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Exposure to maternal obesity alters gene expression in the preimplantation ovine conceptus



Embryonic and fetal exposure to maternal obesity causes several maladaptive morphological and epigenetic changes in exposed offspring. The timing of these events is unclear, but changes can be observed even after a short exposure to maternal obesity around the time of conception. The hypothesis of this work is that maternal obesity influences the ovine preimplantation conceptus early in pregnancy, and this exposure will affect gene expression in embryonic and extraembryonic tissues.


Obese and lean ewe groups were established by overfeeding or normal feeding, respectively. Ewes were then bred to genetically similar rams. Conceptuses were collected at day 14 of gestation. Morphological assessments were made, conceptuses were sexed by genomic PCR analysis, and samples underwent RNA-sequencing analysis. While no obvious morphological differences existed between conceptuses, differentially expressed genes (≥ 2-fold; ≥ 0.2 RPKM; ≤ 0.05 FDR) were detected based on maternal obesity exposure (n = 21). Also, differential effects of maternal obesity were noted on each conceptus sex (n = 347). A large portion of differentially expressed genes were associated with embryogenesis and placental development.


Findings reveal that the preimplantation ovine conceptus genome responds to maternal obesity in a sex-dependent manner. The sexual dimorphism in response to the maternal environment coupled with changes in placental gene expression may explain aberrations in phenotype observed in offspring derived from obese females.


Obesity is a prominent cause of various adverse health conditions, including heart disease, stroke, type 2 diabetes, and some cancers in humans and other mammals [1]. The prevalence of these conditions may be one of the leading causes of preventable death among adults. Lifestyle choices and poor diet are recognized as the main factors leading to obesity, however, more recent evidence suggests that intrauterine exposure to an obesogenic environment is a contributing factor predisposing offspring to obesity-related disorders. Approximately one-third of child-bearing age women in the United States (20 to 39 years of age) are overweight, and another one-third are obese [2]. Postnatal eating and dietary habits of offspring increase the likelihood of childhood and adult obesity in offspring, however, obesity-related disorders can manifest in these offspring even in the absence of the obese phenotype [3, 4]. The postnatal onset of these events that were manifested in utero is a hallmark feature of the fetal origins of adult disease (FOAD) or developmental origins of health and disease (DOHAD) phenomena that have been observed in all mammals studied to date. [5]. These adverse outcomes may be caused by epigenetic modifications to the genome or by direct, non-genomic modification of organ and tissue development during the embryonic and fetal periods of gestation.

The initial concept of DOAHD applied to human offspring exposed to under nutrition in utero, however, it has since grown to also encompass the state of over nutrition during early development. Animal models have been used extensively to study this phenomenon. Reports in rodents reveal that increased maternal adiposity results in insulin resistance, hyperlipidemia, and increased body weight in offspring [6]. Additionally, exposure to maternal obesity is linked to altered skeletal muscle function [7] and reduced muscle mass in male and female offspring [8]. The relationship between nutrition in utero and muscle growth is important in animal agriculture, as skeletal muscle development is directly related to meat quality in various species including the sheep [9,10,11]. Furthermore, ewes subjected to fetal exposure to maternal obesity were hyperglycemic, hyperinsulinemic, and showed significant increases in pancreatic weight at mid-gestation [12]. Similar to the mouse model, the obese ewe produces lambs exhibiting altered growth, adiposity, and glucose tolerance in adulthood [13]. While the effects of maternal obesity are known to have lasting effects in offspring, methods to alleviate these effects are lacking.

The placenta is a prime target for intrauterine stresses, and modifications in placental development and function are linked to several adverse health events that occur after birth [14, 15]. Maternal obesity has a direct effect on placental nutrient transport, placental vasculature, and blood flow [16,17,18,19], and interestingly, exposure to maternal obesity alters placental development in a sexually dimorphic manner [20,21,22,23,24,25]. Similarly, several fetal outcomes observed in offspring exposed to maternal obesity are sexually-dependent, including glucose intolerance, adiposity, blood pressure, and insulin sensitivity [26,27,28]. The mechanism and timing of the sex-dependent changes in placentation and fetal outcomes are not understood, thus genes involved in placentation were of particular interest in assessing the effects of maternal obesity on the developing embryo.

We were interested in understanding how maternal obesity impacts pre- and peri-implantation embryogenesis. This is a time of significant embryonic and extraembryonic tissue development and cellular restructuring in the embryo and placenta [29]. Critical events occurring during this time include highly controlled changes in embryonic DNA methylation patterns, embryonic cell lineage specification, and embryonic-maternal cross-talk that controls pregnancy recognition [30]. Furthermore, studies utilizing an ovine embryo transfer model showed that exposure to maternal obesity only during the periconceptional period was sufficient to impose altered developmental outcomes in lambs [31, 32]. However, the immediate effects of maternal obesity on conceptus growth and function during peri-implantation development remained unexplored to this point. We propose that exposure to environmental stressors and the resulting disruptions in the genes associated with developmental processes will adversely affect early placentation events and thereby adversely affect embryo competency. The following work examined the validity of this premise by examining the effects of obesity status on reproductive performance and conceptus gene expression profiles of ewes at day 14 of pregnancy.


An increased plane of nutrition affects body parameters of ewes

Providing a corn-based diet altered body conformation of ewes (Table 1). Obese ewes had a greater average body weight at the time of collection compared to lean ewes (P < 0.0001). Similarly, obese ewes had greater BCS (P < 0.0001) and greater back fat measurements (P = 0.002) than their lean counterparts. Obesity did not affect plasma NEFA concentrations, however, NEFA concentrations were reduced at day 14 in both groups (P = 0.03) (Table 1). Circulating glucose concentrations were unaffected by obesity status.

Table 1 Body parameters of obese and lean ewes

Obesity does not Alter various pregnancy parameters

Ewes were sacrificed at day 14 post-breeding, and data were collected to assess the effects of obesity on various pregnancy parameters (Table 2). Pregnancy rate, ovulation rate (CL number), and conceptuses/CL (pregnancies/ovulation) were not affected by obesity status. Also, conceptus length, conceptus sex ratio and IFNT production were not affected by maternal obesity status or conceptus sex at day14. Maternal obesity status also had no effect on circulating P4 concentrations at days 0, 6 and 14 post-estrus.

Table 2 Ewe pregnancy parameters

Exposure to maternal obesity affects conceptus gene expression

RNA-sequencing was completed on a subset of samples (n = 4 of each sex for obese and lean groups) to assess the effects of maternal obesity exposure on gene transcription in the preimplantation ovine conceptus. There was a concern with the completeness of annotation in the ovine genome assembly, so an initial set of annotations were completed against the ovine, bovine, and caprine genomes. Percentages of reads mapped to each genome were similar among species; with 94.2%, 92.1%, and 94.4% mapped reads when using the ovine, bovine, and caprine genomes, respectively. Thus, the ovine genome annotation was used for the various analyses. The ovine genome identified an average of 32,220,571 reads/sample, 42,390 transcripts/sample (see Additional file 1) and 28,381 genes/sample.

There were 21 differentially expressed genes (DEGs) in conceptuses collected from lean versus obese (see Additional file 2). Of these, 10 DEGs were down-regulated and 11 were up-regulated in conceptuses derived from obese ewes (Fig. 1; Table 3). Analysis with the PANTHER GO-Slim Biological Process system identified cellular process (GO: 0009987), metabolic process (GO: 0008152), and cellular component organization (GO: 0071840) as the three largest GO categories represented in the DEGs (11, 6 and 3 genes respectively). KEGG pathway analysis was also performed to analyze the various biological pathways represented within the DEG list. KEGG pathway analysis identified DEGs involved in the PI3K-AKT signaling pathway (PPP2R3A and BRCA1), with specific involvement cell proliferation, angiogenesis and DNA repair. Also, 4 of these DEGs have a known-role in placenta development and function (ALCAM, BRCA1 GP2, GSTA4) and 5 are associated with obesity and insulin resistance (MPHOSPH9, BRCA1, ASP, ALCAM, GP2).

Fig. 1
figure 1

The number of up- and down- regulated genes across experimental comparisons. Ovine conceptuses were collected from obese and lean ewes on day 14 of pregnancy via uterine flush. Conceptus sex was determined by PCR using X- and Y-specific primers, and 4 conceptuses/sex/treatment underwent RNA sequencing (N = 16 total conceptuses). Sequencing analysis was performed using Genomics Workbench 10.1.1 (CLC bio). Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0). Differentially expressed genes (DEGs) were identified as having a FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM. The number of DEGs that were up (gray) or down (black)-regulated is indicated based on obesity status, sex, and changes that were unique in individual comparisons between obese/lean versus male/female conceptuses

Table 3 Obese versus lean DEGs identified in conceptus samples and associated gene ontology (GO) terms

Conceptus sex-dependent changes in gene expression

Conceptus sex also affected transcript profiles. A total of 137 DEGs (109 annotated, 28 unannotated) were detected between male and female conceptuses (see Additional file 3). Of these, 25 DEGs were down-regulated and 112 were up-regulated in male vs female conceptuses (Fig. 1). Gene ontology terms associated with the DEGs include primary metabolic processes, regulation of biological processes, cell death and transport (23, 18, 4, and 8 DEGs, respectively) (Table 4). KEGG analysis identified 9 DEGs involved in metabolic processes (ALDH1A1, B3GALNT1, CKB, CKM, DDC, HPSE, ISYNA1, NMRK, PMM). Metabolic processes represented include glycan biosynthesis and metabolism, carbohydrate metabolism, amino acid metabolism, and the metabolism of cofactors and vitamins, specifically nicotinate and nicotinamide. KEGG analysis also identified protein digestion and absorption (MME, PAG11, PAG4, PAG9), and arginine and proline metabolism (CKB, CKM) to be affected by conceptus sex. Lastly, 33 of these DEGs have a reported involvement in placental development and function.

Table 4 Biological terms detected based on conceptus sex

Maternal obesity differentially impacted gene expression in each conceptus sex

There were 347 DEGs detected when comparing differences in how each conceptus sex was affected by exposure to obese and lean maternal conditions (see Additional file 4).

Between 23 and 167 DEGs were identified in the specific pair-wise comparisons (Fig. 1). The largest numbers of DEGs were detected for lean-derived male versus lean-derived female conceptuses and lean-derived males versus obese-derived females. When examining all the various DEGs as one dataset, 86 of the DEGs were involved in placenta development and function. These DEGs, including several instances where DEGs contained multiple gene variants, are organized on a heat map to describe differential expression trends between the various maternal obesity and conceptus sex groups (Fig. 2, Additional file 5). These DEGs segregated initially based on conceptus sex and thereafter based on obesity status.

Fig. 2
figure 2

Heat map showing clustering patterns for placenta-associated DEGs exhibiting sex and obesity-dependent effects. Ovine conceptuses were collected from obese and lean ewes on day 14 of pregnancy by uterine flush. Conceptus sex was determined by PCR using X- and Y-specific primers, and 4 conceptuses/sex/treatment underwent RNA sequencing (N = 16 total conceptuses). Sequencing analysis was performed using Genomics Workbench 10.1.1 (CLC bio). Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0), and differentially expressed genes (DEGs) were identified as having a FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM. Genes involved in placentation were identified from the list of DEGs via literature search. Individual gene IDs can be found in Additional file 6


Human obesity rates continue to climb in the United States. Though predominantly attributed to lifestyle choices, recent findings suggest exposure to maternal obesity in utero can produce similar metabolic and physiological outcomes in offspring regardless of their postnatal diet [33]. Studies utilizing the mouse model have identified changes in development following obesity exposure during the earliest stages of development [34, 35]; however, an understanding of the timing of these events is currently lacking in sheep. Work until now has focused on characterizing fetal and postnatal outcomes of maternal obesity [12, 13, 31, 32]. The obese ewe produces offspring that exhibit altered growth, adiposity, and glucose tolerance in adulthood [13]. However, the specific times during development when obesity can impact embryonic and fetal programming remained unexplored.

This work sought to establish whether programming events resulting from obesity could be detected early in pregnancy, and specifically during the peri-implantation period. This allowed us to examine changes in gene expression that would occur solely from alterations in oocyte maturation, fertilization, and embryonic and conceptus development. The extended period of pre-implantation conceptus development that occurs in the sheep and other ruminants permitted us to collect large conceptus samples that were at least largely and potentially totally devoid of endometrium [36, 37]. Collecting at this time also provided us with the opportunity to examine conceptuses when they were comprised primarily of extraembryonic membranes, and specifically trophectoderm and endoderm. This permitted a detailed description of how obesity status impacts early placental development and allowed us to identify the existence of early developmental programming in the sheep.

One interesting facet of this study was that many of the metabolic and endocrine parameters normally associated with obesity in humans and rodents were not evident in this work. Notably, NEFA concentrations were not affected by obesity status. This opposes the findings of previous studies that report an increased plasma NEFA concentration accompanying the obese phenotype of sheep [38, 39]. However, this same NEFA response has been reported in pregnant rats maintained on high fat diets [40]. We propose that the increase in NEFA concentrations in obese and lean ewes at D0 occurred because ewes were in estrus, where mating usually will take precedence over eating. Likewise, glucose concentrations were unaffected by obesity status in this study. This is not surprising given that ruminants utilize volatile fatty acids for a constant-state level of glucose production, whereas monogastrics actively absorb glucose. This means an obese state was achieved in this work without inducing hyperglycemic or diabetic states.

Obesity can negatively impact the establishment of pregnancy in cow and human models [41, 42]. However, previous work in the sheep reported no effect of donor ewe adiposity on ovulation rate, fertilization rate, pregnancy rate, conceptus growth, or birth weight. [31, 43]. It was interesting to observe that obesity-dependent changes in peri-implantation conceptus gene expression exist in the absence of effects on ovulation rate, pregnancy rate, pregnancies per ovulation, conceptus length, P4 production, and IFNT production. A small group of DEGs existed (n = 21). Several DEGs were part of various GO terms involving cellular and metabolic processes and cellular component organization. These findings are supported by studies in the rodent model, which describe reduced blastocyst rates, retarded embryonic development, and altered regulation of crucial metabolic genes following exposure to maternal obesity [44, 45].

Some of these obesity-dependent changes in gene expression noted in this work may represent early signs of adiposity in offspring [46]. Five of the twenty-one obesity-dependent DEGs are associated with obesity and insulin resistance (MPHOSPH9, BRCA1, ASP, ALCAM, GP2) [47,48,49,50,51]. Also, DEGs associated with placental development were detected in this work. Placental mal-programming is associated with various peri- and post-natal disorders, and at least two obesity-dependent DEGs have been associated with placental disorders. The first is activated leukocyte cell adhesion molecule (ALCAM), which is a TE-expressed protein in human placentae whose expression is diminished during preeclampsia [52, 53]. The second is breast cancer gene 1 (BRCA1), a tumor suppressor protein that facilitates DNA repair or cell destruction after DNA damage. This factor also plays active roles in TE proliferation and invasion [54,55,56].

Conceptuses exposed to maternal obesity also showed differential expression of genes associated with response to oxidative stress (BRCA1, GSTA4). Oxidative stress occurs naturally in the uterus, and oxidation is an essential facet of embryogenesis [57]. Oxidative stress may also impair development with decreases in embryonic competency and cell survival observed in stressed versus non-stressed embryos [58, 59]. These previous findings compliment the DEGs associated with DNA repair identified in this work. The differential expression of genes involved in the response to oxidative stress may indicate abnormal oxygen environment in utero, thus resulting in changes in gene expression in conceptuses exposed to maternal obesity.

It also was important that sex of the conceptus be considered in this work. There are numerous examples in mammals of how maternal obesity and other intrauterine stresses differentially affect male and female fetuses (reviewed in [60, 61]). The mechanisms behind the differential developmental programming of male and female embryos is not completely known. In early embryogenesis this likely occurs, at least in part, by incomplete X-inactivation in female conceptuses, leading to an up-regulation of X-linked genes in female conceptuses. In cattle, X-inactivation occurs primarily between the blastocyst stage and day 14 of conceptus development, although, sexual dimorphism still exists by day 19 of pregnancy in this species [62, 63]. There is no evidence suggesting that ovine conceptuses experience a similar ontogeny of X-linked gene inactivation, and certainly the timing of these events will be shifted forward by 3 to 4 days given the more rapid development of ovine conceptuses prior to implantation [64]. However, the closeness between these species in early conceptus development make this phenomenon an attractive explanation for at least some of the sex-dependent events detected in this work. Additionally, it is possible that male and female embryos respond differently to uterine histotroph during early embryogenesis. This idea is reinforced by studies reporting sexually dimorphic gene expression as early as the morula and blastocyst stages in cattle [65, 66]. This variation in gene expression may lead to disparities in cell survival and lineage specification during early development in male and female embryos.

One set of sex-dependent DEGs of special note are the placental-specific aspartic proteases that are known as pregnancy-specific glycoproteins (PAGs). In ruminants, PAGs are classified as ancient or modern members of this multigenic family based on whether they are produced solely from mononucleated or binucleated TE, respectively [67]. Five PAG gene transcripts were identified herein (PAG1, 2, 4, 9, 11), which represent both modern and ancient categories. In all instances, these PAG transcripts were greater in abundance in male conceptuses than female conceptuses. The greatest difference was PAG9, which was 220-fold greater in male than female conceptuses. Individual PAG genes are expressed at different stage of pregnancy in cattle and presumably other ruminants. Several of the PAGs identified here are expressed early in gestation (e.g. PAG4, 9) whereas the others are produced throughout gestation but predominantly during mid- and late-gestation [68, 69]. Identifying PAGs produced by both TE cell types indicates that this outcome does not reflect changes in the distribution of mononucleate and binucleate cell types. The biological significance of PAGs remain unclear.

Several other notable DEGs were identified based on conceptus sex. Fibroblast growth factor receptor 1 (FGFR1) is one of four tyrosine kinase receptor genes that control the various actions of FGFs throughout the body [70]. It is implicated as a contributing factor to fetal growth restriction induced by placental insufficiency in women [71, 72]. Another is mucin-15 (MUC15), a cell membrane-bound mucin that controls TE invasion [73, 74]. A third DEG of note is the amino acid transporter, SLC6A14, is a sodium-dependent, neutral and cationic amino acid transporter. Though it has a broad specificity, SLC6A14 is essential for leucine uptake in mouse TE [75]. Also, a disintegrin and metalloprotease 19 (ADAM19) impacts TE invasion and adhesion in the human [76]. Lastly, placental lactogen and one member of the placental prolactin-related protein (PRP) family (termed PRP4) was differentially expressed in male and female conceptuses. Collectively, the differential expression of these genes implies that there is a naturally-occurring sexual dimorphism in placental development and function.

Exposure to maternal obesity affected male and female conceptuses differently. The individual comparisons generally did not share DEGs, but the same GO terms with the highest DEG representation were similar in both male and female conceptuses. These were cellular processes and metabolic processes. Work in the area of developmental programming utilizing mouse, rat and ovine models shows that male and female offspring respond differently in the presence of various environmental stressors in utero [21, 77, 78], and a similar phenomenon appears to be present in this model.

Samples were collected at day 14 of gestation, during the elongation phase of conceptus development and just prior to implantation into the uterus [37]. This phase of development is marked by an exponential increase in length of the trophectoderm, with the conceptus growing from 1 mm on day 11 to around 19 cm on day 15 [79, 80]. At the time of collection, the trophectoderm is the predominant tissue of the conceptus. Thus, it is not surprising that a subset of DEGs were associated with placental development and function. Between 19 and 26% of the obesity, sex, and obesity by sex DEGs were related to the placenta. An official GO term is not available for placental development and function, so this DEG category was developed in-house by identifying DEGs that have been studied in the placenta, trophectoderm and/or trophoblast of humans, rodents and/or domestic animals. The DEGs identified through this search included those that contained various placental functions, including trophoblast adhesion and implantation, placental vasculature and angiogenesis, and cellular responses to hypoxia and preeclampsia. Although a majority of the published reports used for this assessment were made in post-implantation or late gestation placentae (for examples, see [19, 81, 82]), there were several noteworthy outcomes that relate to post-implantation and late gestational problems. Abnormal TE adhesion and implantation are recognized precursors to preeclampsia in humans, as preeclampsia is characterized by shallow TE invasion [83, 84]. Likewise, pro- and anti-angiogenic factors are misregulated in preeclampsia, resulting in hypertension, the clinical hallmark of preeclampsia [85]. Therefore, while samples in this study were collected immediately prior to uterine implantation, it appears that the mechanisms responsible for implantation and placentation are already perturbed at day 14 of gestation. Furthermore, these maladaptive placental precursors may help to explain the altered gestational growth trajectory observed in ewes born to obese ewes [46].

It remains unclear what is driving these obesity-dependent changes in conceptus gene expression. It certainly is possible that direct interactions of maternally-derived factors (e.g. hormones, metabolites) may be promoting changes in conceptus gene expression, although we have not identified any indication of this type of regulation in the gene ontology screening. A more probable explanation is that the uterus is driving these conceptus responses to maternal obesity. Uterine secretions (i.e. histotroph) control peri-implantation conceptus development in sheep and other ruminants [86]. Progesterone is a central controller of histotroph production in early pregnancy [87], but progesterone concentrations were not affected by obesity status in this study. An alternative way uterine function may be influenced is by low-grade inflammatory events that accompany obesity [88]. Localized inflammatory responses are observed in the rat and horse uterus in an obese state, and these responses are probably driven, at least in part, by pro-inflammatory cytokine actions within the endometrium [89, 90]. These and other pro-inflammatory factors likely affect uterine homeostasis in ways that cause conceptuses to respond differently to their uterine environment.


These results indicate that the conceptus genome is susceptible to perturbations caused by maternal obesity early in development, even though morphological changes to the conceptus nor alterations in maternal reproductive parameters are detectable. These effects of maternal obesity also are sexually dimorphic. Furthermore, this work identifies genes involved with placental development, and specifically adhesion, implantation, angiogenesis and placental vasculature as major targets of genetic regulation. The altered expression of these transcripts may be some of the earliest indications of implantation failure and subsequent placental insufficiency that are observed in obese females. Further work should focus on identifying the morphological changes resulting from the misregulation of these placental genes in later gestation.


Animal use

Sheep used in this work were provided by the Virginia Tech Sheep Center (Blacksburg, VA). All animal work was completed in compliance and with the approval of the Virginia Tech Institutional Animal Care and Use Committee (IACUC; #14–104).

Dietary treatments were imposed ~ 4 months prior to the start of the study to establish the obese and lean phenotypes. Dorset ewes, 1–3 years in age, were assigned randomly to lean or obese groups. The obese state was induced by feeding 1 kg corn/day and providing ad libitum exposure to high quality pasture in the summer and orchard grass hay in the fall and winter months. Ewes that achieved a body condition score (BCS) ≥4 (scale of 1–5) were considered “obese” as per the BCS standards described by Thompson and Meyer [91]. Lean ewes were kept on a maintenance diet composed of previously grazed pasture in the summer months and poor-quality hay in the fall and winter months. Ewes with a BCS of 2.5–3 where chosen from this group. Back fat measurements were collected on a subset of ewes (n = 4 lean and 5 obese ewes) via ultrasonography. Once an obese and lean ewe model was established, animals were subjected to an estrous synchronization protocol in fall and winter months (September to February). The protocol began with controlled internal drug release (CIDR) device (Pfizer, New York, NY) insertion and Cystorelin (Merial, Lyon, France) injection (50 μg; IM) followed 7 days later with CIDR removal and Lutalyse (Zoetis, Parsippany, NJ) injection (15 mg; IM) [92]. Ewes were then bred to genetically-related Dorset rams (three-quarter siblings).

Blood analyses

Blood samples were collected from the jugular vein at day 0, 6, and 14 of gestation (day 0 = day of breeding) and maintained on ice until plasma was isolated via centrifugation (1500 g × 15 min). Plasma was stored at − 20 °C. Ewes were kept off-feed for 12 h prior to the day 14 blood collections. Plasma NEFA concentrations were determined using the NEFA-HR(2) Microtiter procedure according to manufacturer instructions (Wako Diagnostics, Mountain View, CA). Plasma progesterone concentrations were determined using the IMMULITE 2000 XPi Immunoassay system (Siemens Medical Solutions Diagnostics, Tarrytown, NY state). Plasma glucose concentrations were assessed using Glucose Colorimetric Assay Kit (Ann Arbor, MI).

Conceptus collections

Ewes were sacrificed on day 14 of gestation. Body weight was recorded at the time of sacrifice. The uterus was excised by mid-ventral dissection. Each uterine horn was flushed with 30 mL Dulbecco’s PBS [pH 7.2] (Gibco, Gaithersburg, MD) to recover conceptuses. Individual conceptuses were teased apart, and each conceptus length was recorded. An example of a flushed conceptus is shown in Additional File 6. The number of corpora lutea (CL) was recorded and used to determine the percentage of pregnancies per ovulation. Individual conceptuses were snap-frozen in liquid nitrogen, and stored at − 80 °C.

IFNT analysis

Individual uterine flushes were assessed for interferon-tau (IFNT) protein content by the ISRE-Luc bioassay described previously by this laboratory [93]. In brief, Madin-Darby bovine kidney cells (MDBK; ATCC#CCL-22) that were transduced with an ISRE-Luc reporter were plated into 96-well polystyrene plates with opaque walls and optically clear bottoms (Corning Inc., Corning, NY) at a density of 5–10 × 105 cells/well in Dulbecco’s modified eagle medium (DMEM, 25 mM glucose; Life Technologies, Grand Island, NY) containing 10% (v/v) fetal bovine serum (FBS), and antibiotics (50 IU Penicillin G and 50 μg/ml Streptomycin sulfate). After 4 h incubation at 37 °C in 5% CO2, medium was replaced with 50 μl of medium and either the sample or standard. Recombinant human IFNA was used as the assay standard (3.87 × 108 IU/mg; EMD Biosciences, Billerica, MA). A 1:3 serial dilution of IFNA was completed to generate the standard curve. Samples were prepared by mixing DMEM containing 10% FBS and antibiotic with the flush solution (no more than one-half the final volume of medium added to each well). Cells were incubated at 37 °C overnight (16–24 h). Luciferase activity was determined by adding 50 μl of One-Glo Luciferase Assay Substrate (Promega Corp., Madison, WI) to each well. After 10 min of agitation, the plate was read using an Infinite M200 PRO Plate Reader (TECAN Systems Inc., San Jose, CA).

RNA and DNA extraction

Conceptus RNA and DNA were isolated using the AllPrep DNA/RNA mini kit (Qiagen, Hilden, Germany). Prior to PCR analysis, samples underwent an on-column DNase1 digestion (Life Technologies, Carlsbad, CA). Samples were reverse transcribed using a High Capacity cDNA Reverse Transcription Kit (Life Technologies). Quality of RNA was examined using the Experion RNA StdSens Analysis Kit (BioRad, Hercules, CA).

Conceptus sexing

Conceptus sex was determined using a previously described PCR-based approach [94] using GoTaq Green Master Mix (Promega, city state) and an Eppendorf Realplex4 Mastercycler (Hamburg, Germany). The thermocycler was programmed for an initial 5 min, 95 °C denaturation step followed by 40 cycles of 95C, 56 °C. and 72 °C, and ending with a 5-min polishing step at 72 °C. Samples were then digested with the Sac1 enzyme for 3 h at 37 °C, loaded onto a 1% (w/v) agarose gel and electrophoresed. DNA was detected using SYBR Safe DNA gel stain (ThermoFisher, Waltham, MA). Male conceptuses were identified by the presence of 3 bands, while females appeared as a double band.

RNA-sequencing analysis

RNA samples (n = 4 samples/sex/treatment; 16 total samples) were sequenced by Cofactor Genomics (St. Louis, MO), using an Illumina-based sequencing platform using single end 75 base reads.

Sequencing analysis was performed using CLC Genomics Workbench 10.1.1 (Qiagen; Germantown, MD). Reads were imported in CLC genomics workbench and cleaned to remove reads containing adapters and low-quality reads from raw data. Sequences were then aligned to the Ovis aries reference genome (NCBI; Oar_4.0) from Ensembl. Sequences were also mapped to the Bos taurus (Ensembl;UMB3.1) and Capra hircus (NCBI; ASM170441v1) genomes for an initial comparative analysis. Expression values were expressed in reads per kilobase of transcript per million (RPKM). An empirical analysis of differential gene expression was performed using the Robinson and Smyth Exact Test (Robinson and Smyth, 2007). A negative binomial distribution (NB) was assumed. False discovery rate (FDR) was controlled at a rate of 5% using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995). The list of DEGs also were limited to those containing ≥2-fold change and ≥ 0.2 RPKM. Gene ontology (GO) groupings were examined in DEGs using the functional classification analysis in the PANTHER Classification System (version 12.0). KEGG Mapper (v3.1) was used for DEG pathway analysis. Placenta-associated genes were identified through a literature search using the search terms “placenta”, “trophectoderm”, and “trophoblast” as there are not currently GO categories for these terms.

Statistical analysis

Ewe body weight, metabolic parameters and reproductive parameters were analyzed using the general linear model of the statistical analysis system (SAS Institute, Cary, NC). Conceptus sex ratio was analyzed using PROC FREQ of SAS. A repeated measures analysis and within day ANOVA were used to analyze plasma NEFA, glucose and progesterone data (SAS Institute, Cary, NC).



ADAM Metallopeptidase Domain 19


Activated leukocyte cell adhesion molecule


Aldehyde Dehydrogenase 1 Family Member A1


Acylation-stimulating protein


Beta-1,3-N-Acetylgalactosaminyltransferase 1


Body condition score


Breast cancer 1


Controlled internal drug release


Creatine Kinase B


Creatine Kinase, M-Type


Corpus luteum


Dopa Decarboxylase


Differentially expressed gene(s)


Dulbecco’s Modified Eagle Medium


Deoxyribonucleic acid


Developmental origins of health and disease


Fetal bovine serum


False discovery rate


Fibroblast growth factor receptor 1


Fetal origins of adult disease


Gene ontology


Glycoprotein 2


Glutathione S-Transferase Alpha 4








Interferon stimulated response element


Inositol-3-Phosphate Synthase 1


Membrane Metalloendopeptidase


M-Phase Phosphoprotein 9




National Center for Biotechnology Information


Non-esterified fatty acids


Nicotinamide riboside kinase




Pregnancy associated glycoprotein 11


Pregnancy associated glycoprotein 2


Pregnancy associated glycoprotein 4


Pregnancy associated glycoprotein 9


Polymerase chain reaction




Serine/threonine-protein phosphatase 2A regulatory subunit B″ subunit alpha


Prolactin-related protein family 4


Ribonucleic acid


Reads per kilobase million


Solute Carrier Family 6 Member 14




  1. Pi-Sunyer X. The medical risks of obesity. Postgrad Med. 2009;121(6):21–33.

    Article  Google Scholar 

  2. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity in the United States, 2009-2010. NCHS data brief. 2012;(82):1–8.

  3. Mitanchez D, Chavatte-Palmer P. Review shows that maternal obesity induces serious adverse neonatal effects and is associated with childhood obesity in their offspring. Acta Paediatr. 2018.

  4. Gaillard R, Santos S, Duijts L, Felix JF. Childhood health consequences of maternal obesity during pregnancy: a narrative review. Ann Nutr Metab. 2016;69(3–4):171–80.

    Article  CAS  Google Scholar 

  5. Fukuoka H. DOHaD (developmental origins of health and disease) and birth cohort research. J Nutr Sci Vitaminol (Tokyo). 2015;61(Suppl):S2–4.

    Article  CAS  Google Scholar 

  6. White CL, Purpera MN, Morrison CD. Maternal obesity is necessary for programming effect of high-fat diet on offspring. Am J Physiol Regul Integr Comp Physiol. 2009;296(5):R1464–72.

    Article  CAS  Google Scholar 

  7. Simar D, Chen H, Lambert K, Mercier J, Morris MJ. Interaction between maternal obesity and post-natal over-nutrition on skeletal muscle metabolism. Nutr Metab Cardiovasc Dis. 2012;22(3):269–76.

    Article  CAS  Google Scholar 

  8. Samuelsson AM, Matthews PA, Argenton M, Christie MR, McConnell JM, Jansen EH, Piersma AH, Ozanne SE, Twinn DF, Remacle C, et al. Diet-induced obesity in female mice leads to offspring hyperphagia, adiposity, hypertension, and insulin resistance: a novel murine model of developmental programming. Hypertension. 2008;51(2):383–92.

    Article  CAS  Google Scholar 

  9. Ozawa S, Mitsuhashi T, Mitsumoto M, Matsumoto S, Itoh N, Itagaki K, Kohno Y, Dohgo T. The characteristics of muscle fiber types of longissimus thoracis muscle and their influences on the quantity and quality of meat from Japanese black steers. Meat Sci. 2000;54(1):65–70.

    Article  CAS  Google Scholar 

  10. Ryu YC, Kim BC. The relationship between muscle fiber characteristics, postmortem metabolic rate, and meat quality of pig longissimus dorsi muscle. Meat Sci. 2005;71(2):351–7.

    Article  CAS  Google Scholar 

  11. Teixeira A, Batista S, Delfa R, Cadavez V. Lamb meat quality of two breeds with protected origin designation. Influence of breed, sex and live weight. Meat Sci. 2005;71(3):530–6.

    Article  CAS  Google Scholar 

  12. Zhang L, Long NM, Hein SM, Ma Y, Nathanielsz PW, Ford SP. Maternal obesity in ewes results in reduced fetal pancreatic beta-cell numbers in late gestation and decreased circulating insulin concentration at term. Domest Anim Endocrinol. 2011;40(1):30–9.

    Article  Google Scholar 

  13. Long NM, Ford SP, Nathanielsz PW. Maternal obesity eliminates the neonatal lamb plasma leptin peak. J Physiol. 2011;589(Pt 6):1455–62.

    Article  CAS  Google Scholar 

  14. St-Pierre J, Laurent L, King S, Vaillancourt C. Effects of prenatal maternal stress on serotonin and fetal development. Placenta. 2016;48(Suppl 1):S66–71.

    Article  CAS  Google Scholar 

  15. Burton GJ, Fowden AL, Thornburg KL. Placental origins of chronic disease. Physiol Rev. 2016;96(4):1509–65.

    Article  CAS  Google Scholar 

  16. Jones HN, Woollett LA, Barbour N, Prasad PD, Powell TL, Jansson T. High-fat diet before and during pregnancy causes marked up-regulation of placental nutrient transport and fetal overgrowth in C57/BL6 mice. FASEB J. 2009;23(1):271–8.

    Article  CAS  Google Scholar 

  17. Jansson N, Rosario FJ, Gaccioli F, Lager S, Jones HN, Roos S, Jansson T, Powell TL. Activation of placental mTOR signaling and amino acid transporters in obese women giving birth to large babies. J Clin Endocrinol Metab. 2013;98(1):105–13.

    Article  CAS  Google Scholar 

  18. Frias AE, Morgan TK, Evans AE, Rasanen J, Oh KY, Thornburg KL, Grove KL. Maternal high-fat diet disturbs uteroplacental hemodynamics and increases the frequency of stillbirth in a nonhuman primate model of excess nutrition. Endocrinology. 2011;152(6):2456–64.

    Article  CAS  Google Scholar 

  19. Ma Y, Zhu MJ, Zhang L, Hein SM, Nathanielsz PW, Ford SP. Maternal obesity and overnutrition alter fetal growth rate and cotyledonary vascularity and angiogenic factor expression in the ewe. Am J Physiol Regul Integr Comp Physiol. 2010;299(1):R249–58.

    Article  CAS  Google Scholar 

  20. Wilcoxon JS, Schwartz J, Aird F, Redei EE. Sexually dimorphic effects of maternal alcohol intake and adrenalectomy on left ventricular hypertrophy in rat offspring. Am J Physiol Endocrinol Metab. 2003;285(1):E31–9.

    Article  CAS  Google Scholar 

  21. Mao J, Zhang X, Sieli PT, Falduto MT, Torres KE, Rosenfeld CS. Contrasting effects of different maternal diets on sexually dimorphic gene expression in the murine placenta. Proc Natl Acad Sci U S A. 2010;107(12):5557–62.

    Article  CAS  Google Scholar 

  22. Gallou-Kabani C, Gabory A, Tost J, Karimi M, Mayeur S, Lesage J, Boudadi E, Gross MS, Taurelle J, Vige A, et al. Sex- and diet-specific changes of imprinted gene expression and DNA methylation in mouse placenta under a high-fat diet. PLoS One. 2010;5(12):e14398.

    Article  CAS  Google Scholar 

  23. Vickers MH, Clayton ZE, Yap C, Sloboda DM. Maternal fructose intake during pregnancy and lactation alters placental growth and leads to sex-specific changes in fetal and neonatal endocrine function. Endocrinology. 2011;152(4):1378–87.

    Article  CAS  Google Scholar 

  24. Clifton VL. Sexually dimorphic effects of maternal asthma during pregnancy on placental glucocorticoid metabolism and fetal growth. Cell Tissue Res. 2005;322(1):63–71.

    Article  CAS  Google Scholar 

  25. Stark MJ, Wright IM, Clifton VL. Sex-specific alterations in placental 11beta-hydroxysteroid dehydrogenase 2 activity and early postnatal clinical course following antenatal betamethasone. Am J Physiol Regul Integr Comp Physiol. 2009;297(2):R510–4.

    Article  CAS  Google Scholar 

  26. Dearden L, Balthasar N. Sexual dimorphism in offspring glucose-sensitive hypothalamic gene expression and physiological responses to maternal high-fat diet feeding. Endocrinology. 2014;155(6):2144–54.

    Article  Google Scholar 

  27. Elahi MM, Cagampang FR, Mukhtar D, Anthony FW, Ohri SK, Hanson MA. Long-term maternal high-fat feeding from weaning through pregnancy and lactation predisposes offspring to hypertension, raised plasma lipids and fatty liver in mice. Br J Nutr. 2009;102(4):514–9.

    Article  CAS  Google Scholar 

  28. Mingrone G, Manco M, Mora ME, Guidone C, Iaconelli A, Gniuli D, Leccesi L, Chiellini C, Ghirlanda G. Influence of maternal obesity on insulin sensitivity and secretion in offspring. Diabetes Care. 2008;31(9):1872–6.

    Article  Google Scholar 

  29. Hall V, Hinrichs K, Lazzari G, Betts DH, Hyttel P. Early embryonic development, assisted reproductive technologies, and pluripotent stem cell biology in domestic mammals. Vet J. 2013;197(2):128–42.

    Article  CAS  Google Scholar 

  30. Iliadou AN, Janson PC, Cnattingius S. Epigenetics and assisted reproductive technology. J Intern Med. 2011;270(5):414–20.

    Article  CAS  Google Scholar 

  31. Rattanatray L, MacLaughlin SM, Kleemann DO, Walker SK, Muhlhausler BS, McMillen IC. Impact of maternal periconceptional overnutrition on fat mass and expression of adipogenic and lipogenic genes in visceral and subcutaneous fat depots in the postnatal lamb. Endocrinology. 2010;151(11):5195–205.

    Article  CAS  Google Scholar 

  32. Nicholas LM, Morrison JL, Rattanatray L, Ozanne SE, Kleemann DO, Walker SK, Maclaughlin SM, Zhang S, Martin-Gronert MS, McMillen IC. Differential effects of exposure to maternal obesity or maternal weight loss during the Periconceptional period in the sheep on insulin Signalling molecules in skeletal muscle of the offspring at 4 months of age. PLoS One. 2013;8(12):e84594.

    Article  Google Scholar 

  33. Howie GJ, Sloboda DM, Kamal T, Vickers MH. Maternal nutritional history predicts obesity in adult offspring independent of postnatal diet. J Physiol. 2009;587(Pt 4):905–15.

    Article  CAS  Google Scholar 

  34. Sasson IE, Vitins AP, Mainigi MA, Moley KH, Simmons RA. Pre-gestational vs gestational exposure to maternal obesity differentially programs the offspring in mice. Diabetologia. 2015;58(3):615–24.

    Article  CAS  Google Scholar 

  35. Igosheva N, Abramov AY, Poston L, Eckert JJ, Fleming TP, Duchen MR, McConnell J. Maternal diet-induced obesity alters mitochondrial activity and redox status in mouse oocytes and zygotes. PLoS One. 2010;5(4):e10074.

    Article  Google Scholar 

  36. Spencer TE, Johnson GA, Bazer FW, Burghardt RC. Implantation mechanisms: insights from the sheep. Reproduction. 2004;128(6):657–68.

    Article  CAS  Google Scholar 

  37. Guillomot M, Flechon JE, Wintenberger-Torres S. Conceptus attachment in the ewe: an ultrastructural study. Placenta. 1981;2(2):169–82.

    Article  CAS  Google Scholar 

  38. Sebert SP, Hyatt MA, Chan LL, Patel N, Bell RC, Keisler D, Stephenson T, Budge H, Symonds ME, Gardner DS. Maternal nutrient restriction between early and midgestation and its impact upon appetite regulation after juvenile obesity. Endocrinology. 2009;150(2):634–41.

    Article  CAS  Google Scholar 

  39. Williams PJ, Kurlak LO, Perkins AC, Budge H, Stephenson T, Keisler D, Symonds ME, Gardner DS. Hypertension and impaired renal function accompany juvenile obesity: the effect of prenatal diet. Kidney Int. 2007;72(3):279–89.

    Article  CAS  Google Scholar 

  40. Cerf ME, Herrera E. High fat diet administration during specific periods of pregnancy alters maternal fatty acid profiles in the near-term rat. Nutrients. 2016;8(1).

    Article  Google Scholar 

  41. Velazquez MA, Hadeler KG, Herrmann D, Kues WA, Ulbrich SE, Meyer HH, Remy B, Beckers JF, Sauerwein H, Niemann H. In vivo oocyte developmental competence is reduced in lean but not in obese superovulated dairy cows after intraovarian administration of IGF1. Reproduction. 2011;142(1):41–52.

    Article  CAS  Google Scholar 

  42. van der Steeg JW, Steures P, Eijkemans MJ, Habbema JD, Hompes PG, Burggraaff JM, Oosterhuis GJ, Bossuyt PM, van der Veen F, Mol BW: Obesity affects spontaneous pregnancy chances in subfertile, ovulatory women. Hum Reprod 2008, 23(2):324–328.

  43. Wallace JM, Milne JS, Adam CL, Aitken RP. Impact of donor and recipient adiposity on placental and fetal growth in adolescent sheep. Reproduction. 2017;153(4):381–94.

    Article  CAS  Google Scholar 

  44. Bermejo-Alvarez P, Rosenfeld CS, Roberts RM. Effect of maternal obesity on estrous cyclicity, embryo development and blastocyst gene expression in a mouse model. Hum Reprod. 2012;27(12):3513–22.

    Article  CAS  Google Scholar 

  45. Binder NK, Mitchell M, Gardner DK. Parental diet-induced obesity leads to retarded early mouse embryo development and altered carbohydrate utilisation by the blastocyst. Reprod Fertil Dev. 2012;24(6):804–12.

    Article  CAS  Google Scholar 

  46. Long NM, George LA, Uthlaut AB, Smith DT, Nijland MJ, Nathanielsz PW, Ford SP. Maternal obesity and increased nutrient intake before and during gestation in the ewe results in altered growth, adiposity, and glucose tolerance in adult offspring. J Anim Sci. 2010;88(11):3546–53.

    Article  CAS  Google Scholar 

  47. Matsuba R, Imamura M, Tanaka Y, Iwata M, Hirose H, Kaku K, Maegawa H, Watada H, Tobe K, Kashiwagi A, et al. Replication study in a Japanese population of six susceptibility loci for type 2 diabetes originally identified by a Transethnic meta-analysis of genome-wide association studies. PLoS One. 2016;11(4):e0154093.

    Article  Google Scholar 

  48. Ortega FJ, Moreno-Navarrete JM, Mayas D, Garcia-Santos E, Gomez-Serrano M, Rodriguez-Hermosa JI, Ruiz B, Ricart W, Tinahones FJ, Fruhbeck G, et al. Breast cancer 1 (BrCa1) may be behind decreased lipogenesis in adipose tissue from obese subjects. PLoS One. 2012;7(5):e33233.

    Article  CAS  Google Scholar 

  49. Smith SR, Gawronska-Kozak B, Janderova L, Nguyen T, Murrell A, Stephens JM, Mynatt RL. Agouti expression in human adipose tissue: functional consequences and increased expression in type 2 diabetes. Diabetes. 2003;52(12):2914–22.

    Article  CAS  Google Scholar 

  50. Gonzalez-Muniesa P, Marrades MP, Martinez JA, Moreno-Aliaga MJ. Differential proinflammatory and oxidative stress response and vulnerability to metabolic syndrome in habitual high-fat young male consumers putatively predisposed by their genetic background. Int J Mol Sci. 2013;14(9):17238–55.

    Article  Google Scholar 

  51. Wen W, Zheng W, Okada Y, Takeuchi F, Tabara Y, Hwang JY, Dorajoo R, Li H, Tsai FJ, Yang X, et al. Meta-analysis of genome-wide association studies in east Asian-ancestry populations identifies four new loci for body mass index. Hum Mol Genet. 2014;23(20):5492–504.

    Article  CAS  Google Scholar 

  52. Yeung KR, Chiu CL, Pidsley R, Makris A, Hennessy A, Lind JM. DNA methylation profiles in preeclampsia and healthy control placentas. Am J Physiol Heart Circ Physiol. 2016;310(10):H1295–303.

    Article  Google Scholar 

  53. Panagodage S, Yong HE, Da Silva Costa F, Borg AJ, Kalionis B, Brennecke SP, Murthi P. Low-dose acetylsalicylic acid treatment modulates the production of cytokines and improves trophoblast function in an in vitro model of early-onset preeclampsia. Am J Pathol. 2016;186(12):3217–24.

    Article  CAS  Google Scholar 

  54. Li L, Cohen M, Wu J, Sow MH, Nikolic B, Bischof P, Irminger-Finger I. Identification of BARD1 splice-isoforms involved in human trophoblast invasion. Int J Biochem Cell Biol. 2007;39(9):1659–72.

    Article  CAS  Google Scholar 

  55. Suzuki A, de la Pompa JL, Hakem R, Elia A, Yoshida R, Mo R, Nishina H, Chuang T, Wakeham A, Itie A, et al. Brca2 is required for embryonic cellular proliferation in the mouse. Genes Dev. 1997;11(10):1242–52.

    Article  CAS  Google Scholar 

  56. Hakem R, de la Pompa JL, Sirard C, Mo R, Woo M, Hakem A, Wakeham A, Potter J, Reitmair A, Billia F, et al. The tumor suppressor gene Brca1 is required for embryonic cellular proliferation in the mouse. Cell. 1996;85(7):1009–23.

    Article  CAS  Google Scholar 

  57. Dennery PA. Effects of oxidative stress on embryonic development. Birth defects research Part C, Embryo today : reviews. 2007;81(3):155–62.

    Article  CAS  Google Scholar 

  58. Yoon SB, Choi SA, Sim BW, Kim JS, Mun SE, Jeong PS, Yang HJ, Lee Y, Park YH, Song BS, et al. Developmental competence of bovine early embryos depends on the coupled response between oxidative and endoplasmic reticulum stress. Biol Reprod. 2014;90(5):104.

    Article  Google Scholar 

  59. Thompson JG, Simpson AC, Pugh PA, Donnelly PE, Tervit HR. Effect of oxygen concentration on in-vitro development of preimplantation sheep and cattle embryos. J Reprod Fertil. 1990;89(2):573–8.

    Article  CAS  Google Scholar 

  60. Gabory A, Roseboom TJ, Moore T, Moore LG, Junien C. Placental contribution to the origins of sexual dimorphism in health and diseases: sex chromosomes and epigenetics. Biol Sex Differ. 2013;4(1):5.

    Article  Google Scholar 

  61. Rosenfeld CS. Periconceptional influences on offspring sex ratio and placental responses. Reprod Fertil Dev. 2011;24(1):45–58.

    Article  Google Scholar 

  62. Forde N, Maillo V, O'Gaora P, Simintiras CA, Sturmey RG, Ealy AD, Spencer TE, Gutierrez-Adan A, Rizos D, Lonergan P. Sexually dimorphic gene expression in bovine conceptuses at the initiation of implantation. Biol Reprod. 2016;95(4):92.

    Article  Google Scholar 

  63. Bermejo-Alvarez P, Rizos D, Lonergan P, Gutierrez-Adan A. Transcriptional sexual dimorphism in elongating bovine embryos: implications for XCI and sex determination genes. Reproduction. 2011;141(6):801–8.

    Article  CAS  Google Scholar 

  64. Bazer FW, Spencer TE, Thatcher WW. Growth and development of the ovine conceptus. J Anim Sci. 2012;90(1):159–70.

    Article  CAS  Google Scholar 

  65. Denicol AC, Leao BC, Dobbs KB, Mingoti GZ, Hansen PJ. Influence of sex on basal and Dickkopf-1 regulated gene expression in the bovine Morula. PLoS One. 2015;10(7):e0133587.

    Article  Google Scholar 

  66. Bermejo-Alvarez P, Rizos D, Rath D, Lonergan P, Gutierrez-Adan A. Sex determines the expression level of one third of the actively expressed genes in bovine blastocysts. Proc Natl Acad Sci U S A. 2010;107(8):3394–9.

    Article  CAS  Google Scholar 

  67. Telugu BP, Walker AM, Green JA. Characterization of the bovine pregnancy-associated glycoprotein gene family--analysis of gene sequences, regulatory regions within the promoter and expression of selected genes. BMC Genomics. 2009;10:185.

    Article  Google Scholar 

  68. Green JA, Xie S, Quan X, Bao B, Gan X, Mathialagan N, Beckers JF, Roberts RM. Pregnancy-associated bovine and ovine glycoproteins exhibit spatially and temporally distinct expression patterns during pregnancy. Biol Reprod. 2000;62(6):1624–31.

    Article  CAS  Google Scholar 

  69. Touzard E, Reinaud P, Dubois O, Guyader-Joly C, Humblot P, Ponsart C, Charpigny G. Specific expression patterns and cell distribution of ancient and modern PAG in bovine placenta during pregnancy. Reproduction. 2013;146(4):347–62.

    Article  CAS  Google Scholar 

  70. Groth C, Lardelli M. The structure and function of vertebrate fibroblast growth factor receptor 1. Int J Dev Biol. 2002;46(4):393–400.

    CAS  PubMed  Google Scholar 

  71. Huang L, Shen Z, Xu Q, Huang X, Chen Q, Li D. Increased levels of microRNA-424 are associated with the pathogenesis of fetal growth restriction. Placenta. 2013;34(7):624–7.

    Article  CAS  Google Scholar 

  72. Mouillet JF, Donker RB, Mishima T, Cronqvist T, Chu T, Sadovsky Y. The unique expression and function of miR-424 in human placental trophoblasts. Biol Reprod. 2013;89(2):25.

    Article  Google Scholar 

  73. Shyu MK, Lin MC, Shih JC, Lee CN, Huang J, Liao CH, Huang IF, Chen HY, Huang MC, Hsieh FJ. Mucin 15 is expressed in human placenta and suppresses invasion of trophoblast-like cells in vitro. Hum Reprod. 2007;22(10):2723–32.

    Article  CAS  Google Scholar 

  74. Assou S, Boumela I, Haouzi D, Monzo C, Dechaud H, Kadoch IJ, Hamamah S. Transcriptome analysis during human trophectoderm specification suggests new roles of metabolic and epigenetic genes. PLoS One. 2012;7(6):e39306.

    Article  CAS  Google Scholar 

  75. Gonzalez IM, Martin PM, Burdsal C, Sloan JL, Mager S, Harris T, Sutherland AE. Leucine and arginine regulate trophoblast motility through mTOR-dependent and independent pathways in the preimplantation mouse embryo. Dev Biol. 2012;361(2):286–300.

    Article  CAS  Google Scholar 

  76. Zhao M, Qiu W, Li Y, Sang QA, Wang Y. Dynamic change of Adamalysin 19 (ADAM19) in human placentas and its effects on cell invasion and adhesion in human trophoblastic cells. Sci China C Life Sci. 2009;52(8):710–8.

    Article  Google Scholar 

  77. Khan IY, Taylor PD, Dekou V, Seed PT, Lakasing L, Graham D, Dominiczak AF, Hanson MA, Poston L. Gender-linked hypertension in offspring of lard-fed pregnant rats. Hypertension. 2003;41(1):168–75.

    Article  CAS  Google Scholar 

  78. Gilbert JS, Ford SP, Lang AL, Pahl LR, Drumhiller MC, Babcock SA, Nathanielsz PW, Nijland MJ. Nutrient restriction impairs nephrogenesis in a gender-specific manner in the ovine fetus. Pediatr Res. 2007;61(1):42–7.

    Article  Google Scholar 

  79. Wales RG, Cuneo CL. Morphology and chemical analysis of the sheep conceptus from the 13th to the 19th day of pregnancy. Reprod Fertil Dev. 1989;1(1):31–9.

    Article  CAS  Google Scholar 

  80. Brooks K, Burns G, Spencer TE. Conceptus elongation in ruminants: roles of progesterone, prostaglandin, interferon tau and cortisol. Journal of animal science and biotechnology. 2014;5(1):53.

    Article  Google Scholar 

  81. Zhu MJ, Du M, Nijland MJ, Nathanielsz PW, Hess BW, Moss GE, Ford SP. Down-regulation of growth signaling pathways linked to a reduced cotyledonary vascularity in placentomes of over-nourished, obese pregnant ewes. Placenta. 2009;30(5):405–10.

    Article  CAS  Google Scholar 

  82. Persson M, Cnattingius S, Wikstrom AK, Johansson S. Maternal overweight and obesity and risk of pre-eclampsia in women with type 1 diabetes or type 2 diabetes. Diabetologia. 2016;59(10):2099–105.

    Article  Google Scholar 

  83. Burton GJ, Woods AW, Jauniaux E, Kingdom JC. Rheological and physiological consequences of conversion of the maternal spiral arteries for uteroplacental blood flow during human pregnancy. Placenta. 2009;30(6):473–82.

    Article  CAS  Google Scholar 

  84. Romero R, Chaiworapongsa T. Preeclampsia: a link between trophoblast dysregulation and an antiangiogenic state. J Clin Invest. 2013;123(7):2775–7.

    Article  CAS  Google Scholar 

  85. Wang A, Rana S, Karumanchi SA. Preeclampsia: the role of angiogenic factors in its pathogenesis. Physiology (Bethesda). 2009;24:147–58.

    Google Scholar 

  86. Spencer TE, Forde N, Lonergan P. Insights into conceptus elongation and establishment of pregnancy in ruminants. Reprod Fertil Dev. 2017;29(1):84–100.

    Article  Google Scholar 

  87. Lonergan P, Forde N, Spencer T. Role of progesterone in embryo development in cattle. Reprod Fertil Dev. 2015;28(2):66–74.

    Article  Google Scholar 

  88. Fernández-Sánchez A, Madrigal-Santillán E, Bautista M, Esquivel-Soto J, Morales-González Á, Esquivel-Chirino C, Durante-Montiel I, Sánchez-Rivera G, Valadez-Vega C, Morales-González JA. Inflammation, oxidative stress, and obesity. Int J Mol Sci. 2011;12(5):3117–32.

    Article  Google Scholar 

  89. Shankar K, Zhong Y, Kang P, Lau F, Blackburn ML, Chen J-R, Borengasser SJ, Ronis MJJ, Badger TM. Maternal obesity promotes a Proinflammatory signature in rat uterus and blastocyst. Endocrinology. 2011;152(11):4158–70.

    Article  CAS  Google Scholar 

  90. Sessions-Bresnahan DR, Heuberger AL, Carnevale EM: Obesity in mares promotes uterine inflammation and alters embryo lipid fingerprints and homeostasis†. Biol Reprod 2018:ioy107-ioy107.

  91. Thompson JM, Meyer HH: Body condition scoring of sheep. In.: [Corvallis, Or.]: Oregon State University, Extension Service; 1994.

  92. Cox JF, Allende R, Lara E, Leiva A, Diaz T, Dorado J, Saravia F. Follicular dynamics, interval to ovulation and fertility after AI in short-term progesterone and PGF2alpha oestrous synchronization protocol in sheep. Reproduction in domestic animals = Zuchthygiene. 2012;47(6):946–51.

    Article  CAS  Google Scholar 

  93. McCoski SR, Xie M, Hall EB, Mercadante PM, Spencer TE, Lonergan P, Ealy AD. Validation of an interferon stimulatory response element reporter gene assay for quantifying type I interferons. In: Domest Anim Endocrinol; 2014.

    Google Scholar 

  94. Saravanan TMN, Kumanan A, Kumaresan K. A Sexing of Sheep Embryos Produced In vitro by Polymerase Chain Reaction and Sex-specific Polymorphism. Asian-Australas J Anim Sci. 2003;16(5):650–4.

    Article  CAS  Google Scholar 

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Authors thank Dr. Brent Wilson and Cofactor Genomics for their technical support during sample processing and sequence analysis.

Availability of data and material

All data supporting the results reported in this article can be found in the additional files.


This work was funded by the Commonwealth Health Research Board (Grant #208–01-15). S.R.M. received PhD fellowship support from The Pratt Animal Nutritional Graduate Student Fellowship Program at Virginia Tech.

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Authors and Affiliations



SRM completed every aspect of the project, conducted all analyses, and was a major contributor to writing the manuscript. MTV assisted with the animal portion of the project. CEO assisted with the RNAseq analyses. RRC supervised the RNAseq analyses. ADE conceived and designed the work, oversaw the entire project, and developed the final manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alan D. Ealy.

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All animal work was completed in compliance and with the approval of the Virginia Tech Institutional Animal Care and Use Committee (IACUC; #14–104).

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The authors declare they have no competing interests.

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Additional files

Additional file 1:

Raw data containing all transcripts identified in the RNA-sequencing analysis. Included are reference sequence (RefSeq) and gene ID for each transcript, the max group mean (indicating the mean RPKM for the treatment group with the greatest expression value within each comparison), log2 fold-changes based on obesity status, sex and (XLSX 17599 kb)

Additional file 2:

Obese-derived vs Lean-derived conceptus DEGs. Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0), and differentially expressed genes (DEGs) were identified as having a FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM. (XLSX 11 kb)

Additional file 3:

Male vs Female conceptus DEGs. Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0). Differentially expressed genes (DEGs) were identified as having a FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM. (XLSX 23 kb)

Additional file 4:

DEGs that differed each conceptus sex based on maternal obesity status. Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0). Differentially expressed genes (DEGs) were identified based on differences in conceptus sex in the obese and lean treatment groups (FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM). This table shows differences as they exist within the individual pair-wise comparisons for these various interacting effects, and specifically: 1) obese vs. lean male conceptuses, 2) obese vs. lean female conceptuses, 3) obese male vs. female conceptuses, 4) obese male vs. lean female conceptuses, 5) lean male vs. obese female conceptuses, and 6) lean male vs. female conceptuses. (XLSX 108 kb)

Additional file 5:

Gene IDs for placenta-associated DEGs represented in Fig. 2. Sequences were mapped to the Ovis aries genome (NCBI; Oar_4.0), and differentially expressed genes (DEGs) were identified as having a FDR ≤ 0.05, ≥ 2-fold change, and ≥ 0.2 RPKM. Genes involved in placentation were identified from the list of DEGs via literature search. (XLSX 14 kb)

Additional file 6:

Example of a uterine flush at day 14 breeding containing multiple conceptuses. The photograph was taken immediately after flushing the conceptus from the uterus. The conceptuses are intertwined at this time. After conceptuses are gently uncoiled, the length of each can be determined using the grided plates (1 cm grid). (TIF 212 kb)

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McCoski, S.R., Vailes, M.T., Owens, C.E. et al. Exposure to maternal obesity alters gene expression in the preimplantation ovine conceptus. BMC Genomics 19, 737 (2018).

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