2. 2
Abstract
High-throughput sequencing technologies are now more than ever contributing to
the identification of genetic variants and their association with phenotypic diversity.
Largely, absent from these efforts is the identification of natural epigenetic alleles
(epialleles). From previous experiments, a candidate epiallele was identified in the SVP
(SHORT VEGETATIVE PHASE) gene of the accession Dja-1, which is a natural
accession of Arabidopsis thaliana that displays an early-flowering phenotype. SVP
influences the floral transition in A. thaliana, and mutant alleles of this locus lead to an
early-flowering phenotype. Interestingly, the SVP alleles are methylated in Dja-1
compared to all other surveyed A. thaliana strains, which leads to the following
hypothesis: The methylated alleles of SVP in the Dja-1 strain are causative for the early
flowering phenotype observed in nature. We have characterized the expression of SVP in
Dja-1 using RNA-seq, which has revealed that it has the lowest expression in any
accession. Furthermore, genetic complementation analysis revealed the Dja-1 allele fails
to complement null T-DNA knockout alleles; however, the presence of a transposable
element in the 5’ UTR –discovered after sequencing—eliminates the possibility that SVP
in Dja-1 is a pure epiallele. Treatment with demethylating agents demonstrates significant
reduction of genomic methylation in seedlings; although, phenotypic data of treated adult
tissue still failed to show significant difference in SVP expression or flowering time.
_________________________________________________________________________________________________
Introduction
With the advent of high-throughput sequencing technologies, the identification of
genetic variants and their association with phenotypic diversity is being pursued to better
understand how morphological variation arises between closely related individuals in and
amongst species. One promising reservoir of diversity within species, epigenetic alleles,
has garnered significant attention in recent years because of their latent potential in many
organisms, most notably crop plants (Ji et al., 2015). Epigenetic alleles, or epialleles, are
differentially expressed in the absence of DNA sequence changes and are stably inherited
over generational time, occasionally causing drastically different phenotypic outcomes
such as the decreased fruit pigmentation observed in tomato when the colorless non-
ripening gene is silenced by DNA methylation (Manning et al., 2006). Three classes of
epialleles have been outlined to better define how much these epialleles rely on genetic
factors (Richards, 2006). The first class, obligate epialleles, display a complete
dependency on a genetic variant; whereas, facultative epialleles can form in the presence
of a genetic variant but are not necessarily dependent on it. Last, a pure epiallele forms
spontaneously and is maintained without dependence on a genetic variant. Although
some pure epialleles have been identified (Schmitz et al., 2011), many remain
unexamined; however, increasingly cost effective techniques to study DNA methylation
in high resolution are contributing to a wealth of data from which to identify epialleles of
interest. Utilizing these data to identify and characterize epialleles will be a crucial
3. 3
component of understanding the extent to which epigenetics play a role in morphological
diversity and their potential to be manipulated for more desirable breeding outcomes.
In recent years, one technique that has become increasingly popular for examining
epigenetic variation is bisulfite sequencing. Through sodium bisulfite-induced chemical
conversion of unmethylated cytosines to uracil, followed by PCR amplification that
converts uracil to thymine, one is able to distinguish methylated base pairs from
unmethylated base pairs by comparing the treated DNA sequence with its reference
genome. Therein, it is possible to construct a DNA methylome that shows single base
pair information on the methylation of each cytosine in the genome (Cokus et al., 2008;
Lister et al., 2008). Cytosine DNA methylation is one of the most ubiquitous and heavily
studied modes of epigenetic inheritance (Niederhuth and Schmitz, 2014) and is
established and maintained throughout plant genomes by different enzymes. These
enzymes act to methylate and maintain methylation in three sequence contexts: CG,
CHG, and CHH, where H stands for A, T, or C. CG dinucleotide methylation is
maintained throughout the genome by the enzyme DNA METHYLTRANSFERASE 1
(MET-1), whereas CHG and CHH sites are targeted by RNA directed DNA methylation
(RdDM). RdDM is the major pathway in plants that utilizes small interfering RNAs
(siRNAs) to direct a host of proteins including DNA methyltransferases to specific sites
throughout the genome (Matzke and Mosher, 2014). When found in all three contexts,
cytosine DNA methylation is known to act as a transcriptional repressor (Law and
Jacobsen, 2010).
It is abundantly clear that in plant genomes there exists extensive natural
epigenetic variation (Schmitz et al., 2013). The relationship between genetic variation
and cytosine DNA methylation has been thoroughly examined using locally adapted
strains (called accessions) of the flowering plant Arabidopsis thaliana, a useful model
species for its small, compact genome and its diverse population span throughout the
Northern Hemisphere (Nordborg and Weigel, 2008). The constructions of methylomes
from 152 accession of A. thaliana via bisulfite sequencing led to the discovery that
approximately 35% of the cytosine differentially methylated regions (C-DMRs) are
associated with genetic variation (Schmitz and Schultz et al., 2013). From these
methylomes, SHORT VEGETATIVE PHASE (SVP), a transcriptional repressor of floral
transition (Gregis et al., 2006), stood out as a potential epiallele when compared with all
other accessions within the same species. In Dja-1, a naturally occurring accession of A.
thaliana native to Kyrgyzstan, the 5’ untranslated region (UTR) and promoter are
abundantly methylated; whereas, in all other accession methylation is virtually absent. In
addition, Dja-1 is known to be a summer annual plant, flowering rapidly without
vernalization*. Since the ancient behavior of A. thaliana is as a winter annual—growing
for months without flowering unless induced by long-term cold exposure (Sung and
Amasino, 2005)—Dja-1’s early-flowering phenotype suggests that something may be
disrupting genetic pathways which would lead to a winter annual behavior. SVP is a gene
that, when disrupted, leads to a summer-annual behavior (Hartmann et al., 2000). These
observations in concert were the impetus for our further examination of SVP and the
implications of its hypermethylated 5’ UTR.
In this study, we investigated SVP in Dja-1 (hereafter referred to as SVPepi
) for its
potential as an epiallele, combining both high-throughput sequencing technologies and
phenotypic measurement to examine the role of DNA methylation on floral transition in
4. 4
Dja-1. Further, the use of chemical demethylating agents for studying SVPepi
led us to
examine their efficacy in a more detailed manner than has been previously accomplished.
Although we did identify a depletion of SVPepi
transcription in Dja-1, our subsequent data
suggests genetic variation is likely the cause of transcriptional silencing of SVPepi
;
however, project design flaws limit the interpretation of our results and further
experiments need to be carried out to conclusively dismiss the hypothesis that DNA
methylation was the principal driver of transcriptional inactivation.
Methods
I. Seed sterilization, plate preparation and, chemical treatments
All A. thaliana seeds were sterilized by adding approximately 30-40 seeds to a
microcentrifuge tube and first washing the seeds with 70% ethanol/0.05% Triton X-100
(Ameresco). After removing the initial wash liquid, 1 mL of 95% ethanol was added
under a sterile hood and poured off. Once this step was repeated, the seeds were drawn up
with a pipet and dried on sterile paper before being plated. Initially, all plates were
prepared at one time with Agarose RA, Biotechnology Grade (Ameresco) and added
Linsmaier and Skoog nutrients (Caisson Laboratories, Inc), adding the pre-dissolved
chemical demethylating agents to Erlenmeyer flask containing the liquid agar and
pouring the plates under a sterile hood. 5-azacytidine (Sigma) was initially dissolved to a
concentration of 400 mM in dimethyl sulfoxide (DMSO), whereas, zebularine (Sigma)
was dissolved in water to a concentration of 40 mM.
Once it was discovered that 5-azacytidine quickly breaks down in aqueous
solution, the treatments were altered to limit the effect of degradation. While plates were
prepared in the same manner, they were made fresh every three days. Approximately
0.00244 grams of 5-azacytidine was weighed added to microcentrifuge tubes, and
dissolved in DMSO to a concentration of 400 µM each time the plates were made. Once
the agar plates were ready, a permeable nitrocellulose film was prepared by cutting the
film into a circular size, which could fit on a petri dish, and then placing the film over the
top of the solidified agar. Seeds were then added on top of the film. This allowed for the
removal of the seeds to a freshly prepared plate.
II. Floral transition phenotyping
Dja-1 and Col-0 seeds were initially grown on treated agar plates containing 40 µM
zebularine and 400 µM 5-azacytidine. Control-group seeds were plated on agar
containing no treatment and DMSO (equivalent to the amount in 5-azacytidine solution).
When two primary leaves were visible, the seedlings were transferred to drug-free growth
medium. Every third day, 10 µL of demethylating agent and DMSO solutions—dissolved
in water and stored at 4ºC—were applied to the apical meristem of growing plants by
pipet. When the flower bud of the growing plant became visible, the number of leaves
were counted and recorded as, once flowers are generated, the transition from producing
vegetative structures such as leaves have completed.
III. Measuring SVP mRNA via qRT-PCR
5. 5
Dja-1 seeds were grown on treated plates of 100 µM 5-azacytidine dissolved in
10% DMSO and control plates with no demethylating agent but an equivalent volume of
DMSO to the treated plates. Nitrocellulose film covered all of the plates so that the plates
could be transferred to fresh plates, an important step in keeping the demethylating agents
at an effective concentration. Plates and 5-azacytidine solution were made fresh every
third day and the seedlings were transferred by physically moving the sterilized cellulose
membrane with two pair of forceps to a new plate.
When the primary leaves were visible, the seedlings were collected in 1.5 mL
microcentrifuge tubes (approximately 10 seedlings per tube) and flash frozen in liquid
nitrogen. The microcentrifuge tubes were stored at -80ºC until RNA extractions could be
done. For RNA extraction, seedlings were taken from the -80ºC, re-frozen in liquid
nitrogen, and ground with a mini-pestle. TRIzol was immediately added to the
homogenized tissue, followed by chloroform isolation, and subsequent alcohol wash
steps. RNA was re-suspended in 21 µL of nuclease free water. After normalizing RNA
concentrations, TURBO DNase (Life Technologies) was added to rid the solution of any
genomic DNA that was present after the RNA extraction and the solutions were allowed
to incubate at 37ºC for 30 minutes before adding DNase inactivation reagent and isolating
the pure RNA.
cDNA synthesis was completed by adding the RNA to 5X iScript reaction mix
and iScript reverse transcriptase (Bio-Rad), followed by PCR reaction and 5-fold dilution
of the cDNA product. Next, qRT-PCR was carried out using primers for SVP and a
reference gene that is consistently expressed in all tissues and stages, CLATHARIN
ADAPTER COMPLEX SUBUNIT (CACS). Primer sequences are as follows: SVP
Forward 5’ – CAAGGACTTGACATTGAAGAGCTTCA – 3’ and SVP Reverse 5’ –
CTGATCTCACTAATAATCTTGTCA – 3’; CACS Forward 5’ –
ACTCAGGAAGGTGTACGGTCA – 3’ and CACS Reverse 5’ –
TGCATTTGGAACAGGTTTGT – 3’. Primers were diluted to 10 µM concentration and
added to the SYBR/cDNA mixture on a 384-well PCR plate. The plate was loaded into
the Roche Lightcycler ® 480 II and run for 45 cycles. Data was collected and analyzed,
excluding samples with multiple melting curves and with technical replicate variation
exceeding 1.0 cycles. The relative expression of the treated and untreated samples was
calculated and compared.
IV. MethylC-seq
Seeds from the Col-0 accession were grown in the same way as the Dja-1 seeds,
including plates that contained 400 µM 5-azacytidine and plates that contained 40 µM
zebularine. After primary leaves were visible, single seedlings were isolated from the
plates and flash frozen in liquid nitrogen, then stored at -80ºC until DNA extractions
could be completed. Following DNA extractions from the single seedlings, library
preparation, bisulfite treatment, and sequencing was carried out in accordance with the
published protocol (Urich et al., 2008).
Later, seedlings were grown on 40 µM and 100 µM 5-azacytidine and plated on
nitrocellulose on top of agar-solidified medium. Every three days the seeds were
transferred on top of the nitrocellulose to a freshly made plate with added either
6. 6
demethylating agent or the solvent control in equal volume to keep the concentrations
consistent. MethylC-seq was done on a sample of each seedling (Urich et al., 2015) and
analyzed for weighted methylation level as has been previously described (Schultz and
Schmitz et al., 2013). Weighting of methylation levels is a way to account for differences
in sequencing depth across the MethylC-seq reads by giving more or less weight to a
particular cytosine depending on how many methylated reads are mapped to its location.
If unaddressed, this problem could lead to biased interpretation of the results depending
on how many reads are mapped to a particular cytosine.
Results
I. Hypermethylated SVPepi
in Dja-1 is suspected to have phenotypic ramifications
The creation of an easily navigable browser of over 152 methylomes of A.
thaliana from different accessions, made publically available, led to the identification of
SVP as a source of potential epigenetic variation within the accessions. In the 5’ UTR of
SVPepi
in the accession Dja-1, there exists extensive cytosine DNA methylation, in all
three contexts—indicative of being targeted by the RdDM silencing pathway (Law et al.,
2010). Dja-1 is the only strain that exhibits hypermethylation at this locus, demonstrated
by a representative subset of seven other accessions (Fig 1). Given that hypermethylated
promoter regions are typically associated with transcriptional silencing (Law and
Jacobsen, 2010), this observation led to the following hypothesis: SVPepi
in Dja-1 is
epigenetically silenced by cytosine DNA methylation; consequently causing the floral
transition of Dja-1 to resemble a summer annual early-flowering plant.
To test these hypotheses, we first looked at the expression data generated in
tandem with the 152 methylomes (Schmitz and Schultz et al., 2013). These data were
produced by RNA-sequencing (RNA-seq) that allows for quantification of the amount of
each individual RNA transcript in the cell. Given access to this data set, we examined the
level of SVP mRNA transcript across 156 accessions (Fig. 2B). The amount of SVPepi
in
Dja-1 measured in fragments per kilobase of exon per million fragments mapped
(FPKMs) was the least of any accession. Although SVPepi
was not completely silenced, it
was significantly transcriptionally inhibited—supporting our original hypothesis.
Next, a classic complementation experiment was designed to determine whether
or not the genetic loci causing Dja-1’s summer annual behavior is SVPepi
. This
complementation analysis utilized the late flowering FRIGIDA (FRI) Col-0 accession.
FRI activates the expression of FLOWERING LOCUS C, which itself acts as a suppressor
of flowering in a separate pathway from SVP (Hu et al., 2014). A T-DNA knockout of
FRI (FRI;svp-32) was prepared in addition and was crossed to Dja-1 plants to produce
FRI;svp-32 x Dja-1 seeds. Subsequently, the accessions were planted and their floral
transition phenotype was measured. Both Dja-1 and FRI;svp32 show a similar early-
flowering phenotype; whereas, FRI Col-0 exhibits the winter-annual late-flowering
phenotype. If the gene that was causing the early flowering time phenotype in Dja-1 was
different from the gene in FRI;svp-32, then when crossed their progeny would have at
least one working copy of the each gene from the parental strains, resulting in a late-
flowering phenotype. If the causative alleles are the same gene in each parent, then
7. 7
crossing them should not result in the restoration of function in the gene causing the
early-flowering phenotype. The cross between Dja-1 and FRI;svp-32 displayed an early-
flowering phenotype, failing to complement and demonstrating that the genes which
cause summer-annual flowering in Dja-1 and FRI;svp-32 are the same.
With the knowledge that SVPepi
in Dja-1 was causative for the early-flowering
phenotype of Dja-1, we next needed to investigate whether the observed DNA
methylation has a genetic basis. Because the methylation data from Dja-1 is mapped onto
a reference genome of Col-0, we designed PCR primers to amplify the genetic region
surrounding SVPepi
in Dja-1. Upon sequencing and inspection of SVPepi
and the
surrounding genetic sequence, there was one prominent genetic variant found in SVPepi
, a
seven-kilobase transposable element (TE) that had inserted into the 5’ UTR of the gene
before the transcriptional start site (Fig. 2A). TEs are often the target of RdDM and it has
been proposed that DNA methylation adapted to limit their transcriptional expression
(Kim and Zilberman, 2014). This observation is inconsistent with SVPepi
being a pure
epiallele, due to the presence of genetic variation; however, DNA methylation could still
be the cause of flowering trait variation in Dja-1, as is the case in facultative or obligate
epialleles. Therefore, we further investigated its role and potential for influencing floral
transition.
I. Demethylating agents fail to affect the floral transition of Dja-1
5-azacytidine and zebularine are two commercially available chemical
demethylating agents that act as cytosine analogs and form a covalent bond to the MET-1
enzyme, destroying its capability to maintain DNA methylation (Christman, 2002).
Likewise, these chemicals efficiently have been shown to reactivate the transcription of
TEs (Baubec et al., 2014). If cytosine methylation is transcriptionally silencing SVPepi
,
we hypothesized that Dja-1 seeds treated with demethylating agents would be more
transcriptionally active than those without demethylating treatment. To accomplish this,
quantitative real time polymerase chain reaction (qRT-PCR) was used to measure the
relative expression of SVPepi
mRNA in seedlings grown on treated and untreated agar-
solidified medium (Fig. 3A). Based on preliminary results, expression of SVPepi
is
unaffected when treated with chemical demethylating agents.
To test the phenotypic impact of chemical demethylating agents on Dja-1’s
flowering time, we planted seedlings treated with 400 µM 5-azacytidine and 40 µM
zebularine and allowed them to grow to floral transition. If DNA methylation was
causing transcriptional silencing of SVPepi
in Dja-1, then we would expect a decrease in
DNA methylation to coincide with an increase in expression of SVPepi
and a reversion of
Dja-1 to a winter-annual, late-flowering phenotype. Due to the observation that plants
which are allowed to recover after being treated with a demethylating agent will regain
DNA methylation as they grow to adult plants (Baubec et al., 2014), we attempted to treat
the plants on their apical meristem with the solubilized demethylating agents as they
grew. Like qRT-PCR, this data did not reveal any significant difference between the
control group and the plants treated with chemical demethylating agents (Fig. 3B).
However, the efficacy of the procedure to treat adult tissue was later brought into
question, limiting the quality of this particular data set.
8. 8
I. MethylC-seq demonstrates that 5-azacytidine decreases genome-wide levels of
cytosine DNA methylation
Sequencing of methylomes after bisulfite sequencing (MethylC-seq) has become
a powerful tool in recent years for examining the genome-wide frequency and
distribution of DNA methylation with single base pair resolution. To see if our chemical
demethylating agents were efficacious, MethylC-seq was performed on seedlings that
were treated with 400 µM of 5-azacytidine and 40 µM of zebularine. These treatments
were administered before we had knowledge of the breakdown of 5-azacytidine in
aqueous solution. Plots were generated to examine the efficacy of these treatments,
mapping the percent methylation frequency in a visual form that makes identifying trends
easier (Fig. 4A). With more than half of all methylated cytosines being mapped at 100%
methylation, cytosines maintained as CG dinucleotides were found in the highest fidelity
in untreated control samples. In the 5-azacytidine treated sample, a significant reduction
of highly methylated sites was apparent, whereas, the raw number of methylated
cytosines found was hardly much different. Since MethylC-seq must survey a population
of cells due to limitations in the amount of DNA needed for the reaction (Schultz et al.,
2012), then this data suggests that the demethylating agents are acting on the majority of
methylated CG dinucleotides throughout the genome but not identically in each cell
throughout the population. In methylated cytosine of the CHH context, significantly less
(17.2%) base pairs were found to be methylated and a notable trend to less highly
methylated cytosines is also apparent. In general, RdDM methylation is maintained with
less fidelity than CG dinucleotides throughout a population of cells, therein, it is
unsurprising that demethylating agents would more drastically reduce the total number of
CHH sites methylated. In the zebularine sample, neither of these trends was observed;
however, a lower concentration of the chemical could have made it act more weakly than
the 5-azacytidine treatments. Having demonstrated that these treatments were, at the very
least, effective on seedlings grown on agar-solidified medium, we chose to proceed with
5-azacytidine in subsequent analysis.
To further investigate the effect of 5-azacytidine in high resolution, treatments
were redesigned to account for 5-azacytidine’s rapid degradation. Transferred regularly
to a freshly prepared plate, seedlings grown on 40 µM and 100 µM 5-azacytidine, as well
as, a control plate containing DMSO underwent MethylC-seq and were cross analyzed
against the 400 µM treated sample from the first treatments. Unfortunately, the 100 µM
treated sample was only sequenced to an average depth of 4.4 reads per base pair. With
such a low sequencing depth, even a single demethylated cytosine would cause a
dramatic change in the percent methylation; therefore, we decided to leave the 100 µM
treated sample out of subsequent analysis.
An examination of the genome-wide weighted methylation level reveals that a
reduction in methylation occurs in all contexts of methylation in comparison to a standard
untreated Col-0 sample (Fig 4B). Surprisingly, even the DMSO sample was found to
have drastically reduced DNA methylation. This finding warrants suspicion, as DMSO
has never been shown to have any effect on genomic methylation. The most likely
explanation is that during the MethylC-seq procedure, a contamination or sample mix-up
occurred. Regardless, it is apparent that the 5-azacytidine is an effective demethylating
agent, reducing the percent methylation by about half in the CG context and even more
9. 9
drastically in the CHG and CHH contexts genome wide. In addition, the difference in
weighted methylation was not substantially different between the 40 µM treatment and
the 400 µM treatment, suggesting that 40 µM of 5-azacytidine may be maximally
effective or the 5-azacytidine broke down in the 400µM treatments and this gradual
decrease in concentration lead to a similar amount of demethylation. Although this
finding needs further investigation, it is also possible that the MET-1 enzymes on which
5-azacytidine acts are saturated with the chemical at 40 µM, limiting the efficacy of the
drug to this lower concentration.
To examine the pattern of demethylation at a specific locus and compare it back
to the genome-wide effect, the same analysis was done on the 5’ UTR and promoter
region of FLOWERING WAGENINGEN (FWA). A repressor of floral transition, FWA is
epigenetically silenced by DNA methylation in adult A. thaliana and is commonly used
as a representative epiallele (Fujimoto et al., 2011 and Baubec et al., 2014). Although
methylated cytosines were more frequent in this region, a very similar pattern to the
whole-genome analysis is observed at FWA. All three contexts of cytosine DNA
methylation were reduced in the tissue, however, further investigation needs to be done in
analyzing any increase in efficacy with increase in concentration, as the difference
between in weighted methylation between the treated samples did not show an obvious
trend. Although analysis of more epialleles and genomic location is needed, such similar
decreases in methylation for both genome-wide and FWA weighted methylation levels
suggests that the drug acts without bias throughout the genome.
Discussion
Further investigation is still needed to understand the phenotypic effect of
cytosine DNA methylation in the promoter and 5’ UTR of SVPepi
in Dja-1. After
identifying it as a potential epiallele, hypermethylated in comparison to all other A.
thaliana accessions, RNA-seq data clearly showed its relatively low transcriptional
activity and complementation analysis demonstrated that the allele causing an early-
flowering phenotype was in fact SVP. These findings inspired investigation with
demethylating agents that are capable of transiently reducing cytosine DNA methylation.
It was hypothesized that if cytosine DNA methylation were inhibiting transcriptional
activity, using these chemicals would reactivate expression of SVPepi
and increase the
time until the floral transition of Dja-1 plants. In gathering data on both expression and
floral transition of treated Dja-1 plants, this was not observed and suggests that cytosine
DNA methylation is not the predominant cause of transcriptional inactivation.
There were, however, experimental design flaws that confound the results and
make it difficult to definitively say that methylation is not causing transcriptional
inactivation. Foremost was the oversight that 5-azacytidine breaks down quickly in
aqueous solution. Having failed to realize this, the first treatments with demethylating
agents are a serious source of inconsistency. Without changing out the agar solution with
freshly added 5-azacytidine (as was done in later treatments), it is impossible to know
how much the chemicals degraded and how steadily they acted on the seedlings.
MethylC-seq demonstrated that, at the very least, the 400 µM 5-azacytidine treatments
were working; however, whether the chemical concentration stayed close to 400 µM or
10. 10
was drastically less by the time the seedlings were planted cannot be known. Likewise,
the aliquots of 5-azacytidine solution used to treat the adult plants on their apical
meristem would have quickly degraded and become effectively useless after a week. In
the future, more effective strategies for treating the 5-azacytidine seedlings will be looked
at.
In addition, there is the high likelihood that MethylC-seq data collected for the
DMSO sample was contaminated, giving weighted methylation levels that would only be
expected in the presence of a demethylating agent and that strongly resembled the other
treated samples. The possibility that DMSO causes some inhibition of DNA methylation
enzymes cannot be dismissed outright; however, there is no precedent in the literature for
expecting it should and will warrant investigation going forward.
Notably, many of these experiments are not of publishable quality, needing
replication and revised methodology. Although we are yet unable to answer many of the
questions asked, much more was discovered in the process of trial and error and may be
of use in the future. The need for a studied and effective way to treat adult A. thaliana
with demethylating agents is clear, especially if they are going to be used in the future to
study epigenetic phenomenon in plants.
Other avenues of experimental design should also be investigated. Ideally,
removing the transposon from the 5’ UTR of SVPepi
would allow for unambiguous
investigation of whether or not it is causing the decrease in expression. One way of
removing the transposon would be to utilize the CRISPR-Cas system that efficiently
targets specific sequences in a variety of different organism including A. thaliana (Jiang
et al., 2013). Clustered regular short palindromic repeats (CRISPR) and the enzyme
CRISPR associated protein 9 (Cas9) has been adapted from the immune system of
Streptococcus pyogenes and developed as an efficient nuclease for targeting specific
genetic loci (Wiedenheft et al., 2012; Jinek et al., 2012). By designing two guide RNAs
(gRNA) that target the flanking regions of the transposable element in SVPepi
in Dja-1,
we could conceivably remove the TE. It would be interesting to observe, not only the
effect on flowering time and expression of SVPepi
, but also whether or not DNA
methylation was still present in the 5’ UTR of Dja-1 in progeny of the altered plants. In
addition, a similar experiment could be used to insert the transposable element into the 5’
UTR of SVP in a late-flowering FRI Col-0 plant to observe if it displays a similar
phenotype to Dja-1.
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Figures
Figure 1 | Identification of SVP as a potential epiallele
Screenshot from methylome browser comparing 8 accesions of A. thaliana with Dja-1 at the SVP (AT2G22540.1) locus. Vertical bars indicate cytosines found to be methylated and the height of the bars indicates the
percent of methylated cytosines mapped to that locus.
15. 15
2
6
10
14
18
Zebularine Control 5-azacytidine Control
TotalnumberofLeavesatFT
Effect of Demethylating Agents
on Floral Transition
A B
Figure 3 | The effect of chemical demethylating agents on expression of SVP and flowering time
(A) The effect of demethylating agents, 5-azacytidine and zebularine, on floral transition was quantified by first treating plants on agar-solified medium,
planting them, and counting the number of leaves present when the bud became visible (floral transtion, FT). 5-azacytidine treatments were at a concentra-
tion of 400 µM, whereas, zebularine was treated at a concentration of 40 µM.
(B) qRT-PCR was used to measure the expression of SVP to a houskeeping gene, CACS, which is expressed at similiar levels throughout all cells. 100 µM of
5-azacytidine were used to for the demethylating treatment and the untreated plants had DMSO added to account for the solvent of 5-azacytidine.
0.00
0.05
0.10
0.15
0.20
Treated Untreated
SVPExpressionRelativetoCACS
Effect of Demethylating Agents
on Relative Expression of SVP
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.4
5-azacytidine
CG 1,107,841
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.100.20
5-azacytidine
CHG 344,906
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.040.08
5-azacytidine
CHH 172,540
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.4
Zebularine
CG 1,416,704
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.100.20
Zebularine
CHG 523,294
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.040.08
Zebularine
CHH 543,949
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.00.20.4
Untreated
CG 1,248,812
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.100.20
Untreated
CHG 563,804
Percentage
0.0 0.2 0.4 0.6 0.8 1.0
0.000.040.08
Untreated
CHH 1,000,451
Percentage
A
0.00%
5.00%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
Untreated 40 µM 5-aza 400 µM 5-aza Untreated- DMSO
WeightedcytosineDNAmethylation
Genome-wide effect of demethylating agent
CG
CHG
CHH
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mCHG
mCHH
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mCHG
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B
Figure 4 | High resolution analysis of the effect of demethylateing agents via
MethylC-seq
(A) Percentage of methylated cytosines methylated at a given frequency in the
Col-0 wild type accession. Seedlings were treated with 400 µM 5-azacytidine or 40
µM of zebularine.
(B,C) The genome wide and FWA weighted methylation level of all three contexts
of DNA methylation shown side-by-side for comparison.
C
16. 16
Acknowledgements
Dr. Robert Schmitz is responsible for carrying out the initial observations and
collecting the data from Figure 1 and Figure 2. This work was completed with the help
and guidance of the entire Schmitz Lab including Dr. Chad Niederhuth, Dr. Xuiling Shi,
Dr. Adam Bewick, Lexiang Ji, Drexel Neumann, Brigitte Hofmeister, and Nicholas Rohr.
Further, thank you to Nick Morfey and Dr. David Nelson for helping collect and analyze
qRT-PCR from Figure 3.
