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RESEARCH ARTICLE
Transgenerational Effects of Bisphenol A on Gene
Expression and DNA Methylation of Imprinted
Genes in Brain
Zuzana Drobn ´a,
1
* Anne D. Henriksen,
2
* Jennifer T. Wolstenholme,
3
*
Catalina Montiel,
1
Philip S. Lambeth,
3
Stephen Shang,
3
Erin P. Harris,
3
Changqing Zhou,
4
Jodi A. Flaws,
4
Mazhar Adli,
3
and Emilie F. Rissman
1
1
Center for Human Health and the Environment and Department of Biological Sciences, North Carolina State
University, Raleigh, North Carolina 27695;
2
Department of Integrated Science and Technology, MSC 4102,
James Madison University, Harrisonburg, Virginia 22807;
3
Department of Biochemistry and Molecular
Genetics, University of Virginia School of Medicine, Charlottesville, Virginia 22903; and
4
Department of
Comparative Biosciences, University of Illinois, Urbana, Illinois 61802
Bisphenol A (BPA) is a ubiquitous man-made endocrine disrupting compound (EDC). Developmental
exposure to BPA changes behavioral and reproductive phenotypes, and these effects can last for
generations. We exposed embryos to BPA, producing two lineages: controls and BPA exposed. In the
third filial generation (F3), brain tissues containing the preoptic area, the bed nucleus of the stria
terminalis, and the anterior hypothalamus were collected. RNA sequencing (RNA-seq) and sub-
sequent data analyses revealed 50 differentially regulated genes in the brains of F3 juveniles from
BPA vs control lineages. BPA exposure can lead to loss of imprinting, and one of the two imprinted
genes in our data set, maternally expressed gene 3 (Meg3), has been associated with EDCs and
neurobehavioral phenotypes. We used quantitative polymerase chain reaction to examine the two
imprinted genes in our data set, Meg3 and microRNA-containing gene Mirg (residing in the same
loci). Confirming the RNA-seq, Meg3 messenger RNA was higher in F3 brains from the BPA lineage
than in control brains. This was true in brains from mice produced with two different BPA para-
digms. Next, we used pyrosequencing to probe differentially methylated regions of Meg3.We
found transgenerational effects of BPA on imprinted genes in brain. Given these results, and data on
Meg3 methylation in humans, we suggest this gene may be a biomarker indicative of early life
environmental perturbation. (Endocrinology 159: 132–144, 2018)
Endocrine disrupting compounds (EDCs) are man-
made chemicals used to produce a large variety of
daily-use materials ranging from linings of food cans
to cosmetics and flame retardants. EDCs have enough
structural and electrostatic similarity to steroid hormones
that they are able to interfere with normal hormonal
signaling. Bisphenol A (BPA) is the most widespread of
the EDCs and is detected in .92% of the US population
(1). Experimental studies of BPA are based largely on the
fetal origins of adult disease hypothesis (2). Dams are
dosed with BPA, which also exposes developing embryos,
and dosing is often extended into lactation (3). The ex-
perimental subjects are the offspring, which are examined
as adults. In addition to effects on the first filial generation
(F1) offspring, BPA has transgenerational actions on
subsequent generations (4–6). When multigenerational
or transgenerational effects have been found, particularly
in studies using low doses of EDCs, it has been assumed
ISSN Online 1945-7170
Copyright © 2018 Endocrine Society
Received 8 August 2017. Accepted 14 November 2017.
First Published Online 17 November 2017
*These three authors contributed equally to this publication.
Abbreviations: ANT HT, anterior hypothalamus; B2M, b
2
microglobulin; BNST, bed nu-
cleus of the stria terminalis; BPA, bisphenol A; cDNA, complementary DNA; CpG,
50
–C–phosphate–G–30; DE, differential expression; DMR, differentially methylated region;
EDC, endocrine disrupting compound; F0, female FVB mice; F1, first filial generation; F2,
second filial generation; F3, third filial generation; IG-DMR, intergenic differentially
methylated region; lfc, log-fold change; lncRNA, long non-coding RNA; Meg3, maternally
expressed gene 3; mRNA, messenger RNA; PN, postnatal day; POA, preoptic area; qPCR,
quantitative polymerase chain reaction; RNA-seq, RNA sequencing.
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that epigenetic modifications are responsible for changes
in gene expression (7).
The first transgenerational study using BPA exposure
to F1 embryos in utero revealed reduced fertility in the
third filial generation (F3) of male rats (8, 9). More re-
cently, in female mice, fertility decline has been recorded
in F1, second filial generation (F2), and F3 exposed to
BPA (6). The fact that some phenotypes persisted into the
F3 makes them truly transgenerational. A mixture
of phenotypes including obesity, infertility, and kidney
disease were observed in F3 rats exposed ancestrally to a
combination of BPA and two phthalates (10). In rats and
mice, early life exposure to low doses of BPA affects many
behaviors, including increased anxiety (11, 12), changes
in activity (13), and reductions in some social behaviors
(4, 14–17). Some of the differences in social behaviors
persist in offspring for up to four generations, making
them transgenerational (4, 17).
Here, we asked which genes in the brain are changed
transgenerationally by gestational exposure to BPA in the
F3 generation. Work with the antifungal agent vinclo-
zolin has shown changes in gene expression in F3 rats in
several brain areas (5). In the current study, female mice
consumed BPA incorporated into a phytoestrogen-free
diet, whereas controls received the same diet without
BPA. Nonsibling F1 adults were bred to produce the
F2 generation, which were used to produce F3 mice.
Changes found in the F3 generation are presumably
transmitted via the germline and are likely to be per-
manent (18, 19). Using this paradigm, we have previously
shown transgenerational differences between BPA and
control lineages in behavior, targeted gene expression,
and immunocytochemistry for estrogen receptor a(4,
17, 20).
Brains from males in the F3 lineages were used for
RNA sequencing (RNA-seq). We probed tissue from the
combined preoptic area (POA), bed nucleus of the stria
terminalis (BNST), and anterior hypothalamus (ANT
HT). Because past studies have demonstrated multigen-
erational effects of BPA on imprinted genes (21, 22), we
selected the two imprinted genes in our data set (from the
Dlk1 to Dio3 domain) for subsequent analysis. One of
these genes, maternally expressed gene 3 (Meg3), func-
tions as a tumor suppressor (23, 24) and has been
implicated in neurobehavioral problems (25, 26). In
humans, changes in Meg3 DNA methylation have been
associated with lead exposure, and in mice, methoxyclor
modifies Meg3 methylation in sperm (27, 28). Precocious
puberty onset in rats is correlated with Meg3 expression
in brain (29). Meg3 RNA is expressed in the brain and
pituitary (30, 31). Thus, changes in Meg3 expression
could have transgenerational actions on behavior and
reproduction via either the brain–pituitary–gonadal axis
or the brain–pituitary–adrenal axis. The functions of
Mirg are not known.
Real-time quantitative polymerase chain reaction
(qPCR) was used to measure expression of these genes in
brains of F3 mice of both sexes, of several ages, and in two
different mouse strains (C57BL/6J and FVB). Moreover,
in addition to the C57BL/6J mice we used FVB mice
bred such that females from the BPA lineage mated with
unexposed males in each generation (6). This mating
scheme (Fig. 1) ensures that transgenerational effects are
transmitted via the dam. Finally, we examined DNA
Figure 1. Cartoons illustrating the two breeding schemes used in
the study. Dams are indicated by pink bows. BPA-exposed mice are
indicated by gray color. (A) C57BL/6J black mice were paired, and
half of the females (on left) were exposed to BPA in diet (gray
mice). The subsequent generations were not exposed to additional
BPA but were mated to each other to produce the BPA lineage.
Black mice (right) were not exposed to BPA and served as the
control lineage. (B) White FVB mice were paired, and half the
pregnant females were fed BPA daily from embryonic day 11 to
birth (left). The subsequent generations of females were mated
with unexposed males (white). Control white mice (right) were
not exposed to BPA.
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methylation for some of the 50–C–phosphate–G–30(CpG)
sites in the intergenic region of the Dlk1 to Dio3 domain’s
intergenic differentially methylated region (IG-DMR)
and the promoter of Meg3 differentially methylated re-
gion (DMR) in F3 brains. None of the CpG sites ex-
amined were significantly differentially methylated based
on ancestral BPA status, and we conclude that other
epigenetic mechanisms are involved in transgenerational
modifications in Meg3 expression in brain.
Methods and Materials
Animals
The C57BL/6 mice used were progeny of mice purchased
from the Jackson Laboratory (stock no. 000664; Bar Harbor,
ME). Adult females (between 8 and 10 weeks of age) were
randomly assigned to either a phytoestrogen-free chow (Harlan
Teklad, Madison, WI; catalog no. TD95092) or the identical
chow supplemented with 5 mg/kg BPA diet (Harlan Teklad;
catalog no.TD09386). Mice were placed on the diet 10 days
before pairing with males for 2 weeks. All mice consumed food
and water ad libitum; dams continued on their diets throughout
gestation. During the dosing period, mice were observed daily
for abnormal behavior and signs of toxicity. Lights were on a
12:12 light/dark cycle (lights off at 1200). We have previously
calculated that pregnant C57BL/6J mice consume ~20 mg BPA
per day at this dose and that their blood levels of BPA are within
the range of those found in humans (17). As in our previous
studies (4, 17), all F1 offspring were fostered within 24 hours of
birth to dams on the control diet. Foster dams retained two
of their own pups (these mice were not used in our studies)
and received four foster pups (two of each sex). At weaning,
postnatal day (PN) 21, mice were placed on standard chow
(Harlan Teklad Diet; catalog no. 7912) containing phytoes-
trogens and group housed by litter and sex. Adult F1 males and
females (nonsiblings) were mated to produce F2 mice, and these
were mated to produce the F3 generation (Fig. 1A).
Next, we asked whether our findings in C57BL/6J mice could
generalize to other strains of inbred mice and different BPA
transgenerational paradigms. We conducted an experiment
with a second inbred strain, FVB (Charles River, Wilmington,
MA). All mice received food (Harlan Teklad Rodent Diet
containing phytoestrogens; catalog no. 8604) and water ad
libitum. Using an outcrossed design (Fig. 1B), we mated female
FVB mice (F0) with control male FVB mice at 12 weeks of age.
When pregnancy was confirmed by the appearance of a vaginal
sperm plug, females were removed from the males and in-
dividually caged. Here, BPA exposure was limited to the ma-
ternal line; sires in each generation of mating were unexposed.
From embryonic day 11 to birth, female mice were orally dosed
once daily in the early part of the lights-on phase of the 12:12
light/dark cycle with tocopherol-stripped corn oil containing
one of three doses (0.5, 20, or 50 mg/kg body weight per day) or
no BPA. Mice voluntarily consumed the corn oil administered
in a pipette in the corner of their mouth (6, 32). All of these BPA
doses are lower than the dose used in the experiments with
C57BL/6J mice. During the dosing period, mice were observed
daily for abnormal behavior and signs of toxicity. The F1 fe-
males were used to generate F2 females, and in turn, F2 females
were used to generate F3 females (Fig. 1B). In these experiments,
control and BPA-exposed F1 and F2 females were mated with
fertility-confirmed, nonexposed males to generate the next
generation. All procedures were in compliance with and ap-
proved by the University of Virginia, University of Illinois, or
the North Carolina State University Animal Care and Use
Committees.
Brain collection and tissue punches
For the RNA-seq, qPCR, and DNA methylation studies mice
were euthanized, and brains were rapidly removed and frozen in
powdered dry ice. From PN28 mice, we collected one piece of
tissue that contained the BNST, the POA, and the ANT HT.
Brains were cut (120 mM) in a cryostat (H/I Bright OTF5000;
Hacker Instruments, Huntingdon, England) in the coronal
plane, and tissue punches were collected as we have previously
described (33). None of the mice had been used in behavioral
studies. No more than one mouse of each sex per litter was used
for each experiment.
To collect RNA from PN0 pups, brains were removed and
cut free-hand, and hypothalamus was collected and frozen. On
PN4, F3 pups were euthanized, and whole brains were collected
for use in the gene expression analyses described below.
RNA-seq and analysis
RNA from the BNST, POA, and ANT HT of each mouse
(three males each from F1 and F3 controls and three each from
F1 and F3 BPA lineages) was sent to Expression Analysis
(Durham, NC) for sequencing. Poly-A tailed messenger RNA
(mRNA) and long non-coding RNA (lncRNA) were extracted
and quality tested. Complementary DNA (cDNA) was syn-
thesized from the purified RNA and amplified and sequenced on
an Illumina Hi-SEquation 2000. Between 30.7 and 46.7 million
50-base-pair paired-end reads were obtained for each of the 12
samples. The fragment size was ~175 base pairs, leaving ~75
bases between the paired-end reads unsequenced. We restricted
this analysis to males to include genes from both sex
chromosomes.
The results of the RNA-seq were made available by Ex-
pression Analysis as 24 FASTQ files; one set of paired-end reads
for each of the 12 RNA samples. The FASTQ files contained the
read base calls and their associated Phred quality scores. Av-
erage Phred quality scores were .35 for all samples (34). The
FASTQ files were inspected for individual base call quality and
trimmed by one base. The quality-trimmed FASTQ files were
then aligned to the mm9 mouse reference genome, and then
those aligned reads were assigned to genes and quantified.
Differential expression (DE) analysis was then done to de-
termine which genes were differentially expressed between
treatment and controls in both the F1 and F3 generations. Only
the intersections of the genes from the results of two analysis
approaches are presented here. Complete F3 RNA-seq data will
be uploaded to National Center for Biotechnology Information
GEO database.
Inspecting and quality trimming the FASTQ files was done in
the initial RNA-seq workflow by Expression Analysis using ea-
utils, which is a proprietary tool of that company. In the initial
workflow, the alignment step was done in STAR (35). STAR is
an ultrafast, universal read alignment tool running on the
University of Virginia 24-core Unix platform that is able to
identify and map reads to splice junction sites. The assignment
of the aligned sequence reads to genomic features, and the
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quantification of those reads was done with featureCounts (36).
A principal component analysis plot of the regularized log
transform of the data set indicated that one of the control F3
mice was an extreme outlier relative to all the other mice. This
outlier mouse was removed from the data set, and the data set
was renormalized for the subsequent downstream analyses. DE
analysis of the featureCounts raw counts matrix data were
conducted with DESeq2, a package in Bioconductor (37).
Contrasts between BPA and control lineage mice produced a
log2-fold change (lfc) measure of effect size and an adjusted
Pvalue measure of statistical significance for multiple com-
parisons for ~19,000 genes. Genes were ranked by both ab-
solute value lfc and adjusted Pvalue to determine ones that were
statistically significant between two conditions. In this experi-
ment, genes with lfc .0.5 and an adjusted P,0.05 were
considered differentially expressed.
The exact same workflow was executed on the FASTQ files
from within the Galaxy platform (38) using software that is part
of the Tuxedo Suite for RNA-seq analysis (39). The FASTQ files
were first inspected for quality with FASTQC and then trimmed
by one base with FASTX Trimmer (40, 41). Next, alignment to
the University of California, Santa Cruz, mm9 mouse reference
genome was performed in TopHat2 (42). TopHat2 alignment
produced binary alignment map files, which were then input to
the Tuxedo Suite DE analysis tool Cuffdiff (43). Cuffdiff output
consisted of a table of DE calculations for ~19,000 genes with
measurable expression levels, including FPKM effect sizes
and adjusted Pvalues, as well as other information on tran-
scription start sites, coding sequences, promoters, and transcript-
level DE.
Real-time qPCR
We performed follow-up studies to verify the results of RNA-
seq, and here we report on the expression of imprinted genes
Meg3 and Mirg. Both genes produce noncoding RNAs present
in the imprinted Dlk1 to Dio3 region on mouse chromosome
12. The quantitative analyses of Meg3 and Mirg expression
were conducted on samples derived from the POA, BNST, and
ANT HT from PN28 (n = 4 to 9), hypothalamus from day-of-
birth mice (PN0; n = 6 to 8), and PN4 whole brains (n = 5 to 6
per treatment group). As described above, all mice were in the
F3 generation. For all analyses, only one male and one female
per litter were used to avoid litter effects.
Total RNA was extracted with QIAzol and purified with the
miRNeasy Kit (Qiagen, Valencia, CA; catalog nos. 79306 and
217084) from frozen brain tissues. Concentration of RNA was
measured with NanoDrop (Thermo Fisher Scientific Hanover
Park, IL) and integrity checked by separation of RNA in agarose
gel. Using Reverse Transcription II (Life Technology) and
random primers (Life Technology, Carlsbad, CA; catalog nos.
18064-014 and 48190011), we reverse transcribed 300 ng of
total RNA into cDNA according to the manufacturer’s pro-
tocol. cDNA was diluted before qPCR analysis. Each sample
was analyzed in triplicate. Expression levels of two target
genes (Meg3, Mirg) and endogenous control [b
2
microglobulin
(B2M)] were evaluated with an ABI StepOnePlus system
(Thermo Fisher Scientific, Carlsbad, CA) and Fast Start
SYBRGreen Master Mix (Life Technology; catalog no.
4385612). The following primers were used for amplification:
Meg3 sense 50-TGGGGATGGGTCTCTAGGTG-30and Meg3
antisense 50-CCACTGACCCACAGTAACCC-30,ampliconsize
85 bp (NR_0203633.2 and NR_027651); Mirg sense 50-
TTGACTCCAGAAGATGCTCC-30and Mirg antisense 50-CCT-
CAGGTTCCTAAGCAAGG-30, amplicon size 170 bp (NR_028265.1);
B2M sense 50-GGCTCACACTGAATTCACCCCCAC-30
and B2M antisense 50-ACATGTCTCGATCCCAGTCGGT-30,
amplicon size 104 bp (NM_009735.3). Each set of primers
was initially tested for efficiency (between 95% and 105%)
and specificity, via melting curve analysis. For data evalua-
tion, the comparative DD threshold cycle method was used. A
calibrator sample was run on each plate to adjust for plate-
to-plate variation. Samples with threshold cycle values
.35 cycles, as well as outliers identified as samples with
values above (or below) the 1.5-fold of the interquartile
range from the third (or the first) quartile, were excluded
from the analysis.
DNA methylation
Isolation of DNA
DNA was isolated from BNST, POA, and ANT HT area of
juvenile (PN28) F3 C57BL/6J mice (n = 5 or 6). Frozen brains
were sectioned and collected as described previously. QIAamp
DNA Micro Kit (Qiagen, Valencia, CA; catalog no. 56304) was
used to isolate genomic DNA according to the manufacturer’s
instructions.
Bisulfite treatment and polymerase chain
reaction amplification
Bisulfite-treated DNA was used to evaluate the percentage of
methylation in CpG sites in the promoter of Meg3 on chro-
mosome 12 (44) (Supplemental Fig. 1). We treated 1 mg of DNA
with sodium bisulfite by using the EZ DNA Methylation-Gold
Kit (Zymo Research, Irvine, CA; catalog no. D5006). Briefly,
1mg of DNA was combined with 2 mL of M-Dilution Buffer in
20 ml total volume and incubated at 37°C for 15 minutes before
being combined with CT Conversion Reagent (Zymo Re-
search). This mixture underwent bisulfite treatment at 98°C for
10 minutes and 53°C for 4 hours in a thermal cycler (Eppendorf
AG, Hamburg, Germany). After desulfonation, DNA was pu-
rified with Zymo-Spin IC columns and eluted with 12 mLofM-
Elution Buffer (Zymo Research; catalog no. C1004-250). As a
control, commercially available Methylated Mouse DNA
(Zymo Research; catalog no. D5012) and DNA isolated from
matured mouse sperm were used. See Supplemental Table 1
for details.
Pyrosequencing analysis of the IG-DMR and
Meg3 DMR
To analyze the methylation pattern of the IG-DMR, located
the between Dlk1 and Gtl2 region, and the DMR in Meg3
promoter, we used a quantitative pyrosequencing assay. The
regions of interest span the nucleotide positions for IG-DMR
81241 to 81540 (containing 29 CpGs) and for Meg3 DMR
94226 to 94488 (R5, containing six CpGs). In the National
Center for Biotechnology Information database the gene ac-
cession number is AJ320506.1 and is referred to as the IG-DMR
by Hiura et al. (45) and DMR for Meg3 promoter by Sato et al.
(44). Bisulfite-treated DNA prepared as described above was
amplified by polymerase chain reaction with the ZymoTaq
DNA Polymerase Kit (ZymoResearch; catalog no. E2002).
PCR was performed in buffer containing 5 mM of MgCl
2
with
1mL of bisulfite-treated DNA. Primers used for amplification of
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IG-DMR and Meg3 DMR are listed in Table 1. In both cases,
reverse primers were conjugated with biotin at the 50end, to
allow the enrichment of a single strand with streptavidin beads
for the pyrosequencing reaction. The thermocycler conditions
for each reaction are given in Supplemental Table 1. Single-
strand amplicons were isolated with Pyrosequencing Work
Station and sequenced on a Pyromark Q96 pyrosequencing
instrument (Qiagen).
Statistical analysis
Statistically significant DE for the RNA-seq data set was
defined in this study as a log2-fold change absolute value .0.5
and multiple-test adjusted P,0.05. The STAR/featureCounts/
DESeq2 DE output and the Galaxy TopHat2/Cuffdiff DE
output were examined to determine which genes fell into this
category. The genes that were common to both approaches were
subjected to further exploratory data analysis and visualization,
including volcano plots and heat map clustering. Volcano
plots and heat map clustering were performed in R Statistical
Programming Language. Results from the qPCR and DNA
methylation studies were evaluated with two-way analysis of
variance followed by Tukey post hoc tests. Statistical signifi-
cance was defined as P,0.05.
Results
Identifying differentially expressed genes
associated with BPA exposure
We performed two separate RNA-seq analysis pipe-
lines to identify differentially expressed genes. The STAR/
featureCounts/DESeq2 analysis indicated 129 genes that
were differentially expressed between BPA and control
lineages in the F3 generation. The Galaxy TopHat2/
Cuffdiff analysis identified 124 genes that were differ-
entially expressed between BPA and controls in the F3
generation. Of these, 50 genes were common to both
analyses, 45 were upregulated by BPA, and 5 were down-
regulated. The statistically significant (P,0.05) differ-
entially expressed genes common to both analyses are
displayed in Table 2.
Following DE analysis, the RNA-seq results were vi-
sualized to highlight especially important genes. The
volcano plot in Fig. 2 shows effect size on the x-axis (log
2
fold change) and a measure of statistical significance
(2log
10
of the adjusted Pvalue) on the y-axis. The most
statistically significant differentially expressed genes with
the largest fold changes appear in the upper, outer corners
of the plot. Our plot shows the 50 differentially regulated
genes in the F3 generation. These genes have log2-fold
change absolute values .0.5 and an adjusted P,0.05.
To visualize genes whose expression levels may be
correlated, genes were clustered based on a mathematical
algorithm with correlation distance and average link-
age, which groups genes with similar expression pro-
files across biological replicates. Clustered genes were
depicted in a heat map (Fig. 3), where colors indicate
relative expression levels of a gene across experiments.
Progressively similar gene expression profiles were or-
ganized in a hierarchical tree structure dendrogram. We
show the 50 genes common to both analyses that are
differentially expressed between BPA and control mouse
brains in the F3 generation. Finally, Ingenuity was used to
determine the top canonical gene pathways (Supple-
mental Fig. 2), and top networks were combined to vi-
sualize unions (Supplemental Figs. 3 and 4). Because
pathway analyses are more precise with larger data sets,
we combined all important genes from the STAR/
featureCounts/DESeq2 analysis (n = 129) and Galaxy
TopHat2/Cuffdiff (n = 124). The full data set contained
203 genes because 50 genes were common to both an-
alyses. BPA has been reported to change expression of
imprinted genes, thus we selected the two imprinted genes
(46, 47) in the data set, Meg3 and Mirg, for further
analysis. Expression of both of these genes was higher in
BPA lineage as compared with control brains.
Real-time qPCR
In F3 PN28 POA, BNST, and ANT HT the expression
of Meg3 and Mirg varied by sex; in both cases, males
had a significantly higher level of transcripts than females
[F(1, 21) = 12.36, F(1, 16) = 22.52, respectively, P,
0.001 at least; Fig. 4A, 4D]. For Mirg, trends for an effect
of lineage (P= 0.057) and an interaction between lineage
and sex (P= 0.06) were noted. These trends were caused
by higher gene expression in control males. In the case of
Meg3, BPA lineage males had higher expression than any
other group. The next two experiments extended these
Table 1. Sequences and Positions (AJ320506.1) of Primers
Region Forward Primer (Position) Reverse Primer (Position) Sequencing Primer (Position)
IG-DMR upper
strand
50-GTGGTTTGTTATGGGTAAGTTTT-30(81252
to 81274)
Biotin-50-CTTCCCTCACTCCAAAAATTAAA-30
(81545 to 81567)
50-GGTAAGTTTTATGGTTTATTGTATA-30
(81265 to 81289)
IG-DMR lower
strand
50-TTAGGAGTTAAGGAAAAGAAAGAAATAG-30
(81529 to 81556)
Biotin-50-ATCATAAACAAATCCCATAACTTACT-30
(81259 to 81284)
50-GTTAAGGAAAAGAAAGAAATAGT-30
(81265 to 81289)
Meg3 DMR 50-GTTAGTGTTGGGGATTTTTTTTTAAAG-30
(94226 to 94252)
Biotin-50-TCAACCACCAAAACCAAATTTTTAA-30
(94464 to 94488)
S1: 50-TTAGTTTGGTTTTTAGTATTTAATA-30
(94261 to 94285)
S2: 50-TTTATTAGGGTTTTTTTTTTTATTA-30
(94348 to 94369)
Primer sequences for DNA methylation of the IG-DMR and the promoter (DMR) for Meg3.
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Table 2. Differentially Expressed Genes From RNA-seqof F3 Brain Regions in Males Descended From
BPA-Exposed F1 Females vs Unexposed Control Lineage F3
Gene Gene Description Fold Change log2 Fold Change Padj
Genes Upregulated in F3 due to F1 BPA Exposure
Adam8 Disintegrin and metallopeptidase domain 8 2.49 1.31 0.0001
Adamts16 Disintegrin-like and metallopeptidase (reprolysin type) with
thrombospondin type 1 motif, 16
1.64 0.71 0.0175
Akap8l Kinase (PRKA) anchor protein 8-like 1.49 0.57 0.0134
Ankrd24 Ankyrin repeat domain 24 1.50 0.59 0.0135
Atxn2l Ataxin 2-like related protein 1.45 0.54 0.0028
Bzrap1 TSPO associated protein 1 1.46 0.55 0.0095
Celsr3 Cadherin, EGF LAG seven-pass G-type receptor 3 1.63 0.71 0.0049
Col11a1 Collagen, type XI, a1 2.15 1.10 0.0000
Col24a1 Collagen, type XXIV, a1 1.88 0.91 0.0153
Col4a2 Collagen, type IV, a2 1.54 0.63 0.0134
Fam193b Family with sequence similarity 193, member B 1.49 0.57 0.0162
Flnb Filamin, b1.63 0.71 0.0000
Gigyf1 GRB10 interacting GYF protein 1 1.52 0.61 0.0074
Gm14827 Predicted gene 14827 1.75 0.80 0.0095
Igsf9 Immunoglobulin superfamily, member 9 1.99 0.99 0.0029
Igsf9b Immunoglobulin superfamily, member 9b adhesion protein 1.45 0.54 0.0287
Leng8 Leukocyte receptor cluster member 8 1.81 0.86 0.0442
Lime1 Lck interacting transmembrane adaptor 1 1.62 0.70 0.0024
Lrrc16b Capping protein regulator and myosin 1 linker 3 1.57 0.65 0.0274
Lrrc45 Leucine rich repeat containing 45 1.64 0.71 0.0061
Malat1 Metastasis associated lung adenocarcinoma transcript 1 1.58 0.66 0.0134
Mapk11 Mitogen-activated protein kinase 11 1.53 0.62 0.0287
Meg3 Maternally expressed 3 long noncoding RNA 1.87 0.90 0.0007
Miat Myocardial infarction associated long noncoding RNA 2.00 1.00 0.0000
Mirg miRNA containing gene 1.49 0.58 0.0257
Nbeal2 Neurobeachin-like 2 1.65 0.72 0.0035
Neat1 Nuclear paraspeckle assembly transcript 1 1.76 0.81 0.0035
Nktr Natural killer tumor recognition sequence 1.42 0.50 0.0061
Pan2 PAN2 poly(A) specific ribonuclease subunit 1.47 0.55 0.0100
Plekhg4 Pleckstrin homology domain containing, family G
(with RhoGef domain) member 4
2.03 1.02 0.0028
Plekhn1 Pleckstrin homology domain containing, family N member 1 1.78 0.83 0.0019
Plxna3 Plexin A3 1.53 0.61 0.0017
Pnpla3 Patatin-like phospholipase domain containing 3 1.59 0.66 0.0028
Ptpru Protein tyrosine phosphatase, receptor type, U 1.50 0.59 0.0076
Rgs11 Regulator of G-protein signaling 11 1.69 0.76 0.0098
Rps6kb2 Ribosomal protein S6 kinase, polypeptide 2 1.65 0.72 0.0122
Sema4g Sema domain, immunoglobulin domain, transmembrane
domain, and short cytoplasmic domain (semaphorin) 4G
1.53 0.61 0.0040
Shank1 SH3/ankyrin domain gene 1 1.51 0.59 0.0288
Sim1 Single-minded homolog 1 2.53 1.34 0.0050
Slc2a4rg-ps Solute carrier family 39 (zinc transporter), member 2 1.76 0.82 0.0054
Slc39a2 SH3/ankyrin domain gene 1 2.02 1.01 0.0014
Snhg11 Small nucleolar RNA host gene 11 1.74 0.79 0.0007
Srrm2 Serine/arginine repetitive matrix 2 1.63 0.71 0.0000
Ssh3 Slingshot homolog 3 1.79 0.84 0.0028
Vwa5b2 von Willebrand factor A domain containing 5B2 1.67 0.74 0.0103
Genes Downregulated in F3 due to F1 BPA Exposure
Aldh1a1 Aldehyde dehydrogenase family 1, subfamily A1 0.66 20.59 0.0226
Mt2 Metallothionein 2 0.60 20.73 0.0019
Pmch Promelanin-concentrating hormone 0.39 21.36 0.0274
Rpl23 Ribosomal protein L23 0.66 20.60 0.0386
Rps18 Ribosomal protein S18 0.67 20.57 0.0050
Differentially expressed genes obtained by RNA-seq of male F3 POA, BNST, and ANT HT. F3 males are descendedfrom F1 females exposed to BPA in utero
vs F3 controls from the same lineage. Fold change values and Pvalues are from STAR/featureCounts/DESeq2 analysis and are the genes that were common
to that workflow and the Galaxy TopHat2/Cuffdiff workflow having absolute value log2-fold changes .0.5 and adj P,0.05. There were 45 upregulated
and 5 downregulated common genes. The Padj is the Benjamini-Hochberg, multiple-test-adjusted Pvalue.
Abbreviations: adj, adjusted; miRNA, micro RNA.
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data to different brain regions, different developmental
ages, and another mouse strain.
The entire hypothalamus from PN0 C57BL/6J F3 mice
revealed a trend for higher expression of Meg3 in both
sexes from the BPA lineage [F(1, 25) = 3.17, P,0.087] as
compared with control lineage (Fig. 4B). No statistically
significant effects of sex or lineage were found for Mirg
(Fig. 4E).
Lastly, expression of Meg3 was affected by sex [F(1,
29) = 15.06, P,0.0006] and dose [F(3, 29) = 3.80, P,
0.02], and we noted an interaction [F(3, 29) = 14.54, P,
0.0001] between sex and dose (Fig. 4) in whole brains
from FVB F3 pups. Exposure to 0.5 or 50 mg of BPA/kg
per day significantly increased the expression of Meg3 in
F3 FVB male brain (P,0.03) as compared with controls.
In females, Meg3 was reduced, compared with controls,
only at the lowest BPA exposure level (P,0.02)
(Fig. 4C). Ancestral BPA status also affected expression of
Mirg transcript [F(3, 30) = 7.36, P,0.001], which was
higher in control than in BPA lineage whole brains. The
effect of lineage on Mirg expression was caused by dif-
ferences between control brains, which have significantly
greater expression than brains in the lowest- and the
highest-dose BPA lineages (P,0.001) (Fig. 4F). No sex
differences or interactions were present.
DNA methylation
Because Meg3 gene expression in male brains was
consistent with the RNA-seq data, we limited our DNA
methylation study to this gene. We included PN28 BNST,
POA, and ANT HT from both sexes to determine
whether DNA methylation was correlated with sex dif-
ferences in gene expression. We analyzed methylation
status of 29 CpGs in the IG-DMR region (chromosome
12: 81241 to 81540), a region known
to contain repeated motifs (48), and 6
CpGs in the Meg3 promoter region
(chromosome 12: 94226 to 94488).
We did not find any sex or exposure
related differences in methylation sta-
tus of IG-DMR. These data are dis-
played as heat maps (Fig. 5). However,
in the Meg3 promoter, we found that
three CpG sites were sexually di-
morphic, with higher methylation
in males as compared with females
[F(1, 25) = 9.58, 4.35, 8.44, respectively;
P,0.05 at least] (Fig. 6). Ancestral
BPA had no effect on DNA methyla-
tion in either sex. Considering that the
transcript level of Meg3 was signifi-
cantly lower in females, we expected
CpG methylation to be higher in fe-
males than males. Thus, the observed
sexually dimorphic changes in Meg3
transcript level are probably driven by
mechanisms other than DNA methyl-
ation, although we cannot exclude the
possibility that other CpG sites in
promoter region or IG-DMR that we
did not evaluate may contribute to
those differences.
Discussion
Here we report on RNA-seq, qPCR,
and DNA methylation data from mouse
tissue exposed transgenerationally to an
EDC. After performing two separate
RNA-seq analysis pipelines we found
Figure 2. Volcano plot showing the 50 differentially expressed genes in the F3 generation
common to the STAR/featureCounts/DESeq2 and TopHat/Cuffdiff RNA-seq analyses. Only the
section of the log-scale y-axis for which the adjusted P,0.05 [2log
10
(0.05) = 1.3] is shown.
Four genes (white dots on the right) were upregulated by a log2-fold change of .1 and one
gene (white dot on the left) was downregulated by a log2-fold change of .1 without direct
exposure to BPA. Ctl, control.
138 Drobn ´a et al Transgenerational BPA and Imprinted Genes Endocrinology, January 2018, 159(1):132–144
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50 genes that were significantly different in both ana-
lyses. We selected two genes upregulated by BPA for our
follow-up studies: Meg3 and Mirg. We chose these genes
because BPA has documented effects on other imprinted
genes in other tissues (21, 49, 50). In addition, both genes
are lncRNAs that, as a class, have been implicated as
important epigenetic factors involved in transgenera-
tional inheritance (51). Meg3 and Mirg are related as they
reside in the same imprinted region on mouse distal
chromosome 12 (52). At least three paternally expressed
genes (Dlk1, Rtl1, and Dio3) and four maternally expressed
genes (Meg3, antiRlt1, Rian, and Mirg)
are located in this region.
Meg3 is of particular interest. Our
data show that in males, Meg3, ama-
ternally expressed lncRNA, is altered
by ancestral gestational exposure to
BPA, and this is via maternal inheri-
tance. Meg3 is present in brain, pituitary,
pancreas, placenta, and many other tis-
sues (53, 54). The gene has four to five
isoforms, all of which are present in brain
(55). Meg3 is part of a tumor-suppressing
pathway, which includes p53 (30, 56). In
brain and pituitary, mutations of this
gene are upregulated in several tumor
types, including glioblastomas and pitu-
itary tumors (24, 31). Expression of
Meg3 is noted in 90% to 95% of pitu-
itary cells and is not restricted by cell type
(24). Meg3 is also indirectly involved in a
variety of hormone-related functions in-
cluding the timing of puberty in rats
(29). Human epidemiology studies have
shown that DNA hypermethylation of
the Meg3 promoter in blood cells is
correlated with poor infant temperament
(25) and lead exposure–induced obesity,
and hypomethylation is noted in sperm
(57). The insecticide methoxychlor has
partial estrogenic activity (58) and causes
hypomethylation of Meg3 in sperm and
liver of F1 and F2 mouse offspring from
F0 treated dams (28). We speculate that
this gene is sensitive to environmental
variation and has the potential to be a
useful biomarker in human studies.
The RNA-seq data showed signifi-
cantly more expression of Meg3 in
male PN28 POA, BNST, and ANT HT.
Real-time qPCR conducted on RNA
from brains of C57BL/6J mice col-
lected at two ages (PN28 and PN0),
from two subregions (POA, BNST, and ANT HT and
only the hypothalamus), and in both sexes, largely
confirmed the RNA-seq data for Meg3. In all conditions,
in males we noted at least a trend for more Meg3 ex-
pression in BPA vs control lineage brains. Interestingly,
the qPCR data from the whole brains of FVB F3 mice
confirm the data collected in C57BL/6J mice. Males from
the lowest BPA dose lineage had significantly more Meg3
mRNA than controls. These significant and trending data
confirm RNA-seq data collected in C57BL/6J PN28
brain, and the data generalize to another mouse strain,
Figure 3. Heat map and clustering diagram for the 50 differentially expressed genes in the
F3 generation common to the Star/featureCounts/DESeq2 and TopHat/Cuffdiff RNA-seq
analyses with Benjamini-Hochberg multiple-test-adjusted P,0.05 absolute value and lfcs .
0.5. The colors of the cells indicate the standardized number of normalized mRNA reads of
the F3 BPA and control samples for that gene. In the top part of the heat map, the BPA F3
generation is more highly expressed (shades of purple) than the control F3 generation. In the
bottom part of the heat map, the BPA F3 generation is less expressed (shades of light blue)
than the control F3 generation. Note also that in the horizontal dendrogram the columns
with three biological replicates for BPA F3 cluster together and that the columns with the
two biological replicates for control F3 cluster together.
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Figure 4. Quantitative gene expression analysis of Meg3 and Mirg in (A and D) POA, BNST, and ANT HT of C57BL/6J, PN28 F3 offspring, (B and
E) C57BL/6J, PN0 hypothalamus of F3 offspring, and (C and F) whole brains from PN4 F3 FVB mice. Means 6standard errors of the mean are
shown. Numbers per group are listed in the individual histograms. Dark gray histograms denote males, and white denote females. Light gray
histograms represent data from sexes combined, because there were no sex differences. *Significant overall sex difference, M .F, P,0.05.
**Trend for effect of lineage, BPA .control, P= 0.087. ***Significantly greater than all other male dose groups, P,0.05.
#
Significantly lower
than the female control group, P,0.05.
##
Significantly less than the control female group, P,0.05. BF, BPA lineage female; BM, BPA lineage
male; CF, control lineage female; CM, control lineage male.
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other BPA doses, and a different treatment and breeding
paradigm. In contrast, RNA-seq results showed a sig-
nificant elevation of Mirg in male BPA lineage brains, yet
with qPCR an increase in expression in the BPA lineage
brains was only confirmed only in the PN0 hypothala-
mus. In fact, the reverse effect was noted in the POA,
BNST, and ANT HT of C57BL/6J mice and whole brains
of PN4 FVB mice.
Although we did not find BPA-related differences in
Meg3 methylation, we did find small sex differences in
methylation in three CpG sites. In these cases, females had
lower methylation than males. This result is in contrast to
our qPCR data showing higher Meg3 expression in males
than females. In a microarray study conducted on cortex
and hippocampal tissues from day-of-birth C57BL/6J
mice, Meg3 was higher in female than in male brains
(59). These data were confirmed with qPCR, and thus
these results are the opposite of our qPCR data but are in
agreement with the methylation results we report.
A previous study from our group used microarray to
compare gene expression in F3 whole embryonic brains
on gestational day 18.5 exposed to the same dose of BPA
used here (17). Comparison of the genes common to the
two data sets revealed only two genes that overlap.
Semaphorins are a class of well-characterized guidance
molecules acting primarily during brain development
(60). Semaphorin 4G (Scam4g) is necessary for granular
cell migration during cerebellar formation in mice (61).
The other gene, regulator of G protein signaling (Rgs11),
has been studied in the retina and is involved in de-
polarization of bipolar cells and is associated with one of
the glutamate receptors (62). Less is known about Rgs11
function in brain, where it is expressed throughout, and it
is highest in human cerebellum (63).
To date, one other study used RNA-seq to examine
effects of first-generation in utero exposure to BPA (64).
Two important brain areas were compared in neona-
tal rats: the hippocampus, important for learning and
memory, and the hypothalamus, which is essential for
regulation of the pituitary hormones and other re-
productive functions. Interestingly, none of the important
genes discovered in these areas match the data we present
here. Arambula et al. (64) found differences in expression
of several genes including Esr1, Esr2, and Oxt, and they
validated their RNA-seq data with qPCR. These three
genes were also differentially expressed in F1 mouse brains
exposed to BPA in studies using other rodents and dosing
paradigms (16, 17). Gene expression inF3 vinclozolin and
Figure 5. Heat map and clustering diagram. (A) CpG regions 1 to 8 and 21 to 28 in the IG-DMR of the Dlk1 to Dio3 domain. (B) CpG sites in
the Meg3 promoter DMR. The colors of the cells show percentage methylation, with red denoting highly methylated sites and green representing
less methylated sites. Horizontal lines represent individual samples. BF, BPA lineage female; BM, BPA lineage male; CF, control female; CM,
control male.
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control lineage rats has been assessed in several neural
regions (65, 66). For some of these studies TaqMan qPCR
arrays with 48 select genes were used. The focus of the
study was on neuroendocrine-related functions. None of
the genes identified by the TaqMan arrays are present in
our data set (67). Microarray data from the same group
did not reveal any overlap with the genes in our short list.
We did not find any differences in methylation caused by
ancestral BPA status in the section of the Meg3 promoter we
explored in F3 brains. This finding is indirectly supported
by a study limited to imprinted genes and DNA methylation
(68) in which alterations in DNA methylation in F1 germ
cells did not persist to F3. We speculate that other epigenetic
mechanisms, such as histone modifications, regulate ex-
pression of Meg3 across generations. In fact, genomic im-
printing of loci that include Meg3 is linked to increased
histone acetylation (69). In human and mouse pancreatic
tumors, Meg3 can be regulated by H3K4me3 and DNA
methylation (70). Recently it has been shown that polycomb
repressive complex 2 is required to maintain expression of
maternal lncRNAs from the Meg3–Mirg locus in mouse
embryonic stem cells. In its absence, the entire locus becomes
silent because of de novo methylation at the IG-DMR (71).
Thus, any disturbance, including environmental exposures,
can lead to alterations in IG-DMR methylation, resulting in
transcript-level changes. Future studies will examine other
epigenetic mechanisms that may regulate gene expression
transgenerationally as a result of ancestral BPA.
Acknowledgments
We thank Dr. Stephen D. Turner (University of Virginia) and Dr.
David Scarr (Center for Human Health and the Environment at
North Carolina State University) for technical assistance with
parts of this study.
Financial Support: This work was funded by National
Institute of Environmental Health Sciences (NIEHS) Grants
R01 ES022759 (to E.F.R.) and P01 ES022848 (to J.A.F.), and
Environmental Protection Agency Grant RD-83459301 (to
J.A.F.). We acknowledge help with the pyrosequencing from
NIEHS Center for Human Health and the Environment Grant
P30ES025128. A.D.H. gratefully acknowledges financial support
from the 4-VA programs at James Madison University and the
University of Virginia.
Current Affiliation: J. T. Wolstenholme’s current affil-
iation is the Department of Pharmacology and Toxi-
cology, Virginia Commonwealth University, Richmond,
Virginia 23298.
Correspondence: Emilie Rissman, PhD, Center for Human
Health and the Environment and Department of Biological
Sciences, Thomas Hall Room 3526, North Carolina State
University, Raleigh, North Carolina 27695-7614. E-mail:
e_rissman@ncsu.edu.
Disclosure Summary: The authors have nothing to disclose.
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