104.CrossRefGoogle ScholarPubMed
Vrooman, LA, Bartolomei, MS. Can assisted reproductive technologies cause adult-onset disease? Evidence from human and mouse. Reprod Toxicol. 2017; 68, 7284.CrossRefGoogle ScholarPubMed
Duranthon, V, Chavatte-Palmer, P. Long term effects of ART: What do animals tell us? Mol Reprod Dev. 2018; 85(4), 348368.CrossRefGoogle ScholarPubMed
Ceelen, M, van Weissenbruch, MM, Vermeiden, JP, van Leeuwen, FE, Delemarre-van de Waal, HA. Cardiometabolic differences in children born after in vitro fertilization: follow-up study. J Clin Endocrinol Metab. 2008; 93(5), 16821688.CrossRefGoogle ScholarPubMed
Pontesilli, M, Painter, RC, Grooten, IJ, et al. Subfertility and assisted reproduction techniques are associated with poorer cardiometabolic profiles in childhood. Reprod Biomed Online. 2015; 30(3), 258267.CrossRefGoogle ScholarPubMed
Chen, M, Wu, L, Zhao, J, et al. Altered glucose metabolism in mouse and humans conceived by IVF. Diabetes. 2014; 63(10), 31893198.CrossRefGoogle ScholarPubMed
Scott, KA, Yamazaki, Y, Yamamoto, M, et al. Glucose parameters are altered in mouse offspring produced by assisted reproductive technologies and somatic cell nuclear transfer. Biol Reprod. 2010; 83(2), 220227.CrossRefGoogle ScholarPubMed
Donjacour, A, Liu, X, Lin, W, Simbulan, R, Rinaudo, PF. In vitro fertilization affects growth and glucose metabolism in a sex-specific manner in an outbred mouse model. Biol Reprod. 2014; 90(4), 80.CrossRefGoogle Scholar
Feuer, SK, Liu, X, Donjacour, A, et al. Use of a mouse in vitro fertilization model to understand the developmental origins of health and disease hypothesis. Endocrinology. 2014; 155(5), 19561969.CrossRefGoogle ScholarPubMed
Feuer, SK, Donjacour, A, Simbulan, RK, et al. Sexually dimorphic effect of in vitro fertilization (IVF) on adult mouse fat and liver metabolomes. Endocrinology. 2014; 155(11), 45544567.CrossRefGoogle ScholarPubMed
Sakka, SD, Loutradis, D, Kanaka-Gantenbein, C, et al. Absence of insulin resistance and low-grade inflammation despite early metabolic syndrome manifestations in children born after in vitro fertilization. Fertil Steril. 2010; 94(5), 16931699.CrossRefGoogle ScholarPubMed
Valenzuela-Alcaraz, B, Crispi, F, Bijnens, B, et al. Assisted reproductive technologies are associated with cardiovascular remodeling in utero that persists postnatally. Circulation. 2013; 128(13), 14421450.CrossRefGoogle ScholarPubMed
von Arx, R, Allemann, Y, Sartori, C, et al. Right ventricular dysfunction in children and adolescents conceived by assisted reproductive technologies. J Appl Physiol. 2015; 118(10), 12001206.CrossRefGoogle ScholarPubMed
Watkins, AJ, Platt, D, Papenbrock, T, et al. Mouse embryo culture induces changes in postnatal phenotype including raised systolic blood pressure. Proc Natl Acad Sci USA. 2007; 104(13), 54495454.CrossRefGoogle ScholarPubMed
Reik, W. Stability and flexibility of epigenetic gene regulation in mammalian development. Nature. 2007; 447(7143), 425432.CrossRefGoogle ScholarPubMed
Doherty, AS, Mann, MR, Tremblay, KD, Bartolomei, MS, Schultz, RM. Differential effects of culture on imprinted H19 expression in the preimplantation mouse embryo. Biol Reprod. 2000; 62(6), 15261535.CrossRefGoogle ScholarPubMed
Ruggeri, E, Lira-Albarran, S, Grow, EJ, et al. Sex-specific epigenetic profile of inner cell mass of mice conceived in vivo or by IVF. Mol Hum Reprod. 2020; 26(11), 866878.CrossRefGoogle ScholarPubMed
Nagy, A, Vintersten, K, Behringer, R. Manipulating the Mouse Emrbyo: a Laboratory Manual, 2003. Cold Spring Harbor, New York.Google Scholar
Denomme, MM, McCallie, BR, Parks, JC, Booher, K, Schoolcraft, WB, Katz-Jaffe, MG. Inheritance of epigenetic dysregulation from male factor infertility has a direct impact on reproductive potential. Fertil Steril. 2018; 110(3), 419428.CrossRefGoogle Scholar
Aronesty, E. ea-utils: Command-Line Tools for Processing Biological Sequencing Data, 2011. Expression Analysis, Durham, NC.Google Scholar
Krueger, F, Andrews, SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011; 27(11), 15711572.CrossRefGoogle ScholarPubMed
Langmead, B, Salzberg, SL. Fast gapped-read alignment with Bowtie 2. Nat Meth. 2012; 9(4), 357359.CrossRefGoogle ScholarPubMed
Hansen, KD, Langmead, B, Irizarry, RA. BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biol. 2012; 13(10), R83.CrossRefGoogle ScholarPubMed
Cavalcante, RG, Sartor, MA. annotatr: genomic regions in context. Bioinformatics. 2017; 33(15), 23812383.CrossRefGoogle ScholarPubMed
McLean, CY, Bristor, D, Hiller, M, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010; 28(5), 495501.CrossRefGoogle ScholarPubMed
Bina, M. Imprinted control regions include composite DNA elements consisting of the ZFP57 binding site overlapping MLL1 morphemes. Genomics. 2017; 109(3–4), 265273.CrossRefGoogle ScholarPubMed
Raudvere, U, Kolberg, L, Kuzmin, I, et al. g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res. 2019; 47(W1), W191W198.CrossRefGoogle Scholar
Supek, F, Bosnjak, M, Skunca, N, Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS One. 2011; 6(7), e21800.CrossRefGoogle ScholarPubMed
Ashburner, M, Ball, CA, Blake, JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000; 25(1), 2529.CrossRefGoogle ScholarPubMed
Matys, V, Kel-Margoulis, OV, Fricke, E, et al. TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 2006; 34, D108D110.CrossRefGoogle ScholarPubMed
Karolchik, D, Hinrichs, AS, Furey, TS, et al. The UCSC Table Browser data retrieval tool. Nucleic Acids Res. 2004; 32, D493D496.CrossRefGoogle ScholarPubMed
Karolchik, D, Hinrichs, AS, Kent, WJ. The UCSC genome browser. Curr Protoc Bioinformatics. 2012; 40(1), 14.CrossRefGoogle Scholar
Babak, T, DeVeale, B, Tsang, EK, et al. Genetic conflict reflected in tissue-specific maps of genomic imprinting in human and mouse. Nat Genet. 2015; 47(5), 544549.CrossRefGoogle ScholarPubMed
Colaneri, A, Wang, T, Pagadala, V, et al. A minimal set of tissue-specific hypomethylated CpGs constitute epigenetic signatures of developmental programming. PLoS One. 2013; 8(9), e72670.CrossRefGoogle ScholarPubMed
Kirchner, H, Sinha, I, Gao, H, et al. Altered DNA methylation of glycolytic and lipogenic genes in liver from obese and type 2 diabetic patients. Mol Metab. 2016; 5(3), 171183.CrossRefGoogle ScholarPubMed
Gerdes, P, Richardson, SR, Mager, DL, Faulkner, GJ. Transposable elements in the mammalian embryo: pioneers surviving through stealth and service. Genome Biol. 2016; 17, 100.CrossRefGoogle ScholarPubMed
Lee, E, Iskow, R, Yang, L, et al. Landscape of somatic retrotransposition in human cancers. Science. 2012; 337(6097), 967971.CrossRefGoogle ScholarPubMed
Chuong, EB, Elde, NC, Feschotte, C. Regulatory activities of transposable elements: from conflicts to benefits. Nat Rev Genet. 2017; 18(2), 7186.CrossRefGoogle ScholarPubMed
Scott, EC, Devine, SE. The role of somatic L1 retrotransposition in human cancers. Viruses. 2017; 9(6), 131.CrossRefGoogle ScholarPubMed
Shukla, R, Upton, KR, Munoz-Lopez, M, et al. Endogenous retrotransposition activates oncogenic pathways in hepatocellular carcinoma. Cell. 2013; 153(1), 101111.CrossRefGoogle ScholarPubMed
Schauer, SN, Carreira, PE, Shukla, R, et al. L1 retrotransposition is a common feature of mammalian hepatocarcinogenesis. Genome Res. 2018; 28(5), 639653.CrossRefGoogle ScholarPubMed
Ichiyanagi, K. Epigenetic regulation of transcription and possible functions of mammalian short interspersed elements, SINEs. Genes Genet Syst. 2013; 88(1), 1929.CrossRefGoogle ScholarPubMed
Chappell, G, Kutanzi, K, Uehara, T, et al. Genetic and epigenetic changes in fibrosis-associated hepatocarcinogenesis in mice. Int J Cancer. 2014; 134(12), 27782788.CrossRefGoogle ScholarPubMed
Smith, RL, Soeters, MR, Wust, RCI, Houtkooper, RH. Metabolic flexibility as an adaptation to energy resources and requirements in health and disease. Endocr Rev. 2018; 39(4), 489517.CrossRefGoogle ScholarPubMed
Bar-Tana, J. Type 2 diabetes - unmet need, unresolved pathogenesis, mTORC1-centric paradigm. Rev Endocr Metab Disord. 2020; 21(4), 613629.CrossRefGoogle ScholarPubMed
Esteves, JV, Yonamine, CY, Machado, UF. SLC2A4 expression and its epigenetic regulation as biomarkers for insulin resistance treatment in diabetes mellitus. Biomarkers Med. 2020; 14(6), 413416.CrossRefGoogle ScholarPubMed
Barry, AE, Baldeosingh, R, Lamm, R, et al. Hepatic stellate cells and hepatocarcinogenesis. Front Cell Dev Biol. 2020; 8, 709.CrossRefGoogle ScholarPubMed
Wilson, CL, Mann, DA, Borthwick, LA. Epigenetic reprogramming in liver fibrosis and cancer. Adv Drug Delivery Rev. 2017; 121, 124132.CrossRefGoogle ScholarPubMed
Dhar, D, Baglieri, J, Kisseleva, T, Brenner, DA. Mechanisms of liver fibrosis and its role in liver cancer. Exp Biol Med. 2020; 245(2), 96108.CrossRefGoogle ScholarPubMed
Page, A, Paoli, P, Moran Salvador, E, White, S, French, J, Mann, J. Hepatic stellate cell transdifferentiation involves genome-wide remodeling of the DNA methylation landscape. J Hepatol. 2016; 64(3), 661673.CrossRefGoogle ScholarPubMed
Nikolaou, N, Gathercole, LL, Marchand, L, et al. AKR1D1 is a novel regulator of metabolic phenotype in human hepatocytes and is dysregulated in non-alcoholic fatty liver disease. Metab Clin Exp. 2019; 99, 6780.CrossRefGoogle ScholarPubMed
Pierre, CC, Hercules, SM, Yates, C, Daniel, JM. Dancing from bottoms up - Roles of the POZ-ZF transcription factor Kaiso in Cancer. Biochim Biophys Acta Rev Cancer. 2019; 1871(1), 6474.CrossRefGoogle ScholarPubMed
Chen, Y, Fan, Y, Guo, DY, et al. Study on the relationship between hepatic fibrosis and epithelial-mesenchymal transition in intrahepatic cells. Biomed Pharmacother. 2020; 129, 110413.CrossRefGoogle Scholar
Defossez, PA, Kelly, KF, Filion, GJ, et al. The human enhancer blocker CTC-binding factor interacts with the transcription factor Kaiso. J Biol Chem. 2005; 280(52), 4301743023.CrossRefGoogle ScholarPubMed
Liu, S, Tao, Y. Interplay between chromatin modifications and paused RNA polymerase II in dynamic transition between stalled and activated genes. Biol Rev Camb Philos Soc. 2013; 88(1), 4048.CrossRefGoogle ScholarPubMed
Chen, FX, Smith, ER, Shilatifard, A. Born to run: control of transcription elongation by RNA polymerase II. Nat Rev Mol Cell Biol. 2018; 19(7), 464478.CrossRefGoogle ScholarPubMed
Van Oss, SB, Cucinotta, CE, Arndt, KM. Emerging insights into the roles of the Paf1 complex in gene regulation. Trends Biochem Sci. 2017; 42(10), 788798.CrossRefGoogle ScholarPubMed
Stavraka, C, Blagden, S. The La-Related proteins, a family with connections to cancer. Biomolecules. 2015; 5(4), 27012722.CrossRefGoogle ScholarPubMed
Hancock, ML, Meyer, RC, Mistry, M, et al. Insulin receptor associates with promoters genome-wide and regulates gene expression. Cell. 2019; 177(3), 722736.e22.CrossRefGoogle ScholarPubMed
Roman, AC, Carvajal-Gonzalez, JM, Merino, JM, Mulero-Navarro, S, Fernandez-Salguero, PM. The aryl hydrocarbon receptor in the crossroad of signalling networks with therapeutic value. Pharmacol Ther. 2018; 185, 5063.CrossRefGoogle ScholarPubMed
Girer, NG, Tomlinson, CR, Elferink, CJ. The aryl hydrocarbon receptor in energy balance: the road from dioxin-induced wasting syndrome to combating obesity with ahr ligands. Int J Mol Sci. 2020; 22(1), 49.CrossRefGoogle ScholarPubMed
Lee, JH, Wada, T, Febbraio, M, He, J, Matsubara, T, Lee, MJ, et al. A novel role for the dioxin receptor in fatty acid metabolism and hepatic steatosis. Gastroenterology. 2010; 139(2), 653663.CrossRefGoogle ScholarPubMed
Wang, C, Xu, CX, Krager, SL, Bottum, KM, Liao, DF, Tischkau, SA. Aryl hydrocarbon receptor deficiency enhances insulin sensitivity and reduces PPAR-alpha pathway activity in mice. Environ Health Perspect. 2011; 119(12), 17391744.CrossRefGoogle ScholarPubMed
Shi, Y, Zeng, Z, Yu, J, Tang, B, Tang, R, Xiao, R. The aryl hydrocarbon receptor: an environmental effector in the pathogenesis of fibrosis. Pharmacol Res. 2020; 160, 105180.CrossRefGoogle ScholarPubMed
Andreola, F, Fernandez-Salguero, PM, Chiantore, MV, Petkovich, MP, Gonzalez, FJ, De Luca, LM. Aryl hydrocarbon receptor knockout mice (AHR-/-) exhibit liver retinoid accumulation and reduced retinoic acid metabolism. Cancer Res. 1997; 57(14), 28352838.Google ScholarPubMed
Walisser, JA, Bunger, MK, Glover, E, Bradfield, CA. Gestational exposure of Ahr and Arnt hypomorphs to dioxin rescues vascular development. Proc Natl Acad Sci USA. 2004; 101(47), 1667716682.CrossRefGoogle ScholarPubMed
Carvajal-Gonzalez, JM, Roman, AC, Cerezo-Guisado, MI, Rico-Leo, EM, Martin-Partido, G, Fernandez-Salguero, PM. Loss of dioxin-receptor expression accelerates wound healing in vivo by a mechanism involving TGFbeta. J Cell Sci. 2009; 122, 18231833.CrossRefGoogle ScholarPubMed
Pellicoro, A, Ramachandran, P, Iredale, JP, Fallowfield, JA. Liver fibrosis and repair: immune regulation of wound healing in a solid organ. Nat Rev Immunol. 2014; 14(3), 181194.CrossRefGoogle Scholar
Wang, JN, Li, L, Li, LY, Yan, Q, Li, J, Xu, T. Emerging role and therapeutic implication of Wnt signaling pathways in liver fibrosis. Gene. 2018; 674, 5769.CrossRefGoogle ScholarPubMed
Liu, Z, Wu, X, Zhang, F, et al. AhR expression is increased in hepatocellular carcinoma. J Mol Histol. 2013; 44(4), 455461.CrossRefGoogle ScholarPubMed
Zhang, K, Zhang, YQ, Ai, WB, et al. Hes1, an important gene for activation of hepatic stellate cells, is regulated by Notch1 and TGF-beta/BMP signaling. World J Gastroenterol. 2015; 21(3), 878887.CrossRefGoogle ScholarPubMed
Aimaiti, Y, Yusufukadier, M, Li, W, et al. TGF-beta1 signaling activates hepatic stellate cells through Notch pathway. Cytotechnology. 2019; 71(5), 881891.CrossRefGoogle ScholarPubMed
Mayran, A, Drouin, J. Pioneer transcription factors shape the epigenetic landscape. J Biol Chem. 2018; 293(36), 1379513804.CrossRefGoogle ScholarPubMed
Wang, L, Tong, X, Gu, F, et al. The KLF14 transcription factor regulates hepatic gluconeogenesis in mice. J Biol Chem. 2017; 292(52), 2163121642.CrossRefGoogle ScholarPubMed
Yang, Q, Civelek, M. Transcription Factor KLF14 and Metabolic Syndrome. Front Cardiovasc Med. 2020; 7, 91.CrossRefGoogle ScholarPubMed
Braccini, L, Ciraolo, E, Campa, CC, et al. PI3K-C2gamma is a Rab5 effector selectively controlling endosomal Akt2 activation downstream of insulin signalling. Nat Commun. 2015; 6, 7400.CrossRefGoogle ScholarPubMed
Daimon, M, Sato, H, Oizumi, T, et al. Association of the PIK3C2G gene polymorphisms with type 2 DM in a Japanese population. Biochem Biophys Res Commun. 2008; 365(3), 466471.CrossRefGoogle Scholar
Haydar, S, Grigorescu, F, Vintila, M, et al. Fine-scale haplotype mapping of MUT, AACS, SLC6A15 and PRKCA genes indicates association with insulin resistance of metabolic syndrome and relationship with branched chain amino acid metabolism or regulation. PloS one. 2019; 14(3), e0214122.CrossRefGoogle ScholarPubMed
Bock, C, Tomazou, EM, Brinkman, AB, et al. Quantitative comparison of genome-wide DNA methylation mapping technologies. Nat Biotechnol. 2010; 28(10), 11061114.CrossRefGoogle ScholarPubMed
Conner, EA, Lemmer, ER, Omori, M, Wirth, PJ, Factor, VM, Thorgeirsson, SS. Dual functions of E2F-1 in a transgenic mouse model of liver carcinogenesis. Oncogene. 2000; 19(44), 50545062.CrossRefGoogle Scholar
Supplementary material: File

Lira-Albarrán et al. supplementary material

Lira-Albarrán et al. supplementary material

Download Lira-Albarrán et al. supplementary material(File)
File 4.1 MB