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Sex- and Diet-Specific Changes of Imprinted Gene Expression and DNA Methylation in Mouse Placenta under a High-Fat Diet

  • Catherine Gallou-Kabani ,

    Contributed equally to this work with: Catherine Gallou-Kabani, Anne Gabory

    Affiliation Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France

  • Anne Gabory ,

    Contributed equally to this work with: Catherine Gallou-Kabani, Anne Gabory

    Affiliations Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France, INRA, UMR1198, UMR INRA/ENV Maisons-Alfort/CNRS: Biologie du Développement et Reproduction, (ENV Maisons-Alfort; CNRS), Physiologie Animale et Systèmes d'Elevage, Centre de recherche de Jouy-en-Josas, Jouy-en-Josas, France

  • Jörg Tost,

    Affiliation Laboratoire d'Epigénétique, CEA - Institut de Génomique, Centre National de Génotypage, Evry, France

  • Mohsen Karimi,

    Affiliation Laboratory for Medical Epigenetics, Department of Clinical Neuroscience, Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

  • Sylvain Mayeur,

    Affiliation Unité Environnement Périnatal et Croissance, EA 4489, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

  • Jean Lesage,

    Affiliation Unité Environnement Périnatal et Croissance, EA 4489, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

  • Elsa Boudadi,

    Affiliation Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France

  • Marie-Sylvie Gross,

    Affiliation Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France

  • Julien Taurelle,

    Affiliation Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France

  • Alexandre Vigé,

    Affiliation Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France

  • Christophe Breton,

    Affiliation Unité Environnement Périnatal et Croissance, EA 4489, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

  • Brigitte Reusens,

    Affiliation Laboratory of Cell Biology, Institute of Life Sciences, Catholic University of Louvain, Louvain-la-Neuve, Belgium

  • Claude Remacle,

    Affiliation Laboratory of Cell Biology, Institute of Life Sciences, Catholic University of Louvain, Louvain-la-Neuve, Belgium

  • Didier Vieau,

    Affiliation Unité Environnement Périnatal et Croissance, EA 4489, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

  • Tomas J. Ekström,

    Affiliation Laboratory for Medical Epigenetics, Department of Clinical Neuroscience, Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

  • Jean-Philippe Jais,

    Affiliation SBIM, Université Paris Descartes, Paris, France

  •  [ ... ],
  • Claudine Junien

    Affiliations Inserm, AP-HP, Université Paris-Descartes, Faculté de Médecine, Hôpital Necker-Enfants Malades, U781, Paris, France, INRA, UMR1198, UMR INRA/ENV Maisons-Alfort/CNRS: Biologie du Développement et Reproduction, (ENV Maisons-Alfort; CNRS), Physiologie Animale et Systèmes d'Elevage, Centre de recherche de Jouy-en-Josas, Jouy-en-Josas, France

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Sex- and Diet-Specific Changes of Imprinted Gene Expression and DNA Methylation in Mouse Placenta under a High-Fat Diet

  • Catherine Gallou-Kabani, 
  • Anne Gabory, 
  • Jörg Tost, 
  • Mohsen Karimi, 
  • Sylvain Mayeur, 
  • Jean Lesage, 
  • Elsa Boudadi, 
  • Marie-Sylvie Gross, 
  • Julien Taurelle, 
  • Alexandre Vigé



Changes in imprinted gene dosage in the placenta may compromise the prenatal control of nutritional resources. Indeed monoallelic behaviour and sensitivity to changes in regional epigenetic state render imprinted genes both vulnerable and adaptable.

Methods and Findings

We investigated whether a high-fat diet (HFD) during pregnancy modified the expression of imprinted genes and local and global DNA methylation patterns in the placenta. Pregnant mice were fed a HFD or a control diet (CD) during the first 15 days of gestation. We compared gene expression patterns in total placenta homogenates, for male and female offspring, by the RT-qPCR analysis of 20 imprinted genes. Sexual dimorphism and sensitivity to diet were observed for nine genes from four clusters on chromosomes 6, 7, 12 and 17. As assessed by in situ hybridization, these changes were not due to variation in the proportions of the placental layers. Bisulphite-sequencing analysis of 30 CpGs within the differentially methylated region (DMR) of the chromosome 17 cluster revealed sex- and diet-specific differential methylation of individual CpGs in two conspicuous subregions. Bioinformatic analysis suggested that these differentially methylated CpGs might lie within recognition elements or binding sites for transcription factors or factors involved in chromatin remodelling. Placental global DNA methylation, as assessed by the LUMA technique, was also sexually dimorphic on the CD, with lower methylation levels in male than in female placentae. The HFD led to global DNA hypomethylation only in female placenta. Bisulphite pyrosequencing showed that neither B1 nor LINE repetitive elements could account for these differences in DNA methylation.


A HFD during gestation triggers sex-specific epigenetic alterations within CpG and throughout the genome, together with the deregulation of clusters of imprinted genes important in the control of many cellular, metabolic and physiological functions potentially involved in adaptation and/or evolution. These findings highlight the importance of studying both sexes in epidemiological protocols and dietary interventions.


There is no doubt that much of the increase in obesity can be attributed to lifestyle factors, such as the excess consumption of energy-rich foods, a decline in physical activity, inherited genetic and other factors [1]. However the ‘Developmental Origins of Adult Health and Disease’ (DOHaD) hypothesis provides an alternative hypothesis [2]. Maternal nutrient deprivation has been well characterised in this context. However little is known about the potentially deleterious effects of overnutrition, such as a typical hypercaloric Western diet rich in energy, saturated fats and sugar or a high-fat diet, on the health of offspring, potentially resulting in a metabolic syndrome phenotype in the offspring [3], [4], [5]. Obese and diabetic women are less fertile than women of normal weight, tend to consume more calories, particularly from fat [6], and have a higher rate of adverse pregnancy outcomes [7] and a higher risk of impaired breastfeeding [8]. The proportion of women of child-bearing age who are overweight (25%, 30%, and 50% in France, Germany, and the US, respectively) and do not eat an appropriate diet is significant and increases. We therefore need to identify ways of providing advice, evidence-based dietary recommendations, clinical treatments and counselling for these women and their babies.

There is increasing evidence to suggest that the placenta is involved in determining the risk of cardiovascular disease and cancer (reviewed in [9], [10], [11], [12], [13], [14 Thornburg, 2010 #6165]). The placenta is the primary means of communication and nutrient delivery to the foetus and is presumably involved in foetal homeostasis. It is therefore an appropriate organ for studies investigating how differences in maternal food consumption are sensed by the developing offspring [15]. In mice, the mature placenta (E14.5) consists of three principal layers: an outer layer of trophoblast giant cells, a middle spongiotrophoblast layer (sometimes called the junctional zone) and the innermost labyrinth [16], [17], [18]. Placental function follows a carefully orchestrated developmental cascade during gestation. Both the development and ongoing functions of the placenta may be dynamically regulated by environmental factors, including nutrient status and tissue oxygenation [19]. The timing of certain adverse incidents during development may therefore have a critical effect on the subsequent vasculature of the placenta or on trophoblast and placental function and foetal programming [20], [21].

Despite the important role of the placental in supplying nutrients to the foetus, very few studies have investigated the effects of general nutritional status on blastocyst development and implantation, subsequent placental development and the role of the placenta in adaptive epigenetic processes in response to nutritional stimuli [18], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33]. Only two groups have explored the impact on the global placental gene response of changes in maternal diet [12], [34], [35]. The data obtained suggest that placental development is highly adaptable and that there are many possible types of compensation for suboptimal nutrition [36].

The placenta has long been considered to be an asexual organ, with most placental studies consistently pooling data for male and female placentae into a single group [37]. However, predisposition to metabolic disease differs between the sexes, with women more likely to develop obesity and men, cardiovascular disease. This sexual dimorphism may already exist during development. Indeed, there is mounting evidence to suggest that the sex of the embryo, through the embryo-derived tissues of the placenta, plays a significant role in determining foetal size, nutrition, morbidity and survival [37], [38]. Such differences may appear early, even before the gonads have developed, highlighting the important role of the sex chromosomes [39], [40] (reviewed in [41]). A molecular investigation of the extent to which male and female conceptuses react to the same maternal diet is therefore of interest. Only a handful of studies have reported differences between the sexes, in terms of the expression of individual genes or pathways, in male and female human and rodent placentae. These studies also addressed the impact of differences in the quality of the maternal diet on placental gene expression, with a systematic investigation of the relationship between diet and the expression of sexually dimorphic genes, providing insight into the different sensitivities of male and female foetuses to what the mother eats [12], [35], [37], [42], [43], [44], [45], [46].

Genomic imprinting is an epigenetic phenomenon in which specific mammalian genes are expressed preferentially from the allele inherited either from the father or from the mother. More than 80 genes are imprinted in humans and mice, and it is thought that there may be 100 to 500 imprinted genes in the entire genomes of these species [47], [48]. The placenta is notable amongst mammalian organs for its high and prolific expression of imprinted genes. [49], [50]. Most imprinted genes are grouped into clusters, each of which may contain a mixture of maternally and paternally expressed genes. These clusters are located at about 15 different sites on the chromosomes of the human genome, at sites syntenic to those in mice. These imprinted domains are co-ordinately regulated by imprinting centres, consisting of differentially methylated regions (DMRs) that are methylated either maternally during oogenesis or paternally during spermatogenesis. DMRs act via long-range mechanisms, such as antisense RNA interference, and through methylation-sensitive boundary elements (CTCF) [30], [51], [52], [53]. A network of imprinted genes, including Zac1 and H19, which controls embryonic growth and may be the key to a common mechanism of gene regulation during mammalian evolution, has recently been described [54], [55]. Another important feature associated with imprinted gene loci is the presence of imprinted small non-coding RNAs clusters [56]. The complexity of imprinted domain regulation may also render these domains particularly susceptible to environmental changes of gene expression through nutrition during the prenatal period, beginning in the preimplantation embryo, and in the postnatal period [25], [57], [58], [59]. It has recently been shown that changes in postnatal growth induced by a maternal low protein diet (LPD) at the time of conception may be result partly from the sex-specific programming of imprinted gene expression within the preimplantation embryo itself [25]. The expression profile for imprinted genes has been shown to be altered in placentae from rat foetuses presenting IUGR [60], from infants with a low birth weight [61], [62]} or after superovulation in the midgestation placenta in human pregnancies [63]. Imprinted genes are dosage-sensitive. They encode proteins involved in common pathways and play multiple roles in the placenta, including regulation of the growth and transport capacity, thereby controlling the supply of nutrients to the foetus [53], [64], [65]. They may also directly regulate the growth rate of foetal tissues, thereby controlling foetal nutrient demand. Moreover genetic and molecular studies of the development and evolution of sexual dimorphism [66] have shown that epigenetic marks at imprinted gene DMRs are established in a sex-specific manner in bovine blastocysts, after somatic cloning [67]. It remains unclear how epigenetic modifications fix the effects of early environmental events, in a sex-specific manner, ensuring sustained responses to transient stimuli and resulting in modified gene expression patterns and phenotypes later in life [68].

There is convincing experimental evidence to suggest that epigenetic marks act as a memory of exposure to inappropriate environments in early life. These marks induce long-term changes in gene expression, potentially leading to disease in later life. Disturbed placental epigenetics has been demonstrated in cases of intrauterine growth retardation and small for gestational age, and also appears to be involved in the pathogenesis of pre-eclampsia and gestational trophoblastic disease (reviewed in [69]). Our aims are to identify how and where epigenetic modifications fix the effects of early environmental events (overnutrition associated with a deleterious uterine environment) to ensure sustained responses to transient stimuli, leading to the modification of gene expression patterns and phenotypes later in life [41], [68]. We investigated the ways in which maternal diet might influence imprinted gene expression and epigenetic DNA methylation at the whole-genome level and in imprinted gene DMRs in male and female foetuses during the last third of pregnancy, when morphological development of the placenta is complete [70]. We investigated the impact of a high-fat diet (HFD) during pregnancy on the expression of 20 imprinted genes. We observed sex- and diet-specific differential expression of imprinted genes from four clusters, in the placentae of E15.5 male and female offspring from the litters of pregnant mice fed a HFD since the first day of gestation. Global DNA methylation also showed sex- and diet-specific differences.


Developmental studies

Pregnant females were weighed on the day of the vaginal plug and at E15.5. Overall, HFD-fed mothers had a weight gain that was higher than CD fed mothers (14.0±0.3g vs 10.3±0.3g, p = 0.0001), but when the weight gain is reported in relation to the number of fœtuses, there was no difference in weight gain between animals on the two different diets (2.0±0.13g vs 1.8±0.13g, p = 0.2173). We determined placental and foetal weights at E15.5 for 110 female and 81 male foetuses from mothers on the CD, and for 99 female and 103 male foetuses from mothers on the HFD (Table 1). No gross physical deformities were observed in either the control or the high-fat group and litter size was not affected by the HFD. The main effect of sex was on placental weight, the placenta being heavier for male than for female foetuses, regardless of diet (p<0.0001): 9.7% heavier for the CD and 11.2% heavier for the HFD. Diet affected placental weight regardless of the sex of the offspring (p<0.0001), with the HFD resulting in a 6.4% heavier placenta for females and a 7.9% heavier placenta for males. Embryo weight did not differ significantly between the sexes and was unaffected by diet. Remarkably, the foetal weight to placental weight ratio index (FPI), reflecting nutrient transfer from the placenta to the foetuses, was affected by diet (p = 0.0039), the HFD reducing the FPI, and was different according to the sex (p<0.0001), females having a greater FPI than males.

Table 1. Foetal and placental weights in the high-fat diet mouse model.

Analysis of gene expression by RT-qPCR: effects of sex and of diet

We used RT-qPCR to analyse the expression in the placenta of 20 genes located in seven imprinted clusters on five chromosomes. We studied six pools of female foetuses and six pools of male foetuses from mothers fed the CD, and seven pools of female foetuses and seven pools of male foetuses from mothers fed the HFD. Each pool comprised all the placentae from male or female mice from the same litter (n = 3–7).

ANOVA indicated a main effect of sex on the expression of three genes (Peg10, Slc22a1, Slc22a2; Table 2), males having a weaker expression than females. Post hoc analysis (comparing two groups) showed that the expression of four genes (Peg10, Asb4, Peg3 and Slc22a2) was significantly weaker in male offspring than in female offspring and that the expression of Ascl2 was significantly weaker in female offspring than in male offspring when the mother was fed the CD (Table 2).

Table 2. Placental mRNA levels for 17 candidate genes, determined by RT-qPCR, in the high-fat diet mouse model.

ANOVA indicated a main effect of diet on the expression of three genes located within the same cluster on chromosome 17 (Slc22a1, Slc22a2, Slc22a3) and one gene on chromosome 12: Rtl1. Slc22a2 expression was increased by the HFD, particularly in males, whereas expression levels for Slc22a1 and Slc22a3 were lower when the mother was fed the HFD. For Igf2r, we observed a non-significant trend towards lower levels of expression when the mother was fed the HFD (Table 2). No effect of diet was detected for the expression of 16 transcripts (Gatm, Sgce, Peg10, Ppp1r9a, Pon3, Pon2, Asb4, Peg3, Igf2P0, Igf2, H19, Ascl2, Gtl2, Dlk1, Dio3, and Airn). No interaction between sex and diet was detected for any of the genes analysed (Table 2).

Post-hoc analysis was carried out to check for a sexually dimorphic response to diet in the two groups. Dlk1 and Dio3, showed no global (ANOVA) differences, but the HFD significantly decreased the expression of these genes in females only.

We used another statistical approach, supervised clustering analysis, to confirm the discriminant value of the cluster of genes on chromosome 17. The five genes for which RT-qPCR was carried out that mapped to chromosome 17 (Slc22a1, Slc22a2, Slc22a3, Igf2r, Airn) were studied with a linear discriminant approach (Figure 1). Pooled samples from individuals were projected on the first two discriminant axes, which accounted for 99.6% of the inter-class variability (58.8% and 40.8%, respectively). The compactness and distance of the inertia ellipses confirm that the expression profiles for these five genes can be used to discriminate between pool samples as a function of sex and diet, although this discrimination seems to be better for animals in the CD group than for those in the HFD group (Fig. 1A). As shown by the correlation circle, Slc22a2 contributes mostly to sex discrimination, being overexpressed in females and in the presence of a HFD. By contrast, Slc22a1, Slc22a3 and Igf2r contribute mostly to diet discrimination and are overexpressed in females and in the presence of the CD. By contrast, Airn makes little contribution to the discrimination axes (Fig. 1B).

Figure 1. Linear discriminant supervised clustering analysis.

The five genes mapping to chromosome 17 for which RT-qPCR was carried out (Slc22a1, Slc22a2, Slc22a3, Igf2r, Air) were studied by a linear discriminant approach. (A) Pooled results from individuals were projected onto the first two discriminant axes, which accounted for 99.6% of the inter-class variability. Inertia ellipses represent intra-class variability for each group. Discrimination power increases with the compactness and distance of the ellipses. (B) The correlation circle indicates the contribution of the five genes to the discriminant axes.

Analysis of gene expression by in situ hybridization

The location of the mRNAs for Dio3, Rtl1, Dlk1, Slc22a1, Slc22a2, and Slc22a3 was determined by in situ hybridisation, in four samples per group. The expression of Slc22a1, Slc22a2 and Dio3 was too weak for detection by this technique. In male and female placentae from animals fed the CD, the expression of Slc22a3, Dlk1 and Rtl1 was detected in the labyrinth zone, as previously reported (Figure 2). No difference between males and females was found in the location of the signals in CD and HFD samples. We investigated possible variation in the proportions of the placental layers, using ISH images for Rtl1 to measure the zone of expression (i.e. the labyrinth zone) and to compare the area obtained with the total area of the placenta, for the four different placentae of each group analysed. We detected no differences (Figure 2D). These data strongly suggest that the variation in expression of these imprinted genes is not due to differences in the relative size of the labyrinth zone with respect to the other layers [71], [72].

Figure 2. Analysis of gene expression by in situ hybridization.

Detection by in situ hybridisation of Slc22a3 (A), Dlk1 (B) and Rtl1 (C) in of the placentae of female (F) or male (M) mouse embryos from mothers fed a control (CD) or high fat (HFD) diet. No difference in the distribution of these RNAs was observed, all of which were restricted to the labyrinth layer. The histograms (D) show the proportion of the labyrinth, this area being similar between the four groups.

Sexual dimorphism in methylation of the DMR of the Igf2r cluster in HFD mice

The RT-qPCR analysis detected two clusters (Dio3, Rtl1, Dlk1 on chromosome 12 and Slc22a1, Slc22a2, Slc22a3 on chromosome 17) displaying modified expression of genes involved in regulation of homeostasis. We investigated the epigenetic mechanisms potentially responsible for the changes in expression of these genes, by exploring DMR methylation. Based on the results of the supervised clustering analysis, showing greater discrimination with the Igf2r cluster, we decided to analyse the methylation levels of the DMR of this cluster. We used the bisulphite-sequencing method to analyse a 490 bp fragment encompassing 30 CpG in the DMR within intron 2 of the Igf2r gene [73] (Figure 3A). We studied DNA from the placentae of 12 female and 9 male foetuses from mothers fed the CD and 14 female and 15 male foetuses from mothers fed the HFD, corresponding to three CD litters and four HFD litters. We analysed 22 to 40 clones for each individual placenta, to ensure that we had enough sequences for the reliable determination of % of methylation for each CpG.

Figure 3. Schematic diagram of the Igf2r region on mouse chromosome 17.

(A), Box plot representing global methylation (B), specific CpG2 (C), sexual dimorphism under HFD (D), and sexual dimorphism under CD (E) obtained by bisulphite sequencing analysis of the DMR Igf2r encompassing 30 CpGs. The 30 CpGs are underlined. CpGs displaying sex-specific methylation under HFD and CD are shown in bold. Differences between methylation profiles were analysed by Mann-Whitney tests (p<0.05). F =  female, M =  male.

The analysis of all 30 CpG, as a group, revealed no significant difference between the sexes or between diets (Figure 3B). By contrast, when we analysed each CpG separately, we found significant differences in methylation between the sexes and between the diets. Four clustered CpGs showed statistically significant differences in DNA methylation when the group of females placentae under the HFD were compared to the group of male placentae under a HFD (numbers 1, 2, 3, 4 with 17%, 16%, 17%, 16%, respectively) (Figure 3D). For CpG2, only females showed a difference in methylation under the HFD (Figure 3C). Five clustered CpGs (number 7, 8, 9, 10, 12 with 18%, 12%, 19%, 17%, 19%, respectively) and CpG20 (16%) showed statistically significant differences in DNA methylation when the group of females placentae under a CD were compared to the group of male placentae under a CD (Figure 3E).

We checked for the presence of binding sites/responsive elements for chromatin remodelling factors and transcription factors (Genomatix®) in the Igf2r DMR (File S1). We identified potential consensus binding sites for more than 15 different factors in the region encompassing CpGs 1 to 4, which were differentially methylated as a function of diet. Binding sites or responsive elements for the following transcription factors/chromatin remodelling factors are compatible with the Igf2r DMR, from nucleotides 4 to 129: Pax4, Smarca3, Vbp, Pax6, Yy1, Oct1, Nrf2/Arp, Ppar/Rxr, Egr3, Rxr, Mzf1, Sry/Sox9, Gcm1, Stat6, Nudr/Deaf-1. Several of the corresponding genes, present in the Ensembl database, have been shown to display significant levels of expression in the placenta (Pax4, Smarca3, Nrf2/Arp, Ppar/Rxr, Egr3, Rxr, Stat6), consistent with a potential role for these factors.

For the Dlk1, Rtl1, Dio3 and Gtl2 cluster, we used the more rapid and quantitative pyrosequencing approach, which had already been optimised in our laboratory. We identified statistically significant differences in methylation for two CpGs, at positions 1 and 8 in the DMR, with an effect of sex (CpG 1 and 8; p = 0.044 and p = 0.045) and an effect of diet (CpG 1; p = 0.034). However, in contrast to the Igf2r DMR, these differences were not large enough (less than 10%) for us to be able to speculate about their role (data not shown).

Sexual dimorphism in global DNA methylation in mouse tissues and placenta

Global DNA methylation was assessed by the LUMA technique, in which the ratio of genomic DNA digested by the methylation-sensitive enzyme HpaII to that digested with the methylation-insensitive enzyme MspI indicates the level of cytosine demethylation. Figure 4A shows the distribution of relative methylation in five different tissues of six-month-old female mice fed the CD. The tissues studied were the liver (females n = 41), skeletal muscle (gastrocnemius) (females n = 10), kidney (females n = 20), and testis (males n = 39), together with the placenta at E15.5 (15 males and 25 females, n = 40). As previously reported, we found that the level of global DNA methylation in the placenta was markedly different from that in other somatic tissues (p<0.001) [74], [75], [76]. Differences between tissues were also observed in the % methylation, except between the liver and testis and between the muscle and kidney (Figure 4A). An effect of sex was observed under the CD. Male placentae displayed lower levels (3.3%) of methylation than female placentae (p = 0.035). Diet had an effect on global % methylation, but only in females (2.4% p = 0.032). Female placentae from mothers fed the HFD displayed lower levels of methylation (Figure 4B). The levels of methylation of SINE/B1 and LINE1, common repetitive elements, were assessed by bisulphite-pyrosequencing. No differences were observed for the entire collection of sequences explored (data not shown), demonstrating that the difference in global methylation observed was not due to these repetitive sequences [77].

Figure 4. Box plot representing global methylation of the genome.

Results obtained by LUMA, in five different tissues from six-month-old mice on the CD (liver, muscle, kidney, testis and placenta) at E15.5 (A), and from the placentae of female and male foetuses from mothers fed the CD or the HFD (B). Differences between methylation profiles were analysed by Mann-Whitney tests (p<0.05). Completely unmethylated DNA would have an HpaII/MspI ratio of 1.0, whereas 100% methylated DNA would have an HpaII/MspI ratio close to zero [121].


It has been suggested that changes in imprinted gene dosage in the placentae may compromise the prenatal control of nutritional resources [78]. However, the underlying mechanisms remain unclear. This study is the first to demonstrate that the placentae of male and female foetuses from mothers fed a HFD display changes in both the expression of selected imprinted genes from different clusters, and in genome-wide and CpG-specific DNA methylation, with these changes differing between the sexes.

Experimental and epidemiological studies in humans and animal models have demonstrated that predisposition to impaired glucose tolerance, blood pressure and coronary heart disease, are associated with either low or high FPI [9], [10], [11], [12], [13], [14], [23], [79], [80], [81]. We show here that FPI is sexually dimorphic. Female mice have a higher FPI than male mice. Moreover, we show, for a large number of animals (n = 81 to 110 per group), that feeding the mother a HFD for the first 15 days of gestation only is sufficient to increase placental weight significantly, for both males and females. However, this treatment had no effect on fetal weight, for the foetuses of either sex. Consequently, FPI was also affected by diet, with the HFD reducing FPI in both males and females. It would therefore be interesting to investigate the changes in the respective size of the placenta and foetus at term following the administration of a HFD to pregnant mice [82]. Indeed the FPI changes should not be overestimated since we are looking at E15.5, not at term as in published human data. Altogether the impaired nutrient transfer from the placenta to the foetus, as reflected by the sex- and diet-specific alterations of the FPI, is consistent with the role of placenta in utero in sexual dimorphic programming and subsequent impaired responses in adulthood [81].

Sexual dimorphism for imprinted genes

Only a few studies have reported the differential expression of individual gene products in human male and female placentae [42], [43], [44], [45]. Five of the 20 genes analysed in this study displayed sexual dimorphism when the mother was fed the CD: Peg10, Asb4, Peg3, Slc22a2, Ascl2. This proportion of sexually dimorphic genes is similar to that reported for other tissues or developmental stages [40], [41].

In a similar study performed at E12.5, in mice fed a low-fat diet, a very high-fat diet or an intermediate chow diet, Mao et al. observed that female placentae displayed more striking changes in gene expression with diet than male placentae [12]. This greater reactivity of females was also observed in total embryonic cells taken from mice at E10.5, before sexual differentiation [39]. Remarkably, these cells responded differently to the applied dietary stressors, even before the production of foetal sex hormones. In our study, carried out at E15.5, six genes (Slc22a1, Slc22a2, Slc22a3, Rtl1, Dlk1 and Dio3) displayed changes in expression pattern when the mother was fed the HFD. We observed sex-specific sensitivity to the HFD, with effects limited to or more pronounced in the female placenta for Dlk1, Dio3, Slc22a1 or to the male placenta for Slc22a2 only. Our results are therefore consistent with previous findings that female placentae display more striking changes in gene expression in response to maternal diet than male placentae. As suggested by Penaloza et al., this difference in cell behaviour and sensitivity appears to be driven by the genetic sex of the cells from the outset, with the effects of factors such as hormones subsequently being superimposed on this difference [39]. Concerning the chromosome 17 cluster, (Slc22a2, Slc22a1 and Slc22a3), the sex steroid hormone oestrogen down-regulates renal organic cation transport in animals and may contribute to sex-related differences in xenobiotic accumulation and excretion [83], [84], [85]. However, caution is required when extrapolating transport-related sex differences between species and organs. These data on sexual dimorphism in organic cation transport are nonetheless potentially interesting when trying to understand the differences between the sexes in terms of the response in the placenta. For the chromosome 12 cluster, an effect of diet was observed for the paternally expressed Dlk1, Rtl1 and Dio3 genes, but not for the maternally expressed Gtl2/meg3 genes, with female placentae again more sensitive than male placentae to the effects of the HFD.

One potential limitation of our study is that the placenta contains mixed cell populations. Changes in the proportions of the different cell populations could generate the differences observed, independently of changes in DNA methylation or gene expression in a single cell population [86]. Most expression studies in mice have analysed whole placentae [12], [34], [87], [88], but this analysis should ideally be based on an isolated cell population, making it possible to draw direct conclusions [89], [90]. We addressed this concern, by performing in situ hybridisation to visualise the expression of six genes that were differentially expressed and belonged to two clusters of dysregulated imprinted genes, on chromosomes 12 and 17. We detected no difference in the location of the signals or in the size of the zone of expression, for Rtl1, Dlk1 and Slc22a3, between the male and female offspring of mice fed the CD and HFD. We cannot exclude the possibility of ectopic expression below the level of detection of this technique, but our data strongly suggest that the variation in expression of these genes, which are principally expressed in the labyrinth zone, is not due to a gross enlargement or reduction of the labyrinth zone with respect to the other layers.

Function of the dysregulated imprinted genes

The body has various broad-specificity transporters for the elimination of environmental toxins and metabolic waste products. The non-neuronal monoamine transporters are polyspecific organic cation transporters (Oct1, 2, and 3 or Slc22a1, 2, and 3). They control signal transmission by removing released transmitters, such as dopamine, noradrenaline, adrenaline, 5-hydroxytryptamine and histamine, from the extracellular space [91], [92]. Monoamine concentrations are normally kept low in the placenta. In humans, pre-eclampsia, which is characterized by high blood pressure and proteinuria, is one of the most common causes of perinatal and maternal morbidity and mortality. Monoamine transporters may protect against this condition by preventing vasoconstriction in the placental vascular bed, thereby ensuring stable blood flow to the foetus. In pre-eclampsia, hyperactivity of the sympathetic nervous system and high levels of circulating vasoactive substances, such as monoamines, have been observed. SLC22A3 expression levels have been shown to be significantly lower in pre-eclamptic placentae than in normal placentae [93]. Defective expression of the genes encoding these monoamine transporters might account for the high concentrations of monoamines in patients with pre-eclampsia. The low level of expression of Slc22a3 reported here may have led to similar disturbances in vasoconstriction and nutrient transport, accounting for the lower FPI.

The Dio3, Rtl1, Dlk1 genes of the other cluster were expressed less strongly under a HFD than under a control diet. Interestingly, the maternally expressed Gtl2 gene was not affected, precluding the involvment of this gene in the changes in gene expression of the paternally expressed Dio3, Rtl1, and Dlk1 genes [94]. The Rtl1 gene (retrotransposon-like 1), plays a determinant role in the foeto-maternal interface of mouse placenta [95]. Rtl1 is essential for the maintenance of foetal capillaries, and both its loss and its overproduction cause late-foetal or neonatal death in mice [72]. There is evidence to suggest that genomic imprinting and gene expression at the Dlk1/Dio3 imprinted domain may play a role in controlling adipocyte proliferation and differentiation [96], [97]. However, the roles of Dio3 and Dlk1 in placenta remain unknown. Thus, the decrease in the expression of Slc22a3 and Rtl1 under a HFD may contribute to changes in vascular function, resulting in the misregulation of nutrient transfer to the foetus. This led us to explore the DMR of these two clusters.

Differential CpG methylation of the Igf2r DMR

The transporter genes Slc22a2 and Slc22a3 are imprinted specifically in mouse placenta [32]. The promoters of the repressed paternal alleles of these genes do not display DNA methylation [98]. The Igf2r imprint control element (ICE), which is a DMR containing 30 CpG, plays a crucial role in regulating many imprinted genes in this cluster. We therefore investigated whether adaptation of the nutrient supply to foetal demand in pregnant mice fed a HFD involved the ICE/DMR regulating these important placental transporter systems. We decided to investigate methylation of the DMR, despite previous reports that the difference in methylation is associated with regulation of monoallelic expression, rather than with expression levels per se.

In an analysis of all 30 CpG of the ICE together, we found no statistically significant difference between the sexes or the two diets. However, we observed sex- and diet-specific differential methylation of individual CpGs within two subregions of the DMR. Significantly different levels of methylation between the sexes were found for the first four CpGs in foetuses from mothers fed the HFD. Similarly, different levels of methylation between the sexes were found for the next five CpG and for CpG 20, in foetuses from mothers fed the CD. CpG 2 was the only CpG displaying both dietary and sexual dimorphism.

Bioinformatic analysis suggested that the CpGs displaying sex- and diet-specific differential methylation in the DMR might lie within recognition elements or binding sites for transcription factors or factors involved in chromatin remodelling, or within a higher-order chromatin architecture: Pax4, Smarca3, Nrf2/Arp, Ppar/Rxr, Egr3, Rxr, Stat6. PPAR-alpha and -gamma agonists increase Slc22a1 gene transcription, thereby increasing the levels of the corresponding protein and increasing cellular organic cation uptake [99]. These data suggest that PPAR/RXR is one of the most likely candidate transcription factors, as the HFD contains well-known lipid ligands for these nuclear receptors. It is also tempting to speculate that the factors binding to this subregion may also interact with each other in a fatty acid-controlled transcriptional process. The helicase-like transcription factor (HLTF/SMARCA3) belongs to the SWI/SNF family of proteins. These proteins remodel chromatin in various cellular processes. Another member of the SMARC (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin) family has recently been shown to function as a coactivator of another member of the nuclear receptor family [100]. However, it must be kept in mind that high-fat also correlates with low carbohydrate in the present diet, thus potentially influencing pathways involved in growth such as the insulin- and related signaling pathways.

It remains unclear whether and how these altered methylation profiles directly affect the expression profiles of the imprinted genes Slc22a2, and Slc22a3 and that of the non-imprinted Slc22a1 gene. The silencing of the paternal allele of the three imprinted genes (Igf2r, Slc22a2 and Slc22a3) requires the expression, in cis, of Airn, which overlaps with the promoter of one of these genes (Igf2r) [101]. We observed no change in Airn and Igf2r expression, a decrease in Slc22a1 and Slc22a3 expression and an increase in Slc22a2 expression in the placenta in mice fed the HFD. [98]. Sex- and diet-specific changes in the methylation of groups of CpGs in the DMR may alter the influence of Airn RNA in different ways for the three genes (Igf2r, Slc22a2 and Slc22a3). The promoters of these genes display no differential DNA methylation, therefore, histone modifications, which are likely to underlie the regulation of placental imprinted genes, may constitute an avenue of investigation. However, we were unable to study such modifications due to the mode of placenta sampling in this study.

For the Dlk1, Rtl1, Dio3 and Gtl2 cluster, in contrast to the Igf2r DMR, the differences in DNA methylation were modest. However, as shown very recently by Kagami et al, there is an additional functional DMR in this cluster. The IG-DMR, the DMR studied in the present report, and the Gtl2-DMR function as imprinting control centers in the placenta and the body, respectively [102].

Diet-induced changes in DNA methylation in placenta

The maternal HFD leads to a global hypomethylation in placenta compared to the maternal CD. This hypomethylation is statistically significant in females only. Could this hypomethylation be due to a reduction in methyl donor supply in the diet? To our knowledge, according to reports on food intake of high energy diets during gestation in rodents, the mothers either adjust their food intake in terms of calories regardless of the diet [103] or increase the caloric intake [104], [105]. In the case of the HFD and CD used in the present study (Research diets HFD D12492 and CD D12450B) the supply in vitamines is the same (40 kcal for 4057 kcal diet). Therefore, although the average daily food intake was not measured we can assume that the supply in vitamins B9 and B12 was not decreased in the HFD animals. Thus it is difficult to relate the hypomethylation observed to either an identical or increased level of vitamin supply. A global hypomethylation was also observed in brains of offspring of HF fed mice mothers [106]. However it remains difficult to speculate about the potential role of the highfat/low carbohydrate composition of the diet on the one-carbon metabolism, in the absence of relevant mechanisms to account for a potential link.

Sexual dimorphism and global methylation

To our knowledge, this is the first report of sexual dimorphism for DNA methylation in the placenta under a control diet. This dimorphism may be due to the presence of an inactive X (Xi) chromosome in the female. In mouse extraembryonnic tissues, X chromosome inactivation is imprinted to occur selectively on the paternal X chromosome [107]. However, Weber et al. overturned previous views by showing that Xi was hypermethylated at only a subset of gene-rich regions and, unexpectedly, displayed overall hypomethylation with respect to its active counterpart [108]. Hellman et al. have shown that the active X (Xa) chromosome in females has levels of allele-specific methylation twice those of Xi. A bipartite methylation-demethylation program results in Xa-specific hypomethylation at gene promoters and hypermethylation at gene bodies in both male and female active Xa chromosomes [109].

We investigated this difference in methylation further, by assessing the methylation levels of the two major repetitive elements containing most of the genomic 5-methylcytosine bases: LINE-1 (long interspersed nucleotide element-1) and SINE-1 (short interspersed nucleotide element-1), represented by human Alu elements and the homologous mouse B1 elements. The methylation levels of both LINE-1 and SINE-1 have been reported to be a good indicator of cellular 5-methylcytosine level (i.e., global DNA methylation level) [110], [111]. In our placenta model, no difference in the level of LINE-1 or B1 repetitive element methylation was observed between the sexes or between the diets, CD and HFD. These differences are therefore probably located in non-genic regions, gene bodies and centromeric heterochromatin.

It has been suggested that the inherently lower level of methylation in the placenta than in other tissues [74], [75], [76] may render this organ highly susceptible to the effects of environmental factors, altering epigenetic patterns [32], [36], [112], [113], [114]. Consistent with this hypothesis, there have been several reports of global changes in DNA methylation in the placenta associated with IUGR, pre-eclampsia or undernutrition in the mother [36], [112], [113], [115]. Surprisingly, in this study, only females were sensitive to the HFD, resulting in undermethylation. These observations in mouse support the suggestion put forward by V. Clifton that sexually dimorphic differences in the growth and survival of the foetus are mediated by the sex-specific function of the human placenta [37], [38].


Evidence in favour of non-genetic transgenerational inheritance is accumulating, in some cases with conspicuous, marked sexual dimorphism both for the mode of transmission and for the resulting effects [41]. Finely tuned aspects of the developmental programme, specific to one sex, may be more sensitive to specific environmental challenges, particularly during developmental programming and gametogenesis, but also throughout the individual's life, under the influence of sex steroid hormones. These findings highlight the importance of studying both sexes in epidemiological protocols or dietary interventions, both in humans and in experimental animal models. They pave the way to explorations concerning the possible targeting, by fatty acids and other nutrients, of conspicuous regions in the genome harbouring binding sites for the recruitment of diet- and tissue-specific chromatin remodelling complexes.

Materials and Methods

Ethics statement

All experiments on animals were conducted in accordance with the European Communities Council Directive of 1986 (86/609/EEC). Our laboratory has accreditation from the French Ministry of Agriculture for experimentation with mice (No. A 75-15-02). Approval of full details of the study by an ethics committee is not required under French laws.

Experimental design and nutritional treatments

Four-week-old DBA/2 male and C57BL/6J female mice were obtained from Harlan® and housed in groups until mating. All animals were maintained under controlled light (12 h light/12 h dark cycle, light on at 07:00) and temperature (22±2°C) conditions.

The mice were allowed access to water and the control diet ad libitum. After two weeks of adaptation, DBA/2 male mice were mated with C57BL/6J female mice in the evening. The following day (day 0.5), if a vaginal plug was observed, females were fed either a HFD or a CD ad libitum for 15 days. The pregnant females were killed at E15.5, and placentas and foetuses were dried, weighed and frozen in liquid nitrogen before storage at −80°C. Diets were supplied in pellet form by Research Diets (New Brunswick, USA; CD: D12450B, HFD: D12492). For the CD, 10% of calories were in the form of fat, 20% were in the form of protein and 70% were in the form of carbohydrates. For the HFD, 60% of calories were in the form of fat, 20% were in the form of protein and 20% were in the form of carbohydrates [116].

DNA was extracted from the leg of mouse foetuses, using the DNeasy Tissue Kit (Qiagen). The sex of the foetus was determined by PCR of the SRY gene, as previously described [117].

RNA extraction

Total RNA was extracted from rodent placenta with the RNeasy Mini kit® (Qiagen S.A., Courtaboeuf, France) and its concentration was determinated by measuring absorbance at 260 nm. RNA quality was assessed by agarose gel electrophoresis.

Reverse transcription-quantitative PCR (RT-qPCR)

We determined mRNA levels for the genes of interest by reverse transcription followed by quantitative PCR (RT-qPCR). First-strand cDNAs were synthesised from 2(μg of total RNA in the presence of 50 ng random hexamers (GE Healthcare, Saclay, France), 400 nM dNTPs and 200 U Superscript™ II RNase H Reverse Transcriptase (Invitrogen, Cergy-Pontoise, France), according to the manufacturer's instructions. We checked that there was no DNA contamination by amplifying the 101 bp of the Ucp2 gene, using forward 5′-TGTCGAAGCCTACAAGAC-3′and reverse 5′-CAGCACAGTTGACAATGG-3′primers.

RT-qPCR analyses were carried out with the Absolute Blue qPCR SYBr Green Rox Mix (Thermo Scientific, Courtaboeuf, France), using an ABI PRISM 7300 apparatus, according to the manufacturer's instructions. Each reaction was carried out in a final volume of 25μl, in triplicate. Standard curves were generated for each run from 10-fold dilutions of cDNAs, to determine primer efficiency. Controls lacking reverse transcriptase were carried out alongside quantitative RT-qPCR for experimental samples, with SYBr Green. The controls consistently yielded no amplification below 40 cycles, using the above protocol. The 18S rRNA control was used to normalise the amount of template for each sample. Data were analysed with Microsoft Excel. The list of primers and real-time PCR assay conditions are available upon request.

Bisulphite-cloning-sequencing methylation assay

DNA was isolated from mouse placentae using the DNeasy Tissue Kit (Qiagen). The isolated DNA was then treated with sodium bisulphite, using the EZ DNA Methylation Gold Kit (Proteigene, Saint-Marcel, France). The bisulphite-converted DNA was amplified by semi-nested PCR, using the primers Igf2r 13B-4, Igf2r 13B-2 and Igf2r 13B-5, as previously described [73]. The PCR products were purified with the Qiaquick PCR purification kit (Qiagen, Courtaboeuf, France), cloned with the PMOSblue Blunt Ended Cloning Kit (GE Healthcare, Saclay, France) and sequenced. The bisulphite treatment was more than 98% efficient. Quality control was carried out and methylation profiles were analysed with BiQ Analyzer software [118].

Bisulphite quantitative pyrosequencing methylation assay

We treated 1 µg of genomic DNA with sodium bisulphite, using EpiTect® 96 bisulphite (Qiagen, Courtaboeuf, France) according to the manufacturer's instructions. Quantitative DNA methylation analysis of the bisulphite-treated DNA was performed by pyrosequencing or, in the case of several sequencing primers, by serial pyrosequencing [119]. Regions of interest were amplified from 25 ng of bisulphite-treated mouse genomic DNA, with 5 pmol of forward and reverse primers, one of which was biotinylated. Assays for the Dlk1-Rtl-Dio3-Gtl2 cluster were performed as previously described [120].

DMR assays for the B1 repeat, as a surrogate for global DNA methylation changes, were performed as previously described [111] (Table 3). Primers for the LINE-1 element were designed to amplify nucleotides 64-326 of the consensus sequence (GenBank: D84391.1). Standard reaction conditions were HotStar Taq buffer, 1.6 mM MgCl2, 100 µM dNTPs and 2U HotStar Taq polymerase (Qiagen, Courtaboeuf, France) in a 25 µl volume. The PCR program consisted of 50 cycles of 30 s at 95°C, 30 s at the annealing temperature and 20 s at 72°C. Purification of the PCR product with streptavidin Sepharose HP beads (GE Healthcare, Uppsala, Sweden) and hybridization of the biotinylated PCR products and the sequencing primer were conducted as described in the PSQ96 sample preparation guide, using a vacuum filtration sample transfer device (Pyrosequencing AB, Uppsala, Sweden). Sequencing was performed on a PSQ 96MA system with the PyroGold SQA reagent kit, according to the manufacturer's instructions, and the results were analyzed with Q-CpG software V.1.0.9 (Pyrosequencing AB) [119].

Table 3. Bisulphite pyrosequencing analysis of repeated B1 and LINE sequences.

Luminometric methylation assay (LUMA)

This assay was performed as previously described [121]. Briefly, genomic DNA (200 to 500 ng) was cleaved with HpaII+EcoRI, and MspI+EcoRI in two separate reactions in 96-well pyrosequencing plates. Digestion reactions were run in the PSQ96 MA system (Biotage AB). Peak heights were calculated with PSQ96 MA software. The HpaII/EcoRI and MspI/EcoRI ratios were calculated as (dGTP+dCTP)/dATP for the corresponding reactions. DNA methylation was assessed by calculating the HpaII/MspI ratio or, more precisely, by calculating the (HpaII/EcoRI)/(MspI/EcoRI) ratio.

Statistical analysis

All data are expressed as means ± standard error (SEM). The effects of sex and diet on expression of the 18 genes tested were assessed by two-way ANOVA with post hoc testing (p<0.05), carried out with Statview (SAS Institute, Inc., Cary, NC). Supervised clustering analysis, using a linear discriminant approach, was performed with the ade4 package ( in the R statistical environment ( Differences between methylation profiles were analysed by carrying out Mann-Whitney tests with Statview.

In situ hybridisation

Sections (12 µm thick) of some control and HFD placentae (n = 4) were mounted on gelatin-coated slides, dried and kept at −80°C. In situ hybridisation was performed as previously described [122]. The Dlk1 probe was kindly provided by Dr. A. Ferguson-Smith (Cambridge, UK) and the Slc22a3 probe was provided by Dr. D. Barlow (Vienna, Austria). Dio3, Rtl1, Slc22a1 and Slc22a2 probes were obtained by PCR on placental cDNA with the following primers: Dio3-F ATTCACCCTATGTCATCCCCCAGC and Dio3-R TCCTGAGAGCAAGCCAAAAACG at 54°C, Rtl1-F GCCCAGGAACACTATGTGGAACTC and Rtl1-R AAGTCTCATCATCTGCCTCCCTCG at 65°C, Slc22a1-F GAAGAGAACCACTCAAGCGGTAAGG and Slc22a2-R AGACAAGCGAGGGTCACATTCAAC at 54°C, Slc22a2-F AGACAGGTTTGGGCGGAAGTTC and AAGCAGAAGTTGGGCAGAGTCACG at 54°C. PCR fragments (489, 400, 435 and 315 bp, respectively) were inserted into pCR II vectors according to the TOPO TA cloning protocol (Invitrogen). The probes were linearised and labelled with [35S]-dUTP (1,300 Ci/mmol, Amersham Biosciences, Germany), with the Sp6/T7 Transcription Kit (Roche Diagnostics, Germany). Controls included hybridisation with a sense probe; no specific hybridisation signal was observed under these conditions, for any of the sense probes. For each probe, all the slides were placed against a single X-ray film (Biomax-MR, Kodak, France). All autoradiographs were digitised during the same session. For Slc22a3, Dlk1 and Rtl1, the signal was measured for 4 slides per placenta and 4 placentae per group. The results are expressed in OD x mm2. The measure of the proportion of the labyrinth corresponds to Rtl1 signal surface to total surface ratio.

Supporting Information

File S1.

Search for potential transcription factor binding sites in the 490 bp of the DMR, including the 30 CpGs, with Genomatix.

(0.09 MB DOC)


We thank Dr. D. Barlow (Vienna, Austria) and Dr. A. Fergusson-Smith (Cambridge, UK) for making available the probes for ISH experiments.

Author Contributions

Conceived and designed the experiments: CGK AG JT JL BR CR DV TJE CJ. Performed the experiments: CGK AG JT MK SM EB MSG JT AV CB. Analyzed the data: CGK AG JT JL JPJ CJ. Contributed reagents/materials/analysis tools: JT JL CB BR CR DV. Wrote the paper: CGK AG CJ. Acquired funding for the experiments: JT JL BR CR DV TJE CJ. Supervised: CJ.


  1. 1. McAllister EJ, Dhurandhar NV, Keith SW, Aronne LJ, Barger J, et al. (2009) Ten putative contributors to the obesity epidemic. Crit Rev Food Sci Nutr 49: 868–913.
  2. 2. Barker DJ (1992) The fetal origins of diseases of old age. Eur J Clin Nutr 46: Suppl 3S3–9.
  3. 3. Eckel RH, Alberti KG, Grundy SM, Zimmet PZ (2010) The metabolic syndrome. Lancet 375: 181–183.
  4. 4. Nathanielsz PW, Poston L, Taylor PD (2007) In utero exposure to maternal obesity and diabetes: animal models that identify and characterize implications for future health. Obstet Gynecol Clin North Am 34: 201–212, vii-viii.
  5. 5. Guo F, Jen KL (1995) High-fat feeding during pregnancy and lactation affects offspring metabolism in rats. Physiol Behav 57: 681–686.
  6. 6. Ehrenberg HM, Mercer BM, Catalano PM (2004) The influence of obesity and diabetes on the prevalence of macrosomia. Am J Obstet Gynecol 191: 964–968.
  7. 7. Smith GC, Shah I, Pell JP, Crossley JA, Dobbie R (2007) Maternal obesity in early pregnancy and risk of spontaneous and elective preterm deliveries: a retrospective cohort study. Am J Public Health 97: 157–162.
  8. 8. Janney CA, Zhang D, Sowers M (1997) Lactation and weight retention. Am J Clin Nutr 66: 1116–1124.
  9. 9. Ericsson A, Saljo K, Sjostrand E, Jansson N, Prasad PD, et al. (2007) Brief hyperglycaemia in the early pregnant rat increases fetal weight at term by stimulating placental growth and affecting placental nutrient transport. J Physiol 581: 1323–1332.
  10. 10. Thornburg KL, O'Tierney PF, Louey S (2010) Review: The placenta is a programming agent for cardiovascular disease. Placenta 31: SupplS54–59.
  11. 11. Sibley CP, Brownbill P, Dilworth M, Glazier JD (2010) Review: Adaptation in placental nutrient supply to meet fetal growth demand: implications for programming. Placenta 31: SupplS70–74.
  12. 12. Mao J, Zhang X, Sieli PT, Falduto MT, Torres KE, et al. (2010) Contrasting effects of different maternal diets on sexually dimorphic gene expression in the murine placenta. Proc Natl Acad Sci U S A.
  13. 13. Lim AL, Ferguson-Smith AC (2010) Genomic imprinting effects in a compromised in utero environment: Implications for a healthy pregnancy. Semin Cell Dev Biol 21: 201–208.
  14. 14. Gatford KL, Simmons RA, De Blasio MJ, Robinson JS, Owens JA (2010) Review: Placental programming of postnatal diabetes and impaired insulin action after IUGR. Placenta 31: SupplS60–65.
  15. 15. Simmons DG, Fortier AL, Cross JC (2007) Diverse subtypes and developmental origins of trophoblast giant cells in the mouse placenta. Dev Biol 304: 567–578.
  16. 16. Cross JC (2000) Genetic insights into trophoblast differentiation and placental morphogenesis. Semin Cell Dev Biol 11: 105–113.
  17. 17. Hemberger M, Cross JC (2001) Genes governing placental development. Trends Endocrinol Metab 12: 162–168.
  18. 18. Maltepe E, Bakardjiev AI, Fisher SJ (2010) The placenta: transcriptional, epigenetic, and physiological integration during development. J Clin Invest 120: 1016–1025.
  19. 19. Cross JC, Mickelson L (2006) Nutritional influences on implantation and placental development. Nutr Rev 64: S12–18; discussion S72-91.
  20. 20. Hemberger M (2007) Epigenetic landscape required for placental development. Cell Mol Life Sci 64: 2422–2436.
  21. 21. Myatt L (2006) Placental adaptive responses and fetal programming. J Physiol 572: 25–30.
  22. 22. Fowden AL, Sibley C, Reik W, Constancia M (2006) Imprinted genes, placental development and fetal growth. Horm Res 65: Suppl 350–58.
  23. 23. Barker DJ, Thornburg KL, Osmond C, Kajantie E, Eriksson JG (2010) The surface area of the placenta and hypertension in the offspring in later life. Int J Dev Biol 54: 525–530.
  24. 24. Kwong WY, Wild AE, Roberts P, Willis AC, Fleming TP (2000) Maternal undernutrition during the preimplantation period of rat development causes blastocyst abnormalities and programming of postnatal hypertension. Development 127: 4195–4202.
  25. 25. Kwong WY, Miller DJ, Ursell E, Wild AE, Wilkins AP, et al. (2006) Imprinted gene expression in the rat embryo-fetal axis is altered in response to periconceptional maternal low protein diet. Reproduction 132: 265–277.
  26. 26. Wu Q, Zhou ZJ, Ohsako S (2006) [Effect of environmental contaminants on DNA methyltransferase activity of mouse preimplantation embryos]. Wei Sheng Yan Jiu 35: 30–32.
  27. 27. Watkins AJ, Ursell E, Panton R, Papenbrock T, Hollis L, et al. (2008) Adaptive responses by mouse early embryos to maternal diet protect fetal growth but predispose to adult onset disease. Biol Reprod 78: 299–306.
  28. 28. Ashworth CJ, Toma LM, Hunter MG (2009) Nutritional effects on oocyte and embryo development in mammals: implications for reproductive efficiency and environmental sustainability. Philos Trans R Soc Lond B Biol Sci 364: 3351–3361.
  29. 29. Mitchell M, Schulz SL, Armstrong DT, Lane M (2009) Metabolic and mitochondrial dysfunction in early mouse embryos following maternal dietary protein intervention. Biol Reprod 80: 622–630.
  30. 30. Angiolini E, Fowden A, Coan P, Sandovici I, Smith P, et al. (2006) Regulation of placental efficiency for nutrient transport by imprinted genes. Placenta 27: Suppl98–102.
  31. 31. Constancia M, Angiolini E, Sandovici I, Smith P, Smith R, et al. (2005) Adaptation of nutrient supply to fetal demand in the mouse involves interaction between the Igf2 gene and placental transporter systems. Proc Natl Acad Sci U S A 102: 19219–19224.
  32. 32. Wagschal A, Feil R (2006) Genomic imprinting in the placenta. Cytogenet Genome Res 113: 90–98.
  33. 33. Constancia M, Kelsey G, Reik W (2004) Resourceful imprinting. Nature 432: 53–57.
  34. 34. Gheorghe CP, Goyal R, Mittal A, Longo LD (2010) Gene expression in the placenta: maternal stress and epigenetic responses. Int J Dev Biol 54: 507–523.
  35. 35. Gheorghe CP, Goyal R, Holweger JD, Longo LD (2009) Placental gene expression responses to maternal protein restriction in the mouse. Placenta 30: 411–417.
  36. 36. Coan PM, Vaughan OR, Sekita Y, Finn SL, Burton GJ, et al. (2010) Adaptations in placental phenotype support fetal growth during undernutrition of pregnant mice. J Physiol 588: 527–538.
  37. 37. Clifton VL (2010) Review: Sex and the human placenta: mediating differential strategies of fetal growth and survival. Placenta 31: SupplS33–39.
  38. 38. Clifton VL, Hodyl NA, Murphy VE, Giles WB, Baxter RC, et al. (2010) Effect of maternal asthma, inhaled glucocorticoids and cigarette use during pregnancy on the newborn insulin-like growth factor axis. Growth Horm IGF Res 20: 39–48.
  39. 39. Penaloza C, Estevez B, Orlanski S, Sikorska M, Walker R, et al. (2009) Sex of the cell dictates its response: differential gene expression and sensitivity to cell death inducing stress in male and female cells. FASEB J 23: 1869–1879.
  40. 40. Bermejo-Alvarez P, Rizos D, Rath D, Lonergan P, Gutierrez-Adan A (2010) Sex determines the expression level of one third of the actively expressed genes in bovine blastocysts. Proc Natl Acad Sci U S A 107: 3394–3399.
  41. 41. Gabory A, Attig L, Junien C (2009) Sexual Dimorphism in Environmental Epigenetic Programming. Molecular cellular endocrinology 25: 8–18.
  42. 42. Lehavi O, Aizenstein O, Evans MI, Yaron Y (2005) 2nd-trimester maternal serum human chorionic gonadotropin and alpha-fetoprotein levels in male and female fetuses with Down syndrome. Fetal Diagn Ther 20: 235–238.
  43. 43. Steier JA, Bergsjo PB, Thorsen T, Myking OL (2004) Human chorionic gonadotropin in maternal serum in relation to fetal gender and utero-placental blood flow. Acta Obstet Gynecol Scand 83: 170–174.
  44. 44. Brown MJ, Cook CL, Henry JL, Schultz GS (1987) Levels of epidermal growth factor binding in third-trimester and term human placentas: elevated binding in term placentas of male fetuses. Am J Obstet Gynecol 156: 716–720.
  45. 45. Sood R, Zehnder JL, Druzin ML, Brown PO (2006) Gene expression patterns in human placenta. Proc Natl Acad Sci U S A 103: 5478–5483.
  46. 46. Gheorghe CP, Mohan S, Oberg KC, Longo LD (2007) Gene expression patterns in the hypoxic murine placenta: a role in epigenesis? Reprod Sci 14: 223–233.
  47. 47. Luedi PP, Dietrich FS, Weidman JR, Bosko JM, Jirtle RL, et al. (2007) Computational and experimental identification of novel human imprinted genes. Genome Res 17: 1723–1730.
  48. 48. Luedi PP, Hartemink AJ, Jirtle RL (2005) Genome-wide prediction of imprinted murine genes. Genome Res 15: 875–884.
  49. 49. Frost JM, Moore GE (2010) The importance of imprinting in the human placenta. PLoS Genet 6: e1001015.
  50. 50. Brideau CM, Eilertson KE, Hagarman JA, Bustamante CD, Soloway PD (2010) Successful computational prediction of novel imprinted genes from epigenomic features. Mol Cell Biol 30: 3357–3370.
  51. 51. Weber M, Hagege H, Aptel N, Brunel C, Cathala G, et al. (2005) Epigenetic regulation of mammalian imprinted genes: from primary to functional imprints. Prog Mol Subcell Biol 38: 207–236.
  52. 52. Sibley CP, Coan PM, Ferguson-Smith AC, Dean W, Hughes J, et al. (2004) Placental-specific insulin-like growth factor 2 (Igf2) regulates the diffusional exchange characteristics of the mouse placenta. Proc Natl Acad Sci U S A 101: 8204–8208.
  53. 53. Coan PM, Burton GJ, Ferguson-Smith AC (2005) Imprinted genes in the placenta—a review. Placenta 26: Suppl AS10–20.
  54. 54. Gabory A, Ripoche MA, Le Digarcher A, Watrin F, Ziyyat A, et al. (2009) H19 acts as a trans regulator of the imprinted gene network controlling growth in mice. Development 136: 3413–3421.
  55. 55. Varrault A, Gueydan C, Delalbre A, Bellmann A, Houssami S, et al. (2006) Zac1 regulates an imprinted gene network critically involved in the control of embryonic growth. Dev Cell 11: 711–722.
  56. 56. Noguer-Dance M, Abu-Amero S, Al-Khtib M, Lefevre A, Coullin P, et al. (2010) The primate-specific microRNA gene cluster (C19MC) is imprinted in the placenta. Hum Mol Genet 19: 3566–3582.
  57. 57. Waterland RA, Lin JR, Smith CA, Jirtle RL (2006) Post-weaning diet affects genomic imprinting at the insulin-like growth factor 2 (Igf2) locus. Hum Mol Genet 15: 705–716.
  58. 58. Feil R (2006) Environmental and nutritional effects on the epigenetic regulation of genes. Mutat Res 600: 46–57.
  59. 59. Pembrey M (1996) Imprinting and transgenerational modulation of gene expression; human growth as a model. Acta Genet Med Gemellol (Roma) 45: 111–125.
  60. 60. McMinn J, Wei M, Schupf N, Cusmai J, Johnson EB, et al. (2006) Unbalanced placental expression of imprinted genes in human intrauterine growth restriction. Placenta 27: 540–549.
  61. 61. Apostolidou S, Abu-Amero S, O'Donoghue K, Frost J, Olafsdottir O, et al. (2007) Elevated placental expression of the imprinted PHLDA2 gene is associated with low birth weight. J Mol Med 85: 379–387.
  62. 62. Tabano S, Colapietro P, Cetin I, Grati FR, Zanutto S, et al. (2010) Epigenetic modulation of the IGF2/H19 imprinted domain in human embryonic and extra-embryonic compartments and its possible role in fetal growth restriction. Epigenetics 5: 313–324.
  63. 63. Fortier AL, Lopes FL, Darricarrere N, Martel J, Trasler JM (2008) Superovulation alters the expression of imprinted genes in the midgestation mouse placenta. Hum Mol Genet.
  64. 64. Tycko B, Morison IM (2002) Physiological functions of imprinted genes. J Cell Physiol 192: 245–258.
  65. 65. Charalambous M, Cowley M, Geoghegan F, Smith FM, Radford EJ, et al. (2010) Maternally-inherited Grb10 reduces placental size and efficiency. Dev Biol 337: 1–8.
  66. 66. Williams TM, Carroll SB (2009) Genetic and molecular insights into the development and evolution of sexual dimorphism. Nat Rev Genet 10: 797–804.
  67. 67. Gebert C, Wrenzycki C, Herrmann D, Groger D, Thiel J, et al. (2009) DNA methylation in the IGF2 intragenic DMR is re-established in a sex-specific manner in bovine blastocysts after somatic cloning. Genomics 94: 63–69.
  68. 68. Attig L, Gabory A, Junien C (2010) Early nutrition and epigenetic programming: chasing shadows. Curr Opin Clin Nutr Metab Care 13: 284–293.
  69. 69. Nelissen EC, van Montfoort AP, Dumoulin JC, Evers JL (2010) Epigenetics and the placenta. Hum Reprod Update.
  70. 70. Mueller BR, Bale TL (2008) Sex-specific programming of offspring emotionality after stress early in pregnancy. J Neurosci 28: 9055–9065.
  71. 71. Verhaagh S, Barlow DP, Zwart R (2001) The extraneuronal monoamine transporter Slc22a3/Orct3 co-localizes with the Maoa metabolizing enzyme in mouse placenta. Mech Dev 100: 127–130.
  72. 72. Sekita Y, Wagatsuma H, Nakamura K, Ono R, Kagami M, et al. (2008) Role of retrotransposon-derived imprinted gene, Rtl1, in the feto-maternal interface of mouse placenta. Nat Genet 40: 243–248.
  73. 73. Hiura H, Obata Y, Komiyama J, Shirai M, Kono T (2006) Oocyte growth-dependent progression of maternal imprinting in mice. Genes Cells 11: 353–361.
  74. 74. Razin A, Webb C, Szyf M, Yisraeli J, Rosenthal A, et al. (1984) Variations in DNA methylation during mouse cell differentiation in vivo and in vitro. Proc Natl Acad Sci U S A 81: 2275–2279.
  75. 75. Kokalj-Vokac N, Zagorac A, Pristovnik M, Bourgeois CA, Dutrillaux B (1998) DNA methylation of the extraembryonic tissues: an in situ study on human metaphase chromosomes. Chromosome Res 6: 161–166.
  76. 76. Ng RK, Dean W, Dawson C, Lucifero D, Madeja Z, et al. (2008) Epigenetic restriction of embryonic cell lineage fate by methylation of Elf5. Nat Cell Biol 10: 1280–1290.
  77. 77. Rossant J, Sanford JP, Chapman VM, Andrews GK (1986) Undermethylation of structural gene sequences in extraembryonic lineages of the mouse. Dev Biol 117: 567–573.
  78. 78. Charalambous M, da Rocha ST, Ferguson-Smith AC (2007) Genomic imprinting, growth control and the allocation of nutritional resources: consequences for postnatal life. Curr Opin Endocrinol Diabetes Obes 14: 3–12.
  79. 79. Fowden AL, Forhead AJ, Coan PM, Burton GJ (2008) The placenta and intrauterine programming. J Neuroendocrinol 20: 439–450.
  80. 80. Fowden AL, Sferruzzi-Perri AN, Coan PM, Constancia M, Burton GJ (2009) Placental efficiency and adaptation: endocrine regulation. J Physiol 587: 3459–3472.
  81. 81. Godfrey KM (2002) The role of the placenta in fetal programming-a review. Placenta 23: Suppl AS20–27.
  82. 82. Liang C, Decourcy K, Prater MR (2010) High-saturated-fat diet induces gestational diabetes and placental vasculopathy in C57BL/6 mice. Metabolism 59: 943–950.
  83. 83. Asaka J, Terada T, Okuda M, Katsura T, Inui K (2006) Androgen receptor is responsible for rat organic cation transporter 2 gene regulation but not for rOCT1 and rOCT3. Pharm Res 23: 697–704.
  84. 84. Urakami Y, Okuda M, Saito H, Inui K (2000) Hormonal regulation of organic cation transporter OCT2 expression in rat kidney. FEBS Lett 473: 173–176.
  85. 85. Pelis RM, Hartman RC, Wright SH, Wunz TM, Groves CE (2007) Influence of estrogen and xenoestrogens on basolateral uptake of tetraethylammonium by opossum kidney cells in culture. J Pharmacol Exp Ther 323: 555–561.
  86. 86. Avila L, Yuen RK, Diego-Alvarez D, Penaherrera MS, Jiang R, et al. (2010) Evaluating DNA methylation and gene expression variability in the human term placenta. Placenta.
  87. 87. Gheorghe C, Mohan S, Longo LD (2006) Gene expression patterns in the developing murine placenta. J Soc Gynecol Investig 13: 256–262.
  88. 88. Ishikawa H, Rattigan A, Fundele R, Burgoyne PS (2003) Effects of sex chromosome dosage on placental size in mice. Biol Reprod 69: 483–488.
  89. 89. Ohgane J, Wakayama T, Senda S, Yamazaki Y, Inoue K, et al. (2004) The Sall3 locus is an epigenetic hotspot of aberrant DNA methylation associated with placentomegaly of cloned mice. Genes Cells 9: 253–260.
  90. 90. Alnouti Y, Petrick JS, Klaassen CD (2006) Tissue distribution and ontogeny of organic cation transporters in mice. Drug Metab Dispos 34: 477–482.
  91. 91. Grundemann D, Schomig E (2000) Gene structures of the human non-neuronal monoamine transporters EMT and OCT2. Hum Genet 106: 627–635.
  92. 92. Harlfinger S, Fork C, Lazar A, Schomig E, Grundemann D (2005) Are organic cation transporters capable of transporting prostaglandins? Naunyn Schmiedebergs Arch Pharmacol 372: 125–130.
  93. 93. Bottalico B, Larsson I, Brodszki J, Hernandez-Andrade E, Casslen B, et al. (2004) Norepinephrine transporter (NET), serotonin transporter (SERT), vesicular monoamine transporter (VMAT2) and organic cation transporters (OCT1, 2 and EMT) in human placenta from pre-eclamptic and normotensive pregnancies. Placenta 25: 518–529.
  94. 94. Zhou Y, Cheunsuchon P, Nakayama Y, Lawlor MW, Zhong Y, et al. (2010) Activation of paternally expressed genes and perinatal death caused by deletion of the Gtl2 gene. Development 137: 2643–2652.
  95. 95. Kaneko-Ishino T, Ishino F (2010) Retrotransposon silencing by DNA methylation contributed to the evolution of placentation and genomic imprinting in mammals. Dev Growth Differ 52: 533–543.
  96. 96. Moon YS, Smas CM, Lee K, Villena JA, Kim KH, et al. (2002) Mice lacking paternally expressed Pref-1/Dlk1 display growth retardation and accelerated adiposity. Mol Cell Biol 22: 5585–5592.
  97. 97. Hernandez A, Garcia B, Obregon MJ (2007) Gene expression from the imprinted Dio3 locus is associated with cell proliferation of cultured brown adipocytes. Endocrinology 148: 3968–3976.
  98. 98. Sleutels F, Zwart R, Barlow DP (2002) The non-coding Air RNA is required for silencing autosomal imprinted genes. Nature 415: 810–813.
  99. 99. Nie W, Sweetser S, Rinella M, Green RM (2005) Transcriptional regulation of murine Slc22a1 (Oct1) by peroxisome proliferator agonist receptor-alpha and -gamma. Am J Physiol Gastrointest Liver Physiol 288: G207–212.
  100. 100. Flajollet S, Lefebvre B, Cudejko C, Staels B, Lefebvre P (2007) The core component of the mammalian SWI/SNF complex SMARCD3/BAF60c is a coactivator for the nuclear retinoic acid receptor. Mol Cell Endocrinol 270: 23–32.
  101. 101. Sleutels F, Tjon G, Ludwig T, Barlow DP (2003) Imprinted silencing of Slc22a2 and Slc22a3 does not need transcriptional overlap between Igf2r and Air. Embo J 22: 3696–3704.
  102. 102. Kagami M, O'Sullivan MJ, Green AJ, Watabe Y, Arisaka O, et al. (2010) The IG-DMR and the MEG3-DMR at human chromosome 14q32.2: hierarchical interaction and distinct functional properties as imprinting control centers. PLoS Genet 6: e1000992.
  103. 103. Theys N, Ahn MT, Bouckenooghe T, Reusens B, Remacle C (2010) Maternal malnutrition programs pancreatic islet mitochondrial dysfunction in the adult offspring. In Press. Journal of Nutritional Biochemistry.
  104. 104. Samuelsson AM, Matthews PA, Argenton M, Christie MR, McConnell JM, et al. (2008) Diet-induced obesity in female mice leads to offspring hyperphagia, adiposity, hypertension, and insulin resistance: a novel murine model of developmental programming. Hypertension 51: 383–392.
  105. 105. Jones HN, Woollett LA, Barbour N, Prasad PD, Powell TL, et al. (2009) High-fat diet before and during pregnancy causes marked up-regulation of placental nutrient transport and fetal overgrowth in C57/BL6 mice. FASEB J 23: 271–278.
  106. 106. Vucetic Z, Kimmel J, Totoki K, Hollenbeck E, Reyes TM (2010) Maternal high-fat diet alters methylation and gene expression of dopamine and opioid-related genes. Endocrinology 151: 4756–4764.
  107. 107. Moreira de Mello JC, de Araujo ES, Stabellini R, Fraga AM, de Souza JE, et al. (2010) Random X inactivation and extensive mosaicism in human placenta revealed by analysis of allele-specific gene expression along the X chromosome. PLoS One 5: e10947.
  108. 108. Weber M, Davies JJ, Wittig D, Oakeley EJ, Haase M, et al. (2005) Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat Genet 37: 853–862.
  109. 109. Hellman A, Chess A (2007) Gene body-specific methylation on the active X chromosome. Science 315: 1141–1143.
  110. 110. Fryer AA, Nafee TM, Ismail KM, Carroll WD, Emes RD, et al. (2009) LINE-1 DNA methylation is inversely correlated with cord plasma homocysteine in man: a preliminary study. Epigenetics 4: 394–398.
  111. 111. Jeong KS, Lee S (2005) Estimating the total mouse DNA methylation according to the B1 repetitive elements. Biochem Biophys Res Commun 335: 1211–1216.
  112. 112. Jansson T, Powell TL (2007) Role of the placenta in fetal programming: underlying mechanisms and potential interventional approaches. Clin Sci (Lond) 113: 1–13.
  113. 113. Wu G, Bazer FW, Cudd TA, Meininger CJ, Spencer TE (2004) Maternal nutrition and fetal development. J Nutr 134: 2169–2172.
  114. 114. Hemberger M (2010) Genetic-epigenetic intersection in trophoblast differentiation: implications for extraembryonic tissue function. Epigenetics 5: 24–29.
  115. 115. Kulkarni A, Chavan-Gautam P, Mehendale S, Yadav H, Joshi S (2010) Global DNA Methylation Patterns in Placenta and Its Association with Maternal Hypertension in Pre-Eclampsia. DNA Cell Biol.
  116. 116. Gallou-Kabani C, Vige A, Gross MS, Boileau C, Rabes JP, et al. (2007) Resistance to high-fat diet in the female progeny of obese mice fed a control diet during the periconceptual, gestation, and lactation periods. Am J Physiol Endocrinol Metab 292: E1095–1100.
  117. 117. Yamazaki Y, Mann MR, Lee SS, Marh J, McCarrey JR, et al. (2003) Reprogramming of primordial germ cells begins before migration into the genital ridge, making these cells inadequate donors for reproductive cloning. Proc Natl Acad Sci U S A 100: 12207–12212.
  118. 118. Bock C, Reither S, Mikeska T, Paulsen M, Walter J, et al. (2005) BiQ Analyzer: visualization and quality control for DNA methylation data from bisulfite sequencing. Bioinformatics 21: 4067–4068.
  119. 119. Tost J, Gut IG (2007) Analysis of gene-specific DNA methylation patterns by pyrosequencing technology. Methods Mol Biol 373: 89–102.
  120. 120. Fauque P, Ripoche MA, Tost J, Journot L, Gabory A, et al. (2010) Modulation of imprinted gene network in placenta results in normal development of in vitro manipulated mouse embryos. Hum Mol Genet.
  121. 121. Karimi M, Johansson S, Stach D, Corcoran M, Grander D, et al. (2006) LUMA (LUminometric Methylation Assay)—a high throughput method to the analysis of genomic DNA methylation. Exp Cell Res 312: 1989–1995.
  122. 122. Lesage J, Blondeau B, Grino M, Breant B, Dupouy JP (2001) Maternal undernutrition during late gestation induces fetal overexposure to glucocorticoids and intrauterine growth retardation, and disturbs the hypothalamo-pituitary adrenal axis in the newborn rat. Endocrinology 142: 1692–1702.