Abstract

   Growing evidence supports the hypothesis that the in utero environment
   can have profound implications for fetal development and later life
   offspring health. Current theory suggests conditions experienced in
   utero prepare, or “programme”, the fetus for its anticipated post-natal
   environment. The mechanisms responsible for these programming events
   are poorly understood but are likely to involve gene expression
   changes. Folate is essential for normal fetal development and
   inadequate maternal folate supply during pregnancy has long term
   adverse effects for offspring. We tested the hypothesis that folate
   depletion during pregnancy alters offspring programming through altered
   gene expression. Female C57BL/6J mice were fed diets containing 2 mg or
   0.4 mg folic acid/kg for 4 weeks before mating and throughout
   pregnancy. At 17.5 day gestation, genome-wide gene expression was
   measured in male fetal livers and placentas. In the fetal liver, 989
   genes were expressed differentially (555 up-regulated, 434
   down-regulated) in response to maternal folate depletion, with 460
   genes expressed differentially (250 up-regulated, 255 down-regulated)
   in the placenta. Only 25 differentially expressed genes were common
   between organs. Maternal folate intake during pregnancy influences
   fetal gene expression in a highly organ specific manner which may
   reflect organ-specific functions.

   Keywords: transcriptome, programming, developmental origins of health
   and disease, pregnancy, diet

1. Introduction

   The developmental origins of health and disease (DOHaD) hypothesis
   proposes that in utero and early life exposures can lead to altered
   programming of offspring. Such programming events can cause permanent
   changes in organ development, physiology and metabolism leading to
   altered disease risk in later life. Suboptimal nutrition, both under-
   and over-nutrition, during fetal and neonatal development increases
   susceptibility to a wide range of diseases [[34]1]. These observations
   indicate a degree of plasticity during development, in which the fetal
   phenotype may be altered due to environment cues [[35]2] to prepare it
   for the anticipated post-natal environment [[36]3]. The biological
   mechanisms underlying this “programming” effect of nutrition during
   early life are poorly understood, but are likely to involve changes in
   gene expression.

   The protective effect of adequate dietary folate intake and of folic
   acid supplementation during pregnancy on risk of neural tube defects
   (NTDs) is well established [[37]4,[38]5]. Further, epidemiological
   evidence suggests that adequate dietary folate intake or
   supplementation with folic acid during pregnancy may reduce the risk of
   other congenital defects [[39]6] and adverse pregnancy outcomes
   [[40]7], as well enhancing neurodevelopment [[41]8] and reducing the
   risk of severe language delay [[42]9], autism [[43]10,[44]11] and some
   cancers (leukaemia [[45]12,[46]13,[47]14], brain tumours
   [[48]15,[49]16] and neuroblastoma [[50]17]) [[51]18] in children. In
   rodent models, folate deficiency during pregnancy can cause spontaneous
   abortion, teratogenic effects in offspring, reduced litter number, and
   altered offspring body weight [[52]19,[53]20]. Sufficient maternal
   folate intake during pregnancy is essential for successful pregnancy
   outcomes/normal fetal development and for the long-term health of the
   offspring.

   Folate, a B vitamin, is central to one-carbon metabolism which, in
   addition to formation of the universal methyl donor,
   S-adenosyl-methionine (SAM), interacts with several other cellular
   pathways including amino acid metabolism and biosynthesis of purine and
   pyrimidines [[54]21]. SAM is critical for the methylation of biological
   molecules including DNA, lipids and proteins. Epigenetic mechanisms
   (including methylation of DNA and of histones) which regulate gene
   expression are susceptible to modification via altered SAM availability
   in response to changes in folate intake (reviewed in [[55]22]).
   Therefore, we hypothesised that inadequate folate supply during
   pregnancy alters programming of the offspring via changes in gene
   expression and that this is responsible for the observed adverse
   effects of this maternal nutritional insult on pregnancy outcomes and
   offspring health in later life. Mammals respond to inadequate nutrient
   supply by prioritising allocation of nutrients to specific purposes
   [[56]23,[57]24] which may result in cell, tissue and organ differences
   in gene expression. Little is known about such inter-organ differences
   in fetal gene expression in response to restricted folate supply. We
   hypothesised that the fetal liver and placenta, which represent organs
   with long and short-term consequences for the developing animal, would
   be subject to distinctly different responses to folate depletion. To
   test these hypotheses, we quantified genome-wide gene expression
   patterns in fetal liver and placenta in response to maternal folate
   depletion before, and throughout, pregnancy.

2. Experimental Section

2.1. Animal Husbandry and Experimental Diets

   All animal procedures were approved by the Newcastle University Ethics
   Review Committee and the UK Home Office (Project Licence number
   60/3979) and have been described previously [[58]25]. Animals were
   housed in the Comparative Biology Centre, Newcastle University at 20–22
   °C and with 12 h light and dark cycles. Fresh water was available ad
   libitum. Female C57BL/6J mice were allocated at random to either a low
   folate (0.4 mg folic acid/kg diet) or normal folate diet (2 mg folic
   acid/kg diet) (6 g of allocated diet was offered to each mouse per
   day), and maintained on this diet for 4 weeks prior to mating. Diet
   compositions were modified from AIN-93G [[59]26] and have been
   described previously [[60]25]. l-amino acids were used as a protein
   substitute. All ingredients, other than folic acid, were included in
   both diets at the same concentrations to avoid potential confounding
   through other dietary factors. The degree of folate depletion induced
   by feeding the diet containing 0.4 mg folic acid/kg was sufficient to
   impose a nutritional stress (evidenced by reduced circulating
   concentrations of folate) but not so severe as to limit reproduction.
   The normal folate diet contained 2 mg folic acid/kg diet which is
   considered sufficient to support breeding and maintenance in this
   species. Mice were time mated i.e., a male was added to a cage
   containing two females overnight and removed the following morning.
   Pregnant females, identified by the presence of a vaginal plug, were
   re-caged and offered 10 g/day of allocated diet throughout pregnancy.
   At 17.5 days gestation, dams were killed for collection of blood and
   organs.

2.2. Sample Collection

   Animals were anesthetised using gaseous isoflurane, blood was removed
   by cardiac puncture and animals were killed by cervical dislocation.
   Blood was collected and stored in EDTA tubes. Whole blood
   5-methyltetrahydrofolate (THF) and 5–10-methylTHF concentrations were
   measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS)
   and data reported previously [[61]25]. The uterus, containing all
   fetuses and placentas, was removed and placed immediately in ice cold
   PBS. The liver and placenta of each fetus were removed, weighed and
   snap frozen in liquid nitrogen and stored at −80 °C until required for
   RNA extraction.

2.3. RNA Extraction

   To avoid any potential influence of sex on resultant data, only male
   tissues were analysed. Fetal sex was determined by polymerase chain
   reaction (PCR) of the sex determining region-Y (SRY) gene using DNA
   extracted from embryonic tail tissue [[62]25,[63]27]. RNA was extracted
   from whole fetal livers and placentas of males only using Tri-reagent
   (Sigma-Aldrich, Gillingham, Dorset, SP8 4XT, UK) and following the
   manufacturer’s instructions. Briefly, 50 mg tissue was homogenised in
   500 μL Tri-reagent on ice. A further 500 μL Tri-reagent and 200 μL
   chloroform were added, then the sample was mixed by inversion and
   incubated on ice for 5 min. Samples were then centrifuged at 13,500 rpm
   for 15 min at 4 °C. The upper aqueous phase was removed, RNA was
   precipitated by incubation on ice with 500 μL isopropanol for 10 min,
   after which it was collected by centrifugation at 13,500 rpm for 10 min
   at 4 °C. The supernatant fluid was removed and the pellet was washed
   with 1 mL 75% ethanol for 10 min before centrifuging at 6000 rpm for 5
   min at 4 °C. The supernatant fluid was removed, and the pellet was
   allowed to dry for 10 min before resuspending the RNA in 40 μL water.
   Contaminating DNA was removed using RQ1 DNase (Promega, Southampton,
   Hampshire, SO16 7NS, UK). RNA integrity was checked on an agarose gel
   and concentration and purity were measured using a Nanodrop
   spectrophotometer (Thermo Fisher, Waltham, MA, USA).

2.4. Gene Expression Arrays

   RNA from each tissue was pooled for three male fetuses per litter (5
   μg/fetus with a final concentration of 500 ng/μL) and hybridised to a
   single array for a total of 12 litters (n = 6 per dietary group) for
   each organ. Where a litter had more than three male fetuses, the three
   fetuses with weights closest to the mean litter weight were analysed.

   Genome-wide transcript abundance was determined by ServiceXS
   (Plesmanlaan 1/D, 2333 BZ Leiden, The Netherlands) on the Affymetrix
   GeneChip platform with the NuGO mouse array (NuGO_Mm1a520177). This
   array comprises over 24,000 probe sets, covering the majority of
   established genes. Before the labelling process, the integrity of all
   RNA samples (RNA Integrity Number (RIN) > 8) was confirmed using the
   Agilent 2100 Bioanalyser (Agilent Technologies, Stockport, Cheshire,
   SK8 3GY, UK). Output data were supplied as Affymetrix CEL files and
   imported into R (version 2.15.3) using the Affy package [[64]28]. Data
   from liver and placenta were pre-processed separately using gcRMA
   background correction and quantile normalisation [[65]29] to correct
   for batch effects and other technical confounders. To maximize
   sensitivity and specificity, updated Entrez gene probe-set annotation
   was used from the BrainArray project [[66]30] (version 14.1.0)
   resulting in 16,270 re-annotated probesets mapping to unique
   transcripts. Statistical analysis comparing the two diet groups was
   performed separately for each organ using the empirical Bayes approach
   of the Limma package [[67]31] which performs a moderated t-test. On
   filtering genes for significant changes using False Discovery Rate
   (FDR) values calculated using the Benjamini and Hochberg method (FDR <
   0.05), no genes remained statistically significant. Pathway analysis
   can in part replace FDR corrections by testing for the regulation of
   related genes, which suffers less from oversampling. Genes were,
   therefore, considered to show a differential expression relevant for
   further analysis in enrichment analysis in response to maternal folate
   depletion if there was a significant (p < 0.05) increase or reduction
   of at least 1.2 fold. DAVID [[68]32] was used to carry out Gene
   Ontology enrichment analysis and to investigate KEGG pathways affected
   by maternal folate depletion. The threshold for significance for Gene
   Ontology enrichment analysis was set at p < 0.05 (corrected for
   multiple testing), and at p < 0.05 (uncorrected) for KEGG pathway
   enrichment analysis. Additional pathway analysis was carried out using
   PathVisio 3.2.0 and the curated pathway collection of WikiPathways
   (download date: 1 September 2015), applying the same parameters for
   significant fold-change as stated above, imposing a Z score of 1.9 for
   significance to filter for probable changed pathways. All raw and
   processed microarray data have been deposited in the ArrayExpress
   database (accession ID E-MTAB-3940).

2.5. Validation of Gene Expression Changes Using Real-Time PCR

   To confirm the gene expression changes observed in the microarray
   analysis, real-time PCR was performed on each individual (i.e., not
   pooled) fetal RNA sample that was analysed by microarray hybridisation,
   focusing on 13 gene targets. Target genes were selected on the basis of
   being the most up or down regulated in the liver and placenta. Gene
   transcripts analysed in placental RNA were Cyp21a1, Hbb-y, Slco1b2,
   Ptgs2, Vcan, Lrrn4, and Mettl7b and in fetal liver RNA were Asgr1,
   Hamp, Actc1, Ckm, Tnnc2 and Smpx.

   RNA (1 μg) was reverse transcribed using Quantitect Reverse
   Transcription kit (Qiagen, Cat No. 205313) according to the
   manufacturer’s instructions. Briefly, 1 μg of RNA was incubated with 2
   μL genomic DNA Wipeout buffer in a reaction volume of 14 μL at 42 °C
   for 2 min to remove any genomic DNA. The mixture was then placed
   immediately on ice. RNA was incubated with 1 μL Quantiscript reverse
   transcriptase, 1 μL RT primer mix and 4 μL Quantiscript RT buffer for
   15 min at 42 °C, after which time it was incubated at 95 °C for 3 min.
   The cDNA samples generated were then diluted 1:9 with water for use in
   real time PCR.

   Prior to sample analysis, expression values, linearity and efficiency
   of each assay were determined through cDNA standard curves completed
   for each transcript measured. Transcript levels of the genes of
   interest were measured on a Roche Lightcycler 480 (Roche Applied
   Science, Burgess Hill, West Sussex, RH15 9RY, UK) in a total reaction
   volume of 25 μL using 2.5 μL Quantitect sybr green transcript specific
   primers (Qiagen, see [69]Supplementary Materials Table S1 for details
   of manufacturer’s individual catalogue numbers), 12.5 μL Quantitect
   SYBR green mix (Qiagen Cat. No. 204145), 1 μL diluted cDNA and 9 μL
   water and cycling parameters 95 °C for 5 min (1 cycle); 95 °C for 10 s
   followed by 60 °C for 30 s (40 cycles); followed by a final melt curve
   analysis and cooling to 40 °C. Using the delta CT method, transcript
   levels of the genes of interest were normalised to GAPDH transcript
   levels which were determined using the same procedure and parameters
   described.

2.6. In Silico Analysis of Gene Promoter Regions for Transcription Factor
(TF) Binding Sites

   Genomatix software ([70]https://www.genomatix.de/v3.5 24 July 2015) was
   employed to obtain promoter sequences for genes of interest using the
   Gene2Promoter function. Promoter sequences were analysed for common
   transcription factor binding sites using the Common TFs function. Lists
   of TFs belonging to the transcription factor binding site families
   identified were downloaded from Genomatix and compared with fetal liver
   gene expression data.

2.7. Statistical Analysis

   Statistical analysis of array data is described above. For all other
   datasets, data distributions were examined by the Kolmogorov-Smirnov
   test and all datasets were normally distributed. Analysis of variance
   (Statistical Package for the Social Sciences (SPSS) version 21, IBM,
   Armonk, New York 10504, NY, USA) was used to examine the effects of
   diet on placental weight, placental efficiency and gene expression
   analysis on data obtained from RT PCR analysis. p < 0.05 was considered
   statistically significant.

3. Results

3.1. Influence of Maternal Folate Intake during Pregnancy on Fetal Weight,
Liver Weight, Placental Weight and Placental Efficiency

   Data on the effects of maternal folate depletion on fetal weight and
   fetal liver weight have been presented previously [[71]25]. In
   addition, exposure to the Low Folate diet reduced maternal whole blood
   5’methyl THF concentration significantly (p < 0.001) with values of 666
   (40.9) and 378 (50.0) nmol/L for Normal and Low Folate diets
   respectively [[72]25]. Maternal folate depletion increased fetal weight
   but had no effect on weight of the fetal liver. There was no
   significant influence of maternal folate intake during pregnancy on
   placental weight (mean placental weights were 107.0 mg and 107.3 mg for
   normal (n = 56) and low (n = 37) folate groups respectively (p =
   0.945)). Placental efficiency, calculated by dividing fetal weight by
   placental weight, was not influenced by maternal folate depletion (mean
   placental efficiencies were 7.9 and 9.1 for normal (n = 56) and low (n
   = 37) folate groups respectively (p = 0.200)).

3.2. Influence of Maternal Folate Intake during Pregnancy on Gene Expression
in the Fetal Liver

   In the fetal liver, 989 genes were differentially expressed in response
   to maternal folate depletion, comprising 555 up-regulated genes and 434
   down-regulated genes ([73]Supplementary Materials Table S2). All raw
   and processed microarray data have been deposited in the ArrayExpress
   database (accession ID E-MTAB-3940). Seventy three (7.4%) of these
   differentially expressed genes code for known transcription factor
   proteins (see [74]Supplementary Materials Table S3 for list of genes).
   Although the majority (95.3%) of the gene expression changes were small
   (i.e., ranging from a fold change of 1.2–2), the expression of 47 genes
   was changed by greater than two-fold ([75]Table 1).

Table 1.

   Genes with greater than two-fold expression change in fetal liver in
   response to maternal folate depletion ^1,2.
   Gene Symbol Gene Name Ensembl ID Direction of Change Fold Change p
   Value FDR
   Actc1 actin, alpha, cardiac muscle 1 ENSMUSG00000068614 Down 20.5 0.001
   0.379
   Ckm creatine kinase, muscle ENSMUSG00000030399 Down 14.8 0.001 0.379
   Tnnc2 troponin C2, fast ENSMUSG00000017300 Down 14.0 0.015 0.458
   Smpx small muscle protein, X-linked ENSMUSG00000041476 Down 13.4 0.001
   0.379
   Tnni2 troponin I, skeletal, fast 2 ENSMUSG00000031097 Down 9.1 0.016
   0.460
   Actn2 actinin alpha 2 ENSMUSG00000052374 Down 8.6 0.001 0.379
   Atp1b4 ATPase, (Na^+)/K^+ transporting, beta 4 polypeptide
   ENSMUSG00000016327 Down 7.9 0.009 0.443
   Tnnt3 troponin T3, skeletal, fast ENSMUSG00000061723 Down 7.6 0.016
   0.461
   Eno3 enolase 3, beta muscle ENSMUSG00000060600 Down 7.5 0.003 0.379
   Tnni1 troponin I, skeletal, slow 1 ENSMUSG00000026418 Down 7.2 0.008
   0.435
   Myh8 myosin, heavy polypeptide 8, skeletal muscle, perinatal
   ENSMUSG00000055775 Down 6.9 0.024 0.487
   Casq2 calsequestrin 2 ENSMUSG00000027861 Down 6.7 0.001 0.379
   Mybpc1 myosin binding protein C, slow-type ENSMUSG00000020061 Down 6.6
   0.022 0.477
   Myh3 myosin, heavy polypeptide 3, skeletal muscle, embryonic
   ENSMUSG00000020908 Down 6.6 0.015 0.458
   Ldb3 LIM domain binding 3 ENSMUSG00000021798 Down 6.3 0.002 0.379
   Mylpf myosin light chain, phosphorylatable, fast skeletal muscle
   ENSMUSG00000030672 Down 6.1 0.021 0.477
   Sln Sarcolipin ENSMUSG00000042045 Down 6.0 0.017 0.465
   Myl4 myosin, light polypeptide 4 ENSMUSG00000061086 Down 5.4 0.005
   0.407
   Ckmt2 creatine kinase, mitochondrial 2 ENSMUSG00000021622 Down 4.9
   0.007 0.435
   Myot Myotilin ENSMUSG00000024471 Down 4.6 0.014 0.451
   Csrp3 cysteine and glycine-rich protein 3 ENSMUSG00000030470 Down 4.3
   0.017 0.465
   Srl Sarcalumenin ENSMUSG00000022519 Down 4.1 0.005 0.407
   Pgam2 phosphoglycerate mutase 2 ENSMUSG00000020475 Down 3.6 0.015 0.458
   Atp2a1 ATPase, Ca++ transporting, cardiac muscle, fast twitch 1
   ENSMUSG00000030730 Down 3.6 0.042 0.545
   Tnnt1 troponin T1, skeletal, slow ENSMUSG00000064179 Down 3.4 0.023
   0.481
   Sh3bgr SH3-binding domain glutamic acid-rich protein ENSMUSG00000040666
   Down 3.1 0.002 0.379
   Itgb1bp2 integrin beta 1 binding protein 2 ENSMUSG00000031312 Down 2.9
   0.023 0.481
   Cdh11 cadherin 11 ENSMUSG00000031673 Down 2.6 0.012 0.447
   Crh corticotropin releasing hormone ENSMUSG00000049796 Down 2.5 0.036
   0.529
   Fhl1 four and a half LIM domains 1 ENSMUSG00000023092 Down 2.5 0.002
   0.379
   Apobec2 apolipoprotein B mRNA editing enzyme, catalytic polypeptide 2
   ENSMUSG00000040694 Down 2.4 0.009 0.442
   Egfl6 EGF-like-domain, multiple 6 ENSMUSG00000000402 Down 2.4 0.004
   0.395
   Myom1 myomesin 1 ENSMUSG00000024049 Down 2.4 0.029 0.498
   Mlf1 myeloid leukemia factor 1 ENSMUSG00000048416 Down 2.3 0.020 0.476
   Cav2 caveolin 2 ENSMUSG00000000058 Down 2.3 0.001 0.379
   Shh sonic hedgehog ENSMUSG00000002633 Down 2.2 0.019 0.465
   Slit2 slit homolog 2 (Drosophila) ENSMUSG00000031558 Down 2.2 0.003
   0.379
   Rps6ka6 ribosomal protein S6 kinase polypeptide 6 ENSMUSG00000025665
   Down 2.1 0.034 0.526
   Scn7a sodium channel, voltage-gated, type VII, alpha ENSMUSG00000034810
   Down 2.1 0.020 0.476
   Sparcl1 SPARC-like 1 ENSMUSG00000029309 Down 2.1 0.012 0.447
   Nr1h4 nuclear receptor subfamily 1, group H, member 4
   ENSMUSG00000047638 Up 2.0 0.001 0.379
   Pemt phosphatidylethanolamine N-methyltransferase ENSMUSG00000000301 Up
   2.1 0.021 0.477
   Serpine1 serine (or cysteine) peptidase inhibitor, clade E, member 1
   ENSMUSG00000037411 Up 2.1 0.001 0.379
   LOC100503019 hypothetical protein LOC100503019 NA Up 2.5 0.018 0.465
   Cyp2e1 cytochrome P450, family 2, subfamily e, polypeptide 1
   ENSMUSG00000025479 Up 2.7 0.012 0.443
   Asgr1 asialoglycoprotein receptor 1 ENSMUSG00000020884 Up 2.8 0.010
   0.443
   Hamp hepcidin antimicrobial peptide ENSMUSG00000050440 Up 3.3 0.001
   0.379
   [76]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets.

   Whilst gene ontology analysis found no statistically significant
   influence on biological processes, KEGG pathway analysis revealed that
   “Lysosome” and “Tight Junction” pathways were significantly affected in
   the fetal liver in response to maternal folate depletion ([77]Table 2).
   Analysis of WikiPathways using PathVisio found 13 pathways in which a
   significant number of genes had altered expression in the fetal liver
   in response to maternal folate depletion ([78]Table 3).

Table 2.

   KEGG pathways in the fetal liver altered by maternal folate depletion
   during pregnancy ^1.
   KEGG Pathway Term Pathway Name Total Genes on Pathway Number of Altered
   Genes Differentially Expressed Genes p Value
   mmu04142 Lysosome 119 12 Ap3m1 (ENSMUSG00000021824), Gm2a
   (ENSMUSG00000000594) 0.031
   Atp6v0a1 (ENSMUSG00000019302), Naga (ENSMUSG00000022453)
   Arsg (ENSMUSG00000020604), Gba (ENSMUSG00000028048)
   Cd68 (ENSMUSG00000018774), Ap3s2 (ENSMUSG00000063801)
   Gla (ENSMUSG00000031266), Dnase2b (ENSMUSG00000028185)
   Galns (ENSMUSG00000015027), Gaa (ENSMUSG00000025579)
   mmu04530 Tight junction 135 13 Tjp1 (ENSMUSG00000030516), B230120H23Rik
   (ENSMUSG00000004085) 0.033
   Myh3 (ENSMUSG00000020908), Hcls1 (ENSMUSG00000022831)
   Gnai3 (ENSMUSG00000000001), Myh8 (ENSMUSG00000055775)
   Nras (ENSMUSG00000027852), Actn2 (ENSMUSG00000052374)
   Ppp2r1a (ENSMUSG00000007564), Epb4.1l2 (ENSMUSG00000019978)
   Mylpf (ENSMUSG00000030672), Spnb2 (ENSMUSG00000020315),
   Akt2 (ENSMUSG00000004056)
   [79]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively.

Table 3.

   WikiPathways in the fetal liver altered by maternal folate depletion
   during pregnancy ^1,2 and identified using PathVisio.
   Pathway Number of Genes Altered on Pathway Number of Genes Measured on
   Pathway Total Number of Genes on Pathway % Affected Z Score p-Value
   (Permuted)
   Striated Muscle Contraction 16 32 46 50 9.35 <0.001
   Adipogenesis genes 16 111 133 14 2.95 0.005
   Fatty Acid Biosynthesis 5 21 26 24 2.93 0.011
   Iron Homeostasis 3 10 16 30 2.77 0.013
   TGF Beta Signaling Pathway 7 42 53 17 2.36 0.015
   miR-1 in cardiac development 1 2 6 50 2.33 0.029
   One carbon metabolism and related pathways 6 37 86 16 2.11 0.028
   EPO Receptor Signaling 4 21 27 19 2.09 0.038
   Spinal Cord Injury 11 85 110 13 2.04 0.035
   Alanine and aspartate metabolism 2 8 43 25 1.94 0.038
   Methylation 2 8 15 25 1.94 0.045
   Osteoblast 2 8 14 25 1.94 0.040
   [80]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets.

3.3. Influence of Maternal Folate Intake during Pregnancy on Gene Expression
in the Placenta

   In the placenta, 460 genes were differentially expressed (250
   up-regulated and 255 down-regulated) in response to maternal folate
   depletion ([81]Supplementary Materials Table S4). All raw and processed
   microarray data have been deposited in the ArrayExpress database
   (accession ID E-MTAB-3940). Twenty two (4.8%) of these differentially
   expressed genes code for known transcription factor proteins (see
   [82]Supplementary Materials Table S5 for list of genes). Of all the
   genes expressed differentially, only three had a change in expression
   of greater than two-fold ([83]Table 4), with the vast majority (99.4%)
   of changes being small (i.e., ranging from 1.2 to 2 fold change).

Table 4.

   Genes with greater than two-fold expression change in the placenta in
   response to maternal low folate intake ^1,2.
   Gene Symbol Gene Name Ensembl ID Direction of Change Fold Change p
   Value FDR
   Cyp21a1 cytochrome P450, family 21, subfamily a, polypeptide 1
   ENSMUSG00000024365 Down 2.5 0.002 0.999
   Hbb-y hemoglobin Y, beta-like embryonic chain ENSMUSG00000052187 Down
   2.2 0.035 0.999
   Slco1b2 solute carrier organic anion transporter family, member 1b2
   ENSMUSG00000030236 Down 2.1 0.011 0.999
   [84]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets.

   Whilst gene ontology analysis found no statistically significant
   effects on biological processes in placenta, KEGG pathway analysis
   revealed that “Amino sugar and nucleotide sugar metabolism”, “Valine,
   leucine and isoleucine degradation” and “Complement and coagulation
   cascades” pathways were significantly affected in the placenta in
   response to maternal folate depletion ([85]Table 5). Interrogation of
   WikiPathways using PathVisio found 13 pathways which were altered
   significantly in response to maternal folate depletion ([86]Table 6).

Table 5.

   KEGG pathways in the placenta altered by maternal folate depletion
   during pregnancy ^1, 2.
   KEGG Pathway Term Pathway Name Total Genes on Pathway Number of Altered
   Genes Differentially Expressed Genes p Value
   mmu00520 Amino sugar and nucleotide sugar metabolism 44 5 Gnpda2
   (ENSMUSG00000029209), Pgm2 (ENSMUSG00000025791), Uap1
   (ENSMUSG00000026670), Gmppb (ENSMUSG00000070284), Pgm3
   (ENSMUSG00000056131) 0.017
   mmu00280 Valine, leucine and isoleucine degradation 46 5 Mccc2
   (ENSMUSG00000021646), Oxct2a (ENSMUSG00000076436), Hsd17b10
   (ENSMUSG00000025260), Bckdhb (ENSMUSG00000032263), Abat
   (ENSMUSG00000057880) 0.019
   mmu04610 Complement and coagulation cascades 75 6 Cd55
   (ENSMUSG00000026399), Serpina1b (ENSMUSG00000071178), F11
   (ENSMUSG00000031645), F2 (ENSMUSG00000027249), C9 (ENSMUSG00000022149),
   C3 (ENSMUSG00000024164) 0.026
   [87]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets.

Table 6.

   WikiPathways in the placenta altered by maternal folate depletion ^1,2
   during pregnancy and identified using PathVisio.
   Pathway Number of Genes Altered on Pathway Number of Genes Measured on
   Pathway Total Number of Genes on Pathway % Affected Z Score p-Value
   (Permuted)
   Complement Activation, Classical Pathway 3 13 19 23 3.77 0.002
   Statin Pathway 3 16 29 19 3.26 >0.000
   Alanine and aspartate metabolism 2 8 43 25 3.25 0.007
   Glucocorticoid & Mineralocorticoid Metabolism 2 9 27 22 3 0.016
   Selenium metabolism/Selenoproteins 3 18 49 17 2.98 0.015
   Alzheimers Disease 6 54 91 11 2.98 0.006
   Nuclear Receptors 4 31 38 13 2.79 0.015
   Glucuronidation 2 10 33 20 2.78 0.012
   Arachidonate Epoxygenase Epoxide Hydrolase 1 3 13 33 2.76 0.037
   Polyol pathway 1 3 12 33 2.76 0.024
   Complement and Coagulation Cascades 5 54 64 9 2.24 0.015
   Acetylcholine Synthesis 1 5 18 20 1.97 0.050
   Aflatoxin B1 metabolism 1 5 11 20 1.97 0.037
   [88]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets.

3.4. Comparison of Gene Expression Changes in the Placenta and Fetal Liver in
Response to Maternal Folate Depletion

   More genes in the fetal liver than in the placenta had altered
   expression in response to maternal folate intake during pregnancy (n =
   989 and 460 respectively). Only 25 genes were common to the data-sets
   for fetal liver and placenta (see [89]Table 7 for gene list). The
   expected overlap between two random subsets with elements of 989 and
   460 respectively picked from a set of 16270 elements (the total number
   of measured genes) is 28, hence the observed overlap of 25 genes is
   likely due to chance. Of the genes found to respond to maternal folate
   in both placenta and fetal liver, only four displayed the same
   direction of change in both organs, with 21 showing the opposite
   direction of change ([90]Figure 1), which suggests that finding
   expression changes in the same genes in the two organs may be due to
   chance.

Table 7.

   Genes differentially expressed in both fetal liver and placental organs
   in response to maternal folate depletion ^1,2,3.
   Gene Symbol Ensembl ID Expression fold Change in Fetal Liver p Value
   for Fetal Liver Expression Fold Change in Placenta p Value for Placenta
   A830035A12RIK NA 1.5 0.025 −1.5 0.019
   Aadat ENSMUSG00000057228 −1.3 0.033 −1.3 0.031
   Akr7a5 ENSMUSG00000028743 1.2 0.023 −1.3 0.003
   Apon ENSMUSG00000051716 1.4 0.019 −1.4 0.021
   Atp6v0a1 ENSMUSG00000019302 1.2 0.028 −1.3 0.007
   Atrnl1 ENSMUSG00000054843 −1.3 0.013 1.3 0.008
   Bcas3 ENSMUSG00000059439 1.2 0.034 −1.2 0.035
   Col15a1 ENSMUSG00000028339 −1.3 0.013 −1.2 0.029
   Cyld ENSMUSG00000036712 −1.3 0.030 1.3 0.024
   E130309D02RIK ENSMUSG00000039244 1.2 0.015 −1.2 0.027
   Fkbp8 ENSMUSG00000019428 1.2 0.045 −1.3 0.020
   Inpp1 ENSMUSG00000026102 1.2 0.019 −1.2 0.026
   Itgb4 ENSMUSG00000020758 1.3 0.027 −1.2 0.039
   Med6 ENSMUSG00000002679 −1.4 0.009 1.3 0.029
   Nubpl ENSMUSG00000035142 1.6 0.014 1.5 0.040
   Oxct2a ENSMUSG00000076436 −1.3 0.024 1.5 0.004
   Pgm3 ENSMUSG00000056131 1.2 0.045 −1.3 0.028
   Prtg ENSMUSG00000036030 1.3 0.026 1.2 0.048
   Rbp2 ENSMUSG00000032454 1.5 0.036 −1.9 0.001
   Sepx1 ENSMUSG00000075705 1.2 0.040 −1.3 0.026
   Slc13a3 ENSMUSG00000018459 1.6 0.003 −1.4 0.018
   Slc39a5 ENSMUSG00000039878 1.4 0.049 −1.4 0.037
   Slc48a1 ENSMUSG00000081534 1.3 0.012 −1.2 0.041
   Slc6a13 ENSMUSG00000030108 1.3 0.021 −1.2 0.048
   Tomm40 ENSMUSG00000002984 1.4 0.021 −1.5 0.001
   [91]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets; ^3 A negative fold change indicates
   lower expression in offspring from dams fed the Low folate diet.

Figure 1.

   [92]Figure 1
   [93]Open in a new tab

   Scatterplot summarising the direction and level of fold change in
   expression of genes which were altered in both fetal liver and placenta
   by maternal folate depletion ^1,2,3. ^1 The Low and Normal folate diets
   contained 0.4 and 2.0 mg folic acid/kg diet respectively; ^2 For each
   comparison, data were obtained from three male fetuses from each of six
   litters from dams fed either the Low or Normal folate diets; ^3 A
   negative fold change indicates lower expression in offspring from dams
   fed the Low folate diet.

   No common KEGG pathways were significantly influenced by maternal
   folate intake in both the liver and placenta ([94]Table 2 and [95]Table
   5). Use of PathVisio to interrogate WikiPathways revealed that “Alanine
   and aspartate metabolism” may be altered in both the fetal liver and
   the placenta of offspring of folate depleted mothers ([96]Table 3 and
   [97]Table 6). However, different genes in the pathway were
   differentially expressed in response to maternal folate depletion in
   the two tissues. In the fetal liver Agxt and Pcx were up-regulated in
   response to maternal folate depletion, whilst in the placenta Abat and
   Asl were down regulated.

3.5. Validation of Gene Expression Data from Array Analysis by RT-qPCR
Analysis

   For a subset of genes from both liver and placenta which showed altered
   expression in response to maternal folate depletion using microarray
   analysis, data were validated by RT-qPCR. For fetal liver, where the
   largest fold changes in response to maternal folate depletion were
   found in down regulated genes, we selected the four most down regulated
   genes i.e., Actc1, Ckm, Tnn2 and Smpx. In addition, we analysed the two
   most up regulated genes i.e., Hamp and Asgr1. All genes showed the same
   direction of change using both methods ([98]Table 8) but for 5/6 genes
   measured by RT-qPCR the change in expression was not statistically
   significant.

Table 8.

   RT-qPCR expression analysis of selected genes which were differentially
   expressed in fetal liver in response to maternal folate depletion ^1,2
   when assayed by microarray.
   Gene Name Mean Expression Low Folate Group SEM Mean Expression Normal
   Folate Group SEM p Value Direction of Change in Agreement with Array
   Asgr1 0.35 0.07 0.12 0.07 0.050 Yes
   Hamp 4.00 0.75 1.73 0.75 0.058 Yes
   Actc1 3.63 3.04 8.29 3.04 0.305 Yes
   Ckm 1.12 0.95 3.30 0.95 0.134 Yes
   Tnnc2 0.51 0.66 2.39 0.66 0.073 Yes
   Smpx 0.11 0.09 0.38 0.09 0.066 Yes
   [99]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diets. Expression values are in arbitrary
   units calculated using the delta CT method; GAPDH was used as the
   reference gene. Expression levels were quantified in individual fetuses
   (n = 18 per group) with mean expression levels calculated for
   individuals litters (n = 6 per group) for use in statistical analyses
   to match procedures used for array data.

   For placenta, fold changes in expression for up- and down-regulated
   genes in response to maternal folate depletion were similar and so the
   three genes with the largest fold changes in each direction were
   selected for validation analysis i.e., Cyp21a1, Hbb-y and Slco1b2 for
   down-regulated genes and Ptgs2, Vcan and Lrrn4 for up-regulated genes.
   In addition, a gene of particular interest, Mettl7b, was also selected
   for RT-PCR analysis. This gene encodes the protein
   methyltransferase-like 7B, and is likely to have methyltransferase
   activity (inferred through sequence similarity with other protein
   methyltransferases ([100]http://www.uniprot.org/uniprot/Q6UX53)), and
   thus may have a role in epigenetic regulation of gene expression. All
   seven genes showed the same directional changes in expression in
   response to maternal folate depletion when assayed by RT-qPCR and by
   microarray but for 6/7 genes measured by RT-qPCR the change in
   expression was not statistically significant ([101]Table 9).

Table 9.

   RT-qPCR expression analysis of selected genes which were differentially
   expressed in placenta in response to maternal folate depletion ^1,2
   when assayed by microarray. Expression values are in arbitrary units
   calculated using the delta cycle threshold (CT) method. GAPDH was used
   as the reference gene. Expression levels were quantified in individual
   fetuses (n = 18 per group) with mean expression levels calculated for
   individuals litters (n = 6 per group) for use in statistical analyses
   to match procedures used for array data.
   Gene Name Mean Expression Low Folate Group SEM Mean Expression Normal
   Folate Group SEM p Value Direction of Change in Agreement with Array
   Cyp21a1 0.55 0.13 0.88 0.13 0.118 Yes
   Hbb-y 0.39 0.16 0.83 0.16 0.076 Yes
   Slco1b2 0.29 0.08 0.49 0.08 0.106 Yes
   Ptgs2 0.31 0.03 0.22 0.03 0.030 Yes
   Vcan 0.66 0.09 0.46 0.09 0.144 Yes
   Lrrn4 0.05 0.01 0.03 0.01 0.118 Yes
   Mettl7b 3.07 0.61 4.83 0.61 0.068 Yes
   [102]Open in a new tab

   ^1 The Low and Normal folate diets contained 0.4 and 2.0 mg folic
   acid/kg diet respectively; ^2 For each comparison, data were obtained
   from three male fetuses from each of six litters from dams fed either
   the Low or Normal folate diet.

3.6. Comparison of Gene Expression Changes in Fetal Liver in Response to
Maternal Folate Depletion with Similar Published Transcriptomic Studies

   Previous studies have reported gene expression changes at the
   transcriptomic level in the liver of rodents in response to diets low
   in folate [[103]33,[104]34,[105]35]. Although several aspects of design
   differ between studies (summarised in [106]Table 10), to identify a key
   set of genes in the liver that respond to changes in folate intake (or
   more broadly, changes in one carbon metabolism), we compared reported
   changes in gene expression between our data and three other studies
   [[107]33,[108]34,[109]35]. Of the 989 genes which were differentially
   expressed in the fetal liver in response to maternal folate depletion
   in our study, 4, 89, 90 and 239 genes were also found to be
   differentially expressed in CBA mice, BALB/c mice, CBA/Ca mice and
   Wistar rats respectively [[110]33,[111]34,[112]35] (full list of these
   genes for individual studies are in [113]Supplementary Materials Table
   S6). Comparison of the differentially expressed genes from all studies
   revealed a set of 21 key genes whose expression was affected by altered
   folate/methyl donor intake in at least four of the five data sets (see
   [114]Table 11). Importantly, none of the 25 genes which we found were
   expressed differentially in both fetal liver and placenta in response
   to maternal folate depletion are in this list of 21 genes.

Table 10.

   Overview of experimental designs of studies investigating the influence
   of folate/methyl donor intake on genome wide gene expression in the
   liver.
   Study Model Diets Period of Exposure Arrays
   This study Male C57Bl6J mice 2 mg folic acid/kg OR 4 weeks prior to
   mating to 17.5 days gestation NuGO mouse array (NuGO_Mm1a520177)
   0.4 mg folic acid/kg
   Champier et al. [[115]33] Male CBA mice 8 mg folic acid + 10 g of
   succinylsulfathiazole/kg OR 8–12 weeks of age CodeLinkUniset Mouse
   Whole Genome bioarrays
   0 mg folic acid + 10 g of succinylsulfathiazole/kg
   Glen et al. [[116]35] Male BALB/c & CBA/Ca mice Low methionine (0.18%,
   w/w) & lacking choline & folic acid OR 4–12 weeks of age NimbleGen 12 ×
   135 K Mouse Expression Array
   Low methionine (0.18%, w/w) & supplemented with choline & folic acid
   Chen et al. [[117]34] Wistar rats Standard food OR 1 month before
   pregnancy to 21 days post-weaning Agilent Arrays
   Diet without vitamin B[12] & folate
   [118]Open in a new tab

Table 11.

   Genes which were differentially expressed in response to low dietary
   folate/methyl donor intake in the liver across multiple studies ^1.
   Gene Differentially Expressed
   Gene Symbol McKay et al. Champier et al. [[119]33] Glen et al.
   [[120]35] (BALB/c Mice) Glen et al. [[121]35] (CBA/Ca Mice) Chen et al.
   [[122]34]
   ACOT2 Y N Y Y Y
   COL6A2 Y N Y Y Y
   CSTB Y N Y Y Y
   DCTD Y N Y Y Y
   ENTPD2 Y N Y Y Y
   FETUB Y N Y Y Y
   FGF21 N Y Y Y Y
   IL7R Y N Y Y Y
   JUB Y N Y Y Y
   LTBP2 Y N Y Y Y
   OXCT1 Y N Y Y Y
   RHBDF1 Y N Y Y Y
   RUNX3 Y N Y Y Y
   SERPINE1 Y N Y Y Y
   SLC15A3 Y N Y Y Y
   SLC30A10 Y N Y Y Y
   SLC39A5 Y N Y Y Y
   SLC41A3 Y N Y Y Y
   SLPI Y N Y Y Y
   SORCS2 Y N Y Y Y
   TMIE Y N Y Y Y
   [123]Open in a new tab

   ^1 For details of diet compositions, please see [124]Table 10. Y = Yes;
   N = No.

3.7. In Silico Analysis of Promoter Regions of Key Folate/Methyl Donor
Responsive Genes for Transcription Factor Binding Sites

   For these 21 genes found to be affected robustly in liver by altered
   folate supply ([125]Table 11), 76 unique promoter regions were found
   for 130 transcripts using the Gene2Promoter function in Genomatix (data
   not shown). Transcription factor binding sites for five families of
   transcription factors were present in 90% of the promoters
   investigated; ETS1 factors (ETSF), Kruppel like transcription factors
   (KLFS), Nuclear receptor subfamily 2 factors (NR2F), RXR heterodimer
   binding site (RXRF) and SOX/SRY sex/testis determining and related HMG
   box factors (SORY). Of these, the RXRF transcription factors had
   binding sites in all 76 analysed promoters. TFs belonging to the five
   identified families were compared with TFs found to be differentially
   expressed in the fetal liver and five TFs were found to overlap viz.
   Elk3, Nr2c1, Nr2f1, Rxra, and Sox30.

   However the same analysis on randomly-selected sets of 21 genes that
   were affected by folate supply from each of the five studies plus two
   sets of 21 genes that did not respond to maternal folate supply
   revealed similar occurrence rates for these same transcription factor
   binding sites. Thus, this analysis identified no potential
   transcriptional regulatory mechanisms which may be responsible
   exclusively for coordinating the liver-specific changes in expression
   of these key genes in response to folate supply.

4. Discussion

   Here we describe gene expression changes at the transcriptome level in
   the placenta and fetal liver in response to maternal folate depletion
   before mating and throughout pregnancy. Ames’ triage theory posits that
   if availability of a specific nutrient is inadequate, Darwinian
   processes ensure that essential functions, i.e., those required for
   short-term survival and/or reproduction, dependent on that nutrient
   that are protected at the expense of those functions that are less
   essential i.e., where reduced function does not have short term
   negative consequences. However, such prioritisation of some most
   critical (short-term) functions may impact adversely on other functions
   which may have long-term insidious effects that increase risk of
   diseases associated with ageing [[126]23,[127]24]. In response to
   inadequate maternal folate intake during pregnancy, we hypothesised
   that, due to different organ-specific functions, individual fetal
   organs would implement differential prioritisation hierarchies and thus
   display differential gene expression changes in response to folate
   depletion. We chose to investigate gene expression in the liver and
   placenta as examples of organs with very different roles in mammalian
   function across the lifecourse. In addition, the liver represents a
   major site for folate storage and metabolism, whilst the placenta
   (containing both maternal and fetal cells) is the route for delivery of
   nutrients (including folate) from the dam to the fetus during
   development. Our observations support our hypothesis that specific
   fetal organs exhibit specific transcriptional responses to maternal
   folate depletion. It is plausible that these organ-specific changes in
   gene expression are due to differential pathway prioritisation in each
   organ which reflect their contrasting functions.

   The primary function of the placenta is the transfer of nutrients to
   the fetus, so it is essential that this function is protected to
   support fetal growth and development. In response to maternal folate
   depletion, we saw no changes in pathways associated with nutrient
   transport, suggesting that placental transfer of nutrients to the fetus
   was protected despite the reduced maternal folate intake. We observed
   no teratogenic effects of this reduced nutrient supply on the offspring
   [[128]25]. It is important to note that we analysed whole placental
   samples containing both maternal and fetal cell populations and so we
   are unable to determine the cellular origin of the observed expression
   changes.

   The liver is a highly metabolic organ responsible for a wide range of
   functions that are important at all life stages and include defence of
   the body against xenobiotics, assisting with digestion and with
   metabolism of absorbed nutrients, regulating blood lipids, synthesis of
   a wide range of secreted proteins and hormonal regulation. As such,
   during periods of undernutrition, it may not be possible for the liver
   to maintain all important functions, so that those functions essential
   for short-term survival and/or reproduction may be prioritised. The
   sequela is that some functions not critical for short-term survival but
   which are important for long term health may be de-prioritised leading
   to impaired function which may have significant long-term adverse
   effects for the organism. We observed that maternal folate depletion
   altered several processes and pathways, each of which could impact
   adversely on long-term liver function and organismal health. These
   included “adipogenesis genes”, “fatty acid biosynthesis” and “iron
   homeostasis” pathways. Whilst only one time point was investigated here
   (so that we are unable to comment on long-term gene expression changes
   or phenotypic outcomes), these observations are consistent with the
   fact that diets deficient in folate and choline can induce
   non-alcoholic fatty liver disease (NAFLD) in rodent models [[129]36].
   We observed up-regulation of genes involved in “fatty acid
   biosynthesis” (5/5 differentially expressed genes present on the
   pathway), and an abundance of up-regulated genes involved in the
   “adipogenesis genes” pathway (10/16 differentially expressed genes
   present on the pathway). Up-regulation of these genes may result in
   overall up-regulation of the pathways that potentially could result in
   altered hepatic fatty acid metabolism in offspring. Indeed, we observed
   that when the offspring of folate depleted dams were fed a high fat
   diet from weaning [[130]37], they had significantly increased plasma
   triacylglycerol (TAG) concentrations whilst plasma TAG concentrations
   were unaffected in the offspring of folate replete dams [[131]37].
   Taken together, these data suggest that maternal folate depletion
   results in an altered response to high fat feeding which may be via
   programmed transcriptional changes in pathways associated with fat
   metabolism in the liver.

   This analysis has focussed on the genes which were differentially
   expressed in the liver and in the placenta in response to maternal
   folate depletion. However, it is important to recognise that there are
   alternative explanations for genes which did not change in response to
   this nutritional insult. Whilst such unaltered genes may be components
   of pathways which are especially critical to that particular organ, it
   is also possible that these genes are simply unresponsive to folate
   supply. The present study design is unable to distinguish between these
   alternatives.

   It is important to highlight that most of the gene expression changes
   observed in this study were relatively small and not statistically
   significant when applying the more stringent FDR value so that these
   data should be interpreted with caution. However, our observations are
   consistent with findings from other studies [[132]33,[133]34] and
   confirms the subtle, but pervasive, effects on gene expression of
   folate/methyl donor depletion. Furthermore, it is pertinent to point
   out that our gene expression studies were undertaken in male offspring
   only and it is possible, if theoretically unlikely, that effects could
   be different in females.

   Whilst we show clearly that folate responsive gene expression changes
   are organ specific, the mechanisms behind the observed organ specific
   expression changes are less clear. A plausible mechanistic explanation
   could be based on inter-organ differences in expression of
   transcription factors (TFs) when exposed to inadequate folate intake.
   We tested this hypothesis by identifying all TFs which were
   differentially expressed in the liver and in the placenta in response
   to maternal folate depletion. In the fetal liver, we found that
   expression of 73 TFs differed in folate replete vs. folate depleted
   offspring, which accounted for 7.4% of the altered genes. In contrast,
   in the placenta only 22 TFs (4.8% of altered genes) displayed altered
   expression. Consistent with the idea that organ-specific changes in
   gene expression profiles are driven by organ-specific changes in TF
   expression, there was very little overlap between the TFs that were
   altered in liver and placenta—only one TF, Med6, was common between the
   organs.

   It is plausible that changes in epigenetic processes are responsible
   for the organ-specific patterns in gene expression in response to
   folate depletion. Epigenetic marks, including DNA methylation, are
   modifiable by diet and other environmental factors and constitute an
   important and flexible system for regulating gene expression
   [[134]38,[135]39]. Folate is central to one-carbon metabolism and the
   formation of the universal methyl donor SAM, which is critical for the
   methylation of biological molecules including DNA. Indeed the influence
   of dietary folate intake on DNA methylation patterns has been reported
   widely [[136]25,[137]34,[138]40,[139]41,[140]42] and may be responsible
   for the organ specific folate responsive gene expression changes
   observed here.

   Although previous studies have reported gene specific expression
   changes in the rat placenta in response to increased levels of folate
   in the maternal diet [[141]42,[142]43], to the best of our knowledge
   this is the first report describing gene expression changes in response
   to low maternal folate (or methyl donor) intake in this organ, and the
   first study to investigate this at the transcriptomic level. However,
   previous studies have used transcriptomic approaches to investigate
   gene expression changes in the liver in response to low
   folate-containing diets
   [[143]33,[144]34,[145]35,[146]36,[147]44,[148]45] so we compared our
   data with outcomes from these studies. Whilst there were differences in
   gene expression profiles between studies, likely to be due to
   differences in rodent models, diet composition, duration and timing of
   the nutrient insult and the particular transcriptomic approaches
   employed ([149]Table 10), we uncovered a key set of genes which were
   differentially expressed in the liver in response to low dietary
   folate/methyl donor intake across multiple studies ([150]Table 11).
   Importantly, expression of none of these genes was altered in placenta
   by maternal folate depletion, indicating that these changes reflect a
   liver-specific response rather than being genes that are generally
   malleable in response to perturbation in folate supply. Moreover, this
   observation substantiates our suggestion that the transcriptome
   responses of fetal liver and placenta to folate restriction are
   distinct and physiologically-appropriate. Of the key set of 21 genes
   differentially expressed across multiple studies ([151]Table 11), the
   use of DAVID [[152]32] to carry out Gene Ontology enrichment analysis
   suggested that three genes are involved in wound healing i.e., JUB,
   ENTPD2 and SERPINE1 and, thus, altered transcription of genes
   associated with wound healing may help explain the observed association
   between low methyl donor intake and liver damage [[153]36].
   Furthermore, the discovery of these key folate responsive genes may
   provide candidate biomarkers for future studies of folate adequacy.
   Such studies should test the effects of different doses of folate
   without potential confounding from other dietary factors which may have
   been an issue in some of the studies included in [154]Table 10.

   To investigate potential mechanisms through which expression of these
   key genes in the liver are altered in response to methyl donor intake,
   the promoter regions were interrogated for the presence of common
   transcription factor binding sites. Whilst binding sites for five
   families of transcription factors were found to be highly represented
   in the promoters of these 21 genes, similar occurrence rates of these
   same transcription factor binding sites were also observed when seven
   randomly selected sets of genes were analysed. This suggests that this
   specific set of TFs is not responsible for co-ordinating
   transcriptional responses to maternal folate/methyl-donor supply in the
   liver. However, it is possible that there are regulatory regions
   outside the promoters of the genes investigated here which would merit
   investigation in future studies.

5. Conclusions

   The data presented here suggest that maternal folate status during
   pregnancy influences gene expression in the fetus in a highly
   organ-specific manner. We hypothesise that this organ specificity is a
   rational response to limited nutrient supply which protects the most
   essential functions of each individual organ for short term survival
   (and reproduction), at the expense of less immediately essential
   processes which may lead to long-term adverse health sequelae. However,
   as we have noted above, there are viable alternative explanations for
   our observations. Our observations are consistent with the DOHaD
   hypothesis and suggest a plausible mechanism by which inadequate folate
   supply during early development leads to changes in gene expression to
   protect functions of the liver that are appropriate in this particular
   developmental and nutritional context, but that may contribute to the
   aetiology of cardiometabolic diseases if the postnatal environment is
   such that these changes become disadvantageous.

Acknowledgments