Medicine, Faculty of
Medical Genetics, Department of
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UBCV
Ha, Amanda
Doctor of Philosophy - PhD
University of British Columbia
Genomic imprinting is an epigenetic phenomenon by which the expression of certain genes follows a parent-of-origin-specific pattern. The sub-proximal end of mouse Chr 6 contains an imprinted domain comprised of the paternally expressed gene Mest, and the maternally expressed genes Copg2 and Klf14. The Mest locus harbors the only gametic differentially methylated region (gDMR) in the region, which may act as an Imprinting Control Region for the coordinated regulation of these three imprinted genes. The Mest-Klf14 imprinted domain shares syntenic homology with human Chr 7q32. Therefore, loss of Mest function, or Klf14 overexpression may contribute to the maternal uniparental disomy 7 (mUPD7) growth retardation phenotype associated with Sliver- Russell syndrome (SRS). Here, I investigate the function of Mest, and its gDMR. In Chapter 3, I leveraged a previously generated Mest KO mouse line to characterize the function of Mest in developmental pathways. Embryonic growth retardation observed in Mest KO mice was independent of gross placental abnormalities in vivo, but associated with altered Wnt signalling in cell assays. Based on additional proteomic and metabolomic characterization, I hypothesize that the putative epoxide hydrolase, known as MEST, acts upon metabolites within the endoplasmic reticulum lumen. In Chapter 4, I explored the function of the Mest gDMR. While the imprinted regulation of both Mest and Copg2 has been well documented, the mechanism of Klf14 imprinting is unknown. Klf14 expression is lost in embryos lacking maternal methylation iii genome-wide, indicating that maternally-inherited DNA methylation (DNAme) is paradoxically required for its expression. Through CRISPR-Cas9 mutagenesis and allele-specific chromosome conformation experiments in F1 embryonic stem cells, I demonstrate that the Mest gDMR regulates imprinting of Klf14 through long-range chromatin looping, permitting differential promoter-enhancer interactions between parental alleles. I propose a model whereby CTCF binding to the unmethylated paternal Mest gDMR structures paternal allele-specific sub-TADs required for Klf14 silencing. Altogether, my results illustrate both the function and mechanisms regulating imprinting at the Mest-Klf14 imprinted domain which may impact the management of patients with Silver-Russell or metabolic syndromes.
FUNCTIONAL CHARACTERIZATION OF MEST AND ITS IMPRINTED GAMETIC DIFFERENTIALLY METHYLATED REGION by Amanda Ha B.Sc., The University of Victoria, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2022 © Amanda Ha, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Functional characterization of Mest and its imprinted gametic differentially methylated region submitted by Amanda Ha in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Medical Genetics Examining Committee: Dr. Louis Lefebvre, Associate Professor, Medical Genetics, UBC Supervisor Dr. Carolyn Brown, Professor, Medical Genetics, UBC Supervisory Committee Member Dr. LeAnn Howe, Professor, Biochemistry and Molecular Biology, UBC University Examiner Dr. Wendy Robinson, Professor, Medical Genetics, UBC University Examiner Dr. Marisa Bartolomei, Professor, Cell and Developmental Biology, University of Pennsylvania External Examiner Additional Supervisory Committee Members: Dr. T. Michael Underhill, Professor, Cellular and Physiological Science, UBC Supervisory Committee Member Dr. Pamela Hoodless, Professor, Medical Genetics, UBC Supervisory Committee Member iii Abstract Genomic imprinting is an epigenetic phenomenon by which the expression of certain genes follows a parent-of-origin-specific pattern. The sub-proximal end of mouse Chr 6 contains an imprinted domain comprised of the paternally expressed gene Mest, and the maternally expressed genes Copg2 and Klf14. The Mest locus harbors the only gametic differentially methylated region (gDMR) in the region, which may act as an Imprinting Control Region for the coordinated regulation of these three imprinted genes. The Mest-Klf14 imprinted domain shares syntenic homology with human Chr 7q32. Therefore, loss of Mest function, or Klf14 overexpression may contribute to the maternal uniparental disomy 7 (mUPD7) growth retardation phenotype associated with Sliver-Russell syndrome (SRS). Here, I investigate the function of Mest, and its gDMR. In Chapter 3, I leveraged a previously generated Mest KO mouse line to characterize the function of Mest in developmental pathways. Embryonic growth retardation observed in Mest KO mice was independent of gross placental abnormalities in vivo, but associated with altered Wnt signalling in cell assays. Based on additional proteomic and metabolomic characterization, I hypothesize that the putative epoxide hydrolase, known as MEST, acts upon metabolites within the endoplasmic reticulum lumen. In Chapter 4, I explored the function of the Mest gDMR. While the imprinted regulation of both Mest and Copg2 has been well documented, the mechanism of Klf14 imprinting is unknown. Klf14 expression is lost in embryos lacking maternal methylation iv genome-wide, indicating that maternally-inherited DNA methylation (DNAme) is paradoxically required for its expression. Through CRISPR-Cas9 mutagenesis and allele-specific chromosome conformation experiments in F1 embryonic stem cells, I demonstrate that the Mest gDMR regulates imprinting of Klf14 through long-range chromatin looping, permitting differential promoter-enhancer interactions between parental alleles. I propose a model whereby CTCF binding to the unmethylated paternal Mest gDMR structures paternal allele-specific sub-TADs required for Klf14 silencing. Altogether, my results illustrate both the function and mechanisms regulating imprinting at the Mest-Klf14 imprinted domain which may impact the management of patients with Silver-Russell or metabolic syndromes. v Lay Summary In placental mammals, some genes are expressed only when inherited from the mother or father. These “imprinted genes” are associated with rare developmental syndromes, and play different roles during development. This thesis aims to expand upon our understanding of both the function and regulation of the locus encompassing the paternally expressed gene Mest and the maternally expressed gene Klf14. Using the mouse as a model system, I have shown that Mest plays a role in regulating embryonic growth independent of placental defects. Furthermore, I show that parental allele-specific DNA methylation at the Mest locus is responsible for controlling the imprinting of Klf14 through long-range DNA looping. Taken together, my work deepens our understanding of the function of imprinted genes and also brings insight on the broader aspects of gene regulation. vi Preface The experiments reported in this thesis were designed in collaboration with the supervisor, Dr. Louis Lefebvre, and conducted by the candidate. The candidate was the major contributor to data collection, data analysis, and manuscript writing. Work performed by collaborators is indicated. Animal studies were reviewed and approved by the University of British Columbia Committee on Animal Care under protocols A13-0115, A15-0181, A15-0291, and A19-0209. Chapter 3 The candidate, Amanda Ha, participated in the study design, performed the experiments, and generated the figures. Metabolomics was performed by the BC Children’s Hospital Research Center, Analytical core for Metabolomics and Nutrition (AcMaN). Mass spectrometry analysis was performed in collaboration with the Overall lab at UBC. Chapter 4 Amanda Ha participated in the study design, performed the experiments, and generated the figures. Amanda Ha, Louis Lefebvre, and Aaron Bogutz wrote the manuscript with input from Daan Noordermeer (DN) and Benoit Moindrot (BM). The 4C-seq methodology was developed by DN and BM, who helped AH to establish this technique vii at UBC. Allele-specific CTCF ChIP-seq, and 4C-seq from the Mest gDMR viewpoint were performed by BM. viii Table of Contents Abstract .......................................................................................................................... iii Lay Summary .................................................................................................................. v Preface ........................................................................................................................... vi Table of Contents ........................................................................................................ viii List of Tables ............................................................................................................... xiii List of Figures .............................................................................................................. xiv List of Abbreviations .................................................................................................... xv Acknowledgements .................................................................................................... xvii Dedication .................................................................................................................... xix Chapter 1: Introduction .................................................................................................. 1 1.1 Historical overview of genomic imprinting .......................................................... 1 1.2 Evolutionary history of imprinting ....................................................................... 3 1.3 DNA methylation ................................................................................................ 4 1.4 Chromatin architecture ....................................................................................... 6 1.5 Mechanisms of imprinted gene regulation by gametic DMRs ............................ 8 1.5.1 DNA methylation ......................................................................................... 9 1.5.2 Non-coding RNA-mediated silencing ........................................................ 11 1.5.3 Insulator functions ..................................................................................... 12 1.5.4 Allele-specific looping ............................................................................... 13 1.6 Sub-proximal Mmu6 imprinting domain ........................................................... 14 ix 1.6.1 Regulation of imprinting in the Mest-Klf14 domain ................................... 14 1.6.2 Mest .......................................................................................................... 18 1.6.3 Mest KO mouse models ............................................................................ 18 1.6.4 miR-335 .................................................................................................... 21 1.6.5 Copg2 ....................................................................................................... 22 1.6.6 Klf14 .......................................................................................................... 23 1.6.7 Klf14 KO mouse models ........................................................................... 23 1.6.8 Human homology and disease ................................................................. 25 1.6.8.1 Silver-Russell syndrome .................................................................... 26 1.6.8.2 Metabolic disorders ............................................................................ 28 1.7 Mouse placenta ................................................................................................ 29 1.7.1 Imprinted genes in the mouse placenta .................................................... 30 1.8 Wnt signaling.................................................................................................... 33 1.9 Mest regulation of Wnt signaling ...................................................................... 35 1.10 Thesis theme and objectives ........................................................................... 36 Chapter 2: Materials and Methods .............................................................................. 38 2.1 Mouse strains ................................................................................................... 38 2.2 Polymerase chain reaction ............................................................................... 38 2.3 Genotyping ....................................................................................................... 38 2.4 Dissections and fixations ................................................................................. 39 2.5 Hematoxylin and eosin staining ....................................................................... 40 2.6 Morphometric analysis ..................................................................................... 40 x 2.7 Immunohistochemistry ..................................................................................... 41 2.8 In situ hybridization .......................................................................................... 42 2.9 Periodic-acid Schiff staining ............................................................................. 42 2.10 RNA-seq ........................................................................................................... 42 2.11 Metabolomic analysis ....................................................................................... 43 2.12 Derivation of mouse embryonic fibroblasts ...................................................... 43 2.13 Derivation of mouse embryonic stem cells ...................................................... 44 2.14 RNA extraction ................................................................................................. 46 2.15 Reverse transcription ....................................................................................... 47 2.16 Quantitative RT-PCR ....................................................................................... 47 2.17 TOPFlash Assay .............................................................................................. 48 2.18 Episomal system for MEST expression ........................................................... 48 2.19 Western blot ..................................................................................................... 50 2.20 MEST peptide preparation for MS ................................................................... 51 2.21 MEST GFP fusions .......................................................................................... 52 2.22 Split-GFP .......................................................................................................... 52 2.23 Coverslip fixation and processing .................................................................... 53 2.24 Generation of Mest gDMR KO ......................................................................... 54 2.25 SNP Pyrosequencing ....................................................................................... 54 2.26 Vascular progenitor cell differentiation ............................................................. 55 2.27 FACs and flow cytometry ................................................................................. 55 2.28 4C viewpoint design ......................................................................................... 56 xi 2.29 4C sample preparation ..................................................................................... 56 2.30 4C-seq library preparation and sequencing ..................................................... 57 2.31 4C-seq data analysis ....................................................................................... 58 2.32 Allele-specific RNA-seq and ChIP-seq analysis .............................................. 59 2.33 CTCF motif discovery ....................................................................................... 59 Chapter 3: Characterization of MEST function .......................................................... 62 3.1 Background ...................................................................................................... 62 3.2 Results ............................................................................................................. 63 3.2.1 Mest is not required for placental development ........................................ 63 3.2.1.1 Mest deficiency is not associated with abnormal triglyceride levels in the placenta ......................................................................................................... 71 3.2.2 Mest deficiency has minor effects on placental metabolism ..................... 73 3.2.3 Mest is a Wnt inhibitor ............................................................................... 78 3.2.4 MEST as a putative epoxide hydrolase .................................................... 81 3.2.5 Characterization of MEST topology within the ER .................................... 86 3.3 Discussion ........................................................................................................ 95 3.4 Conclusion ..................................................................................................... 100 Chapter 4: Characterization of the mechanism driving Klf14 imprinting .............. 101 4.1 Background .................................................................................................... 101 4.2 Results ........................................................................................................... 102 4.2.1 Developmental dynamics of imprinted Klf14 expression ........................ 102 4.2.2 Chromosome topology of the Mest-Klf14 locus ...................................... 105 xii 4.2.3 Loss of Klf14 imprinting upon deletion of the Mest gDMR ...................... 111 4.2.4 The Mest gDMR is essential for paternal sub-TADs organization .......... 114 4.3 Discussion ...................................................................................................... 118 4.4 Conclusion ..................................................................................................... 122 Chapter 5: Discussion ................................................................................................ 123 5.1 Major findings ................................................................................................. 123 5.2 Comparison with other mouse models ........................................................... 124 5.3 Significance of imprinting at the Mest locus ................................................... 127 5.4 Evolutionary conservation .............................................................................. 128 5.5 Future directions ............................................................................................ 131 5.6 Final remarks ................................................................................................. 133 References .................................................................................................................. 135 Appendices ................................................................................................................. 166 Appendix A Supplementary materials for Chapter 3 ................................................. 166 Appendix B Supplementary materials for Chapter 4 ................................................. 172 xiii List of Tables Table 2.1 Chromosome count and sex of Mest WT and pKO ESC lines ....................... 45 Table 2.2 Chromosome count and sex of new F1 ESC lines ......................................... 46 Table 2.3 Mest imprinting in F1 ESCs ............................................................................ 46 Table A.1 Significantly upregulated genes in the Mest pKO E17.5 placentae, compared to Mest WT. .................................................................................................................. 166 Table A.2 Significantly downregulated genes in the Mest pKO E17.5 placentae, compared to WT. .......................................................................................................... 167 Table A.3 Qualitative enrichment of dysregulated metabolite groups in male WT and pKO E17.5 placenta ..................................................................................................... 168 Table A.4 Qualitative enrichment of dysregulated lipid groups in male WT and pKO E17.5 placenta ............................................................................................................. 169 Table A.5 Qualitative enrichment of dysregulated metabolite groups in female WT and pKO E17.5 placenta ..................................................................................................... 170 Table A.6 Qualitative enrichment of dysregulated lipid groups in female WT and pKO E17.5 placenta ............................................................................................................. 171 Table B.1 Datasets used in this study .......................................................................... 172 xiv List of Figures Table 2.1 Chromosome count and sex of Mest WT and pKO ESC lines ....................... 45 Table 2.2 Chromosome count and sex of new F1 ESC lines ......................................... 46 Table 2.3 Mest imprinting in F1 ESCs ............................................................................ 46 Table A.1 Significantly upregulated genes in the Mest pKO E17.5 placentae, compared to Mest WT. .................................................................................................................. 166 Table A.2 Significantly downregulated genes in the Mest pKO E17.5 placentae, compared to WT. .......................................................................................................... 167 Table A.3 Qualitative enrichment of dysregulated metabolite groups in male WT and pKO E17.5 placenta ..................................................................................................... 168 Table A.4 Qualitative enrichment of dysregulated lipid groups in male WT and pKO E17.5 placenta ............................................................................................................. 169 Table A.5 Qualitative enrichment of dysregulated metabolite groups in female WT and pKO E17.5 placenta ..................................................................................................... 170 Table A.6 Qualitative enrichment of dysregulated lipid groups in female WT and pKO E17.5 placenta ............................................................................................................. 171 Table B.1 Datasets used in this study .......................................................................... 172 xv List of Abbreviations 4C circular chromosome conformation capture ChIP chromatin immunoprecipitation Chr chromosome CNS central nervous system CpG cytosine-phosphate-guanidine dinucleotide CRISPR clustered regularly interspaced short palindromic repeats CTCF CCCTC binding factor DNA deoxyribonucleic acid DNAme DNA methylation DNMT DNA methyltransferase EH epoxide hydrolase ER endoplasmic reticulum ESC embryonic stem cell FACs fluorescence activated cell sorting gDMR gametic differentially methylated region H3K27me3 trimethylation of histone H3 at lysine 27 H3K4me3 trimethylation of histone H3 at lysine 4 H3K9me3 trimethylation of histone H3 at lysine 9 ICM inner cell mass ICR imprinting control region ISH in situ hybridization KO knockout lncRNA long noncoding RNA MEF mouse embryonic fibroblast mKO maternal knockout (KO/+) MS mass spectrometry ORF open reading frame PAS Periodic acid Schiff PBS phosphate-buffered saline PCR polymerase chain reaction pKO paternal knockout (+/KO) qRT-PCR quantitative reverse transcription polymerase chain reaction RNA ribonucleic acid sDMR somatic differentially methylated region shRNA short hairpin RNA SNP single nucleotide polymorphism SRS Silver-Russell syndrome xvi TAD topologically associated domain UPD uniparental disomy UTR untranslated region VP vascular progenitor WT wildtype xvii Acknowledgements Over the course of my degree, I have had the privilege to work with, and learn from many talented scientists. I am eternally grateful to my supervisor Dr. Louis Lefebvre for his invaluable mentorship and investment into my academic and personal growth. Thank you for providing me the intellectual environment to develop as a researcher. I would also like to thank my committee members: Dr. Michael Underhill, Dr. Carolyn Brown, and Dr. Pamela Hoodless for their thoughtful advice and feedback throughout my studies. I would like to thank the former and current members of the Lefebvre Lab: Aaron Bogutz, Rochelle Szeto, Sherry Fang, Kai-Wei Chang, and Nolan Ashworth who have truly made my PhD experience memorable and fun. I owe particular thanks to Aaron for his patience and advocacy over the years. He is an exceptional mentor, and truly went above and beyond for me. I also thank my colleagues in the Molecular Epigenetics Group, particularly the Brown and Lorincz labs, who have shared with me their technical expertise, and made my time in the lab so enjoyable. Special thanks to Samantha Peeters, Riley Horvath, Thomas Dixon-McDougall, Bradley Balaton, Christine Yang, James Kwan, Thomas Nguyen, Julien Richard Albert, Julie Brind’Amour, Kris Jensen, Kenjiro Shirane, Kentaro Mochizuki, and Stanley Zhou. xviii Thanks to my partner Brandon, for his constant support and encouragement. To my extended family, including the Vans, thank you for your hospitality and compassion. To Arcadia, thank you for sparking my lifelong passion for learning. Finally, to my family: John, Jun, and Ryan thank you for your unwavering love and support, and for always encouraging me to pursue my passions. xix Dedication To my parents, 1 Chapter 1: Introduction 1.1 Historical overview of genomic imprinting The theory of genomic imprinting in mammals first arose from studies in the early 1980s demonstrating that the maternal and paternal genomes were not functionally equivalent during mouse development (Surani et al. 1986, 1984; Barton et al. 1984; McGrath and Solter 1984). Pronuclear transfer experiments were used to generate gynogenetic (two maternal copies) and androgenetic (two paternal copies) conceptuses. The resulting mouse embryos did not survive to term, and displayed somewhat opposing phenotypes. Gynogenetic conceptuses were capable of developing up until the 25-somite stage, but failed to develop extraembryonic lineages. Conversely, androgenetic conceptuses were capable of developing extra-embryonic tissues but had underdeveloped embryos (Surani et al. 1984). These experiments demonstrated that despite identical genomic sequence, maternal and paternal genomes differed in their potential for embryonic and extraembryonic development. It was proposed that retention of a “genomic imprint” on parental genomes following fertilization was required for embryogenesis. Parent-of-origin effects were also observed in recombination-based models in the 1980s. Robertsonian translocations, describing the fusion of two acrocentric chromosomes resulting in full chromosomal uniparental disomy (UPD), identified entire chromosomes responsible for parent-of-origin effects (Cattanach and Kirk 1985; Searle and Beechey 1982). For example, Robertsonian translocations involving chromosomes 2 11 and 13 were associated with parent-of-origin effects on fetal growth with mUPD11 associated with smaller mice, while pUPD11 resulted in larger mice (Cattanach and Kirk 1985). Combined with reciprocal translocations involving non-homologous chromosomes generating UPDs of chromosomal fragments, specific regions on mouse chromosomes 2, 6, 7, 8, and 17 were identified with having parent-of-origin-specific effects (Cattanach 1986; Cattanach and Kirk 1985). Based on these experiments, it was theorized that parent-of-origin specific expression of genes within these regions were involved, rather than entire chromosomes. These foundational experiments on Robertsonian and reciprocal translocations would be used to generate a non-complementation map (Searle and Beechey 1978), a precursor to the current mouse imprinting map (Williamson CM, Blake A, Thomas S, Beechey CV, Hancock J, Cattanach BM 2013). The first imprinted genes, transcribed from only one parental allele, were identified in 1991: Insulin-like growth factor 2 receptor (Igf2r) , insulin-like growth factor 2 (Igf2), and H19 (Barlow et al. 1991; Barton et al. 1991; DeChiara et al. 1991; Ferguson-Smith et al. 1991; Bartolomei et al. 1991). Loss of paternal Igf2 or maternal Igf2r resulted in reciprocal growth phenotypes: loss of Igf2 is associated with growth retardation whereas loss of Igf2r promotes growth. Since then, more than 200 imprinted genes have been identified in the mouse and human, of which 63 are common to both species (Tucci et al. 2019). 3 1.2 Evolutionary history of imprinting Genomic imprinting has only been described in therian mammals, including placental mammals (eutheria) and marsupials, which have short-lived placentas (metatheria). Monotremes, egg laying mammals, show no evidence of genomic imprinting to date, despite having regions orthologous to eutherian imprinted domains. Notably, only six imprinted genes have been identified in marsupials so far, also shared by both human and mice (Renfree et al. 2013). These observations indicate that genomic imprinting might be less common within marsupials, suggesting that acquisition of imprinting may be correlated with viviparity and extensive maternal-fetal nutrient exchange. Multiple theories have been proposed to explain how genomic imprinting evolved. The parental conflict theory suggests that genomic imprinting arose to balance maternal and fetal growth (Moore and Haig 1991). Most mammals are non-monogamous, where the father may not be related to the progeny of the female. Therefore, distributing resources across current and future pregnancies would promote maternal reproductive fitness while having robust offspring would increase paternal reproductive fitness. Several imprinted genes fit within this parental conflict dogma. Accordingly, some maternally expressed genes restrict placental and fetal growth (ex. Grb10, Igf2r, Phlda2, Cdkn1c), while some paternally expressed genes increase demand on maternal resources to enhance placental and fetal growth (ex. Mest, Igf2, Peg10) (Wilkins & Haig 2003). A second popular theory, the host defense model, proposes that genomic imprinting evolved from the host-defense mechanism utilized to silence foreign DNA 4 elements (Barlow 1993). This theory is supported by the observation that some imprinted genes arose through retrotransposition. Imprinted retrotransposed genes broadly fall into three categories: retrotransposon-like, X-chromosome derived (retro-genes), and autosomal derived. Peg10 is an example of a retrotransposon-like paternally expressed gene derived from a transposon (Suzuki et al. 2007). Nap1l5 and U2af1-rs1/Zrsr1 are examples of imprinted retrogenes (Mccole et al. 2011). Klf14 is an example of an intronless transposed copy of an autosomal gene (Parker-Katiraee et al. 2007). DNA methylation is the common mechanism underlying both host defense silencing of foreign elements, and genomic imprinting, thus implicating a co-opting of epigenetic machinery. For example, ZFP57 belongs to a family of KRAB Zn-finger proteins involved in both the host defense mechanisms and in the maintenance of DNA methylation at most gametic differentially methylated regions (gDMRs) during post fertilization epigenetic reprogramming (Strogantsev et al. 2015). Notably, some genes may also have become imprinted as a “bystander” in the evolution of an imprinted domain. In other words, some genes were affected by the imprinting mechanism due to their proximity to another imprinted gene(Varmuza and Mann 1994). 1.3 DNA methylation As parent-of-origin effects associated with imprinting could not be attributed to genetics, genomic imprinting was considered an epigenetic phenomenon. Shortly after the discovery of the first imprinted genes, allele-specific DNA methylation (DNAme) was observed at H19, implicating DNAme as a regulator of imprinted expression (Ferguson- 5 Smith et al. 1993; Bartolomei et al. 1993). The DNA methyltransferase DNMT1 was later identified as required for the maintenance of imprinted expression at H19, Igf2, and Igf2r (Li et al. 1993). DNA methyltransferases (DNMTs) are a class of enzymes responsible for catalyzing the addition of a methyl group on the 5’ carbon of cytosines at 5’-cytosine-guanine-3’ (CpG) dinucleotides. DNAme in promoter regions is associated with epigenetic transcriptional silencing through inhibiting transcription factor accessibility or blocking transcriptional machinery (Yin et al. 2017; Rose and Klose 2014). Maintenance methyltransferases such as DNMT1, and its co-factor UHRF1/NP95 (Sharif et al. 2007), maintain methylation following DNA replication by recognizing hemi-methylated DNA, whereas de novo DNMTs establish methylation in the absence of prior methylation and include DNMT3A, 3B, 3C, and the non-catalytic cofactor DNMT3L. The action of DNMTs correlate with the establishment and maintenance of DNAme during the two waves of epigenetic remodeling during mouse development. Following fertilization, the genome undergoes a wave of global DNA demethylation whereas imprinted gametic differentially methylated regions (gDMRs) are maintained. In this thesis, we refer to these specific imprinted regions, acquiring DNAme from one gamete and maintained throughout development, as the gDMRs. Following implantation, DNAme is re-established de novo by DNMT3A, and 3B. At E11.5 the second wave of DNA demethylation, including at gDMRs, occurs within gonadal primordial germ cells, allowing for the resetting of epigenetic marks and subsequent re- 6 establishment of de novo germline methylation in an oocyte- or sperm-specific manner, mediated by DNMT3A, and 3L (Kaneda et al. 2004; Bourc’his et al. 2001). Unique to the female germline is DNMT1o, an oocyte-specific isoform. Lack of maternal DNMT1o has been associated with normal imprinting in oocytes, but abnormal imprinting in conceptuses, suggesting a failure in imprinting maintenance in the preimplantation embryo (Howell et al. 2001). Additionally, Dnmt1o KO placentae present with gross abnormalities involving elevated triglycerides, and abnormal lipid metabolism attributed to dysregulation of imprinted genes (Himes et al. 2015). Notably, of 20 gDMRs analyzed, loss of methylation at the Mest gDMR was most highly associated with the elevated triglyceride phenotype in those mutant placentae. 1.4 Chromatin architecture The genome is organized into topologically associating domains (TADs), megabase sized domains with preferential local contacts (Dixon et al. 2012; Nora et al. 2012). TADs represent the average of frequencies in interactions within a population, often encompassing several million cells. At the single-cell level, chromatin loops are dynamic and variable. As such, rare chromatin loops are not represented by TAD structures but may be resolved as sequencing resolution increases. TADs are largely invariant between different cell-types, but intra-TAD interactions, such as those between promoters and enhancers, may be dynamic and tissue-specific (Bonev et al. 2017). TAD boundaries are defined by regions where the probability of directional interactions 7 drops. These borders are not strict physical borders, are dynamic through development, and are enriched for architectural proteins such as CTCF and cohesin (Bonev et al. 2017; Dixon et al. 2012; Rao et al. 2017). According to the loop extrusion model, chromatin is propelled through the ring-like cohesin complex until stalled by CTCF, resulting in the formation of loops (Fudenberg et al. 2016; Sanborn et al. 2015). TAD boundaries often coincide with regulatory domains, with promoter-enhancer interactions limited to the TAD. Furthermore, the majority of TAD boundaries are conserved between mouse and human (Rao et al. 2014). Based on these observations, TADs have been proposed as both a structural and regulatory unit of the genome. However, the exact function of TADs in gene regulation is contested and it remains to be determined how TAD architecture defines transcription (reviewed: Oudelaar & Higgs 2021). Nevertheless, disruptions in TAD architecture are associated with dysregulation of enhancer-promoter interactions, and misexpression (Paliou et al. 2019; Lupiáñez et al. 2015). Conversely, there have also been reports observing only mild transcriptional changes upon TAD disruption. For example, targeted manipulations of CTCF binding sites at the Shh (Williamson et al. 2019), Sox9–Kcnj2 (Despang et al. 2019), and HoxD (Rodríguez-Carballo et al. 2020) loci demonstrated the robustness of transcription against disruptions to TAD organization. Shh is adjacent to two CTCF binding sites in ESCs, defining a TAD. Independent deletions of these two CTCF binding sites (~ 1kb) was associated with perturbations in TAD structure, and changes in enhancer-promoter proximity in ESC, but did not translate to changes in Shh 8 transcription in vitro. Furthermore, global depletions of architectural proteins CTCF (Nora et al. 2017), and cohesin (Rao et al. 2017) in ESC affects transcription of only a small subset of genes. It is unknown why some TAD boundaries have a stronger effect on transcription than others. Altogether, these observations suggest that the relationship between transcription, regulation, and TAD architecture may be context dependent, and remains a topic for future research. 1.5 Mechanisms of imprinted gene regulation by gametic DMRs Imprinted genes are not randomly distributed throughout the genome, but are found in clusters, suggesting that they are co-regulated. An element regulating the imprinting of two or more genes is called an imprinting control region (ICR) (Spahn and Barlow 2003). ICRs are typically short CpG-rich sequences differentially methylated between parental genomes, and these DNAme differences are classified as either a gametic (gDMR) or somatic/secondary DMR (sDMR). DNAme at gDMRs originates directly from the sperm or egg, while sDMRs are established after fertilization and may be tissue-specific. Canonical genomic imprinting is mediated by DNAme, and is distinct from non-canonical imprinting, which is mediated by maternal H3K27me3 (Hanna & Kelsey 2021). In the mouse genome, there are 23 maternally methylated gDMRs and 3 paternally methylated gDMRs (Andergassen et al. 2017; Stewart et al. 2016). The maternal gDMRs are all located at promoter-proximal CpG islands of imprinted genes, 9 whereas paternal gDMR are located within intergenic regions (Schulz et al. 2010). In addition to DNA methylation, ICRs may also harbor allele-specific histone modifications. While the active parental allele is marked with H3K4me3 in expressing cells, the inactive allele is often marked with H3K9me3 and/or H4K20me3 (McEwen and Ferguson-Smith 2010) 1.5.1 DNA methylation DNAme over an ICR encompassing a promoter CpG island is a classic mechanism of imprinted gene regulation. For example, the Mest gDMR overlapping the Mest promoter is methylated in oocytes, and hypomethylated in the sperm (Lefebvre et al. 1998; Lucifero et al. 2002)(Figure 1.1A). Upon fertilization, DNAme is maintained in an allele-specific manner, permitting expression of only the unmethylated paternal allele of Mest. Aside from DNAme over the ICR (Figure 1.1A), epigenetic mechanisms implicated in the regulation of imprinting include allele-specific histone modifications (Lewis et al. 2004), non-coding RNA-mediated silencing (Figure 1.1B) (Fitzpatrick et al. 2002), and insulator functions (Figure 1.1C). 10 Figure 1.1 Mechanisms regulating genomic imprinting A) Allele-specific promoter methylation at CpG dinucleotides directs imprinted expression of only the hypomethylated Mest allele. At Mest, the gDMR is maternally methylated and overlaps exon 1. B) Long non-coding RNA mediated epigenetic silencing regulates Kcnq1 and Cdkn1c within the IC2 domain. IC2 overlaps the promoter of the lncRNA Kcnq1ot1. Maternal methylation of IC2 blocks Kcnq1ot1 expression and thus permits the expression of Kcnq1, Cdkn1c and other protein-coding genes in the region. Paternal hypomethylation of IC2 permits expression of Kcnq1ot1 only, which subsequently silences the neighboring Cdkn1c and Kcnq1 genes in cis. C) Formation of a DNA methylation-sensitive insulator at IC1. The intergenic IC1 (H19 DMR) is paternally methylated. The unmethylated maternal allele binds CTCF, creating an insulator or maternal-specific sub-TAD, occluding Igf2 from its enhancers but allowing enhancer interaction with H19. On the methylated paternal allele, methylation 11 occludes CTCF binding to permit Igf2-enhancer interaction. H19 is silenced via spread of paternal methylation from IC1, generating a sDMR at the H19 promoter. Active genes are represented as colored boxes, and silent genes are represented as grey boxes. White and black lollipops represent unmethylated and methylated CpG islands. Blue pentagons represent CTCF. Green boxes represent DMRs. M: maternal allele, P: paternal allele. 1.5.2 Non-coding RNA-mediated silencing Silencing by lncRNAs occurs through recruitment of chromatin regulators leading to repressive modifications, or transcriptional interference (Pauler et al. 2007). The majority of imprinted clusters contain at least one lncRNA (Barlow and Bartolomei 2014), with some acting in cis to silence neighboring genes. This mechanism is reminiscent of Xist lncRNA mediated X-chromosome inactivation, thus implicating a co-opting of this mechanism in the regulation of some imprinted clusters. For example, the lncRNA Kcnq1ot1 at the Kcnq1 imprinting domain on mouse chromosome 7 is regulated by maternal-specific methylation over IC2 (KvDMR1), located within intron 10 of the Kcnq1 gene (Mancini-DiNardo et al. 2006; Umlauf et al. 2004; Fitzpatrick et al. 2002). This gDMR overlaps the promoter of the lncRNA, thereby allowing for only paternal expression of Kcnq1ot1 lncRNA (Figure 1.1B). Kcnq1ot1 in turn represses paternal expression of Cdkn1c, Kcnq1 and other genes in cis, allowing for their expression only from the maternal allele. 12 1.5.3 Insulator functions Silencing via insulator functions occurs through blocking promoter-enhancer interaction mediated by the DNA-binding protein CCCTC binding factor (CTCF) (Bell et al. 1999). CTCF is an architectural and insulator protein, where DNA methylation at specific CpG sites within its binding motif can inhibit binding (Maurano et al. 2015; Stadler et al. 2011). Allele-specific CTCF binding has been identified on the unmethylated allele at a number of imprinted DMRs including the Mest gDMR (Prickett et al. 2013), H19 gDMR (Bell and Felsenfeld 2000; Hark et al. 2000; Kanduri et al. 2000; Szabó et al. 2000), Peg13 gDMR (Singh et al. 2011), Meg3 sDMR (Lin et al. 2011; Llères et al. 2019; Rosa et al. 2005), and at the Rasgrf1 locus (Yoon et al. 2005). Aside from its role as an insulator, CTCF mediated allele-specific looping may also be involved in the tethering of distant enhancers to promoters thereby promoting transcription as discussed in Chapter 5 (Kubo et al. 2021). The H19/Igf2 locus regulated by imprinting control region 1 (IC1, H19 DMR) is a paradigm for CTCF-mediated insulator functions in the regulation of imprinting (Figure 1.1C). IC1 is paternally methylated, blocking CTCF from binding and allowing for the shared H19/Igf2 enhancer to activate paternal Igf2 expression only. Spread of paternal methylation from IC1 to the H19 promoter generates a somatic DMR (sDMR) that prevents expression of H19 from the paternal allele (Hark et al. 2000; Bell and Felsenfeld 2000; Kurukuti et al. 2006; Ferguson-Smith 2011; Szabó et al. 2000; Kanduri et al. 2000). Conversely, on the unmethylated maternal allele, CTCF binds and 13 insulates the Igf2 promoter from the enhancer, allowing for maternal H19-enhancer engagement only. In this paradigm, the gDMR regulates imprinting via allele-specific segregation of promoter-enhancer interactions. 1.5.4 Allele-specific looping Recent developments into CTCF biology have broadened the traditional view of this protein as a simple insulator. CTCF binding was found to be enriched at the borders of topologically associated domains (TADs), and nested “sub-TADs”. TADs represent a unit of genomic organization, with enriched intra-domain contacts, thus restricting enhancer-promoter interactions and therefore associated with transcriptional regulation (Nora et al. 2012; Dixon et al. 2012). Notably, allele-specific CTCF binding at paternal ICRs has been shown to shape allele-specific sub-TADs required for imprinting at the Dlk1-Dio3, and Igf2-H19 domains (Llères et al. 2019). The formation of allele-specific sub-TADs observed at the Igf2-H19 domain is in keeping with our understanding of the insulator model at IC1 (Figure 1.1C). Here, a maternal allele-specific sub-TAD is formed due to CTCF binding on the unmethylated IC1 (Figure 1.1C). The formation of this maternal sub-TAD groups H19 with its enhancers, allowing for maternal expression. On the paternal allele, paternal methylation of IC1 inhibits CTCF binding, and this sub-TAD is not formed, allowing for interaction between Igf2 and its enhancers. 14 1.6 Sub-proximal Mmu6 imprinting domain The proximal end of mouse Chr6 (Mmu6) contains two imprinted domains. Maternal UPD of the region is associated with embryonic growth retardation, while paternal UPD is associated with overgrowth (Beechey 2004, 2000). The sub-proximal domain contains the paternally expressed gene Mest and the maternally expressed genes Copg2, and Klf14. Transcription from the Mest promoter also produces the paternally expressed microRNA miR-335, encoded from intron 2 of the Mest mRNA (Yang et al. 2014; Hiramuki et al. 2015). Other imprinted transcripts have been described at the Mest-Copg2 locus, such as Copg2AS and Mit1/Lb9 (Lee et al. 2000), although these are now thought to be part of MestXL (see below). Notably, this imprinted domain lacks an annotated lncRNA. At the present time, there are two mouse models describing loss of Mest (Lefebvre et al. 1998; Anunciado-Koza et al. 2017), one miR-335 KO (Hiramuki et al. 2015) and at least four mouse models describing Klf14 deletion (Small et al. 2018; Koppes et al. 2019; Argmann et al. 2017). In this thesis, the function and regulation of Mest and Klf14 are discussed. 1.6.1 Regulation of imprinting in the Mest-Klf14 domain The only known gDMR in the Mest-Klf14 imprinting domain is found overlapping the Mest promoter. This sequence acquires DNAme in developing oocytes and maintains methylation uniquely on this allele throughout development (Lefebvre et al. 1997; Lucifero et al. 2004). This differential methylation is directly implicated in regulating Mest 15 expression: maternal methylation inhibits expression from the maternal allele and also precludes CTCF binding (Prickett et al. 2013) (Figure 1.2A). Aside from regulating the Mest gDMR via allele-specific promoter DNAme, the gDMR is also involved in regulating Copg2 imprinting via a secondary mechanism. Mest and Copg2 are arranged in a tail-to-tail orientation, and in most tissues their 3’UTR regions overlap by less than 1 kb. In derivatives of the central nervous system (CNS), however, a longer form of the Mest RNA, dubbed MestXL, is expressed through alternative polyadenylation (MacIsaac et al. 2012). The production of this longer MestXL isoform interferes with expression of Copg2 from the paternal allele, possibly through transcriptional interference, and resulting in preferential maternal expression of Copg2 in those cells (Figure 1.2A) (MacIsaac et al. 2012). In Mest +/KO embryos (pKO), MestXL is truncated by the insertion of polyadenylation sequence allowing for biallelic Copg2 expression. In this model, Klf14 imprinting is unperturbed (Figure 1.2B). Although the tissue-specific formation of MestXL allows imprinted transcription from the Mest gDMR to indirectly regulate Copg2 allelic usage, the mechanism controlling Klf14 imprinting is unknown. The Klf14 locus is located >200kb from the Mest gDMR and harbors no allele-specific epigenetic modifications at its promoter region (Parker-Katiraee et al. 2007). Furthermore, in a model of global depletion of maternal DNA methylation in Dnmt3amatKO/+ embryos, Klf14 expression is lost (Figure 1.2C) (Kaneda et al. 2004). This elegant experiment demonstrated that Klf14 expression from 16 the maternal allele requires maternal DNAme somewhere in the genome. Similarly, Klf14 expression was also lost in Trim28/Kap1 KO adipocytes (Bond et al. 2021). KAP1 is a transcriptional repressor and imprinting maintenance enzyme which mediates heterochromatin formation through recruiting histone methyltransferases such as SETDB1. SETDB1 is responsible for deposition of H3K9me3, which promotes DNAme maintenance (Strogantsev et al. 2015; Rothbart et al. 2012). In this model of adipocyte-specific KAP1 depletion, loss of Klf14 expression may be due to failure of DNAme maintenance or deposition of epigenetic marks. However, as there are no allele-specific epigenetic modifications at the Klf14 promoter itself, these observations indicate that imprinting hallmarks at another linked locus are responsible for Klf14 imprinting. Combined, these observations suggest Klf14 expression is independent of MestXL, and suggest that, paradoxically, repressive epigenetic modifications such as DNAme at the Mest gDMR are required for Klf14 expression. As the Mest gDMR is the only gDMR in the region, it may have a role in the regulation of Klf14 through long range chromatin interactions as observed at the H19/Igf2 locus. The hypothesis that the maternally methylated Mest gDMR regulates Klf14 imprinting will be addressed in Chapter 4. 17 Figure 1.2 Regulation of imprinting in the Mest domain A) Cartoon representation of imprinting in WT CNS-derived cells. Maternal methylation at the Mest gDMR allows for only paternal expression of Mest. In the CNS, MestXL is transcribed on the paternal allele therefore blocking expression of Copg2 via transcriptional interference. Klf14 is maternally expressed. B) Mest truncation in Mest KO mice results in the loss of imprinting of Copg2, with no effect on Klf14 imprinting. C) Global depletion of maternal methylation in Dnmt3amatKO/+ offspring results in loss of imprinting of Mest, and Klf14. Active genes are represented as colored boxes, and silent genes are represented as grey boxes. White and black lollipops represent unmethylated and methylated CpG islands. Green boxes represent DMRs. M: maternal allele, P: paternal allele. 18 1.6.2 Mest Mest codes for a highly conserved putative enzyme belonging to the α/β-hydrolase fold superfamily (Kaneko-Ishino et al., 1995; Sansom et al., 2005), which has been shown to be localized to the endoplasmic reticulum (ER)(Prudovsky et al. 2018; Jung et al. 2011). Although MEST encodes a putative epoxide hydrolase, no enzymatic activity has been confirmed so far, so its substrate is still unknown (Morisseau 2013; Decker et al. 2009). In the mouse, Mest is highly expressed in embryonic and extraembryonic mesodermal lineages, including in the early embryo and placenta (Mayer et al. 2000; Lefebvre et al. 1998). Within the placenta, Mest is paternally expressed in the fetal endothelial cells of the labyrinth, chorionic plate, early decidua, and hemangioblast precursors (Mayer et al. 2000). Mest has also been shown to be important in embryonic neuronal development within the cortex and midbrain (Ji et al. 2017; Mesman et al. 2017). In keeping with the dogma for the growth-promoting function of paternally expressed genes, Mest KO mice are embryonically growth restricted on a mixed 129X1/SvJ ´ 129S1/SvImJ mouse background (Lefebvre et al. 1998). Additionally, loss of imprinting of Mest (biallelic expression) was associated with increased body, spleen and kidney weights in interspecific Mus musculus and Mus spretus F1 hybrids (Shi et al. 2004), demonstrating that maintenance of imprinting at Mest is perturbed in inter-species crosses. 1.6.3 Mest KO mouse models The Mesttm1Masu (MGI: 2181803) mouse model, hereby named Mest KO, was previously generated through a targeted promoter trap approach (Lefebvre et al. 1998, 1997). A 19 splice acceptor-IRES-βgeo-pA cassette was used to replace the predicted catalytic regions encompassing exons 3-8, and part of 9 (Figure 1.3). Transcription terminates upstream of exon 9, producing truncated Mest and MestXL transcripts (MacIsaac et al., 2012). Using this allele, Mest imprinted expression can be examined via X-gal staining of reciprocal mKO and pKO embryos, where signal is only observed upon paternal transmission of the KO allele. Notably, the sequences required for miR-335 production within Mest intron 2 are unperturbed in this KO allele. Consequently, miR-335 remains paternally expressed, with approximately 50% lower expression in pKO animals compared to wild-type (MacIsaac et al., 2012). Figure 1.3 Schematic of the Mest WT and KO alleles The Mest KO allele is composed of a splice acceptor-IRES-lacZ/neo fusion-poly(A) cassette, replacing Mest exons 3-8, and part of exon 9. The Mest ORF is represented by black boxes, and 5’ and 3’ untranslated regions are represented by grey boxes. miR-335 is located in Mest intron 2 and the location of the CpG island is indicated by the green line under exon 1. Phenotypically, paternal inheritance of the Mest KO allele on the mixed 129 strain background was associated with embryonic growth retardation with no postnatal catch-up (Lefebvre et al. 1998). Additionally, Mest KO mothers exhibited abnormal 20 maternal behavior, reflected in a lack of maternal care. Aside from this original study, the Mest KO line has been used to characterize the function of Mest in neurogenesis, where loss of Mest was associated with abnormal neuronal development and migration (Mesman et al. 2017; Sansom et al. 2005). Furthermore, Mest has also been shown to mediate muscle regeneration independent of miR-335 (Hiramuki et al. 2015). The exact mechanism linking Mest function to these phenotypes is unknown. Postnatally, Mest has also been shown to play a role in lipid metabolism. Mest upregulation was associated with adipocyte enlargement and adipose tissue expansion in various models of obesity (Anunciado-Koza et al. 2016b; Chu et al. 2014; Anunciado-Koza et al. 2017; Takahashi et al. 2005; Kamei et al. 2007; Voigt et al. 2015; Nikonova et al. 2008; Koza et al. 2006; Anunciado-Koza et al. 2016a; Jura et al. 2016). However, these studies are confounded by the co-expression of intronic miR-335 which is also implicated in adipogenesis (Nakanishi et al. 2009; Zhu et al. 2014). Nevertheless, in a targeted Mest deletion model where miR-335 expression was unperturbed, Mest KO mice were resistant to diet induced obesity with minimal effects on transcription (Anunciado-Koza et al. 2017). A total of 36 (27 downregulated, 9 upregulated) genes were differentially expressed in Mest KO epididymal white adipose tissue (eWAT). Based on this observation, the postnatal lipid phenotype in KO mice is primarily due to loss of Mest function. 21 1.6.4 miR-335 miR-335 is a paternally expressed microRNA processed from intron 2 of Mest, sharing coordinated expression with its host gene (Hiramuki et al. 2015; Ronchetti et al. 2008; Dohi et al. 2013). miRNAs are produced via RNA pol II transcription, and function to regulate gene expression via mRNA degradation or translational inhibition depending on 3’ UTR complementarity with their targets (Gebert & MacRae 2019). miR-335 is predicted to target hundreds of genes, and has been associated with Wnt activation (Zhang et al. 2011; Lin et al. 2014), cholesterol synthesis (Raihan et al. 2018), and mesendodermal fate commitment via targeting endodermal transcription factors Foxa2 and Sox17 (Yang et al. 2014). In humans, miR-335 was first implicated as a suppressor of breast cancer metastasis through targeting the transcription factor SOX4 and the extracellular matrix factor tenascin C (Tavazoie et al. 2008). This relationship between miR-335 and cancer has since been expanded to encompass both tumor suppressor and promoter functions spanning across a variety of cancers, highlighting its pleiotropic role (Luo et al. 2016). Notably, studies examining either Mest or miR-335 function through manipulating the endogenous genomic sequence may be unable to attribute a phenotype to solely either transcript. For example, the Mest KO allele discussed (Lefebvre et al. 1998) retained the sequences important for miR-335 expression and processing. Mest KO mice therefore lose expression of Mest, while miR-335 is only downregulated. In this case, the growth retardation phenotype observed in Mest KO mice may be due to 22 dysregulation of Mest or miR-335. However, in an independent deletion of miR-335, no growth retardation was observed, indicating Mest is likely the main gene responsible for this growth phenotype (Hiramuki et al. 2015). 1.6.5 Copg2 Copg2 codes for a subunit of the coatomer subcomplex (COPI vesicles) involved in Golgi-intracellular transport (Moelleken et al. 2007). Maternal expression of Copg2 in the developing embryo and adult brain was first described in F1 crosses between C57BL/6 × M. m. molossinus (Lee et al. 2000). However, in crosses between C57BL/6 × M. spretus Copg2 was biallelically expressed (Yun et al. 2003). More recently, high-throughput genome-wide screens on bulk tissues using reciprocal C57BL6/J × CAST/EiJ (Babak et al. 2015; Gregg et al. 2011), and C57BL/6J × JF1 mice (Bouschet et al. 2017a) further corroborated Copg2 maternal expression in embryonic brain (E15, E17.5), and adult cortex and hypothalamus. Similar experiments in reciprocal CAST × FVB mice revealed Copg2 expression was maternally biased (allelic ratio of 0.6), but below the threshold of imprinted expression (ratio of 0.7) (Andergassen et al. 2017). Altogether, Copg2 imprinting appears less stringent and is restricted to neuronal lineages. The observation that imprinting varies across different hybrid strains may be attributed to genetic variation related to the Mest polyadenylation sequence or 3’UTR as previously proposed (MacIsaac et al. 2012). 23 1.6.6 Klf14 Klf14 is a maternally expressed gene coding for a Krüppel-like transcription factor, located approximately 200 kb downstream from the Mest gDMR. The KLF14 protein is a member of the Sp/KLF zinc finger family of transcription factors, and is most similar to KLF16. KLFs have diverse functions in development, including regulation of cell proliferation, differentiation, and metabolism (Oishi and Manabe 2018). Since Klf14 is a single-exon, intron-less gene, it is thought to have arisen through retrotransposition of Klf16 during early protoeutherian evolution (Parker-Katiraee et al. 2007). Kfl14 was shown to be expressed and imprinted in all embryonic and extra-embryonic tissues tested at E15.5, including the yolk sac, and placental labyrinth (Parker-Katiraee et al. 2007). In adult tissues, Klf14 expression is most highly expressed in the pituitary and tongue (Argmann et al. 2017; Andergassen et al. 2017). 1.6.7 Klf14 KO mouse models Loss of Klf14 in the mouse has been well described (Guo et al. 2015; Fan et al. 2015; De Assuncao et al. 2014; Koppes et al. 2019). The majority of studies have focused on the loss of Klf14 in relation to metabolism (reviewed: Yang & Civelek 2020). In brief, Small et al. utilized three different Klf14 KO mouse lines to study its function in metabolism (Small et al. 2018). Whole body Klf14tm1(KOMP)Vlcg KO mice (MGI: 3812953) were generated by the KOMP repository via insertion of a neomycin cassette, and deletion of the entire Kfl14 exon. A second line utilized a 7bp frameshift. The third 24 mouse line is a conditional allele, which was used in an adipose-tissue specific deletion. In general, Klf14 depletion was associated with a modest reduction in HDL-C levels (~15%). Intriguingly, the adipose-specific depletion of Klf14 was associated with insulin resistance characterized by increased triglycerides, impaired glucose tolerance, and dysregulation of a network of 87 genes enriched in functions relating to lipid and triglyceride metabolic processes. Argmann et al. also used the whole body Klf14tm1(KOMP)Vlcg KO model to assess the role of Klf14 in adipogenesis. Male mice homozygous for the Klf14 KO allele were fed a normal chow, or high fat diet. Contrary to previous results, there were no differences in HDL-C levels, weight gain, or insulin resistance between genotypes (Argmann et al. 2017). There were also no differentially expressed genes (DEG) identified by RNA-seq of inguinal white adipose tissue, whereas 240 DEGs were identified in the pituitary (153 up, 87 down). Inconsistencies between this and the previously discussed studies may stem from their study being too underpowered to detect small differences, and also highlights the inherent variability of in vivo models. Mouse models utilizing lineage-specific deletions of Klf14, such as in adipose tissue, may provide better insight into gene function. For example, two groups further examined Klf14 function in the liver, the organ responsible for the majority of HDL-C synthesis and modulation of blood glucose levels. Guo et al. generated a liver-specific deletion of Klf14 (Albumin-Cre) in the mouse. Homozygous loss of hepatic Klf14 was associated with reduced HDL-C levels (Guo et al. 2015). Wang et al. examined 25 adenovirus mediated Klf14 overexpression both in vivo, and in primary hepatocytes. Klf14 overexpression was associated with increased triglycerides, and plasma glucose levels, representing impaired glucose tolerance (Wang et al. 2017). While these studies do confirm the role of Klf14 in metabolism, their results may be confounding as Klf14 is not expressed in the adult mouse liver, and is only very lowly expressed in the fetal liver (Koppes et al. 2019; Argmann et al. 2017). The majority of in vivo mouse models of Klf14 function have used homozygous deletions of Klf14 as opposed to maternal-specific deletions only. Additionally, there has been only one study to date examining the loss of Klf14 in utero. This most recent Klf14 KO mouse line was generated via a large 4.9kb deletion of the region spanning the promoter and open reading frame. Loss of maternal Klf14 during in utero development resulted in slight placental overgrowth, with no effect on fetal growth (Koppes et al. 2019). Only twenty differentially expressed genes were identified in Klf14 mKO placenta, of which none overlapped the previously identified Klf14 targets in adipose tissue. Overall, these mouse models of Klf14 depletion illustrate the function of Klf14 as a metabolic regulator but also highlights potential tissue-specific functions. 1.6.8 Human homology and disease The MEST-KLF14 imprinted domain, along with the MEST gDMR, are conserved in humans (Kobayashi et al. 1997; Riesewijk et al. 1997). Notably, there are two major isoforms of MEST: isoform 1 initiating from exon 1c has been shown to be preferentially 26 paternally expressed, while the shorter isoform 2 initiating from exon 1a exhibits more variable and tissue specific imprinting (McMinn et al. 2006). MEST isoform 2 is paternally expressed in fetal placenta, and kidney, but is biallelic in other fetal tissues tested including the brain and heart (Nakabayashi et al. 2002). The locus also harbors a 4.2kb paternally expressed antisense lncRNA MESTIT1 located in the first intron of isoform 2 which may function in MEST gene regulation (Nakabayashi et al. 2002). Dysregulation of the MEST-KLF14 imprinting domain is associated with Silver-Russell syndrome, as well as adult-onset diseases. Imprinting syndromes are heterogenous, and can result from duplications, deletions, UPD, mutations. Imprinting syndromes may also arise due to epimutations, such as hypo or hypermethylation of a DMR. In the case of the MEST gDMR, dysregulation may lead to changes in expression of MEST, miR-335, COPG2, and KLF14. For example, MEST upregulation and modest hypomethylation over the gDMR-promoter has been observed in neural tube defects (Chang et al. 2021). Conversely, MEST downregulation, and gDMR hypermethylation has been associated with various cancers and adverse pregnancy outcomes including missed abortion, and gestational diabetes (Peng et al. 2016; Dohi et al. 2013; El Hajj et al. 2013; Png et al. 2011). 1.6.8.1 Silver-Russell syndrome Silver-Russell syndrome (SRS) was first described independently by Silver and Russell in a subset of children (Silver 1953; Russell 1954). The syndrome is characterized by 27 intrauterine and postnatal growth retardation, macrocephaly, body asymmetry, triangular facial features, and fifth finger clinodactyly. Congenital malformations, renal and cardiac defects are also associated with SRS. The majority of cases are born small for gestational age, with growth restriction persisting into adulthood. The incidence is estimated to range from 1/75,000 to 1/100,000 live births. SRS is genetically heterogenous, with two major molecular subgroups that present with distinct growth dynamics. Hypomethylation at the H19 ICR on chromosome 11p15.5 accounts for up to 60% of patients, while mUPD for chromosome 7 accounts for approximately 5-10% (Kotzot et al. 1995; Preece et al. 1997). SRS mUPD7 cases are born relatively larger than 11p15 SRS cases, but present with more severe postnatal growth retardation and neurocognitive problems (Binder et al. 2008; Wakeling et al. 2017). The exact genomic region responsible for SRS due to mUPD7 is unknown. Several imprinted genes are localized on human Chr 7, including GRB10 at 7p11 and MEST at 7q32.2. Maternal duplications (Eggermann et al. 2008; Hannula et al. 2001) and paternal microdeletions (Carrera et al. 2016) specifically at 7q32 have been reported in SRS, encompassing only the MEST imprinting domain. Recently, a paternally inherited 79-kb microdeletion was observed in a patient with SRS-like phenotypes: growth retardation but lacking body asymmetry (Vincent et al. 2022). This is the smallest deletion to date associated with SRS-like symptoms, encompassing only the imprinted genes MEST, MEST1T1, MIR-335, and 3’ of COPG2, thus narrowing down the pathogenic gene(s) responsible. Although the studies discussed implicate the 28 role of MEST in mUPD7 SRS, there has been no conclusive report linking the gene itself to the phenotype. For example, there have been no reports of coding mutations, or mutations leading to MEST dysregulation, or aberrant methylation at the DMR in SRS patients (Schöherr et al. 2008; Kobayashi et al. 2001). However, since the growth retardation phenotype observed in Mest KO mice is similar to mUPD7 SRS, MEST is considered a candidate gene (Lefebvre et al. 1998). 1.6.8.2 Metabolic disorders KLF14 has been proposed as a master regulator of metabolic phenotypes (Chen et al. 2020), implicated in regulating a network of up to 385 genes in adipose tissue, of which 177 genes show enrichment for the KLF14 binding motif (Small et al. 2018). Genome wide association studies (GWAS) first identified parent-of-origin effects at rs4731702 and rs972283 approximately 14kb upstream of KLF14 (Kong et al. 2009; Voight et al. 2010). These haplotypes are associated with increased risk for type 2 diabetes, and decreased KLF14 expression when maternally inherited. Furthermore, rs4731702 has also been associated with HDL-C levels and decreased risk for myocardial infarction (Chen et al. 2012; Teslovich et al. 2010). More recent characterization into the KLF14 risk allele revealed that although rs4731702 was associated with lower KLF14 expression irrespective of sex, female carriers were at a greater risk for developing insulin resistance, and dyslipidemia associated with type II diabetes (Small et al. 2018). This may be reflective of the higher basal levels of KLF14 expression in females. Combined, these observations highlight the sex-specific differences associated with 29 KLF14 function in humans, which have not been recapitulated in the mouse, therefore bringing into question the use of the mouse as a model system. 1.7 Mouse placenta The placenta is an interfacial organ responsible for the exchange of nutrients, gas, and waste products between mother and fetus. The mouse is used as a model to study human placentation due to the short generation time and ability to manipulate genetics or physiological conditions. Both human and mouse placentae are haemochorial, where the fetal trophoblast cells are in direct contact with maternal blood, and share some signaling pathways important for regulating placental development. While the mouse and human placenta share some common cell types, there are also distinct structural differences (Rossant & Cross 2001; Watson & Cross 2005; Woods et al. 2018). For example, while the mouse placenta has three distinct trophoblast cell layers separating maternal blood spaces with fetal cells, the human placenta only has a single trophoblast layer. The mouse placenta is composed of three main layers: trophoblast giant cell (TGC) layer, spongiotrophoblast/junctional zone, and labyrinth. The layers are composed of different cell types, and have unique functions (reviewed: Rossant & Cross 2001; Watson & Cross 2005; Woods et al. 2018). TGCs, generated from endoreplication, a process that does not occur in humans, comprise the outermost layer of the placenta (Hu and Cross 2010). There are at least four subtypes of TGCs, which 30 secrete a broad range of hormones and placental lactogens required for pregnancy (Hu and Cross 2010). Adjacent to the TGCs is the junctional zone, comprised of spongiotrophoblast cells (SpT) derived from the ectoplacental cone, and a layer of glycogen cells positive for the marker Pcdh12 (Bouillot et al. 2006). The junctional zone similarly plays a role in endocrine signaling via secretion of hormones, growth factors, and cytokines (Soares 2004). Glycogen cells, with their ability to store and release large amounts of glycogen, may play a role in supplying glycogen as an energy source to the growing conceptus. The third placental compartment constitutes the labyrinth: a highly vascularized layer composed of fetal blood vessels bathed in maternal blood. The labyrinth layer forms via chorio-allantoic fusion between the chorionic plate mesothelium and allantoic mesoderm at E8.5. Branching morphogenesis within the labyrinth is controlled by the transcription factor Gcm1 (Anson-Cartwright et al. 2000). The labyrinth is made of three continuous layers where nutrient exchange occurs: syncytiotrophoblast (SynT) layer I is in contact with maternal blood, SynT layer II lines the fetal vasculature (Simmons et al. 2008), and the third layer is composed of mesoderm derived endothelial cells lining the fetal vessel. Additionally, a discontinuous monolayer of sinusoidal TGCs is adjacent to SynT I. 1.7.1 Imprinted genes in the mouse placenta A large number of imprinted genes are expressed in the mouse placenta and involved in placental development (Cleaton et al. 2014; Lefebvre 2012). Disturbances in placental function are associated with compromised nutrient supply to the fetus and are 31 associated with growth retardation. However, it is not always clear the extent by which placental failure influences fetal development. Notably, the function of maternally expressed Ascl2 in placental development has been well characterized. Ascl2 encodes a basic helix-loop-helix transcription factor. Partial loss of function of the maternally expressed gene Ascl2 is associated with embryonic growth restriction, reduction in junctional zone formation, and ablation of the glycogen cell population (Oh-McGinnis et al. 2011). Chimeras harboring WT extraembryonic tissues and Ascl2 KO embryonic tissues resulted in viable embryos thus rescuing the phenotype and demonstrating that embryonic lethality was solely due to a placental failure (Guillemot et al. 1994). Phlda2/Ipl, a maternally expressed gene restricted to the labyrinth, also has placental-specific functions. Phlda2 deficiency has been associated with fetal growth restriction, placentamegaly, and expansion of the junctional zone and glycogen cell population (Frank et al. 2002; Tunster et al. 2016). Through mediating junctional zone development, Phlda2 indirectly modulates growth via production of placental hormones from this compartment. Aside from the junctional zone, imprinted genes are also involved in formation of the placental labyrinth. Dysregulated imprinting and impaired transport of nutrients attributed to diminished surface area at the maternal-fetal interface have been described (Woods et al. 2018). Loss of the paternally expressed gene Igf2 encoding a growth promoting factor, is associated with a smaller labyrinth, defects in placental transport, and fetal growth restriction (Constância et al. 2002; Sibley et al. 2004). 32 Similarly, loss of the retrotransposon-derived paternally expressed Peg10 is associated with lack of labyrinth development, contributing to early embryonic lethality by E10.5 (Ono et al. 2006). In general, the function of most imprinted genes, aside from Ascl2, fits within the parental conflict dogma: paternally expressed promote placental development whereas maternally expressed genes are suppressive. As discussed, imprinted genes serve an array of functions within the placenta, with no sole unifying biochemical role. However, imprinted genes may also influence embryonic growth via placenta-independent pathways. For example, the main source of paternal Dlk1 expression is fetal. Loss of paternal Dlk1 is associated with pre- and postnatal growth retardation, adiposity defects, and skeletal abnormalities (Moon et al. 2002; Cleaton et al. 2016). Conversely, Dlk1 loss of imprinting (two-fold upregulation) is associated with embryonic overgrowth while its expression within the placenta remained at low levels (Teixeira da Rocha et al. 2009). The exact mechanism underlying this observed phenotype is unknown, but may be due to modulation of the pituitary growth hormone axis and nutrient metabolism by DLK1 (Charalambous et al. 2014). The relationship between placental metabolism and imprinting is poorly understood. Metabolomic profiling has only just begun to determine baseline metabolite concentrations in normal placentae, revealing sex-specific differences relating to placental mitochondrial function (Saoi et al. 2020). For example, mitochondrial- 33 associated metabolites, such as those within the carnitine family associated with fatty acid metabolism, were found to be higher in female placentae. The implications of placental sexual dimorphism in relation to growth and metabolism remains to be determined. 1.8 Wnt signaling The Wnt pathway is a highly conserved developmental pathway responsible for a variety of processes including stem cell renewal, proliferation, embryogenesis, patterning, and tissue homeostasis (Clevers et al. 2014; Clevers and Nusse 2012; Logan and Nusse 2004). Defects in Wnt signaling are associated with both failed embryonic and postnatal development (Nusse and Clevers 2017). The Wnt pathway can be classified as β-catenin dependent (canonical) or independent (non-canonical). There are two pools of β-catenin, cytosolic and membrane-bound. The cytosolic pool is regulated by canonical Wnt signaling, while the more stable membrane-bound pool is associated with planar cell polarity signaling associated with actin cytoskeleton complexes. In brief, the canonical Wnt pathway revolves around the formation of the β-catenin destruction complex. This complex is composed of the scaffolding proteins APC and AXIN, and kinases CK1 and GSK3β. In the absence of Wnt, the β-catenin destruction complex resides in the cytoplasm, where it phosphorylates β-catenin. β-catenin is subsequently ubiquitinated and degraded by the proteasome. In the presence 34 of Wnt ligands, Wnt binds to its co-receptors LRP5/6 and Frizzled, which recruits Disheveled and tethers the destruction complex to the membrane, rendering it inactive. β-catenin is stabilized and enters the nucleus, where it binds to the lymphoid enhancer-binding factor 1/T cell-specific transcription factor (TCF/LEF) family of transcription factors to activate transcription of Wnt target genes. There are several well-known Wnt target genes including Myc, CyclinD, and Axin2. The Wnt pathway can be regulated through inhibition of destruction complex proteins. A large number of Wnt regulators, either secreted or membrane-bound, act at the level of receptor-ligand activation. For example, DKK1, SOST, and ZNRF3 all act to inhibit Wnt-LRP6 binding. LRP6 is a single-pass transmembrane protein located at the plasma membrane, with a large extracellular domain subject to ligand binding. DKK1, a secreted protein, inhibits Wnt signaling by binding LRP5/6, inducing its removal from the plasma membrane and preventing formatting of the Wnt-receptor complex (Mao et al. 2001; Sakane et al. 2010; Semënov et al. 2001). SOST, a secreted glycoprotein, binds to the extracellular domain of LRP6, effectively blocking binding of some Wnt ligands (Wnt1, Wnt2, and Wnt9b signaling but not Wnt3a) (Kim et al. 2020). ZNRF3, a E3 ubiquitin ligase located on the cell membrane, acts on Frizzled, resulting in turnover of Frizzled and LRP6 receptors (Hao et al. 2012). Wnt signaling may also be regulated at the cell-extrinsic level. Wnt ligands are secreted lipid-modified glycoproteins, requiring lipid modification by porcupine (Porc) for 35 secretion and export form the ER (Van den Heuvel et al. 1993; Willert et al. 2003). Similarly, Notum, an extracellular carboxylesterase, acts as a Wnt antagonist by removing an essential palmitoleate from Wnt ligands that is required for binding to the Frizzled receptor (Kakugawa et al. 2015). 1.9 Mest regulation of Wnt signaling Wnt signaling may be the key pathway linking the relationship between Mest and adipogenesis in the mouse models previously discussed. The Wnt pathway is an established inhibitor of adipogenesis, mainly through inhibition of the key transcription factors C/EBPα and PPARγ (Ross et al. 2020; de Winter and Nusse 2021). The observations that Mest is upregulated in models of obesity (Anunciado-Koza et al., 2016b; Chu et al., 2014; Kamei et al., 2007; Nikonova et al., 2008), that loss of Mest is protective against diet-induced adipose tissue expansion (Anunciado-Koza et al. 2017), and combined with reports demonstrating the function of Mest as a Wnt inhibitor (Jung et al. 2011; Prasad et al. 2021; Ji et al. 2017; Li et al. 2014), all point towards a biologically meaningful relationship between Mest and Wnt signaling. Mechanistically, Mest has been shown to inhibit the Wnt pathway in a dose-dependent manner (Jung et al. 2011). Mest overexpression was associated with reduced glycosylation of the Wnt co-receptor LRP6, resulting in its retention in the ER. The reduction of mature LRP6 at the cell surface made the cell insensitive to Wnt ligands, and also reduced the levels of cytosolic β-catenin protein. This function of 36 MEST in LRP6 modulation is in keeping with the protein’s localization to the ER, the site of N-linked protein glycosylation. As MEST encodes a putative epoxide hydrolase enzyme, one can speculate that its substrate spectrum may include Wnt receptors, such as LRP6 as discussed, Wnt ligands or fatty acid epoxides important in lipid signaling. However, no MEST substrates have been identified yet, and it is unknown if Mest actually codes for a functional enzyme. 1.10 Thesis theme and objectives The sub-proximal Mmu6 imprinting domain is composed of the paternally expressed gene Mest, and maternally expressed genes Copg2 and Klf14. Mest is considered a candidate gene for SRS based on the growth retardation phenotype in KO mice. However, the exact function of the MEST protein is unknown. Furthermore, while the mechanisms regulating Mest (Lefebvre et al. 1997) and Copg2 (MacIsaac et al. 2012) imprinting are well characterized, the mechanism underlying Klf14 imprinting is unknown. My thesis work aims to elucidate the functions of MEST, and further characterize the mechanism regulating imprinting within the Mest domain on Mmu6. In Chapter 3, I utilize a Mest KO model previously generated to further characterize the role of Mest in developmental pathways. I also employed a metabolomic and proteomic approach to study the MEST protein, via identification of putative substrates, and characterization of topology within the endoplasmic reticulum. In Chapter 4, I characterize the function of 37 the Mest gDMR in regulation of Klf14 imprinting, and present a model based on observations arising from Mest gDMR deletions in ESCs. I demonstrate that the Mest gDMR regulates Klf14 imprinting through formation of allele-specific sub-TADs, segregating Klf14 from its putative enhancer(s) on the paternal allele. In Chapter 5, I discuss the significance of my work, emphasizing the importance of Mest and its gDMR in developmental processes. 38 Chapter 2: Materials and Methods 2.1 Mouse strains C57BL/6 and CAST mice were bred and housed in groups of two to five per cage. The mouse facility was maintained between 20-26 °C, 40-60% relative humidity, and on a 12hr light cycle. For all genotypes, the maternal allele is presented first. The Mest KO line was previously generated as described (Lefebvre et al. 1998). The Mest KO mouse line was backcrossed more than 10 times onto the C57BL/6J reference background. Mest WT (+/+) females were mated to Mest KO (+/KO) males for paternal transmission of the mutant allele (pKO). Animal studies were reviewed and approved by the University of British Columbia Committee on Animal Care under protocols A13-0115, A15-0181, A15-0291, and A19-0209. 2.2 Polymerase chain reaction General PCR cycling conditions are as follows: 10 minutes at 95°C, followed by 35 cycles of 30s at 95°C, 30s at 58°C, 1 min at 72°C, and a final 5 min final elongation at 72°C. PCR products were visualized by agarose gel electrophoresis. A list of primers is available (Table 2.4). 2.3 Genotyping Mice were genotyped at weaning age by ear punch HotSHOT lysis and PCR (Truett et al. 2000). Genotyping of the KO allele was performed with primers 702A and IRES1. 39 Genotyping of the Mest WT allele was performed with primers 702A and 702C. For sexing, the Y chromosome was detected with primers ZFy1a-ZFy1b. All primer sequences used in this thesis available in Table 2.4. PCR products were visualized by agarose gel electrophoresis. When available, a sample of the yolk sac was kept for PCR genotyping, and X-gal staining to test for transmission of the paternal Mest KO allele: yolk sacs were briefly fixed in 4% PFA, 0.2% glutaraldehyde, incubated overnight in X-gal staining buffer (1 mg/ml X-gal, 4 mM K4Fe(CN)6, 4 mM K3Fe(CN)6, 2 mM MgCl2), and visualized the next day. 2.4 Dissections and fixations For timed mating, the day of the vaginal plug is E0.5. Females were sacrificed at specified time points by CO2 euthanasia followed by cervical dislocation, and yolk sac samples processed for PCR genotyping and X-gal staining. Samples were dissected in cold PBS. All dissected samples were put in fresh 4% PFA/1X PBS (Sigma) for fixing overnight at 4°C with gentle rotation. For paraffin sectioning, samples were fixed overnight in 70% ethanol at 4°C. The ethanol was changed the morning after, and samples stored at 4°C until further processing. The sample was then subjected to a series of four 30 min ethanol washes (75%, 90%, 100%, 100%), two 30 min xylene washes at room temperature, and three incubations with paraffin at 65°C for three hours. Fresh paraffin was changed every 30 min. The tissues were paraffin-embedded, and 10µm paraffin sections were made by hand using Leica’s RM2255 microtome. For cryo-sectioning, samples were incubated sequentially with 10% and 30% sucrose/1X 40 DEPC PBS overnight, and then embedded in Tissue-Tek O.C.T over dry ice. Cryo-blocks were stored at -80°C until processing. Cryo-sections of 12µm were made using a Leica CM3050 cryostat, collected on Superfrost plus slides (Fisher) and stored at -20˚C. 2.5 Hematoxylin and eosin staining Hematoxylin was prepared with 5% Aluminum Potassium Sulfate (Fisher Scientific), 0.1% Hematoxylin (Fisher Scientific), 0.02% Sodium Iodate (Fisher Scientific) and 2% Glacial Acetic Acid (Fisher Scientific). Paraffin sections were de-paraffinized, and rehydrated through a series of washes at 2 minute intervals (2 ´ xylene, 2 ´ 100% EtOH, 70% EtOH, 50% EtOH, water). The slides were stained in hematoxylin for 15 min, placed under running water, and washed in Scott’s tap water substitute (2% MgSO4, 0.35% NaHCO3 in distilled water). Sections were then dehydrated through a series of washes at 2 minute intervals (30% EtOH, 50% EtOH, 70% EtOH, 2 x 100% EtOH, 2 x xylene), and counterstained with eosin (Sigma-Aldrich) for 30 seconds. Finally, slides were washed twice in 2 min washes of 100%EtOH, and xylene, and mounted with Entellan mounting media. Subsequent analyses of the tissues were made using a light microscope (Leica MS5). 2.6 Morphometric analysis Midline placental paraffin sections were stained with hematoxylin and eosin. Images were taken on a Leica DMI6000B inverted microscope, captured using a digital CCD color QImaging MicroPublisher 3.3 RTV camera, and stitched together in Adobe 41 Photoshop. Placental layers were identified by hand in Adobe Illustrator based on cell morphology of the trophoblast giant cell layer, and junctional/labyrinth zones from H&E stained-sections. The area of each layer was calculated in Openlab. The chorionic plate was excluded from measurements. Measurements were confirmed via analysis of two adjacent slides. 2.7 Immunohistochemistry Paraffin sections were deparaffinized and rehydrated as previously described (Section 2.5), blocked with 0.3% hydrogen peroxide for 30 min, and then incubated in blocking solution (5% goat normal serum and 0.5% BSA in PBS-T) for 1.5hours. Rabbit polyclonal anti-laminin (Sigma L9393) was incubated with the slides overnight at 4˚C at a 1:100 dilution in blocking solution overnight in a humidified chamber. The sections were then washed twice with PBS, incubated with a 1:1000 dilution of the secondary biotinylated goat anti-rabbit antibody in blocking solution for 30 min at room temperature in the dark, and washed twice in PBS. Staining was performed using the Vectastain Elite ABC kit (Vector) for 30 min, followed by DAB substrate until color formation was sufficient. Sections were washed with PBS, counterstained with hematoxylin for 15) minute, washed in Scott’s Tap water solution, dehydrated, and mounted with Entellan mounting medium (EM Science). 42 2.8 In situ hybridization ISH and DIG-labeled probe preparation were performed as described (Oh-Mcginnis et al. 2010). 2.9 Periodic-acid Schiff staining Paraffin sections were deparaffinized, rehydrated, and blocked (1% sodium bisulfite) for 1 hour RT. The negative control section was incubated with amylase for 30 min. All sections were then incubated with 2% periodic acid for 5 min, washed for 5 min under running tap water, treated with Schiff’s reagent for 3 minutes, and rinsed with running tap water. Hematoxylin was used as the counterstain, and Scott’s tap water substitute was used to sharpen the contrast. Sections were subsequently dehydrated as previously described (Section 2.5) and mounted with Entellen mounting medium. 2.10 RNA-seq RNA was isolated from E17.5 placentae using Trizol (Invitrogen) per the manufacturer’s instruction. Library construction and paired-end sequencing was performed at the Biomedical Research Centre at UBC, as part of the UBC Sequencing + Bioinformatics Consortium. Reads were aligned using STAR (Dobin et al. 2013) to the UCSC mm10 genome assembly using default parameters. For determination of significantly differentially expressed genes, the selection criteria are as follows: fold change ≥ 1.5-fold change, z-score ≤ -1 or ≥ -1, and Fragments Per Kilobase Million (FPKM) >1. 43 2.11 Metabolomic analysis E17.5 placentae were collected, snap frozen, and sent for metabolomic analysis at the BC Children’s Hospital Research Center, Analytical core for Metabolomics and Nutrition (AcMaN). Total triglyceride levels were measured by spectrophotometric assay. Metabolomics was performed using the Agilent 1290 UHPLC and Agilent 6530 QTOF. Statistical analysis was performed using a two-tailed t-test (p ≤ 0.05), and was adjusted to control the false detection rate (FDR) at a cutoff of 0.01 (Benjamini-Hochberg). Qualitative pathway enrichment analysis was performed on all statistically significant entities (p ≤ 0.05) prior to multiple-testing correction using MetaboAnalyst 5.0 (Pang et al. 2021). 2.12 Derivation of mouse embryonic fibroblasts MEFs were derived from E13.5 embryos obtained from timed mating between a C57BL/6 female and Mest +/KO male. A sample of the yolk sac was kept for genotyping and each embryo was processed independently. The head, and internal organs were removed. The remaining tissue was minced, washed in 70% ethanol, and washed twice with 1X PBS. The tissue was incubated at 37°C with 0.05% Trypsin-EDTA, 0.05mg/mL DNaseI, and 5 mM beads in a 50mL falcon tube shaking for 1 hour to create a single cell suspension. The suspension was then decanted onto a 100 mm tissue culture plate briefly coated with 0.1% gelatin, with a total of 18mL PEF media (PEFM) (DMEM,10% FBS, 1/100 (v/v) L-glutamine, 1/100 pen/strep) and grown at 5% CO2 at 37°C. The media was changed the next day, and cells were monitored until ready for passaging 44 upon 70% confluency. Genotyping of the Mest KO allele, and sexing was as previously described. 2.13 Derivation of mouse embryonic stem cells All ESC lines used in this thesis were derived as previously described (Hayashi and Saitou 2013; Ying et al. 2008). To generate Mest pKO ESC, C57BL/6 females and Mest +/KO males were paired (Table 2.1). To generate reciprocal F1 ESC (BC: C57BL/6J ´ CAST, and CB: CAST ´ C57BL/6J), the females were either C57BL/6J or CAST, crossed with a male of the reciprocal strain (Table 2.2). Individual E3.5 blastocysts were isolated in M2 media, and cultured in N2B27 media with 2i (1 μM of PD0325901, 3 μM of CHIR99021) and LIF on a layer of Mitomycin-C treated feeders. LIF was made in house (A. Bogutz, Lefebvre Lab). N2B27 medium was composed of 495ml of DMEM/F12-no phenol red (Gibco), 480 ml of Neurobasal medium (Gibco), 10 ml of B27 supplement minus vitamin A (Gibco), 5 ml of penicillin/streptomycin (Gibco), 5 ml of 200 μM L-glutamine (Gibco), 0.9 ml of 100 mM 2-mercaptoethanol, and 5mL of N2 solution. N2 solution was composed of 3.595 ml of DMEM/F12-no phenol red (Gibco), 0.5 ml of 25 μg/ml of insulin (Sigma), 0.5 ml of 100 μg/ml of apotransferrin (Sigma), 0.333 ml of BSA Fraction V (7.5%) (Gibco), 16.7 μl of 0.6 μg/ml progesterone (Sigma), 50 μl of 160 μg/ml putrescine (Sigma), and 5 μl of 3 μM of sodium selenite (Sigma). 40ml aliquots of N2B27 were stored at −80°C for up to 3 months. 45 For all the experiments described here, I used male ESC lines with normal chromosome number. For experiments involving Klf14 imprinting, I used F1 ESC with faithful imprinting of Mest (Table 2.3). ESCs were transitioned and maintained in standard ESM media (Gibco) containing 15% FBS (Hyclone, Premium Multicell), 1 mM sodium pyruvate (Gibco), 0.1 mM non-essential amino acids (Gibco), 0.1 mM 2-mercaptoethanol (Sigma), 2 mM L-Glutamine (Gibco), 50 µg/mL penicillin and streptomycin (Gibco), and 0.1X LIF. All cell lines were maintained in a 37°C incubator containing 5% CO2. Table 2.1 Chromosome count and sex of Mest WT and pKO ESC lines Line Sex Mest genotype % 40 chromosomes Mest 1.1 XY +/KO 93 Mest 1.2 XY +/KO 95 Mest 1.3 XY +/KO 89 Mest 1.4 XX +/+ ND Mest 2.2 XY +/+ ND Mest 2.3 XY +/+ 88 Mest 2.7 XY +/KO 78 Mest 3.1 XY +/KO 89 Mest 3.3 XY +/+ 85 Mest 3.4 XY +/+ 98 ND = not determined 46 Table 2.2 Chromosome count and sex of new F1 ESC lines Female Male Line Sex % 40 chromosomes C57BL/6 CAST BC1.1* XY 93 BC1.2 XX ND BC1.3 XY 95 BC2.1 XY 88 BC2.2 XX ND BC2.3 XY 91 BC2.4 XX ND CAST C57BL/6 CB1.1* XY 90 CB1.2 XX ND CB1.3 XY 95 *F1 ESC lines used in this study ND = not determined Table 2.3 Mest imprinting in F1 ESCs Allelic ratio Mat/(Mat+Pat) BC 1.1 gDNA 0.476 cDNA 0.239 CB 1.1 gDNA 0.530 cDNA 0.222 2.14 RNA extraction Samples were snap frozen on dry ice, or liquid nitrogen, and stored at -80°C. Total RNA was extracted using Trizol (Invitrogen Life Technologies, CA) according to the manufacturer’s directions and resuspended in 25-50 μl DEPC dH2O. 10 μl of RNA was treated with 1 μl RQ1 DNaseI (Promega) in 2.5 μl of 10x RQl buffer (Promega), 1 μl of 47 RNase inhibitor (Promega), and 10.5 μl of dH2O for 1-1.5 hours at 37°C. DNaseI was inactivated by incubation at 65°C for 15 min. 2.15 Reverse transcription Complementary DNA (cDNA) was generated using M-MLV reverse transcriptase (Invitrogen) and random pentadecamers (N15). 10 μl of DNase-treated RNA was added to 9 μl of the master mix (2 μl of N15, 5 μl dH2O, 2 μl 10uM dNTPs) and incubated at 65°C for 10 minutes. 19 μl of the second master mix (8 μl 5X first strand synthesis buffer (Invitrogen), 4 μl 0.1M DTT (Invitrogen), 0.5 μl RNasin, 6.5 μl dH2O) was added. 19 μl of the final mix was aliquoted into separate tubes as RT- controls. 1 μl of MMLV RT was added to the positively labelled tubes. All tubes were incubated at 42°C for 1 hour, and inactivated at 72°C for 15 minutes. 2.16 Quantitative RT-PCR Quantitative RT-PCR (qRT-PCR) experiments were performed using EvaGreen dye (Biotium) on a QuantStudio 3 Real-Time PCR system (Thermo Fischer Scientific). The qRT-PCR cycling conditions are as follows: 95°C 2 minutes followed by 35 cycles of 95°C 30 sec, 58-62°C 30 sec, 72°C 30 sec, and 79-85°C 1s plate read depending on the primer pair. Relative expression was calculated by normalization to Ppia expression, a marker identified as a robust housekeeping gene for mouse expression studies (Mamo et al. 2007). All other primers for qRT-PCR were designed using Primer Express 3.0 software, and ordered through IDT. All primer sequences are available in Table 2.4. 48 qRT-PCR results were analyzed using LinReg PCR software using the 2-ΔΔCT method (Livak and Schmittgen 2001; Ruijter et al. 2009). Ct values of technical triplicates were averaged and used to calculate relative expression. A two-tailed t-test was used to determine significance. Notably, as Klf14 is an intron-less gene, RT- samples were run as negative controls. 2.17 TOPFlash Assay ESC, MEFs, and vascular progenitors (VPs) were transiently transfected with pSTF (Veeman et al. 2003) and pRL-TK (Promega) via Lipofectamine 3000 (Promega) according to the manufacturer’s directions in 12-wells. The TOPFlash pSTF Wnt reporter plasmid contains 7 TCF/LEF1 binding sites driving Firefly luciferase expression. The pRL-TK plasmid, used as an internal control for normalization, comprised of a minimal promoter driving Renilla luciferase. The Wnt pathway was activated with either 30 mM LiCl (Sigma) for 6 hours, or 100 ng/ml rWNT3A for 16 hours (Peprotech). LiCl activates Wnt indirectly through inhibition of GSK3β. Firefly and Renilla luciferase activities were detected via the Dual-Luciferase reporter system (Promega) in white bottom 96-well plates according to the manufacturer’s protocol. Technical and biological triplicates were assayed. 2.18 Episomal system for MEST expression PCR primers Mest F1 and R1 were used to generate unique 5’ MluI, and 3’ NotI restriction sites, and introduce an ATG start codon at the Mest ORF from the WT Mest 49 expression construct: pPeg1-ORF (Lefebvre lab). The modified Mest ORF was subcloned into pPyCAG_IP (Niwa et al. 2002). The resulting plasmid contains a CAG promoter driving Mest cDNA and an IRES-puromycin. Dual FLAG and HA tags were added to the C-terminus of Mest by two rounds of PCR using primers 0395E, Mest R3a, and Mest R3b with Q5 DNA polymerase (New England Biolabs) producing the plasmid pPyCAG_MEST_FLAG_HA. Independent mutations of the histidine at positions 311 and 314 to alanine were performed using primers 0395E with H311Ar or H314Ar, generating H311A and H314A mutants, respectively. All plasmids were verified by Sanger sequencing (Genewiz). To express WT and mutant Mest, I employed an episomal system in HEK293T cells. Plasmids containing a polyoma origin of replication will be maintained as an episome in cells expressing SV40 large T antigen, such as HEK293T (Gassmann et al. 1995). The Mest expression constructs (WT, H311A, H314A) carried both a polyoma origin of replication, an SV40 origin of replication, and the puromycin resistance gene. HEK293T cells were used due to both their ease of transfection, relatively high protein productivity, and expression of SV40 large T antigen. Therefore, transfected plasmids were maintained in a semi-stable manner in HEK293T cells when cultured under constant puromycin selection. Importantly, employing an episomal system gives very high transfection efficiencies by supertransfection (Niwa et al. 1998) without integration of the plasmid. The pPyCAG-IP control (parental plasmid), and Mest WT, H311A, and H314A mutants were independently transfected into HEK293T cells by Lipofectamine 50 3000. Puromycin selection (2 µg/ml) was started the next day and maintained for two days post transfection. Cells were expanded onto 10-cm dishes, and cultured in PEFM + puromycin to maintain the episome. Cell pellets were stored at -80°C. 2.19 Western blot Cell pellets were lysed in a modified RIPA buffer (150 mM NaCl, 50 mM Tris-Cl pH8.0, 1% Triton X-100, 1 mM EDTA, 1X protease inhibitor for 20 minutes at 4°C with rotation, sonicated for 10 min (30 sec on, 30 sec off), and centrifuged 10,000 rpm at 4°C for 10 min. The resulting cell lysate was aliquoted and stored at -80°C. Cell extracts were prepared in 1X Laemmli sample buffer, and boiled at 95°C for 5 min. 10 μl of cell extract was run per well at 120 V for 15 min, and 150 V for 1-1.5hrs. Gels were transferred onto a PVDF membrane (Hybond-PLUS) at 100 V for 1hour at 4°C in transfer buffer (25 mM Tris, 190 mM glycine, 20% methanol). For immunoblotting, the membrane was blocked in Tris-buffered saline (20 mM Tris-HCl pH 7.5, 150 mM NaCl) with 3% BSA and 2.5% serum for 1hour at RT with shaking. The primary Flag antibody (Sigma F14725) was added at a 1:2000 dilution, and incubated o/n at 4°C. The next day, the membrane was washed with 1X TBS-T, incubated with 1:20,000 LICOR IR-Dye secondary antibody in blocking solution at 1hr RT, washed again, and visualized on the Odyssey imaging system (LiCOR Biosciences). 51 2.20 MEST peptide preparation for MS MEST protein was isolated using the ANTI-FLAG M2 Affinity gel (Sigma) using the “Batch-IP” protocol per manufacturer’s directions. Protein concentration was quantified using the bicinchoninic acid assay (BCA), and 1.25 mg/ml of protein was used to bind to 75 μl of resin for 1.5 hours at 4°C with rotation. Protein was eluted from the beads first, using 0.1 M glycine-HCl pH 3.5 (Sigma), neutralized with 1 M HEPES pH7.5 (Sigma) and secondly with 0.1 M glycine-HCl pH 10. Subsequent peptide preparation was performed with the Overall lab at UBC. Protein was reduced with a final concentration of 5 mM DTT at 37°C for 1hour, and alkylated with N-ethylmaleimide (Sigma) at a final concentration of 15 mM at 10 min in the dark. NEM was quenched with 1 M DTT. The pH of the samples was adjusted to pH 7.5-8, and split into two different digestion reactions. Trypsin and chymotrypsin were added to a final concentration of 1 µg/ul. CaCl2 was added to the chymotrypsin digest to a concentration of 10 mM. Samples were digested o/n at 37°C. The next day, samples were acidified with 0.5% formic acid to pH 3.3. MS stage tips were hand made. In brief, C18 filters were prepped with 100% acetonitrile, followed by Buffer A (2% Acetonitrile, 0.5% formic acid). The acidified sample was then loaded onto the filter. Residual detergents were removed with two washes of Buffer A. The resulting peptides were eluted in Buffer B (80% Acetonitrile, 0.5% formic acid), and put under a speed vacuum to remove the formic acid. The concentration of peptides was quantified by Nanodrop and loaded onto the mass spectrometer. 52 2.21 MEST GFP fusions COS7 cells, a gift from Dr. Robert Nabi, were used for all ER-localization related experiments due to their well-defined ER. Plasmids composing of GFP fusions to the N- and C-terminus of the entire MEST ORF, previously made by Connie Lee in the Lefebvre lab, were transfected into COS7 cells using Lipofectamine 3000 on gelatin coated coverslips. Coverslips were stained for actin using Phalloidin 594 (Thermo Fisher, ab176757) according to manufacturer’s directions, and counterstained using 1 µg/ml DAPI (Sigma). 2.22 Split-GFP Split-GFP utilizes the self-assembling fragments of 215 amino acids comprising GFP β-strands 1–10 (S1–10) and 16 amino acids comprising GFP β-strand 11 (S11) to visualize protein localization (Cabantous et al. 2005). Individually, the Split-GFP fragments do not produce fluorescence. GFP complementation only occurs when the fragments are within the same cellular compartment and able to interact. The traditional Split-GFP approach employs co-transfection of plasmids harboring the S1-10 GFP epitope, and a S11 fusion to the protein of interest. Variants of the S1-10 epitope allow for expression in either the cytosol (Sandio Biotech), or ER lumen (Zhong and Fang 2012). To both control for transfection efficiency, and visualize the ER, the calreticulin signal sequence-mCherry fragment from mCherry-ER-3 (Addgene #55041) was subcloned into both the ER and cytosolic S1-10 plasmids. The resulting plasmids 53 encompass either a cytosolic or luminal S1-10 epitope, in addition to a mCherry-ER marker. Therefore, all transformants are characterized by a red ER. For MEST topology experiments, a total of four S11-Mest fusions were generated. The S11 epitope was fused to either the N-terminus (N-S11), - after the signal peptide - C-terminus (C-S11), or internal to Mest (S176-S11, R263-S11). In general, S11 fusions were generated using two rounds of PCR with Phusion polymerase (Thermo Fisher) using the parental pPyCAG_Mest_FLAG_HA vector previously described. All primer sequences are available in Table 2.4. The S1-10 and S11 constructs were co-transfected into COS7 cells on gelatinized coverslips using Lipofectamine 3000 according to manufacturer’s directions. Puromycin selection (2 µg/ml) was started the next day for two days. 2.23 Coverslip fixation and processing Coverslips were incubated in fresh fixation reagent (3% PFA+0.2% GA in PBS) for 15 min, and washed in PBS-CM (PBS, 1 mM MgCl2, 0.1 mM CaCl2). Fluorescence was quenched using fresh 1 mg/ml sodium borohydride (Sigma) for 10 min with shaking, and washed with PBS-CM, and PBS. Coverslips were mounted with Vectashield (Vector labs), sealed with clear nail polish, and stored at 4°C in the dark. Imaging was performed using a Leica SP5 confocal microscope (LSI imaging core). 54 2.24 Generation of Mest gDMR KO The Mest gDMR was deleted in reciprocal F1 ESC using CRISPR-Cas9. Two short guide RNAs were designed to flank part of the gDMR to generate a ~2kb deletion encompassing the CTCF binding site. Individual sgRNAs were designed using the Wellcome Sanger Institute Genome Editing tools available at https://wge.stemcell.sanger.ac.uk/ (Hodgkins et al. 2015). The guides were cloned into a vector (pPuro2-hU6-gRNA-CBh-Cas9) containing the Cas9 endonuclease gene and conferring puromycin resistance (Bogutz et al. 2019). Vectors were transiently transfected into reciprocal F1 ESC using Lipofectamine 3000 (Invitrogen) per the manufacturer’s instruction. Puromycin selection (1 µg/ml) was started after 24 hrs and maintained for two days. After 7-12 days of culture, individual colonies were picked, expanded, and screened for the deletion by PCR and Sanger sequencing. PCR was performed with primers flanking the 5’ and 3’ sgRNA loci (Table 2.4). 2.25 SNP Pyrosequencing Pyrosequencing to analyze allele-specific expression was performed using the PyroMark MD system (Qiagen) according to the manufacturer’s instructions. PCR amplification was performed using the forward biotinylated primer (Biotin-Klf14 F3) and Klf14 R1. Two SNPs were analyzed to assay Klf14 imprinting per sample using amplification primers Klf14 S1 and Klf14 S2. Amplification and sequencing primer sequences are available in Table 2.4. A two-tailed t-test was used to compare B6:CAST 55 allele expression in F1 reciprocal hybrids. 2.26 Vascular progenitor cell differentiation ESCs were differentiated into vascular progenitors (VPs) as previously described (McCloskey et al. 2012; Yamashita et al. 2000). Approximately 30,000 ESCs were plated per 35 mm dish coated with collagen IV (Sigma). The differentiation medium was composed of a-MEM with no nucleosides (Sigma) with 10% FBS, 2 mM L-Glutamine (Gibco), 50 µg/ml penicillin and streptomycin (Gibco), and 0.05 mM 2-mercaptoethanol (Sigma). Plates were incubated for 4 days with no media changes. 2.27 FACs and flow cytometry Vascular progenitors (VPs) were dissociated using TrypLE Express, and the cell pellet was washed with FACS buffer (PBS with 2 mM EDTA, 2% FBS (Gibco). VPs were sorted with rat anti-mouse FLK1+ antibody (BD Biosciences). In brief, cells were blocked with 5% FBS, incubated with the primary FLK1+ antibody for 1hour at 4°C with rotation, washed three times with FACs buffer, and incubated with goat anti-rat Alexa488 for 30 min with propidium iodide (1X, Roche). Pellets were resuspended in FACS buffer and put through a single cell strainer. Samples were either analyzed by flow cytometry (BD LSRII-561), or given to the UBC Flow Cytometry Facility for sorting. 56 2.28 4C viewpoint design The strategy for designing allele specific viewpoints for 4C was based on allele-specific restriction enzyme sites. Primer sequences are available in Table A.1. The library generated would be composed of only one of the two alleles (ex. B6 or CAST). In this study, only the CAST allele is analyzed. The strategy implemented generates an allele-specific library, and does not require paired-end sequencing. 2.29 4C sample preparation Allele-specific in-nucleus 4C-seq was performed as before (Llères et al. 2019), and described in detail in a recent manuscript from our collaborators (Miranda et al. 2022). The MboI-NlaIII restriction enzyme pair were used. In brief, approximately 4-5 million cells were crosslinked with 2% formaldehyde for 10 minutes, and quenched with 1M glycine. Cells were washed with PBS, and the pellet was snap-frozen in liquid nitrogen for storage at -80°C. The cell pellet was lysed twice on ice for 10 min with lysis buffer: 10 mM NaCl, 10 mM Tris–HCl pH 8, 0.2% v/v NP-40 and 1X protease inhibitors. Following centrifugation for 5 minutes at 2500 g (4°C), nuclei were washed with 500 μl of cold lysis buffer, and resuspended in 100 µl 0.5% SDS for 10 min at 62°C while shaking in a Thermomixer (900 rpm). Triton X-100 was added to a final concentration of 1%, and incubated for 15 min at 37°C (900 rpm). Chromatin was digested for 4hours at 37°C (900rpm) with 400 U of MboI in 1X restriction buffer with BSA. 400 U of MboI was added every 4 hours, for a total of 1200 U incubated overnight at 37°C (900 rpm). MboI was inactivated at 65°C for 20 minutes (600 rpm). 990 µl of 1.5X ligation master mix 57 (150 μl commercial 10X Ligation Buffer, 757 μl H2O, 75 μl 20% Triton-X100, 8 μl 20 mg/ml BSA) was added, and incubated at 16°C for 15 minutes (900rpm). Digested chromatin was ligated using 5 µl of T4 DNA ligase (20 U/µl, Weiss units) for 4hr at 16°C (900rpm). Samples were de-crosslinked by incubation overnight at 65°C (900rpm). Proteins were digested using Proteinase K and 20% SDS for 4hr at 45°C (900rpm). DNA was purified by phenol-choloroform-IAA extraction followed by ethanol precipitation. DNA was resuspended in 100-200 μl of ultrapure water, and incubated for 1 hour at 37°C. The second digestion was performed using NlaIII (1 U/ug of material) overnight at 37 °C (750 rpm), and heat inactivated for 20 minutes at 65°C (600 rpm). The second ligation was performed in a total volume of 14 ml in 1X ligation buffer (660 mM Tris pH 7.5, 50 mM MgCl2, 50 mM DTT, 10 mM ATP) with 200 U of T4 DNA ligase for 4 hours at 16 °C, followed by 30 minutes at 20–25 °C (600 rpm). DNA was purified by phenol-chloroform-IAA extraction and ethanol precipitation, and resuspended in 100-200 μl of 10 mM Tris pH 8.0, and purified using QIAquick columns (QIAgen). The 4C material was quantified by Qubit dsDNA broad range (Thermo Fisher Scientific), and stored at -20°C. The efficiencies at each digestion and ligation step were evaluated by agarose gel electrophoresis. 2.30 4C-seq library preparation and sequencing 4C material was amplified by inverse PCR using primers flanking the viewpoint of interest, and incorporating unique indices as previously described (Table 2.4) (Matelot and Noordermeer 2016). PCR was performed using Expand Long Template PCR 58 system (Roche) per the manufacturer’s instructions. 75ng of material was used per PCR reaction. A total of 16 PCR reactions were pooled to generate complex 4C material. Pooled PCR reactions were purified using QIAquick columns, and visualized on a 1.5% agarose gel. 4C libraries were run on a single-end Illumina Nextseq2000 100 cycles P2 run (400 million reads). Samples were quantified, and pooled by the staff at the BRC, as part of the UBC Sequencing + Bioinformatics Consortium. 2.31 4C-seq data analysis 4C-seq datasets were mapped and translated into restriction fragments using c4ctus onto mm39 (https://github.com/NoordermeerLab/c4ctus). For the Mest gDMR viewpoint, reads were aligned using Bowtie2 (Langmead and Salzberg 2012). For the Klf14 distal viewpoint, reads were aligned using STAR and only uniquely mapped reads were considered (Dobin et al. 2013). Raw 4C-seq scores were generated based on the read density across valid restriction fragments. 4C-seq scores were smoothed using a running mean across 21 MboI-NlaIII restriction fragments. 4C-seq scores then normalized based on the sum of interactions of the 5 TADs encompassing the viewpoint to allow for comparison across different samples (Thierion et al. 2017). The coordinate for TAD boundaries in ESC on mm10 called from (Bonev et al. 2017) dataset were converted to mm39 using LiftOver. The region used for normalization on mm39 was Chr6: 30.39-31.25 Mb. The log2 ratio between 4C-seq scores between alleles was calculated using VisRseq (Younesy et al. 2015). BedGraphToBigWig (UCSC) was used to convert 4C-seq scores from bedgraph to bigwig format for visualization. 59 2.32 Allele-specific RNA-seq and ChIP-seq analysis Publicly available RNA-seq and ChIP-seq datasets referenced in this thesis are available in Table A.1. Allele-specific processing of RNA-seq was performed using MEA (Richard Albert et al. 2018). Processed reads were used to calculate RPKMs using VisR (Younesy et al. 2015). ChIP-seq was aligned using bwa (Li and Durbin 2009). Data was visualized using UCSC (Kent et al. 2002). 2.33 CTCF motif discovery CTCF motif analysis was performed using genome-wide predictions generated by HOMER (Heinz et al. 2010) and JASPAR (Castro-Mondragon et al. 2022). The CTCF in vivo ChIP-seq peak was obtained using UCSC TableBrowser in the mm10 assembly. The sequence was searched for the canonical CTCF motif using the CTCF position frequency matrix obtained from JASPAR (MA0139.1) using FIMO (Grant et al. 2011). Table 2.4 List of primers used in this study Primer name Sequence (5’-3’) Reaction Reference Genotyping 702A GTTATAGCCAGTCGAGTAAGTATGC Mest WT, KO (Lefebvre et al. 1998) 702C TCCCAGTGGATCACCTGAGC Mest WT (Lefebvre et al. 1998) IRES1 AGACCGCGAAGAGTTTGTCCTC Mest KO (Lefebvre et al. 1998) ZFy1a GACTAGACATGTCTTAACATCTGTCC Zfy1a Lefebvre lab Zfy1b CCTATTGCATGGACAGCAGCTTATG Zfy1a Lefebvre lab Mest 5’ F1 CCTTCCTCCCTCCCCTTAAT Mest gDMR KO This study Mest 3’ R1 CACCCAGCTGACACTGAAAA This study Mest 3’ F1 TTAGGAGGTGGTGGTGAAGC This study Mest 3’ R1 GTTTGCTTTGGTTTGTGGGT This study 60 Mest expression plasmid construction Mest F1 TAAGCCAAGCTTACGCGTATGGTGCGCCGAGATCGCTTG This study Mest R1 GGCTTCATCAACTCCTTCTGAGCGGCCGCAG This study Mest R3a CTGCGGCCGCTCATTTGTCATCGTCGTCCTTGTAGTCAGCGAAGGAGTTGATGAAGCC C terminus FLAG tag This study Mest R3b CTGCGGCCGCTCAAGCGTAATCTGGAACATCGTATGGGTAGAGCTTGACTTTGTCATCGTCGTCCTTG N terminus HA tag This study 0395E AGCAGGCCAGCATCG Mest Lefebvre lab H311Ar GTGTCGATTCTGGATGACGCCATTAGCCACTACCCAC Mest H311A This study H314Ar TGGATGACCACATTAGCGCCTACCCACAGCTAGAGG Mest H314A This study Split-GFP N-S11 Mest P2 CTGCACGAGTACGTGAACGCCGCCGGCATCACAGGCGACGGCGGCAGCGGCGGCGGCAGCGCCGCCTGGTGGGTCCAAGTAGGG S11 N terminus This study N-S11 Mest P3 CGAGTACGCGTACCATGGTGCGCCGAGATCGCTTGCGCAGGATGAGAGAGCGGGACCACATGGTGCTGCACGAGTACGTGAACG S11 N terminus This study C-S11 Mest P7 GTGCAGCACCATGTGGTCCCGGCTGCCGCCGCCGCTGCCGCCGTCGCCAGCGAAGGAGTTGATGAAGCC S11 C terminus This study C-S11 Mest P9 AGAGTCGCGGCCGCTTTATGTGATGCCGGCGGCGTTCACGTACTCGTGCAGCACCATGTGGTCCCG S11 C terminus This study Mest 263 S11 R1 GGCGTTCACGTACTCGTGCAGCACCATGTGGTCCCGGCTGCCGCCTCTTCTGAATTTCTTCCTTTG R263 S11 This study Mest 263 S11 R2 GAAGCAAGCGCTCCCACCCAGCGGCTGCCGCCTGTGATGCCGGCGGCGTTCACGTACTCGTGCAG R263 S11 This study S11 176 F CGGGCGGCAGCCGGGACCACATGGTGCTGCACGAGTACGTGAACGCCGCCGGCATCACAGGCGGCT S176 S11 This study S11 176 R CGAGCCGCCTGTGATGCCGGCGGCGTTCACGTACTCGTGCAGCACCATGTGGTCCCGGCTGCCGCC S176 S11 This study Mest gDMR CRISPR KO sgRNA1 targeting gDMR: GCCCACCCCATGGCGGGATC Mest gDMR This study 61 sgRNA2 targeting gDMR: CACTGCGCGGCACGATCTAG Mest gDMR This study qRT-PCR Ppia F CGCGTCTCCTTCGAGCTGTTTG Ppia (Mamo et al. 2007) Ppia R TGTAAAGTCACCACCCTGGCACAT Ppia (Mamo et al. 2007) Klf14 qF1 GGTGAGAGCAGCTAGACAATAG Klf14 This study Klf14 qR1 CTGGGACACACAACAGAAGA Klf14 This study Pyrosequencing Klf14 F3-biotinylated B)GATGAGCTAGCCCGCCACT Klf14 This study Klf14 R2 R1 GGCCAGAAGAGGAGCTGGAG Klf14 This study Klf14 R2 S1 AGTGCGACGACGACC Klf14 This study Klf14 M1 S1 TTTTCACCGGTGTGCGT Klf14 This study 4C-distal viewpoint Klf14-19 F1-P7 2.1 CAAGCAGAAGACGGCATACGAGATCGTGATGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 F1-P7 2.2 CAAGCAGAAGACGGCATACGAGATACATCGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 F1-P7 2.4 CAAGCAGAAGACGGCATACGAGATTGGTCAGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 F1-P7 2.5 CAAGCAGAAGACGGCATACGAGATCACTGTGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 F1-P7 2.6 CAAGCAGAAGACGGCATACGAGATATTGGCGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 F1-P7 2.7 CAAGCAGAAGACGGCATACGAGATGATCTGGTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTTTTTCAGCTCCTCCTGAACC 4C-seq Klf14 distal This study Klf14-19 R1-P5 AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATCTTTCTTCACCAAAATACCACTAGAATG 4C-seq Klf14 distal This study 62 Chapter 3: Characterization of MEST function 3.1 Background The imprinting and expression profile of the Mest gene has been well characterized (Lefebvre et al. 1997; Kaneko-Ishino et al. 1995; Kobayashi et al. 1997; Shi et al. 2004), but the function of the MEST protein is less clear. MEST codes for a highly conserved endoplasmic reticulum (ER) (Jung et al. 2011; Nikonova et al. 2008; Prudovsky et al. 2018) putative epoxide hydrolase (EH) belonging to the α/β-hydrolase fold superfamily (Kaneko-Ishino et al., 1995; Sansom et al., 2005). Other members of the α/β-hydrolase fold superfamily include lipases and esterases (Nardini and Dijkstra 1999). While MEST enzymatic activity has not been confirmed, the protein has been shown to bind cholesterol (Hulce et al. 2013), and lipids (Niphakis et al. 2015) in cell-based assays. In vivo, Mest is implicated as both a regulator of triglyceride metabolism in Dnmt1o KO placenta (Himes et al. 2015), and adipogenesis (Anunciado-Koza et al. 2017; Nikonova et al. 2008; Takahashi et al. 2005). These observations, combined with the embryonic growth retardation and postnatal growth restriction observed in Mest pKO mice (Lefebvre et al. 1998), suggest MEST may regulate growth as a modulator of lipid metabolism. While there is strong evidence implicating Mest in growth and adipogenesis, only a handful of studies have explored the mechanistic function of Mest in regards to these pathways. As MEST encodes a putative epoxide hydrolase enzyme, one can speculate that its substrate spectrum may include metabolites or fatty acid epoxides important in lipid signaling. 63 Here, I present further characterization of Mest function using a previously established single-gene Mest KO mouse model, and examine MEST protein topology in the context of metabolism. My results demonstrate that loss of Mest impacts placental metabolism in a sex-specific manner independent of gross placental defects in vivo. In vitro, my results suggest Mest may be a modulator of Wnt signaling. Taken together, my results highlight the function of MEST as a mediator of cell signaling, and also bring insight into the consequences of epigenetic alterations at the locus. 3.2 Results 3.2.1 Mest is not required for placental development Previous studies on Mest paternal KO (pKO) mice on a 129/Sv background observed lower embryonic and placental weights but otherwise normal morphology (Lefebvre et al. 1998). To rule out strain specific effects, the Mest KO mouse line was backcrossed >10 times onto the C57BL/6J reference strain background. Similarly, on the C57BL/6 background, pKO embryos were approximately 20% smaller than their WT littermates. This phenotype can be observed as early as E15.5 and persists postnatally (Figure 3.1A). This supports previous observations, and suggests that the role of Mest as a positive regulator of growth is not strain specific. The fetal/placental weight ratio, used as a measure for placental efficiency, was significantly different at E15.5 and E17.5 in Mest pKO animals (Figure 3.1B). KO embryos had a smaller fetal/placental weight ratio, suggesting a lower placental efficiency. 64 Aside from placental size, imprinted genes may also affect placental morphology and function. For example, Dlk1 deficiency is associated with embryonic growth retardation, no change in placental weights, but approximately a 10% reduction in the labyrinth zone (Appelbe et al. 2013). Gross placental morphological characterization of WT and pKO Mest placentae revealed normal formation of all three placental layers from E13.5 to E17.5. Furthermore, pKO placentae had similar junctional zone and labyrinth areas compared to WT (Figure 3.1C). These observations suggest Mest is dispensable for placental morphogenesis. Within the placenta, Mest is specifically expressed within the fetal endothelial cells of the labyrinth layer, lining fetal vessels where nutrient exchange occurs (Mayer et al. 2000). To assess the role of Mest in establishing this placental layer, labyrinth vasculature was characterized by IHC for laminin, a marker for the basement membrane where fetal blood vessels and endothelial cells sit (Figure 3.2A). Qualitatively, there were no major differences between WT and pKO placenta at E13.5, the stage preceding the observed in utero growth retardation, suggesting Mest deficiency did not “prime” the placenta for failure. Similarly, there were also no differences in laminin signal at E15.5, the stage where growth retardation was first observed. The lack of a placental phenotype before and after the peak of Mest expression at E14 (Mayer et al. 2000) suggests Mest is not critical for vasculature development. 65 Figure 3.1 Embryonic growth retardation in Mest pKO mice is not due to gross placenta defects. A) Embryonic and postnatal growth curves showing mean weight ± SD. Wildtype Mest+/+ females were mated to Mest+/KO males for paternal transmission of the transgene. Genotypes were confirmed by PCR, and lacZ staining of the yolk sac. The number of samples are indicated below the graph. B) Fetal/placental weight ratios showing mean ± SD. C) Morphometric analysis of placental layers represented as a volume percentage with gestational age. Analysis was performed on 3 WT and 3 KO placentae. Three sections around midline were analyzed for each placenta. 66 As the fetal vasculature is in close contact with trophoblast cells composing the trilaminar labyrinth, I next assessed if there were defects in trophoblast development within this compartment. I performed in situ hybridization (ISH) experiments for Gcm1 (Figure 3.2B), responsible for initiation of labyrinth branching and a marker for the labyrinth syncytiotrophoblast layer II. The labyrinth forms at approximately E8.5, and villi can be observed as early as E10.5. The E11.5 stage was chosen to best visualize the establishment of labyrinth branching. I did not observe any notable differences between Gcm1 signal between genotypes, suggesting that loss of Mest within the labyrinth was not associated with defects in chorio-allantoic branching or establishment of the syncytiotrophoblast layer II. The lack of an intrinsic phenotype within the placental labyrinth, where Mest is expressed, leaves open the possibility Mest may function extrinsically within the junctional zone. The junctional zone is populated by glycogen cells, which are theorized to be important for embryonic growth and development (Lefebvre 2012). I performed ISH for Pcdh12, a marker for glycogen trophoblast cells (Bouillot et al. 2006), in combination with Periodic acid Schiff (PAS) staining for total glycogen. Pcdh12+ glycogen cells begin to accumulate at E12.5, and migrate towards the decidua by E17.5. ISH for Pcdh12 at E17.5 suggested an overall higher number of Pcdh12+ glycogen cells in pKO placentae (Figure 3.2C). Contrasting ISH however, PAS staining revealed no significant differences in total glycogen content between genotypes (Figure 3.2D). Combined, these observations indicate loss of Mest may promote expansion of 67 the glycogen cell population, but not glycogen content. It is currently unknown what signaling mechanisms may be responsible for this phenotype. As an additional measure to characterize Mest pKO placentae, the transcriptome between WT and pKO placentae were analyzed. A total of 24 differentially expressed genes were identified (z score ≥1 and ≤-1, fold change ≥1.5) (Figure 3.3): 10 up in KO, and 14 down in pKO (including Mest) (Tables A.1, A.2). Notably, the expression of previously characterized placental markers Gcm1 and Pcdh12 were not significantly different. 68 Figure 3.2 Placental labyrinth architecture and glycogen composition in Mest pKO placenta. 69 A) IHC for laminin marking the basement membrane in E13.5 and E15.5 WT (n=3) and KO (n=3) male placenta. Dark brown staining represents laminin expression. Hematoxylin (blue) was used as the counterstain. B) ISH showing the expression pattern of Gcm1, a marker of labyrinth branching, at E11.5. Multiple sections for each genotype were assessed, and representative slides are shown. Sense probes (not shown) showed no staining. Dark purple staining represents gene expression. Nuclear fast red was used as the counterstain. C) ISH showing expression patterns of Pcdh12, a marker for glycogen cells, at E17.5. D) PAS showing glycogen content of E17.5 placenta. Scale bar: 1mm. lb: labyrinth layer, ch: chorion, jz: junctional zone, d: decidua. Figure 3.3 Gene expression analysis of Mest pKO placentae. Scatterplot of RNA-seq data from WT (n=3) and Mest pKO (n=3) E17.5 placentae. Data points are colored whether they are upregulated in KO (z score ≥1, blue), downregulated in KO (z score ≤-1, red), or not differentially expressed (grey). The threshold for differential expression is set at a fold change ≥1.5. 70 Taken together, Mest appears dispensable for placental development. On the C57BL/6 strain background, WT and pKO placentae are phenotypically similar based on placental weights and composition of placental layers. The expansion of Pcdh12+ glycogen cells within pKO placentae observed by ISH is confounded by the lack of an apparent increase in glycogen, suggestive of a defect in glycogen metabolism or sequestration. Alternatively, expansion of the Pcdh12+ population may have occurred as a response to the reduced metabolic capability in pKO placentae, thus making this observation secondary to a primary metabolic defect. However, the lack of Pcdh12 upregulation in pKO placentae by RNA-seq contrasts with what was observed by qualitative ISH, suggesting the ISH was underpowered to examine the relationship between Mest and glycogen. Altogether, my results were unexpected based on the expression profile of Mest and the growth retardation phenotype observed in pKO animals. My results contrast with the function of other imprinted genes whose disruption often manifests with a more significant placental phenotype (Coan et al. 2005; Lefebvre 2012). Based on these observations, Mest does not play a role in placental development, but rather may regulate growth through facilitating fetal-nutrient delivery as a buffer between mother and embryo. For example, Mest may modulate metabolism via sequestration of nutrients within the placenta, nutrients which would otherwise move freely in the bloodstream. 71 3.2.1.1 Mest deficiency is not associated with abnormal triglyceride levels in the placenta Placental metabolism is sensitive to disruptions in imprinting, as observed in the Dnmt1o KO model, in which DNAme imprints are stochastically lost (Himes et al. 2015). Loss of DNA methylation over the Mest gDMR led to approximately 2-fold upregulation of Mest mRNA levels and was most significantly associated with increased placental triglycerides (Himes et al. 2015). However, the Dnmt1o KO model is a complex system where a number of gDMRs are dysregulated, thus possibly confounding the interpretation of these results. To directly assess the role of Mest in placental metabolism, I took advantage of our KO model. If Mest is indeed positively associated with placental triglycerides as suggested by the Dnmt1o KO model, Mest pKO placentae should harbor lower levels of triglycerides. However, in the single-gene Mest pKO model, there were surprisingly no differences in placental triglycerides at E17.5, the same development stage that was analysed in the original Dnmt1o KO study (Figure 3.4A). These results indicate that the original Dnmt1o KO observation was due to secondary placental defects, or compounded by simultaneous dysregulation at other gDMRs. Alternatively, loss of DNAme over the Mest gDMR may have impacted expression of other imprinted genes within the domain, such as Klf14, as addressed in Chapter 4. The lack of transcriptional differences between Mest WT and pKO placentae (Figure 3.3), where the Mest putative 72 catalytic region is specifically deleted, further implicates the function of the Mest gDMR itself in Mest-independent functions. Figure 3.4 Effect of Mest deficiency on the placental metabolome A) Total triglyceride levels in WT (n=11) and pKO (n=5) E17.5 placentae, normalized to total protein content (p-value = 0.48). 73 B) Scatterplot of log2 normalized metabolite levels in WT male (n=3) and WT female (n=7) E17.5 placenta as determined by HPLC-MS. C) Scatterplot of log2 normalized metabolite levels in pKO male (n=4) and pKO female (n=5) E17.5 placentae. D) Scatterplot of log2 normalized metabolite levels in male WT (n=3) and pKO (n=4). E) Scatterplot of log2 normalized metabolite levels in female WT (n=7) and pKO (n=5). For all plots, detected entities are color-coded based on statistical significance as indicated. A FDR cutoff of 10% (Benjamini-Hochberg) was used. The raw intensity values for statistically significant entities are shown. Error bars represent mean ± SD. 3.2.2 Mest deficiency has minor effects on placental metabolism Having established that loss of Mest does not impact placental triglyceride levels in vivo, despite the protein’s putative interactions with both lipids and cholesterol, an untargeted metabolomics approach was used to broaden the search for dysregulated metabolites and their respective pathways in the mutants. Discovery metabolite profiling on E17.5 WT and pKO placentae was performed at the Analytical Core for Metabolomics and Nutrition (ACMaN) at BC Children's Hospital Research Institute by high performance liquid chromatography (HPLC) and mass spectrophotometry, and a total of 2641 entities were detected. Metabolites were identified based on accurate mass and compared to a reference library for tentative compound identification. While this approach enables global tentative characterization of the metabolome, a key limitation to this approach is the accurate identification of compounds. Only a minor number of metabolites (58) may be positively identified based on available standards, while the remaining metabolites are best fit to the library. 74 A comparative metabolomic approach was first used to characterize WT male (n=3) with WT female (n=7) placentae. There were only minor sex-specific metabolomic differences (p value ≤ 0.05, Benjamini-Hocherberg FDR 10%) (Figure 3.4B). Seven entities were detected as differential between WT male and female placentae, of which three metabolites were characterized: leucyl-glutamate, o-Benzosemiquinone, and 11Z-tetradecenoyl-CoA. Notably, these three metabolites were undetected in male placentae, indicating this observation may be an artifact. Similarly, Mest pKO male (n=4) and pKO female (n=5) placentae also shared a similar metabolic profile (Figure 3.4C). Only one entity was differential between the sexes following multiple testing correction, and was not assigned to any compound. The lack of sexual dimorphism in WT placentae conflicts with previous reports characterizing E18.5 C57BL/6J placentae by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). In these larger scale studies (n=28, 16), female E18.5 C57BL/6J placentae exhibited higher levels of metabolites within the carnitine family (Saoi et al. 2020; Gohir et al. 2019). While carnitine and its derivatives were detected in both male and female placentae in our study, there were no sex-specific differences. The discrepancy between my data and previous reports may be due to the lower power of our experiment, or variability in mouse facilities. Taking into account sexual dimorphism, male and female placentae were analyzed separately. In male placentae, Mest deficiency was associated with 14 differential entities (WT n=3, pKO n=4) following multiple testing correction (p value ≤ 75 0.05, Benjamini-Hocherberg FDR 10%)(Figure 3.4D). 6/14 entities were mapped to a compound, of which 3 metabolites were below the limit of detection in WT male placentae (leucyl-glutamate, GlcCer(d16:2(4E,6E)/20:0) Esi+16.684002, beta alanine) (Figure 3.4D). The remaining 3 metabolites: secobryononic acid, cysteinyl-aspartate, and 2-C-Methyl-D-erythritol 4-phosphate (MEP) were all higher in pKO male placentae. While there were subtle changes in the metabolomic profile in males, female WT (n=7) and Mest pKO (n=5) had only one differential entity: minoxidil, present at higher levels in the KO (Figure 3.4E). Notably, 1110 out of 2641 detected entities (42%) were not assigned to any specific compound. These entities may represent an uncharacterized structure/modification that has yet to be annotated. Due to the large number of uncharacterized entities, a less stringent statistical method forgoing multiple-testing correction was used for functional enrichment analysis using MetaboAnalyst to identify dysregulated metabolomic pathways, and structures (Pang et al. 2021). In male placentae, a total of 83 compounds (p value ≤ 0.05) were identified as being different between WT and pKO. Benzamides and fatty amides were strongly elevated in WT placentae (Figure 3.5A, Table A.3, A.4). Fold enrichment was calculated based on the number of compounds matched to a metabolite group/expected number of matches. Subsequently, qualitative enrichment analysis of metabolic pathways did not reveal any statistically significant altered pathways. However, two compounds involved in glycerophospholipid metabolism were identified in pKO placenta: phosphatidylcholine and lysophosphatidyl-choline. Phosphatidylcholine was not detected in 2/3 WT male 76 placentae, indicating this observation may be an artifact (Figure 3.5B). In female placentae, a total of 99 compounds were differentially identified between genotypes. Fatty amides were strongly elevated in female pKO placenta (Figure 3.5C, Table A.5, A.6). Aside from this group, there were no statistically significant enrichment of any other metabolite or lipid group. Accordingly, qualitative pathway enrichment analysis did not identify any dysregulated pathways. Taken together, Mest deficiency appears to impact the placental metabolome of males and females differently. Female placentae may be more robust to perturbations in Mest function, evidenced by a lack of differential entities detected. Although 14 differential entities were identified between WT and pKO male placentae, the identified compounds were not grouped within similar metabolic pathways, nor belonged to the same structural family. The less stringent statistical method did identify an enrichment of benzamides and fatty amides in WT male placentae. However, the fatty amide group is enriched in female KO placentae. Due to the untargeted metabolomics approach, the exact concentration and identification of fatty amides present in the placental samples is unknown. A targeted approach utilizing a panel of fatty-amide standards is needed to confirm the relationship between Mest and this metabolite group. Altogether, Mest deficiency is not associated with major defects in placental metabolism. 77 Figure 3.5 Placental metabolomic enrichment associated with Mest deficiency A) Dot plot representing enrichment ratio (hits/expected) and statistical significance of metabolite and lipid groups elevated in WT males. Dot size and coloring represent the enrichment ratio, and p-value respectively. Metabolite groups in bold are statistically significant (p value ≤ 0.05, Bonferroni FDR 10%). B) Raw intensity values for glycerophospholipid metabolism associated compounds in male WT and pKO placentae. Error bars represent mean ± SD. C) Dot plot representing enrichment ratio (hits/expected) and statistical significance of metabolite and lipid groups elevated in pKO females. 78 3.2.3 Mest is a Wnt inhibitor As I was unable to detect any metabolic differences in placentae between genotypes that could lead to growth retardation, I next aimed to document changes within the embryo. However, subtle changes in cell signaling may not be observable through analysis on bulk tissues in vivo. To overcome the inherent heterogeneity of embryonic tissue in vivo, I derived WT and KO mouse embryonic stem cells (ESC) and mouse embryonic fibroblast (MEF) lines using the Mest KO mouse model, to study the function of Mest in cell-based assays. Both overexpression (Li et al. 2014; Jung et al. 2011) and shRNA knockdown (Ji et al. 2017) experiments in cultured cells have suggested that Mest may act as an inhibitor of the Wnt pathway. Following up on these observations, I assessed Wnt signaling in my cell panel, expecting upregulation of Wnt signaling in Mest pKO cells. For these assays, I used the luciferase based TOPFLASH reporter system (Molenaar et al. 1996) to quantify the extent of Wnt activation, whereby β-catenin drives luciferase expression. I stimulated Wnt signaling through inhibition of GSK3β by LiCl (Klein and Melton 1996), or addition of recombinant WNT3A (Willert et al. 2003). Primed ESCs (grown in serum+LIF) harbor low endogenous levels of Wnt activity (Aulicino et al. 2020; Lyashenko et al. 2011), with different cell lines exhibiting variable responses to exogenous stimulation (Faunes et al. 2013). In line with published reports, only low levels of Wnt reporter activity were detected in Mest WT and pKO ESCs, and ESCs were also non-responsive to exogenous WNT ligands (Figure 3.6A). As Mest is 79 only lowly expressed in ESC, any phenotype present may have been missed. Therefore, ESC were differentiated into a heterogenous mixture of vascular progenitor cells (VPs), where both Mest expression and Wnt signaling are upregulated (Kanki et al. 2017). The differentiation involves a short four-day culture on a collagen IV matrix, and VPs were not additionally purified based on the mesodermal marker FLK1 in this experiment. Therefore, the population assayed was comprised of a spectrum of undifferentiated and differentiated ESCs. Figure 3.6 In vitro characterization of Wnt activity A) TOPFlash assay of WT and pKO ESCs, and differentiated ESCs (diff). B) TOPFlash assay of WT and pKO MEFs. The Wnt pathway was activated with either 30 mM LiCl (8hr) or rWNT3A (16hr). Experiments were performed with biological and technical triplicates. Graphs show mean ± SD. *p < 0.05. 80 There were no differences in Wnt activity in untreated (p=0.071), or rWNT3A treated differentiated ESCs (p=0.78), but increased Wnt activation in WT cells treated with LiCl only (p=0.045) (Figure 3.6A). These data suggested Mest may activate the Wnt pathway in VPs. This observation conflicts with the proposed function of Mest as a Wnt inhibitor from the published overexpression model, which may be due to the heterogeneity associated with the differentiation model. As an alternative to VPs, I next aimed to characterize Mest using a different mesoderm derived in vitro model: MEFs. ESC derived VPs represent an earlier mesodermal cell type capable of contributing to hematopoietic, smooth muscle, and endothelial lineages thus making this a heterogenous model (Kanki et al. 2017; Yamashita et al. 2000). MEFs were derived from E12.5 embryos and represent a more differentiated population. Similar to VPs, both Mest expression and Wnt signaling are active in MEFs. In MEFs, there were no statistically significant differences between genotypes in untreated cells (p=0.85) (Figure 3.5B). There was a trend of Wnt upregulation in KO MEFs stimulated with rWNT3A (p=0.26) that did not reach levels of significance. Upon treatment with LiCl, the Wnt pathway was upregulated approximately 3-fold in KO MEFs compared to WT (p=0.01). This data suggests Mest may be a Wnt inhibitor in MEFs, supporting published reports. Here, I assessed the role of Mest in Wnt signaling across a variety of in vitro models. Loss of Mest did not lead to changes in Wnt signaling between genotypes upon 81 rWNT3A treatment. I observed downregulation and upregulation of Wnt signaling only upon inhibition of GSK3β in differentiated ESC and MEFs respectively. My results indicate that Mest acts as a Wnt activator in VPs, but an inhibitor in MEFs. Due to these conflicting results, the extent by which transcription from the Mest locus regulates Wnt signaling remains to be determined. Nonetheless, my results in MEFs are consistent with published literature highlighting the function of Mest as a Wnt inhibitor. 3.2.4 MEST as a putative epoxide hydrolase My results up to this point have illustrated the downstream effects of Mest depletion. However, the exact mechanism linking Mest depletion with the observed phenotypes is unknown. MEST codes for a putative epoxide hydrolase localized to the endoplasmic reticulum with potential substrates including lipid epoxides. This sub-cellular localization of MEST supports its proposed function as a regulator of the maturation and glycosylation of the Wnt co-receptor LRP6, as previously suggested (Jung et al. 2011), and makes it unlikely for MEST to inhibit Wnt signaling at the level of ß-catenin/TCF interaction within the nucleus. In order to provide further insight into MEST protein function, I subsequently took a proteomic approach focussed on substrate(s) identification and protein structure characterization. Traditionally, epoxide hydrolase substrates have been identified through recombinant protein expression followed by substrate screening, as successfully performed for microsomal and soluble epoxide hydrolase (mEH, sEH) (Decker et al. 82 2009). However, this approach is limited by the substrates available to test. To overcome this limitation, I aimed to take an unbiased approach based on mass spectrometry and exploitation of the putative MEST active site for substrate trapping. Most epoxide hydrolases act via a 2-step reaction via a catalytic triad where a covalent intermediate between the enzyme and substrate is formed (Figure 3.7A). The catalytic triad is composed of a catalytic nucleophile-acid-base. MEST has a predicted catalytic triad: D147, D284, H311/H314. D147 acts as the catalytic nucleophile and attacks the epoxide ring to form a covalent ester bond with the substrate. The bond is then hydrolyzed when activated by the base H311or H314, which forms a charge relay system with the acidic D284. For MEST, there are two possible histidine residues that may act as the base within the catalytic triad: H311 or H314. First, I characterized the tertiary structure of MEST using the recently established AlphaFold protein prediction database (Jumper et al. 2021). If MEST does indeed contain a functional catalytic triad, one would expect those residues to be close together in 3D space. Indeed, the predicted structure of MEST does support its proposed function as an enzyme (Figure 3.7B). MEST was predicted to be a globular-type protein. The active site residues neighbor each other in 3D space, and a putative epoxide-coordinating tyrosine residue (Decker et al. 2012) was also localized within this domain. Furthermore, the catalytic nucleophile (D147) was situated at the elbow formed between a predicted β-sheet and the following α-helix. This ‘nucleophilic elbow’ is a common 83 characteristic of catalytic triads within the α/β hydrolase family (Nardini and Dijkstra 1999). Combined, these observations strengthened the argument that MEST contains a functional catalytic triad, and thus gives support for subsequent substrate identification experiments. The experimental approach for MEST substrate identification was based on the reaction dynamics of catalytic triad enzymes, where the substrate is at one point covalently attached to the enzyme. To capture this enzyme-substrate intermediate, we attempted to prevent the hydrolysis of this covalent bond via mutation of the catalytic histidine. There are two histidine residues within the putative catalytic triad in MEST, which were mutated to alanine individually generating two mutant lines: H311A and H314A. We hypothesized that the substrate would be trapped on the catalytic aspartate residue (D147) in H311A/H314A mutants. The substrate-modified peptide should result in a different MS/MS spectrum when compared to WT. For protein purification, dual FLAG and HA tags were added to the C-terminus of Mest. The expression construct was subsequently transfected into HEK293T cells, and the presence of MEST in cell lysates was confirmed by Western blot, with antibodies for either FLAG or HA. There was no size difference between WT or mutant MEST constructs, and the detected protein was of the expected size, at approximately 40kDa (Figure 3.7C). We expected the substrate to be a small metabolite, therefore we did not expect to detect a size difference of the mutant proteins upon migration on SDS-PAGE 84 gels. Intriguingly, I observed two bands on the western blot at 40kDa and slightly lower, suggesting cleavage or post-translational modifications of the protein. Figure 3.7 Attempted identification of MEST substrate(s) by mass spectrometry A. MEST has a predicted catalytic triad: D147 (red), H311/H314(blue), and D284 (purple) which may act via a 2-step reaction mechanism. The reaction mechanism is described in the text. B. Prediction of MEST structure using AlphaFold, and visualized by ChimeraX (Jumper et al. 2021; Goddard et al. 2018). The predicted transmembrane domain (blue), and residues of the putative catalytic triad are highlighted. 85 C. Western blot detection of WT MEST and two single site mutants, H311A and H314A, in HEK293T cells using anti-FLAG or anti-HA antibody. D. Representative MS spectrum characterizing the D147-peptide sequence (LSHDYGDIVAQ) in WT MEST lysate. For MS, WT and mutant MEST proteins were purified from HEK293T cell lysates using a FLAG antibody. The Overall lab performed a trial tandem mass spectrometry (MS/MS) run on purified WT lysate digested with either typsin or chymotrypsin. The traditional approach to protein characterization by MS includes proteolytic digestion, where the spectra of the obtained peptides is compared to a peptide library. Protein identification is subsequently determined based on the mapped peptides. The substrate-trap approach used in this thesis utilizes the traditional MS workflow. If successful, the substrate should be covalently bound to the catalytic D147 residue resulting in a “substrate-modified peptide.” The resulting modified peptide should therefore have a different MS spectrum when compared to the WT unmodified peptide. The spectrum of the WT unmodified peptide digested with either trypsin/chymotrypsin is predicted in silico. Accordingly, the MEST peptide containing the catalytic D147 was detectable by MS, indicating that the IP and MS parameters were suitable (Figure 3.7D). As we predicted that the substrate would be covalently bound to D147, resulting in a “substrate-modified peptide”, it was imperative that we were able to detect this wild-type 86 fragment. Subsequently, WT, H311A, and H314A lysates were immunoprecipitated and analyzed. MEST and the D147-peptide were detected in WT, H311A, and H314 lysates. However, conventional database searches with MSFragger and Byonic were unable to identify any novel peaks in the mutant (Kong et al. 2017; Bern et al. 2012). A number of caveats of the experiment hindered identification of putative substrates. It is unknown whether the substrate(s) are present in our cell line, if the substrate-trap actually worked for MEST, or if the covalent modification is stable through MS analysis. Complexities involving protein-protein interaction, or substrate channelling may also hinder in vitro discovery. Furthermore, a human cell line was used for expression of murine Mest. Therefore, the MEST protein produced may have been misfolded, or non-functional. 3.2.5 Characterization of MEST topology within the ER As my experiment in identifying MEST substrates was inconclusive, I took a different approach in characterizing the protein based on its localization to the ER. The ER is the principal site of protein production and maturation. The ER is also the site of lipid synthesis and transport (Wilfling et al. 2013). The orientation of resident ER proteins within the membrane may provide further insight into their function. The putative catalytic site of MEST may face either the ER lumen or cytosol, therefore giving clues as to possible substrates, co-factors, and the site of biochemical reactions implicating MEST. 87 For example, similar investigations into the relationship between structure and function have been performed on diacylglycerol O-acyltransferase 2 (DGAT2). DGATs are involved in synthesizing triacylglycerol, destined for storage within lipid droplets. The active site of DGAT2 was determined to face the cytosol, where it catalyzed the production of triacylglycerol from cytosolic acyl-CoA (Stone et al. 2006). The resulting triacylglycerol is stored within the growing lipid droplet forming within the cytosolic leaflet of the ER. Based on the mm10 annotation of the Mest locus, there are three main mRNA isoforms expressed due to alternative promoter usage (Figure 3.8A). The major Mest isoform 2 initiates from exon 1 which overlaps the maternal gDMR, methylated during oogenesis. The oocyte-specific isoform Mest variant 3 initiates upstream of exon 1 at an oocyte-specific CGI promoter. The alternative exon usage results in different N-terminal domain between these two isoforms. The N-terminus of proteins often harbors signal peptides required for protein cellular localization. For proteins to be retained in the ER as opposed to entering the secretory pathway, structural motifs such as targeting, retention, or retrieval signals must be present. Well-studied ER motifs include the C-terminus KDEL sequence (Gomord et al. 1999), and a specifically positioned N-terminus di-arginine (RR) motif (Schutze et al. 1994). This RR motif has been shown to interact with coatomer (COPI) complexes required for retrograde transport from the Golgi back to the ER (Michelsen et al. 2005) 88 Figure 3.8 In silico characterization of MEST isoforms A) UCSC snapshot illustrating DNAme and RNA-seq in MII oocytes, and ESC: MII DNAme (Wang et al. 2014), ESC DNAme (Li et al. 2015), MII RNAseq (Zhang et al. 89 2016), and ESC RNAseq (Bouschet et al. 2017b). The TSS for Mest isoforms are highlighted (light blue). B) Transmembrane domain predictions for MEST variants 2 (major) and 3 (oocyte) determined by TMHMM (Möller et al. 2001). The catalytic residues of MEST, and the N-terminus sequence encompassing the RR motif are indicated. C) Hierarchical tree representing subcellular localization predictions for MEST variants 2 and 3 generated by DeepLoc (Almagro Armenteros et al. 2017). The major MEST variant (isoform 2) contains an N-terminus RR motif at positions 3, and 4, absent from the oocyte-specific isoform (Figure 3.8B). This observation suggested that these two MEST isoforms may have different cellular localizations. Indeed, localization predictions using the DeepLoc algorithm (Almagro Armenteros et al. 2017) predicted that the oocyte-specific MEST isoform is soluble, contrasting with the endoplasmic reticulum localization of the major MEST isoform (Figure 3.8C). This observation was also supported by the weaker probability for predicted transmembrane domains in the oocyte isoform by the protein topology predictor transmembrane hidden Markov model (TMHMM) (Möller et al. 2001), whereas up to three transmembrane domains were predicted for the major MEST isoform. While the oocyte-specific Mest isoform is highly expressed in oocytes, the protein itself has not been characterized in the literature. Transcription of the oocyte isoform is predicted to be required for establishment of DNAme at the gDMR during oocyte growth 90 (Chotalia et al. 2009; Xu et al. 2019; Brind’Amour et al. 2018), but it remains to be determined if the oocyte MEST protein is functional or has any biological significance. Notably, MEST peptides have been detected in two separate proteomic screens in mouse MII oocytes (Wang et al. 2010; Pfeiffer et al. 2011), suggesting that translation of the mRNA does occur. However, the relative abundance of MEST protein in oocytes is at low to moderate levels. For this thesis, the function and localization of the major MEST isoform is discussed. The N-terminus of the major MEST isoform harbors both a highly predicted transmembrane domain, as well as a di-arginine motif required for ER localization. Aside from this motif, proteins often harbor additional N-terminus signal peptides (SP) essential for ER targeting. To characterize the predicted N-terminus ER localization signal, I transfected COS7 cells with plasmids expressing GFP fused to either the N or C terminus of MEST (Figure 3.9). COS7 cells were used due to their ease of transfection and well-defined ER. As expected, GFP fusion to the C-terminus of MEST (MEST-GFP fusion) resulted in reticular GFP signal indicative of the ER. However, GFP fusion to the N-terminus (GFP-MEST), disrupting both the predicted ER localization signal and positioning of the di-arginine retrieval motif, resulted in some reticular signal but also abundant protein aggregation. This aggregation may possibly reflect protein accumulation within the Golgi due to disruption of the di-arginine motif required for retrograde transport. These results demonstrate that the N-terminus, where the putative 91 localization signal and RR motif reside, is important in MEST ER localization and provides a foundation for further characterization of protein topology. Figure 3.9 The N-terminus of MEST is important for correct protein localization in COS7 cells. Characterization of localization by GFP fusion to the N or C terminus of MEST by confocal microscopy (Leica SP5). Constructs were transiently transfected into COS7 cells, and counterstained with DAPI (blue) and Phalloidin (red). Cartoon depictions of the MEST-GFP constructs are indicated: GFP, signal peptide (SP), transmembrane domain (TM). Cells were counterstained with DAPI (blue) and Phalloidin (red). 92 After confirming that the MEST N-terminus is critical for localization, I next characterized the protein’s membrane topology within the ER. The ER is made up of a continuous network of membranes, which separates the ER lumen from the cytosol. MEST has anywhere from 1 to 3 predicted transmembrane domains (Figure 3.8B), and characterization of the compartment into which the putative catalytic triad resides would further our understanding of possible MEST substrates. Additionally, the residues of the putative catalytic triad may be on the same, or on different sides of the ER membrane. If the putative active site is situated on opposite sides of the ER membrane, the observation would argue against MEST as a functional hydrolase. MEST ER topology was characterized using the Split-GFP system (Figure 3.10A). Split-GFP is a bipartite system involving two self-assembling GFP fragments (Cabantous et al. 2005). The small GFP S-11 epitope is fused to the protein of interest, and only produces fluorescence upon complementation with the larger GFP S1-10 polypeptide, when both are allowed to interact in the same cellular compartment. The traditional Split-GFP system employs co-transfection of two plasmids encoding a S11-protein fusion and S1-10 epitope. However, a limitation of this method was the lack of a positive transfection control, and inability to visualize the ER. Therefore, the system was modified by integrating a mCherry-ER reporter into the S1-10 expression construct, which acts as a positive control targeted to the ER. Four S11-MEST constructs were designed. The GFP-S11 epitope was added to the N and C termini of MEST, as well as at two internal positions, after S176 and R263. For the N-terminal fusion, the S11 93 epitope was inserted following the predicted ER localization signal of MEST to allow for appropriate localization. S176 was chosen due to its proximity to the catalytic nucleophile D147. R263 was chosen as it is the amino acid before the last predicted transmembrane domain. The S11-N terminal fusion produces GFP fluorescence only when co-transfected with the cytosolic S1-10 (Figure 3.10B). Conversely, both internal-S11 and S11-C terminus fusions only produced GFP in the ER lumen, as shown by the colocalization of signal with the mCherry-ER fusion. These results suggest that MEST is a type II transmembrane protein, where the N terminus resides in the cytosol and the C terminus (and active site) resides in the lumen (Figure 3.10C). As the putative active site was localized within the ER lumen, the site of protein synthesis and glycosylation, MEST may play a role in an aspect of post-transcriptional regulation, or act on substrates within this compartment. 94 Figure 3.10 MEST topology in the endoplasmic reticulum by Split-GFP. A. Schematic of the Split-GFP system comprised of the GFP β-strands 1–10 (S1–10) and GFP β-strand 11 (S11). Complementation and fluorescence occur only when both fragments are localized to the same cellular compartment and interact. B. Split-GFP experiments using S11 constructs co-transfected with either (mCherry-ER)-cytoplasmic S1-10 or (mCherry-ER)-ER S1-10 in COS7 cells. The S11 epitope was fused to the N/C termini, and at S167 and R263. Cartoon illustrating the location of the signal peptide (SP), S11 epitope (green), and predicted transmembrane domain (grey) within MEST. Cell nuclei were stained with DAPI. C. Cartoon illustrating a possible configuration of MEST within the ER. The amino acids of the predicted catalytic triad, and locations of the inserted S11 epitopes are highlighted. 95 3.3 Discussion Mest has been shown to play roles in embryonic growth and adipogenesis. Here, I further characterized the role of Mest in developmental growth pathways. My observations in pKO mice indicate that Mest is not required for placental development, and is not associated with major defects in placental metabolism. The lack of any placental phenotype contrasts with the high expression of Mest within this tissue. Furthermore, loss of Mest was not associated with defects in placental triglyceride metabolism, as previously suggested by the Dnmt1o KO model. Notably, the Dnmt1o KO model is unable to attribute the lipid phenotype to solely the Mest gDMR or Mest upregulation. Accordingly, the lack of a triglyceride phenotype in the single-gene Mest pKO placentae suggests other gDMRS or imprinted genes are implicated. For example, loss of methylation at the Peg10 DMR was also reported to be negatively associated with placental triglycerides but not statistically significant. The combinatorial effect of dysregulation at the Mest and Peg10 gDMRs may be responsible for the phenotype. Alternatively, it is also possible that the phenotype is only present upon Mest overexpression. Another possibility explaining the lack of downregulated triglycerides in Mest pKO placenta, may be due to insufficient power of the experiment. Mest deficiency may be associated with only a minor phenotype, which this study was too underpowered to detect. Phenotypic differences may have been observed if Mest KO mice were 96 challenged (ex. high-fat diet). Furthermore, while the original Dnmt1o KO model was on a 129/SvTac strain background, our Mest KO model was on the C57BL/6 background leaving open the possibility of strain-specific effects. For example, C57BL/6 mice are more susceptible to adverse metabolic outcomes such as higher body weight, and hyperglycemia (Sabidó et al. 2013; Berglund et al. 2008). Therefore, our single-gene Mest KO model may not be appropriate for direct comparison with the Dnmt1o KO study. Altogether, my results suggest Mest does not play a large role in placental development or metabolism. The function of MEST in the placenta may be redundant or compensated by homologous proteins. MEST encodes a putative epoxide hydrolase (EH). There are five known mammalian EH containing a/β hydrolase folds: soluble EH (sEH), microsomal EH (mEH), EH3, EH4, and putatively MEST (Decker et al. 2009; Marowsky et al. 2010). The biological relevance, structure, and substrate spectra of mEH and sEH have been extensively characterized. In general, mEH and sEH are responsible for acting on xenobiotic metabolites and endogenous signaling molecules, respectively. However, there have been reports on catalytic promiscuity within this protein family, suggesting that epoxide hydrolases may have overlapping substrate spectra. For example, both mEH and sEH are capable of hydrolyzing cytochrome P450-derived lipid metabolites such as epoxyeicosatrienoic acids (EETs) (Edin et al. 2018). It is possible that loss of MEST in the placenta was compensated by the function of mEH, sEH, or other proteins within the family which are also expressed in the placenta. 97 MEST is most homologous to the microsomal EH (mEH) based on sequence homology. mEH encodes for a type I ER protein with a luminal N-terminus, cytosolic C-terminus, and an active site facing the cytosol (Holler et al. 1997; Friedberg et al. 1994). My results indicated that the putative active site of MEST faces the ER lumen and is a type II ER protein, with a cytosolic N-terminus and luminal C-terminus. Due to the differential cellular localizations between MEST, mEH and cytosolic sEH, it remains to be determined if MEST shares their substrate spectra if MEST is indeed a functional enzyme. Due to its luminal localization, MEST may play a larger role in hydrolyzing metabolites destined to be trafficked to other parts of the cell. As mEH and sEH are localized to the cytosolic face of the ER and cytosol/peroxisome, respectively, these proteins may play more important roles in hydrolyzing substrates subject to intracellular diffusion. Overall, my protein topology results also complement the proposed function of MEST as a modulator of LRP6 glycosylation and Wnt signalling, as the ER lumen is the major site of N-linked glycosylation. Regulation of Wnt signaling may occur at the level of receptor-mediated activation at the cell surface, β-catenin stabilization within the cytoplasm, or at the level of transcriptional regulation at the nucleus. LRP6, a Wnt co-receptor, activates Wnt signaling at the first stage of the Wnt pathway. The glycosylation of LRP6, and subsequently Wnt signalling was shown to be inhibited upon Mest overexpression (Jung et al. 2011). Similarly, various models of Mest depletion and overexpression have also suggested that Mest acts as a Wnt inhibitor (Prasad et al. 2021; Jung et al. 2011; Li et 98 al. 2014; Ji et al. 2017). Our results in Mest pKO cells partially support previously published data: Mest was shown to be a Wnt inhibitor in MEFs, but a Wnt activator in unsorted differentiated vascular progenitor cells. It is important to note that both MEFs and vascular progenitor cells represent a mixed population with varying levels of endogenous Wnt, Mest, and miR-335 activity. In these experiments, MEFs may represent a less heterogenous, and thus better system to study Wnt signaling. In MEFs, we were only able to detect differences in Wnt signaling between genotypes that reach statistical significance upon Wnt stimulation with the GSK3β inhibitor LiCl. Mest pKO MEFs had approximately 3-fold higher levels of Wnt signaling upon LiCl treatment. We did not observe significant levels of upregulation in pKO MEFs when treated with rWNT3A. This conclusion is at odds with the previously discussed relationship between MEST and LRP6 in HEK293T (Jung et al. 2011). We expected Mest pKO MEFs to have increased availability of LRP6, and therefore be more receptive to rWNT3A ligands. The observation that WT and KO MEFs shared similar levels of Wnt signaling upon rWNT3A treatment indicated that Mest may not play a major role at this initial step of receptor-mediated activation. One explanation for this discrepancy between published data and our results may be their use of an ectopic expression model. Mest overexpression may have resulted in confounding factors involving post-transcriptional regulation, or improper localization of the protein. Therefore, the relationship between LRP6 maturation in the context of MEST overexpression may not be biologically relevant. 99 Our results are also confounded by feedback mechanisms involving Wnt signaling. The microRNA miR-335, encoded from intron 2 of Mest and co-regulated with Mest is involved in Wnt activation, through targeting the Wnt inhibitor DKK1 (Zhang et al. 2011; Lin et al. 2014). Based on these observations, Mest and miR-335 have opposing effects, and may be in a feedback loop with Wnt signaling. Indeed, a majority of studies highlighting impaired adipogenesis or aberrant Wnt signaling due to Mest depletion by shRNA have failed to address the confounding expression of miR-335 (Jung et al. 2011; Prasad et al. 2021). Due to the limitations of this study, I was similarly unable to fully discriminate this function of Mest from miR-335 in our KO model. Additionally, the traditional ligands used for activation of Wnt signaling (LiCl, rWNT3A) are not specific to receptor complexes. For example, the ligands are unable to discriminate between LRP5 or LRP6 mediated activation. Recently, synthetic agonists have been developed that activate Wnt signaling in a receptor subtype specific manner. Examples of surrogate Wnt agonists include chimeric Fc fusion proteins, encompassing specific LRP and FZD binding domains (Gumber et al. 2020; Chen et al. 2020; Janda et al. 2017). Treatment of cells with these surrogate Wnt agonists leads to receptor specific activation and dimerization. The implementation of these specific agonists in future experiments may provide further insight into Mest function. In conclusion, there are two possible avenues by which Mest may influence growth: via Wnt-dependent and Wnt-independent mechanisms. Firstly, my results 100 demonstrated that Mest is indeed a Wnt inhibitor in MEFs. Functionally, MEST may have a role in direct modification of Wnt ligands, other than LRP6, within the ER lumen. Alternatively, Wnt inhibition by Mest may be a secondary effect. The β-catenin destruction complex responsible for Wnt activation has roles aside from its namesake function. For example, in the absence of Wnt signaling, the complex has been shown to repress macropinocytosis (Albrecht et al. 2021). Secondly, MEST may influence growth pathways via Wnt-independent mechanisms through modification of signaling metabolites, in keeping with the function of other homologous epoxide hydrolases. These metabolites may be fatty acid epoxides such as cytochrome P450-derived EETs, as in the case for mEH. 3.4 Conclusion Growth retardation observed in Mest pKO embryos is independent of gross placental defects, but may be attributed to Wnt pathway dysregulation. Topological characterization of MEST within the ER lumen supports its putative function as an enzyme, possibly acting on fatty acid epoxides destined for intracellular transport. My results leave the outstanding questions: Is the metabolic phenotype associated with the Mest gDMR in Dnmt1o KO placenta due to dysregulation of other imprinted genes within the domain? I address this area of interest in Chapter 4. 101 Chapter 4: Characterization of the mechanism driving Klf14 imprinting 4.1 Background The sub-proximal end of mouse Chr6 contains an imprinted domain comprised of the paternally expressed gene Mest and the maternally expressed genes Copg2 and Klf14. Transcription from the Mest promoter produces three different paternally expressed RNAs: the Mest/Peg1 mRNA (Sado et al. 1993; Kaneko-Ishino et al. 1995), the intronic miR-335 (Hiramuki et al. 2015) and the extended MestXL transcript regulating allelic usage at the neighbouring Copg2 gene in neuronal tissues (MacIsaac et al. 2012). The mechanism underlying Klf14 imprinting is still unknown. Previous work showed that Klf14 expression is lost in embryos lacking maternally inherited DNAme genome-wide, paradoxically implicating oocyte-derived DNAme as essential for Klf14 expression in cis (Parker-Katiraee et al. 2007). The only known gDMR in the domain is found at the Mest promoter. This CpG-rich sequence acquires maternal DNAme in developing oocytes and maintains methylation uniquely on this allele throughout development (Lucifero et al. 2004; Lefebvre et al. 1997). In addition to promoting paternal expression of Mest, the Mest gDMR also contains an allele-specific CTCF binding site (Prickett et al. 2013). CTCF binding is effectively blocked by DNAme within or neighboring its consensus binding site, suggesting a direct mechanism for allelic CTCF binding to the unmethylated paternal allele of the Mest gDMR (Mukhopadhyay et al. 2004; Wiehle et al. 2019). Here I investigate the chromatin structure at this imprinting domain in the context of sub-TAD organization. I developed an in vitro model to study Klf14 imprinting 102 and apply allele-specific CTCF binding and high-resolution 3D chromatin conformation assays to characterize the structure of the Mest-Klf14 imprinting domain. I show that allelic CTCF binding at the Mest gDMR is responsible for establishing paternal allele-specific sub-TADs. By CRISPR/Cas9 mutagenesis of the Mest gDMR in ESCs, I show that deletion of the unmethylated paternal allele leads to loss of imprinting at Klf14. This is the first study to examine allele-specific chromatin organization at the Mest-Klf14 imprinting domain and to implicate sub-TAD formation by a maternal gDMR in imprinted gene regulation. 4.2 Results 4.2.1 Developmental dynamics of imprinted Klf14 expression Klf14 was first identified as a maternally expressed gene in reciprocal BL6´JF1 F1 embryos (Parker-Katiraee et al. 2007). Klf14 was shown to be strictly imprinted in all embryonic and extraembryonic tissues tested at E15.5, despite the lack of allele-specific histone modifications at the CGI promoter. As there was no data at earlier timepoints, however, the relationship between Klf14 imprinting acquisition and transcription in the context of development remained to be determined. To further understand the regulation of Klf14 imprinting, I mined publicly available expression datasets from F1 tissues (Figure 4.1A). Klf14 is only very weakly expressed in ESCs (Andergassen et al. 2017), and was not detected in the inner cell mass (ICM) (Zhang et al. 2016). Postimplantation, Klf14 expression was not detected prior to E9.5 in 103 the embryo (Babak et al. 2015, 2008), but visceral endoderm (VE) shows biallelic expression at this stage (Andergassen et al. 2017). Klf14 was highly expressed and imprinted in the placenta and tongue at E16.5 and P3 respectively (Andergassen et al. 2017; Babak et al. 2015), and was also imprinted in E16.5 tissues showing lower levels of expression, such as liver and heart. Mining publicly available datasets, I also investigated the allelic distribution of a variety of canonical and non-canonical imprinting marks at the Mest and Klf14 promoters. As expected for a canonical imprinted DMR of gametic origin, the Mest gDMR shows ~50% DNAme in mouse embryonic stem cells (ESCs) (Li et al. 2015) (Figure 4.1B). ZFP57, a DNAme-dependent KRAB zinc finger protein responsible for maintaining allelic DNAme at gDMRs during preimplantation development (Li et al. 2008), is bound at the gDMR in undifferentiated F1 ESCs specifically on the methylated maternal allele (Figure 4.1B) (Strogantsev et al. 2015). The unmethylated paternal allele however, is specifically bound by CTCF in adult brain (Prickett et al. 2013). In the ICM, the Mest promoter lacks a strong H3K27me3 signal (Zheng et al. 2016), and low expression is accompanied by low levels of H3K4me3 on the paternal allele (Zhang et al. 2016). The gDMR is also marked by H3K9me3 in ICM, but the allelic nature of this repressive mark cannot be determined due to the lack of SNPs in the dataset mined (Wang et al. 2018). 104 Figure 4.1 Klf14 imprinting arises early in differentiation A) Imprinting and levels of Klf14 mRNA expression in mined RNA-seq data from F1 CAST´ FVB mice. B) Visualization of allele-specific modifications at the Mest and Klf14 loci showing allele-agnostic (total; grey), and allele-specific (maternal: red, paternal: blue) modifications. Data includes DNAme, ChIP-seq for CTCF, and ZFP57, and classical imprinting marks: H3K27me3, H3K4me3, and H3K9me3 from different F1 hybrids with C57BL/6 females. CGI: CpG island. C) DNAme profiles at the Klf14 locus, showing WGBS data from germ cells and adult mouse tissues. Blue lines highlight annotated unmethylated regions. CGI: CpG island. 105 In contrast to what is observed at Mest, DNAme and ZFP57 binding are absent at the CGI promoter of Klf14 (Figure 4.1B). In fact, the Klf14 promoter remains unmethylated in all mouse tissues surveyed, as expected for a typical CGI (Figure 4.1C). In addition, no allelic H3K27me3 or H3K4me3 binding was found at or near the promoter in the ICM. No allelic information is available regarding H3K9me3 binding at the Klf14 promoter due to the lack of variants, although this mark is clearly present in ICM. Altogether, these observations reinforce the idea that Klf14 imprinted expression is acquired during embryogenesis and is controlled by an element or elements found elsewhere in the cluster. 4.2.2 Chromosome topology of the Mest-Klf14 locus The dependence of Klf14 expression on maternal DNA methylation (Parker-Katiraee et al. 2007), coupled with the observation that the Mest gDMR harbors the only maternal allele-specific DNAme mark in this region of the genome, suggests a mechanistic role for the gDMR in the regulation of Klf14 imprinting. In order to understand the 3-D organization of this genomic region better, we reanalyzed high-resolution non-allele-specific Hi-C data from E14TG2a ESCs, a cell type in which TAD structures are already established (Figure 4.2A) (Bonev et al. 2017; Dixon et al. 2012; Nora et al. 2012). After TAD-calling, our analysis revealed that Mest and Klf14 are situated within the same TAD, which encompasses approximately 690 kb of proximal Chr 6 (Figure 4.2A). Further visual inspection revealed the presence of a weaker boundary present at the Mest gDMR (Figure 4.2A; arrowhead). Through allele-specific CTCF ChIP-seq in 106 undifferentiated reciprocal B6´JF1 ESCs, we noted that these intra-TAD interactions were bordered by a paternal allele-specific CTCF binding site overlapping the site previously observed in vivo (Prickett et al. 2013). The edges of the TAD were also enriched for biallelic CTCF peaks, which may act to structure the TAD. Of note, the F1 CTCF ChIP-seq data was aligned to the mouse genome assembly mm10/GRCm38 due to the availability of SNP data, but this build contains a genomic gap 3’ of Mest. CTCF ChIP-seq in parthenogenetic (PR8) and androgenetic (AK2) ESCs (Llères et al. 2019) aligned to mm39/GRCm39 confirmed both the presence of a paternal allele-specific CTCF peak at the Mest gDMR and the lack of additional CTCF binding within the mm10 gap (Figure 4.3). 107 Figure 4.2 The Mest gDMR regulates imprinting of Klf14 A) Hi-C signal (aligned to mm39) within the TAD encompassing Mest and Klf14 in ESCs (grey box, indicated below the Hi-C signal), and CTCF ChIP-seq signal (aligned to mm10) on the maternal (red), and paternal (blue) alleles in reciprocal B6´JF1 ESCs. The Mest gDMR (arrow underneath the Hi-C plot and green box in the TAD track) is 108 indicated within the TAD, above the GENCODE gene list. Note that the GRCm38/mm10 genome assembly includes a 50-kb gap within intron 20 of Copg2. B) The Mest gDMR encompasses a predicted CTCF binding site spanning two CpGs, as determined by MEME-FIMO. The position of the canonical motif and extent of the Mest gDMR and CRISPR-Cas9 deletion (Δ) are highlighted. C) Allelic expression of Klf14 in mesodermal derivatives from wild-type (WT) and mutant F1 ESCs. Reciprocal B6´CAST ESCs (BC-1.1 and CB -1.1) were differentiated and sorted into FLK1- and FLK1+ populations. KO designates the CRISPR-Cas9 deletion of the Mest gDMR and CTCF binding site. Allelic ratios (MAT/(MAT+PAT)) of >0.65 and <0.35 represent maternal (red), and paternal (blue) expression, respectively. ND: no data Figure 4.3 CTCF ChIP-seq in monoparental parthenogenetic and androgenetic ESCs. Cartoon on top depicts the TAD (grey box), gDMR (green box in the TAD track) and genomic gap (dashed lines, all from the mm39 mouse genome assembly. The CTCF ChIP-seq data is from undifferentiated monoparental ESCs. PR8: parthenogenetic; AK2: androgenetic. 109 I noted that paternal CTCF binding in the promoter region of Mest segregates into two peaks separated by approximately 4.5kb (Figure 4.2B, 4.4A). Characterization of individual matches to the canonical CTCF motif based on the position frequency matrix obtained from JASPAR (MA0139.1)(Castro-Mondragon et al. 2022) predicted CTCF binding at both of these peaks. CTCF binding is known to be DNA methylation-sensitive, such as at the H19 DMR (Kanduri et al. 2000; Hark et al. 2000; Szabó et al. 2000), and the three predicted sites (2 upstream motifs, u1 and u2, and one over the gDMR) contain a CpG dinucleotide known to interfere with CTCF binding when methylated (Figure 4.4B)(Wang et al. 2012). The most upstream CTCF binding sites are located outside the gDMR as defined in E12.5 embryos (Tomizawa et al. 2011), and CTCF ChIP-seq in a variety of adult tissues (Abascal et al. 2020) revealed that this peak is only strongly detected in ESCs (Figure 4.4A). DNAme profiles from ESCs and adult heart and lung reveal a gain of DNAme at the upstream binding site, whereas the site located within the gDMR remains at ~50% methylation (Figure 4.4A,C). Based on these observations, we concluded that allele-specific binding over the upstream CTCF site is unique to undifferentiated ESCs, while the CTCF site located within the gDMR shows binding throughout development, concomitant with Klf14 imprinting. Altogether, these data show Mest and Klf14 are within the same overarching TAD and that the Mest gDMR harbours a paternal allele-specific CTCF binding site that may further structure the region. 110 Figure 4.4 Analysis of allelic CTCF binding sites in the Mest promoter. 111 A) UCSC browser screenshot of DNAme, and CTCF ChIP-seq in F1 ESCs and somatic tissues. Predicted CTCF binding sites from HOMER and JASPAR are indicated. The canonical CTCF binding motif (JASPAR MA0139.1) predicted by MEME-FIMO is highlighted over the upstream (u1, u2) and gDMR (g1 ) peaks. B) MEME-FIMO motif analysis of the predicted proximal CTCF binding site. The canonical CTCF motif is indicated. C) Quantification of mean DNA methylation over the proximal and Mest gDMR CTCF binding sites in ESCs and somatic tissues (heart, lung). 4.2.3 Loss of Klf14 imprinting upon deletion of the Mest gDMR For allele-specific studies, I established a new panel of reciprocal F1 C57BL/6 × CAST/EiJ ESC lines from blastocysts. These were established in 2i + LIF medium and I used early passage male ESCs with normal chromosomal counts (BC1.1, CB1.1) and faithful imprinting of Mest (Tables 2.2, 2.3) for further experiments. Due to the lack of detectable Klf14 expression in undifferentiated ESCs, an in vitro mesodermal differentiation system based on expression of the receptor tyrosine kinase KDR (FLK1) in vascular progenitors (VPs) was used (Yamashita et al. 2000) (Figure 4.5A). Flk1 expression is first detected in post-implantation embryos, coinciding with the acquisition of Klf14 imprinting in vivo. Similar to published reports (Kanki et al. 2017), I observed ~4-fold upregulation of Klf14 upon differentiation of CB1.1 ESCs into FLK1+ VPs, and also observed imprinted maternal Klf14 expression in the FLK1+ population (Figure 4.5B). In FLK1- cells, Klf14 was expressed biallelically at a lower level. 112 Figure 4.5 Expression of Klf14 in vascular progenitors. A) Schematic of in vitro differentiation of ESCs into mesoderm and flow cytometry data representation. The proportion of FLK1+ vascular progenitors sorted are indicated. B) Imprinting and expression profile of Klf14 during in vitro differentiation of F1 CAST female x B6 male (CB) ESCs into FLK1- and FLK1+ vascular progenitors. Allelic error bars represent the SD of technical triplicates. Error bars represent the SD of qPCR triplicates. ND: no data. NE: not expressed. 113 C) Characterization of Klf14 expression upon deletion of the Mest gDMR in reciprocal F1 ESCs differentiated into vascular progenitors, by qRT-PCR, normalized to the housekeeping gene Ppia (Mamo 2007). Results for sorted FLK1- and FLK1+ populations are shown. Error bars represent the SD of qPCR triplicates. BC and CB: F1 cell lines with B6 and CAST maternal genomes, respectively. ND: no data. To investigate directly whether the Mest gDMR regulates both Mest and Klf14, I used CRISPR-Cas9 mutagenesis in our F1 ESCs to delete a ~2.1kb region encompassing part of the gDMR, its associated CTCF binding site and exon 1 of Mest (Figure 4.2B, Δ). I was successful in producing lines containing deletions on the paternal allele (+/KO), on the maternal allele (KO/+), or homozygous for the deletion (KO/KO). In undifferentiated ESCs, Klf14 expression was very low, and expression levels generally increased upon differentiation in all cell lines, although to varying degrees, as expected for a heterogenous population of differentiated cells (Figure 4.5B-C). Upon differentiation, all FLK1- populations express Klf14 biallelically (41-56% maternal expression). In WT FLK1+ VPs, Klf14 showed maternally biased expression (71% in BC, 78% in CB). Upon paternal (+/KO) or homozygous (KO/KO) deletion of the CTCF binding site, imprinting was lost (+/KO: 54% and KO/KO: 41% in BC, KO/KO: 41%, CB). Klf14 remained imprinted in maternal KO cells (KO/+; 74% in BC, 74% in CB)(Figure 4.2C). These data demonstrate that Klf14 silencing is dependent upon the paternally unmethylated, CTCF-bound, Mest gDMR in differentiated VPs. Deleting the methylated maternal allele is silent with regard to Klf14 imprinting, still allowing its maternal allele-specific expression. 114 4.2.4 The Mest gDMR is essential for paternal sub-TADs organization Given that the Mest gDMR and Klf14 are separated by approximately 200 kb, I postulated that the allele-specific CTCF binding at the Mest gDMR may modulate long-range chromatin interactions which in turn regulate Klf14 imprinting. Based on aggregated Hi-C and CTCF ChIP-seq data, I hypothesized that the Mest gDMR defines the border of two sub-TADs: proximal and distal of the gDMR relative to the structure of Chr6 (Figure 4.6A). First, our collaborators performed allele-specific 4C-seq on WT B6´JF1 ESCs using a viewpoint situated proximal to the upstream CTCF peak within the proposed proximal sub-TAD. We observed an enrichment of interactions towards the proximal edge of the TAD on the paternal allele only (Figure 4.6A). Conversely, I performed allele-specific 4C-seq on WT B6´CAST ESCs (BC1.1) using a viewpoint situated within the distal edge of the TAD, beyond Klf14. We observed an enrichment of interactions on the paternal allele that stops at the Mest gDMR (Figure 4.6B), whereas the maternal allele has further contacts within the proximal sub-TAD. Together, our results show the formation two paternal-specific sub-TADs, hinged by the Mest gDMR. 115 Figure 4.6 The Mest gDMR is essential for paternal sub-tad organization A) Hi-C of the Mest-Klf14 region (Mest gDMR in green) and 4C-seq in ESCs. 4C-seq signal for the Mest-gDMR viewpoint on the maternal (red), and paternal (blue) allele in 116 B6´JF1 ESCs across the TAD. The difference of the above interactions is provided. Cartoon depicts the sub-TAD characterized (blue), and viewpoint (triangle). B) 4C-seq signal for the Klf14 distal viewpoint on the maternal (red), and paternal (blue) allele in B6´CAST ESCs across the TAD. C) 4C-seq signal for the Klf14 distal viewpoint on the paternal alleles in WT, and Mest gDMR KO B6´CAST ESCs. The Mest gDMR was deleted on the paternal allele in WT/pKO and KO/KO ESCs. D) 4C-seq signal for the Klf14 distal viewpoint on the maternal alleles in WT, and Mest gDMR KO B6´CAST ESCs. The Mest gDMR was deleted on the maternal allele in mKO/+ and KO/KO ESCs. E) Distribution of 4C-seq signal for the Mest gDMR and Klf14 distal viewpoints in the gDMR-proximal (347Kb) and gDMR-distal (313Kb) sub-TADs. Parental bias is defined as Mat-Pat score. The maternal allele for all crosses is from the CAST´B6 ESCs, either WT (black, blue, green), maternal KO (red), or homozygous KO (purple). The paternal allele is from the B6xCAST ESCs, either WT (black, red, purple), paternal KO (blue), or homozygous KO (green). To assess directly the role of the Mest gDMR in sub-TAD formation, I next performed 4C-seq on B6´CAST ESCs carrying the gDMR KO. Deletions of the gDMR on the paternal allele in both +/KO and KO/KO mutant ESCs strongly reduced paternal allele-specific interactions within the distal sub-TAD (Figure 4.6C), while paternal interactions were increased within the gDMR-proximal sub-TAD. Conversely, there were no changes in sub-TAD structure upon Mest gDMR deletion on the maternal allele (KO/+, KO/KO Figure 4.6D). Quantification of the distribution of 4C-seq signal within the gDMR-proximal and -distal sub-TADs revealed a loss of parental allele bias upon 117 deletion of the paternal gDMR only (Figure 4.6E), suggesting a functional equivalence between the methylated maternal allele and the gDMR-deleted paternal allele. Our 4C-seq data demonstrate that the Mest gDMR establishes the boundary between two sub-TADs on the paternal allele only (Figure 4.7). While both alleles are bound by biallelic CTCF sites at the TAD margins, the paternal allele is further structured internally by paternal CTCF binding at the Mest gDMR, whereas the maternal allele adopts a configuration comparable to the overarching TAD. Combined with the loss of imprinting of Klf14 upon deletion of the CTCF binding site specifically on the unmethylated paternal allele, this supports a role for these allelic sub-TAD structures in the long-range regulation of Klf14 imprinting within this imprinted gene cluster. 118 Figure 4.7 Schematic representation of allele-specific sub-TADs at the Mest-Kfl14 domain In wild-type cells, CTCF binding at the unmethylated paternal gDMR permits formation of two paternal sub-TADs, segregating Klf14 from a putative enhancer. No sub-TAD structures are formed on the maternal allele. Upon deletion of the Mest gDMR on the paternal allele (Δ), sub-TAD structure and Klf14 imprinting are lost. CTCF binding (blue pentagons), DNA methylation (lollipops), putative enhancer (orange triangle) as well as maternally (red), and paternally (blue) expressed genes are indicated. 4.3 Discussion In this study, I report for the first time a putative mechanism by which the Mest gDMR regulates imprinting of Klf14. This work also provides the first example of a maternally 119 methylated gDMR regulating imprinting via long-range chromatin looping. CRISPR-Cas9 mutagenesis in ESCs showed the unmethylated allele of the Mest gDMR is both required for Klf14 silencing (Figure 4.2C) and for the establishment of allele-specific sub-TADs (Figure 4.6C). I propose that the formation of this paternal allele-specific sub-TAD, defined by the gDMR, segregates Klf14 from its putative enhancer(s) (Figure 4.7). The Mest-Klf14 imprinted domain provides a unique framework to study various aspects of monoallelic gene regulation by a single maternal DNAme imprint. The Mest gDMR regulates Mest, Copg2, and Klf14 via direct promoter methylation, alternative polyadenylation (MacIsaac et al. 2012) and chromatin looping, respectively. These observations support the hypothesis that the frequent clustering of imprinted genes is a consequence of co-regulation. Intriguingly, this domain may be one of the few imprinted domains lacking a lncRNA. Whereas Mest codes for a hydrolase highly conserved in vertebrates (Sanso et al 2005), Klf14 arose more recently through retrotransposition of Klf16 during the divergence of marsupials from eutherian mammals (Parker-Katiraee et al. 2007). These observations suggest that Klf14 may have become imprinted due to the “bystander effect” (Varmuza and Mann 1994) of being in proximity to the Mest gDMR. The expression and imprinting profile of Klf14 in vivo indicate that its imprint is established during postimplantation development, supported by our in vitro differentiation model. Klf14 was maternally expressed only in FLK1+ vascular 120 progenitors, and not in heterogenous FLK1- cells (Figure 4.2C). In this model for Klf14 imprinting (Figure 4.7), the paternal gDMR and allele-specific CTCF binding site acts as an insulator, blocking access of a putative enhancer to the Klf14 promoter. The acquisition of imprinted expression at Klf14 might therefore correlate with the engagement of this enhancer. I demonstrated that paternal deletion of the Mest gDMR “maternalized” the entire Mest-Klf14 domain, suggesting an equivalence between the maternally methylated allele and a full deletion of the CTCF binding site. Conversely, the model suggests that loss of DNAme at the Mest gDMR would lead to a “paternalization” of the domain, CTCF binding on the maternal allele, and silencing of Klf14. This provides an explanation for the observed loss of Klf14 expression in embryos lacking maternally inherited DNAme genome-wide (Parker-Katiraee et al. 2007). Although our model proposes that the paternal sub-TADs are key in keeping Klf14 silent on the paternal allele, the relationship between TAD structure and gene expression is not always clear. For instance, it remains to be determined how Mest itself can be activated in the presence of those paternal sub-TADs. Aside from challenging the relationship between TADs and transcription, our model for Mest and Klf14 imprinting also expands upon the traditional view of CTCF as an insulator. CTCF binds on the paternal allele of the Mest gDMR-promoter, but does not preclude its expression. This observation may be explained by weaker insulation, or by CTCF-mediated tethering of enhancers to the Mest promoter (Kubo et al. 2021). For instance, this has 121 been observed at the HoxD locus where combinations of CTCF binding mediate interactions between the 3’ and 5’ HoxD genes and their respective enhancers located within different TADs (Rodríguez-Carballo et al. 2017). Ultimately, these observations highlight the multifaceted functions of CTCF as both an insulator and facilitator of promoter-enhancer interactions in the regulation of Klf14 and Mest, respectively. Our functional characterization of the Mest gDMR is in accordance with published findings on the paternal ICRs at the H19-Igf2 and Dlk1-Dio3 imprinted clusters (Llères et al. 2019). At these loci, a paternally methylated gDMR defines the boundary between maternal sub-TADs responsible for promoter-enhancer insulation. Similarly, allele-specific sub-TADs are established in ESCs prior to induction of gene expression, supporting the hypothesis that these structures provide an instructive context for regulation of imprinting during development (De Laat and Duboule 2013; Noordermeer and Feil 2020). The similarity of sub-TAD architecture established by a paternal or maternal ICR suggests this may be a shared mechanism of gene regulation based on DNAme. However, while paternally methylated ICRs are all located at intergenic regions and associated with allele-specific CTCF binding, maternally methylated gDMRs are distinct in that they are all promoter-proximal. Imprinted expression at MEST and KLF14 have been confirmed in human (Riesewijk et al. 1997; Kobayashi et al. 1997; Parker-Katiraee et al. 2007) indicating that the mechanisms underlying genomic imprinting at this locus may contribute to our 122 understanding of genetic or epigenetic abrogations associated with adverse human phenotypes (Prasad et al. 2021; Chang et al. 2021). In particular, maternal uniparental disomy of Chr7 encompassing this domain on 7q32 is associated with a subset of Silver-Russell syndrome (SRS) cases characterized by growth retardation (Eggermann et al. 2012; Preece et al. 1997). The regulation of Klf14 imprinting via the Mest gDMR described here may thus have important implications for the management of SRS patients. 4.4 Conclusion In summary, this study demonstrates that the paternal Mest gDMR is required for Klf14 imprinting in vitro through establishment of paternal allele-specific sub-TADs. Whether or not all maternal gDMRs with paternal allele-specific CTCF binding sites define similar sub-TAD architecture remains to be determined. 123 Chapter 5: Discussion 5.1 Major findings This thesis details the functional characterization of Mest and its imprinted gDMR. Chapter 3 outlined the consequences of in vivo Mest depletion during embryonic development followed by functional characterization of the MEST protein using a two-pronged approach leveraging metabolomics and structural biology. Mest deficient embryos are growth retarded, a phenotype commonly attributed to failed embryonic or placental function. The lack of any gross morphological, metabolic, or transcriptional phenotype observed in Mest pKO placenta suggest Mest function within this tissue may be redundant or compensated by other mechanisms. The observation that Mest pKO embryos are growth retarded both in utero and postnatally, also hints towards a placenta-independent gene function. Indeed, based on published overexpression models (Jung et al. 2011), and combined with my in vitro observations in MEFs, Mest may modulate growth as a Wnt inhibitor within the embryo. Additionally, the structural characterization of the MEST protein presented here revealed that its putative active site faces the ER lumen, further supporting the proposed relationship between MEST, LRP6 maturation, and Wnt regulation. Alternatively, MEST may also act on metabolites within the ER lumen. Following up on the lack of dysregulated triglycerides associated with loss of Mest in our KO model, I assessed the Mest gDMR as a regulatory candidate for the imprinting of Klf14, since deregulation of Klf14 may contribute to the Dnmt1o phenotype. 124 Chapter 4 details the functional characterization of the Mest gDMR required for imprinting of Klf14 via long-range chromatin organization. Klf14 imprinting was lost in pKO and KO/KO deletions of the Mest gDMR in ESC differentiated into vascular progenitors, indicating that the unmethylated paternal Mest gDMR is required for Klf14 silencing. Allele-specific 4C-seq revealed that the paternal gDMR encompassing a paternal allele-specific CTCF binding site defined the border of a sub-TAD responsible for segregating Klf14 from its putative enhancer. On the maternal allele, these sub-TAD structures did not form, allowing Klf14 expression. These results highlight, for the first time, a mechanism whereby sub-TAD mediated imprinting is regulated by a maternal methylated gDMR. Combined, Chapters 3 and 4 of my thesis provide insight into the function and regulation underlying imprinting at the Mest-Klf14 domain. Mest and Klf14 are regulated by a common epigenetic mechanism: methylation at a gDMR acting as an ICR. Similarly, both genes are implicated in the regulation of metabolism, although appear to have differing functions. Whereas Mest promotes adipogenesis (Anunciado-Koza et al. 2017; Vanella et al. 2013), Klf14 expression is protective against adverse metabolic outcomes (Small et al. 2018). 5.2 Comparison with other mouse models At the present time, there have only been two studies examining placental biology in response to dysregulation of the Mest-Klf14 imprinting domain. First, Mest gDMR 125 hypomethylation associated with two-fold Mest upregulation and Klf14 downregulation in the epigenetically heterogenous Dnmt1o KO placenta was associated with increased placental triglycerides (Himes et al. 2013). Second, during the time while I was investigating the loss of Mest within the placenta, the same group reported loss of Klf14 within this tissue. Klf14 mKO placenta were only modestly overgrown, lacking a lipid phenotype, and presented with minimal changes in transcription (20 DEGs) (Koppes et al. 2019). Klf14 deficiency had no effect on fetal growth at E17.5. Altogether, it is apparent single-gene deletions of Mest (this study) and Klf14 (Koppes et al. 2019) are not associated with major placental defects, nor are they required for placental or embryonic development. However, the results presented in Chapter 4 suggest that loss of DNAme at the Mest gDMR, as seen in the Dnmt1o KO model, should be accompanied by loss of Klf14 expression. Perhaps it is the combined and opposite dysregulation of both of these imprinted genes that is associated with elevated placental triglycerides in the Dnmt1o model, suggesting these two genes may work in concert to regulate lipid metabolism. Along the same lines, the functions of Mest and Klf14 in adipose tissue has been more extensively characterized. Both genes are imprinted in adipocytes. Mice carrying adipose-specific deletions of Mest (pKO) and challenged with a high fat diet exhibited decreased adiposity, and improved insulin tolerance (Anunciado-Koza et al. 2017). Conversely, Mest overexpression in adipose tissue is associated with enlarged adipocytes, implicating the gene as a marker for adipocyte size (Takahashi et al. 2005). 126 Klf14 overexpression (1.7x) in adipocytes has also been associated with female-specific resistance to diet-induced fat gain (Yang et al. 2022). Conversely, mice with adipose-specific deletions of Klf14 (KO/KO) were associated with insulin resistance and a dysregulated network of 285 genes (Small et al. 2018), significantly larger than the 20 identified in mKO placenta. Ablation of Klf14 expression in Trim28 KO adipocytes was similarly associated with a shift in triglyceride abundance, with the phenotype more pronounced in females (Bond et al. 2021). The observation that Klf14 expression is dependent on the imprinting maintenance enzyme TRIM28/KAP1 in vivo, also supports our proposed model for Klf14 imprinting. Recruitment of TRIM28 by ZFP57 on the maternal allele subsequently leads to SETDB1 mediated deposition of H3K9me3, responsible for DNAme maintenance (Strogantsev et al. 2015; Rothbart et al. 2012). Loss of TRIM28 could therefore be associated with loss of DNAme over the Mest gDMR in adipocytes, the region’s sole gDMR. As characterized in Chapter 4, Klf14 expression and imprinting is regulated by methylation at this locus. Mest and Klf14 unequivocally have non-redundant and possibly opposing functions postnatally, as observed within adipose tissue. In the placenta, however, this function is notably masked. During embryonic development, adipose tissue is not established until late in gestation (E14-E18) (Wang et al. 2013) concomitant with the apparent growth retardation observed in Mest pKO embryos (E15.5). Therefore, it is plausible impaired function of Mest within the emerging adipocytes of the embryo may be a contributor to both embryonic and postnatal growth restriction. Alternatively, it may 127 also be possible that loss of Mest and/or Klf14 may only present a placental phenotype when the system is challenged. 5.3 Significance of imprinting at the Mest locus The Mest gDMR acts as an ICR, involved in the imprinting of paternally expressed transcripts Mest (Lefebvre et al. 1997), miR-335 , and Mest-XL, and maternally expressed genes Copg2 (MacIsaac et al. 2012), and Klf14. Epigenetic dysregulation of this domain is involved in Silver-Russell syndrome, although the exact causative gene(s) is unknown. Recently, a 79kb paternally inherited microdeletion encompassing MEST, MESTIT1, and part of COPG2 was associated with SRS-like phenotypes (Vincent et al. 2022). This study narrows down MEST as responsible for the growth-retardation phenotype in this patient, a hypothesis supported by in vivo mouse models (Lefebvre et al. 1998). However, deletion of the MEST gDMR may also have implications on KLF14 expression. Differential methylation of the MEST gDMR and TAD structure are conserved between mouse and human. In the mouse, maternal DNAme occludes CTCF binding, allowing for allele-specific binding to the paternal allele only. This CTCF binding site is conserved in human, but the allelic nature of this mark has not been determined yet; presumably only the unmethylated paternal allele is bound by CTCF. Therefore, deletion of the MEST gDMR in humans may be associated with both loss of MEST expression, and KLF14 upregulation, when paternally inherited. Furthermore, while Klf14 imprinted expression is dependent on maternal methylation over the gDMR, as demonstrated in this thesis and implicated by others (Himes et al. 128 2015), the methylation state of its normally hypomethylated CGI promoter may also be implicated. For example, modest levels of DNA methylation (~5-10%) within the Klf14 CGI have been associated with aging, and Type II Diabetes in humans (Bacos et al. 2016). 5.4 Evolutionary conservation Mest is highly conserved in vertebrates, but is only imprinted in eutherians (placental mammals), and marsupials (Kaneko-Ishino et al. 1995; Das et al. 2012; Suzuki et al. 2005). Whereas imprinting of Mest is regulated by a gDMR in eutherians, no DMR at the orthologous locus has been reported in marsupials so far. In fact, the mechanism underlying Mest imprinting in marsupials is unknown. It is possible that differential histone modifications or an undiscovered DMR may be directing gene silencing in those species. For example, the opossum genome contains an uncharacterized intergenic CpG island encompassing MEST exon 6, absent from both mouse and human. It is tempting to speculate that this intergenic CGI is a DMR, and that transcription across this locus is required for establishment of imprinting as observed in the mouse oocyte. Regardless, the regulation of Mest imprinting is guided by different mechanisms in eutherians and marsupials. The emergence of Mest imprinting in eutherians may be closely tied to deviations from the protein’s ancestral function. The putative catalytic region of Mest encoded within exons 2-12 is highly conserved in vertebrates, from humans down to zebrafish 129 (Sansom et al. 2005). The genomic region encompassing the gDMR and Mest exon1 however, is missing in marsupials, monotremes (platypus), and non-mammalian vertebrates (chicken) but is unique to a majority of eutherians (ex. mouse, rat, human). It is possible that acquisition of the Mest gDMR-promoter sequence, encompassing the MEST N-terminus ER localization signal discussed in this thesis, resulted in deviation of protein localization and/or function which coincided with the onset of imprinting in eutherians. This newly acquired domain may have been targeted for silencing as proposed by the host defense model for imprinting acquisition, which suggests that foreign DNA elements are silenced by epigenetic mechanisms (Barlow 1993). The high conservation of Mest, and the acquisition of the gDMR in eutherians contrasts with the situation at the Klf14 locus. Klf14 is thought to have arisen through retrotransposition of Klf16 during the divergence of marsupials from eutherians (Parker-Katiraee et al. 2007). The majority of retrotransposed genes are either silenced or become pseudogenes. Some elements, however, acquire a new promoter, as is the case of Klf14. It is plausible that retrotransposition of Klf16 into the proximity of the Klf14 CGI sequence resulted in acquisition of a new promoter. Klf14, therefore, likely became imprinted due to the “bystander effect” (Varmuza and Mann 1994) of being in proximity to the Mest gDMR based on this evolutionary timescale. Furthermore, the characterization of sub-TAD structures defined by the Mest gDMR raises a number of questions concerning the relationship between TADs and 130 evolution. The insertion of the Mest gDMR sequence was associated with sub-TAD structures on the paternal allele only, whereas the maternal allele was largely invariant because of DNAme-mediated inhibition of CTCF binding. We proposed this “hijacking” of existing chromatin architecture by the paternal unmethylated gDMR is responsible for Klf14 silencing. The co-regulation of Mest and Klf14 by a single gDMR may be the result of an evolutionary pressure to balance the expression of the paternally and maternally expressed genes within this cluster. The paternal sub-TAD configuration also raises concerns over the exact mechanism permitting Mest paternal expression. In line with CTCF’s function as an insulator, CTCF binding over the Mest promoter should limit its interaction with putative enhancers upstream, and permit preferential engagement with putative enhancers in the downstream sub-TAD. If the Mest enhancer is indeed located within the distal sub-TAD, it is unknown why this enhancer would not engage with Klf14 leading to its paternal expression. Based on chromatin state annotations by ChromHMM (Ernst and Kellis 2017) and ENCODE predictions for promoter-enhancer interactions (Abascal et al. 2020), the putative Mest enhancer(s) is localized upstream of the gene. For Mest to be paternally expressed, this cluster of upstream enhancers must bypass the proposed sub-TAD boundary established by paternal allele-specific binding over the Mest gDMR. This model challenges our traditional understanding of CTCF as an insulator element but may be explained by the tethering of distal enhancers by promoter-proximal CTCF binding. This role for promoter-proximal CTCF as a mediator of long-range promoter-enhancer interactions has been described recently in ESCs and NPCs (Kubo et al. 2021). 131 5.5 Future directions As discussed above, the functional relevance of Mest, Klf14, and the epigenetic status of the gDMR all have implications for human diseases. As Chapter 3 largely focused on characterization of Mest KO placenta, the function of embryonic Mest is unknown. One possibility underlying growth retardation observed in KO mice may be due to embryonic or a combination of embryonic and placental Mest deficiency. Metabolic profiling in Mest pKO embryos may provide additional insight into Mest function. Furthermore, as Mest deficiency has minimal effects on transcription, and is protective against diet-induced obesity (Anunciado-Koza et al. 2017), it may be of interest to profile the metabolomic signature of WT and pKO adipose tissue upon challenge with high-fat diet. Additionally, the function of Mest as a Wnt inhibitor through targeting LRP6 in vitro should be further examined through the use of surrogate Wnt agonists. Instead of rWNT3A or LiCl, used in this thesis and which are not specific to LRP6, the Wnt pathway may be activated through surrogate Wnt agonists that heterodimerize FZD with LRP6 specifically in WT and pKO cells. The TOPFLASH assay can subsequently be performed to assess for Wnt activation. If Mest is indeed a negative modulator of LRP6 maturation, Mest deficiency would be associated with increased availability of LRP6 and subsequently increased Wnt activation. An important unanswered question raised in Chapter 4 is the exact relationship between Mest gDMR methylation, and CTCF binding. Motif analysis of the CTCF binding site encompassing the Mest gDMR revealed this locus encompassed two 132 methylated CpGs which may preclude CTCF binding. Site-specific mutations of these CpGs could be performed to unequivocally demonstrate the inhibitory relationship between DNAme, allele-specific CTCF binding, and subsequent sub-TAD structure at this locus. An additional outstanding question raised in Chapter 4 relates to the dynamics of sub-TAD formation. TADs are largely invariant across cell types, while sub-TAD structures and promoter-enhancer contacts are dynamic and vary between different cell types. It is unknown if the sub-TADs characterized in ESCs are stable upon differentiation, and how they reflect in vivo conditions. Furthermore, the possible multiplicity of promoter-enhancer interactions regulating Mest and Klf14 imprinting is beyond the scope of this thesis. It is unknown if these two genes share an enhancer, or are activated by one or more enhancers. As it is unknown whether Mest and Klf14 are regulated by a single enhancer, dissecting the exact regulatory mechanism is complex. Mest/Klf14 regulation may implicate multiple enhancers operating under a model of enhancer cooperativity. Additionally, varying strength of individual enhancers further complicate the model. There are multiple proposed promoter-enhancer interactions upstream Mest annotated by ENCODE (Gorkin et al. 2020). Therefore, classical single-enhancer deletion experiments may not be sufficient to identify the causative enhancer(s) responsible. Additionally, promoter-enhancer contact is not the only requirement for transcription. The proteome (transcription factors, cofactors) at the enhancer and promoter is also an important determinant for transcription. 133 Enhancer discovery may be performed using HiChIP, a method combining Hi-C and ChIP-seq (Mumbach et al. 2016). HiChiP of promoter or enhancer marks (e.g. H3K27ac) may be used to identify chromatin loops associated with active promoters at Mest and Klf14. An important caveat of this approach would be the cell-type assayed. If Mest and Klf14 share an enhancer, supported by the observation that they are often co-expressed, the cell type chosen would need to express both Mest and Klf14 to have established promoter-enhancer contact, therefore ruling out ESC. If there is no shared enhancer, two different cells types expressing either Mest or Klf14 could be surveyed. HiChIP in vascular progenitors, as used in Chapter 4, may be an appropriate cell type for enhancer discovery. Alternatively, FLK1+ vascular progenitors could be further differentiated into hemogenic endothelium-type cells (HE) (Goode et al. 2016). In HE, the TSS of both Mest and Klf14 harbor histone marks for active promoters (H3K27ac and H3K4me3), and are accordingly upregulated (Goode et al. 2016). 5.6 Final remarks The Mest-Klf14 imprinting domain provides a unique framework to study both the significance of parent-of-origin effects on development, and the mechanisms underlying gene regulation. This thesis describes the analysis of both the function and mechanism of Mest and its imprinted gDMR. Compared to other imprinted genes, our understanding of Mest function is still limited. Through a combination of in vivo and in vitro characterizations, my results implicate Mest as an inhibitor of Wnt signaling through targeting putative substrates localized within the ER lumen destined for intracellular 134 transport. It is plausible Silver-Russell and metabolic syndromes are caused by dysregulated Mest regulation of Wnt signaling. While a list of tentative MEST substrates was identified by placental metabolomics, further studies are required to confirm the identity of these predicted entities. My findings on the regulation of Klf14 imprinting by the Mest gDMR also brings insight onto the consequences of dysregulation at this locus. Epimutations at the Mest gDMR may be associated with aberrant Mest and Klf14 expression, therefore necessitating the evaluation of both genes when examining human phenotypes. Additionally, my results also highlight broadly the relationship between chromatin organization, and gene regulation. Differential methylation over the Mest gDMR is conserved in multiple tissues throughout development, suggesting a similar conservation in allele-specific sub-TAD structure as observed in ESC. In summary, this is the first study to closely examine MEST topology and the Mest gDMR. 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Gene FPKM Fold change (KO/WT) Z score WT average KO average Krt15 0.025 1.325 52.553 1.119 AC111044.1 0.282 4.232 15.019 1.859 Gm10713 0.133 1.771 13.359 1.188 Gm5436 0.411 4.406 10.710 1.820 Gm10073 1.792 7.496 4.184 1.872 Rps24-ps2 1.567 4.663 2.976 1.240 Gm16378 5.206 14.859 2.854 2.155 Gm6030 1.948 4.724 2.424 1.074 Fabp3-ps1 7.034 13.023 1.852 1.337 167 Table A.2 Significantly downregulated genes in the Mest pKO E17.5 placentae, compared to WT. Gene FPKM Fold change (KO/WT) Z score WT average KO average Mest 33.516 2.283 14.682 -5.220 Gm8894 8.392 0.637 13.178 -2.581 Gm5514 7.280 0.844 8.621 -2.258 Gm6180 7.155 1.018 7.029 -2.147 Gm5483 3.066 0.606 5.059 -1.284 Gm10269 11.698 4.046 2.891 -1.928 Apom 7.907 3.410 2.319 -1.337 Spink3 8.118 3.840 2.114 -1.237 Gm6169 9.067 4.647 1.951 -1.194 Rps26-ps1 13.061 6.741 1.938 -1.420 Gm2000 22.651 12.890 1.757 -1.637 Spp2 9.738 5.639 1.727 -1.045 Alb 12.484 7.671 1.627 -1.072 Ttr 16.371 10.830 1.512 -1.062 168 Table A.3 Qualitative enrichment of dysregulated metabolite groups in male WT and pKO E17.5 placenta Metabolites Metabolite group Higher in WT males Hits Expect Enrichment ratio (hit/expect) P value FDR Benzamides 4 0.266 15 1.45E-04 0.0353 Benzenes 2 0.0274 73 3.56E-04 0.0435 Sulfonic acids 1 7.26E-04 1377 7.25E-04 0.0442 Pyrrolines 1 7.26E-04 1377 7.25E-04 0.0442 Hydroxycinnamic acids 1 9.07E-04 1103 9.07E-04 0.0442 Piperidines 1 0.00127 787 0.00127 0.0516 Alcohols and polyols 1 0.00381 262 0.0038 0.133 Amino acids and peptides 2 0.131 15 0.00769 0.235 Purines 1 0.0161 62 0.016 0.43 Sphingoid bases 1 0.0178 56 0.0176 0.43 Fatty amides 1 0.0736 14 0.0711 1 Octadecanoids 1 0.0903 11 0.0865 1 Isoprenoids 1 0.257 4 0.228 1 Fatty Acyls 1 0.267 4 0.235 1 Glycerophosphocholines 1 0.853 1 0.578 1 Triradylglycerols 1 6.21 0 0.999 1 Metabolite group Higher in KO males Hits Expect Enrichment ratio (hit/expect) P value FDR Organic sulfuric acids 1 2.52E-04 3968 2.52E-04 0.0615 Benzamides 2 0.0739 27 0.00236 0.288 Pyrimidines 1 0.00393 254 0.00392 0.319 Sphingolipids 1 0.0245 41 0.0243 1 Amino acids and peptides 1 0.0364 27 0.0358 1 Fatty esters 1 0.0943 11 0.0904 1 169 Table A.4 Qualitative enrichment of dysregulated lipid groups in male WT and pKO E17.5 placenta Lipids Lipid group Higher in WT males Hits Expect Enrichment ratio (hit/expect) P value FDR Fatty amides 5 0.0675 74 7.91E-09 1.93E-06 Fatty Acyls 6 0.245 24 1.55E-07 1.89E-05 Sphingoid bases 3 0.0163 184 6.30E-07 5.13E-05 Fatty Acids and Conjugates 4 0.513 8 0.00167 0.102 Prenol lipids 3 0.41 7 0.00792 0.386 Isoprenoids 2 0.236 8 0.0233 0.946 Fatty esters 2 0.311 6 0.0387 1 Octadecanoids 1 0.0828 12 0.0796 1 Eicosanoids 1 0.165 6 0.152 1 Steroids 1 0.174 6 0.16 1 Glycerophosphocholines 2 0.782 3 0.184 1 Glycerophosphates 1 0.68 1 0.497 1 Glycerophosphoserines 1 0.689 1 0.501 1 Glycerophosphoinositols 1 0.725 1 0.52 1 Triradylglycerols 1 5.69 0 0.998 1 Lipid group Higher in KO males Hits Expect Enrichment ratio (hit/expect) P value FDR Prenol lipids 3 0.124 24 2.15E-04 0.0526 Glycerophosphoethanolamines 2 0.219 9 0.0192 1 Neutral glycosphingolipids 1 0.0268 37 0.0265 1 Steroids 1 0.0528 19 0.0515 1 Fatty esters 1 0.0943 11 0.0904 1 Glycerophosphoserines 1 0.209 5 0.19 1 Glycerophosphocholines 1 0.237 4 0.213 1 170 Table A.5 Qualitative enrichment of dysregulated metabolite groups in female WT and pKO E17.5 placenta Metabolites Metabolite group Higher in WT females Hits Expect Enrichment ratio (hit/expect) P value FDR Phenylacetic acids 1 0.00121 826 0.00121 0.295 Fatty alcohols 1 0.0152 66 0.015 1 Glycerophosphoethanolamines 2 0.351 6 0.047 1 Benzamides 1 0.118 8 0.112 1 Fatty Acyls 1 0.119 8 0.112 1 Prenol lipids 1 0.199 5 0.181 1 Metabolite group Higher in KO females Hits Expect Enrichment ratio (hit/expect) P value FDR Monosaccharides 1 0.00489 204 0.00488 1 Benzamides 1 0.0739 14 0.0715 1 Fatty esters 1 0.0943 11 0.0904 1 Prenol lipids 1 0.124 8 0.118 1 Flavonoids 1 0.267 4 0.237 1 171 Table A.6 Qualitative enrichment of dysregulated lipid groups in female WT and pKO E17.5 placenta Lipids Lipid group Higher in WT females Hits Expect Enrichment ratio (hit/expect) P value FDR Prenol lipids 3 0.162 19 4.99E-04 0.122 Glycerophosphoethanolamines 3 0.285 11 0.00255 0.312 Hydrocarbons 1 0.00779 128 0.00777 0.632 Fatty alcohols 1 0.0123 81 0.0122 0.747 Eicosanoids 1 0.065 15 0.0631 1 Fatty Acyls 1 0.0966 10 0.0924 1 Fatty esters 1 0.123 8 0.116 1 Fatty Acids and Conjugates 1 0.202 5 0.184 1 Glycerophosphates 1 0.268 4 0.237 1 Lipid group Higher in KO females Hits Expect Enrichment ratio (hit/expect) P value FDR Fatty amides 2 0.0184 109 1.49E-04 0.0363 Flavonoids 2 0.24 8 0.0226 1 Eicosanoids 1 0.045 22 0.0441 1 Fatty esters 1 0.0849 12 0.0818 1 Prenol lipids 1 0.112 9 0.106 1 Fatty Acids and Conjugates 1 0.14 7 0.132 1 Glycerophosphoethanolamines 1 0.197 5 0.181 1 172 Appendix B Supplementary materials for Chapter 4 Table B.1 Datasets used in this study Species Tissue F1 crosses Data type Accession Reference Mouse ESC DNAme GSE61457 Li, Z. et al Genome Biol 16-115 (2015) Mouse ESC B6×CAST ZFP57 ChIP-seq GSE55382. Strogantsev, R. et al. Genome Biol 30,16-112 (2015) Mouse Brain B6×CAST CTCF ChIP-seq GSE35140 Prickett, A. et al. Genome Res 23, 1624–1635 (2013) Mouse ICM B6X×PWK H3K4me3 GSE71434 Zhang, B. et al. Nature 537, 553–557 (2016) Mouse ICM B6X×PWK H3K27me3 GSE76687 Zheng, H. et al Mol Cell 63(6):1066-79 (2016) Mouse ICM B6×DBA H3K9me3 GSE98149 Wang,C. et al Nat Cell Biol 20(5):620-631 (2018) Mouse Various F1 tissues CAST×FVB RNA-seq GSE75957 Andergassen, D. et al eLife 6:e25125 (2017) Mouse Adult heart, lung DNAme GSE42836 Hon GC, Nat Genet 45(10):1198-206 (2013) Mouse Adult heart, lung CTCF ChIP-seq GSE49847 Yue, F. et al Nature 515(7527):355-64 (2014) Mouse AK2, PR8 mESC CTCF ChIP-seq PRJEB28762 Llères, D. et al Genome Biol 20:272 (2019) Mouse Various CTCF ChIP-seq ENCODE Absacal, F. et al Nature 46(D1):D794-D801 (2020) Mouse Various DNAme DRA000484 Kobayashi, H et al. PLoS Genet 8(1):e1002440 (2012) Mouse Various DNAme MethBase Song, Q et al. PLOS ONE 8(12): e81148 (2013) Mouse ESC Hi-C GSM2533821 GSM2533820 GSM2533819 GSM2533818 Bonev, B. et al Cell 171, 557-572 (2017)
Thesis/Dissertation
eng
Medical Genetics
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Lefebvre, Louis
Functional characterization of Mest and its imprinted gametic differentially methylated region
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