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Making a queen: An epigenetic analysis of the robustness of the honeybee (Apis mellifera) queen developmental pathway

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Specialised castes are considered a key reason for the evolutionary and ecological success of the social insect lifestyle. The most essential caste distinction is between the fertile queen and the sterile workers. Honey bee (Apis mellifera) workers and queens are not genetically distinct, rather these different phenotypes are the result of epigenetically regulated divergent developmental pathways. This is an important phenomenon in understanding the evolution of social insect societies. Here we studied the genomic regulation of the worker and queen developmental pathways, and the robustness of the pathways by transplanting eggs or young larvae to queen cells. Queens could be successfully reared from worker larvae transplanted up to 3 days age, but queens reared from older worker larvae had decreased queen body size and weight compared to queens from transplanted eggs. Gene expression analysis showed that queens raised from worker larvae differed from queens raised from eggs in the expression of genes involved in the immune system, caste differentiation, body development and longevity. DNA methylation levels were also higher in 3-day queen larvae raised from worker larvae compared to that raised from transplanted eggs identifying a possible mechanism stabilizing the two developmental paths. We propose that environmental (nutrition and space) changes induced by the commercial rearing practice result in a suboptimal queen phenotype via epigenetic processes, which may potentially contribute to the evolution of queen-worker dimorphism. This also has potentially contributed to the global increase in honeybee colony failure rates. This article is protected by copyright. All rights reserved.
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Making a queen: an epigenetic analysis of the
robustness of the honeybee (Apis mellifera) queen
developmental pathway
XU JIANG HE,* LIN BIN ZHOU,* QI ZHONG PAN,* ANDREW B. BARRON,W EI YU YA N * and
ZHI JIANG ZENG*
*Honeybee Research Institute, Jiangxi Agricultural University, Nanchang, Jiangxi 330045, China, Department of Biological
Sciences, Macquarie University, North Ryde, NSW 2109, Australia
Abstract
Specialized castes are considered a key reason for the evolutionary and ecological suc-
cess of the social insect lifestyle. The most essential caste distinction is between the
fertile queen and the sterile workers. Honeybee (Apis mellifera) workers and queens
are not genetically distinct, rather these different phenotypes are the result of epige-
netically regulated divergent developmental pathways. This is an important phe-
nomenon in understanding the evolution of social insect societies. Here, we studied
the genomic regulation of the worker and queen developmental pathways, and the
robustness of the pathways by transplanting eggs or young larvae to queen cells.
Queens could be successfully reared from worker larvae transplanted up to 3 days age,
but queens reared from older worker larvae had decreased queen body size and
weight compared with queens from transplanted eggs. Gene expression analysis
showed that queens raised from worker larvae differed from queens raised from eggs
in the expression of genes involved in the immune system, caste differentiation, body
development and longevity. DNA methylation levels were also higher in 3-day-old
queen larvae raised from worker larvae compared with that raised from transplanted
eggs identifying a possible mechanism stabilizing the two developmental paths. We
propose that environmental (nutrition and space) changes induced by the commercial
rearing practice result in a suboptimal queen phenotype via epigenetic processes,
which may potentially contribute to the evolution of queenworker dimorphism. This
also has potentially contributed to the global increase in honeybee colony failure rates.
Keywords: DNA methylation, epigenetic analysis, gene expression, honeybee, immunity, queen
Received 7 March 2016; revision received 12 December 2016; accepted 19 December 2016
Introduction
The evolution of cooperation, cooperative living and
animal societies has been an enduring subject of fasci-
nation for evolutionary biologists (Wilson 1975). Key
insights into the processes of social evolution have
come from studies of the advanced social insects (Eilson
1971; Andersson 1984; Robinson 1999). These have
shaped our understanding of the genetic and ecological
factors that can promote the evolution of sociality
(Queller & Strassmann 1998; Linksvayer & Wade 2005;
Foster et al. 2006). Oster and Wilson have particularly
emphasized the importance of caste in the evolution of
social insect societies (Oster & Wilson 1978). Different
castes within the society specialize on different func-
tions. This specialization promotes efficiencies, which
provides a key selective advantage to social living.
Oster & Wilson (1978) argue castes are one key reason
for the ecological success of the social insect lifestyle.
Queens and workers are the defining caste distinction
for the social insects. Queens have multiple morpholog-
ical and behavioural specializations for extreme fecun-
dity, whereas workers show a similar degree of
Correspondence: Zhi Jiang Zeng, Fax: +86 791 83828176;
E-mail: bees1965@sina.com
©2016 John Wiley & Sons Ltd
Molecular Ecology (2017) 26, 1598–1607 doi: 10.1111/mec.13990
specialization for social roles supporting the queens’
reproduction, and in many social insects workers are
sterile. This is the case for honeybees (Apis mellifera). A
typical colony contains a single reproductive queen sup-
ported by up to 50 000 sterile workers (Winston 1991).
Studies of the bee have shown how the distinction
between queens and workers is not genetic: rather these
two phenotypes are the outcome of different develop-
mental pathways (Nijhout 2003; Linksvayer et al. 2011).
Both queens and workers develop from fertilized
eggs, but differences in nutrition and the amount of
food given to young larvae trigger different epigeneti-
cally regulated developmental pathways (Kucharski
et al. 2008; Maleszka 2014; Maleszka et al. 2014).
Kucharski et al. (2008) reported that nutritional differ-
ences between queen and worker at their larval stage
control their development via DNA methylation. Shi
et al. (2011) showed that the amount of space in which
a larva can develop alters the DNA methylation level of
the larval genome and contributes to the process of
caste differentiation. Changes in gene regulation caused
by these epigenetic mechanisms then establish diver-
gent developmental paths (Simola et al. 2013), involving
particularly genes involved in signal transduction,
gland development and carbohydrate metabolism
(Woodard et al. 2011).
Since the 19th century in commercial beekeeping, it
has been a standard practice to raise queens by trans-
planting eggs or young larvae into artificial queen cells,
which triggers workers to raise a queen (Doolittle 1888;
B
uchler et al. 2013). Within the commercial queen-rear-
ing practice, there is variation in the age at which eggs
or worker larvae are transplanted to queen cells to be
raised as queens. It is not clear how well the honeybees’
developmental processes are able to tolerate this kind
of intervention. Woyke (1971) reported that rearing
queens from young worker larvae resulted in decreased
body size, a smaller spermatheca and fewer ovarioles.
Rangel et al. (2012) reported that colonies from queens
reared from older worker larvae had significantly lower
production of worker comb, drone comb and stored
food compared with colonies from queens reared from
young worker larvae. In fact, concern over the long-
term consequences of commercial queen rearing for bee
stocks is not new. In 1923, Rudolf Steiner predicted that
honeybees would become extinct within 100 years as a
consequence of commercial queen rearing progressively
weakening bee stocks (Thomas 1998). In the current
environment of increased honeybee colony failure rates,
mass deaths of colonies and declining honeybee stocks,
there is a great deal of concern as to whether a decline
in queen bee quality might be a factor in these prob-
lems (van Engelsdorp et al. 2010; Delaney et al. 2011).
Therefore, we hypothesize that environmental (nutrition
and space) changes induced by the commercial rearing
practice may potentially affect queen development via
epigenetic processes. Here, we explored the conse-
quence of age of transplant from worker cells to queen
cells on DNA methylation, gene expression and queen
morphology. We found that the domestic rearing prac-
tice altered queen morphology and induced epigenetic
changes in developing queens, which supports our
hypothesis.
Materials and methods
Three European honeybee colonies (Apis mellifera) each
with a single drone inseminated queen (SDI) were used
throughout this study. These colonies were maintained
at the Honeybee Research Institute, Jiangxi Agricultural
University, Nanchang, China (28.46 uN, 115.49 uE),
according to the standard beekeeping techniques.
Queen-rearing methods
Queens were restricted for 6 h to a plastic honeybee
frame developed by Pan et al. (2013) for laying. The
frame is designed such that the plastic base of this
frame with eggs or larvae can be transferred to plastic
queen cells directly (Pan et al. 2013). Eggs that queen
laid in worker cells were transplanted into queen cells
for rearing new queens when eggs were less than 6 h
old (QWE). For the other experimental groups, day 1,
day 2 and day 3 worker larvae were transplanted into
queen cells for rearing QWL1, QWL2 and QWL3,
respectively. Queen cells with worker eggs or larvae
were returned into their natal colonies (the SDI colo-
nies) for queen rearing.
For the morphological measurements, new emerging
queens were collected and their weight measured using
an analytical balance (FA3204B; Shanghai Precision Sci-
entific Instrument Co., Ltd.). Their thorax width and
length were measured with a zoom stereo microscope
system (Panasonic Co., Ltd.) according to the manufac-
turer’s instructions.
For epigenetic analysis, we sampled 3-day-old larvae
from QWE, QWL1 and QWL2, respectively, from their
queen cell. The fourth group QWL3 sampled 3-day-old
worker larvae directly from worker cells. Each sample
group collected three larvae and there were three bio-
logical replicates, each from different colonies, for each
group. We weighed each larva from these four treat-
ment groups with an analytical balance. All samples
were immediately flash-frozen in liquid nitrogen. The
DNA and RNA from each sample were both extracted
for further DNA methylation and RNA sequencing
analysis. DNA and RNA were extracted from the same
samples.
©2016 John Wiley & Sons Ltd
EPIGENETIC CHANGES IN HONEYBEE QUEEN REARING 1599
RNA-Seq analysis
Total RNA was extracted from larvae according to the
standard protocol for the TRIzol reagent (Life technolo-
gies, California, USA). RNA integrity and concentration
were checked using an Agilent 2100 Bioanalyzer (Agi-
lent Technologies, Inc., Santa Clara, CA, USA).
mRNA was isolated from total RNA using a NEB-
Next Poly(A) mRNA Magnetic Isolation Module (NEB,
E7490). A cDNA library was constructed following the
manufacturer’s instructions for the NEBNext Ultra RNA
Library Prep Kit (NEB, E7530) and the NEBNext Multi-
plex Oligos (NEB, E7500) from Illumina. In brief,
enriched mRNA was fragmented into approximately
200 nt RNA inserts, which were used as templates to
synthesize the cDNA. End-repair/dA-tail and adaptor
ligation were then performed on the double-stranded
cDNA. Suitable fragments were isolated by Agencourt
AMPure XP beads (Beckman Coulter, Inc.) and enriched
by PCR amplification. Finally, the constructed cDNA
libraries were sequenced on a flow cell using an Illu-
mina HiSeq
TM
2500 sequencing platform.
Low-quality reads, such as adaptor-only reads or
reads with >5% unknown nucleotides, were filtered
from subsequent analyses. Reads with a sequencing er-
ror rate less than 1% (Q20 >98%) were retained. These
remaining clean reads were mapped to the honeybee
(A. mellifera) official genes (OGSv3.2) using TOPHAT2
(Kim et al. 2013) software. The aligned records from the
aligners in BAM/SAM format were further examined to
remove potential duplicate molecules. Gene expression
levels were estimated using FPKM values (fragments
per kilobase of exon per million fragments mapped) by
the CUFFLINKS software (Trapnell et al. 2010).
DESeq2 and Q-value statistical methods were used to
evaluate differential gene expression among the four
experimental treatments (Love et al. 2014). The false dis-
covery rate (FDR) control method was used to deter-
mine the appropriate threshold of P-values in multiple
tests comparing gene expression differences by read
counts. Only genes with an absolute value of log2 ratio
1 and FDR significance score <0.05 were used for sub-
sequent analysis. However, gene expression levels of
each gene in all samples were presented using their
ratio of FPKM values.
Sequences differentially expressed between sample
groups were identified by comparison against various
protein databases by BLASTX, including the National Cen-
ter for Biotechnology Information (NCBI) nonredundant
protein (Nr) database, SWISS-PROT database with a cut-
off E-value of 10
5
. Furthermore, genes were searched
against the NCBI nonredundant nucleotide sequence (Nt)
database using BLASTNby a cut-off E-value of 10
5
.
Differentially expressed genes (DEGs) were mapped to
KEGG protein database by BLAST (E-value <1e-5) and
used KOBAS 2.0 software to test the statistical enrichment
of differential expression genes in KEGG pathways (Xie
et al. 2011).
DNA Methylation analysis by bisuphite sequencing
The DNA of each larval sample was extracted using the
Universal Genomic DNA Extraction Kit (DV811A;
TaKaRa). DNA concentration was measured and
adjusted to the same level. Genomic DNA was sheared
with Covaris ultrasonicator (Life Technology). The frag-
mented DNA was purified using AMPure XP beads
and end-repaired. A single ‘A’ nucleotide was added to
the 30ends of the blunt fragments followed by ligation
to methylated adapter with T overhang. 200- to 300-bp
insert size targets were purified by 2% agarose gel elec-
trophoresis. Bisulphite conversion was conducted using
a ZYMO EZ DNA Methylation-GoldTM Kit (ZYMO,
Irvine, CA, USA). The final libraries were generated by
PCR amplification. Bisulphite libraries were analysed
by an Agilent2100 Bioanalyzer (Agilent Technology)
and quantified by QPCR (Agilent QPCR NGS Library
Quantification Kit). The construction of bisulphite
libraries and paired-end sequencing using Illumina
HiSeqTM 2500 (Illumina, San Diego, CA, USA) were
performed at Beijing Biomarker Technology Co., Ltd
(Beijing, China).
After filtering adaptor sequences and PCR-duplicated
reads, genomic fragments from bisulphite libraries were
mapped against the honeybee genome (A. mellifera.
Amel 4.5) using BOWTIE 2 software (Langmead & Salz-
berg 2012). The bismark methylation extractor (Krueger
& Andrews 2011) was used to predict all methylation
sites. Only uniquely mapped reads were retained. The
ratio of C to CT was used to indicate methylation level.
Three methods for DNA methylation level analysis
were used: fraction of methylated cytosines, mean
methylation level and weighted methylation level
(Schultz et al. 2012). The results are presented in Fig. S8
(Supporting information).
Data analysis
Morphological analysis of queens and 3-day-old queen lar-
vae. All data from morphological experiments of each
group were analysed by ANOVA using STATVIEW 5.01 fol-
lowed by a Fisher’s PLSD test (SAS Institute, Cary, NC,
USA).
Correlation analysis between expression and methylation and
map construction of genes and chromosome. Methylated
regions were deemed significantly differentially methy-
lated across QWE, QWL1, QWL2 and QWL3 with a
©2016 John Wiley & Sons Ltd
1600 X. J. HE ET AL.
false discovery rate (FDR) <0.05 and log2 fold change
1.5 in sequence counts using the BSmooth method in R
package 3.1.1 (Hansen et al. 2012). Significantly different
methylated regions (DMRs) of each gene were mapped
to the 16 honeybee chromosomes regions (A. mellifera.
Amel 4.5) using integrative genomics viewer (IGV,
http://www.broadinstitute.org/igv/).
Analysis of RNA-Seq quality and DNA methylation sequenc-
ing. In RNA-Seq, four libraries were generated from
our experimental groups, and summaries of RNA
sequencing analyses are shown in Table S1 (Supporting
information). In each library, more than 98% clean reads
were unique reads of which more than 89% reads were
paired reads. Very few clean reads (<1.4%) were multi-
ple mapped reads. Each library had a sufficient cover-
age of the expected number of distinct genes (stabilized
at 3M reads, Fig. S1, Supporting information). The Pear-
son correlation coefficient among three biological repli-
cates of each experimental group was all 0.80 (Table S2,
Supporting information), a conventionally accepted
threshold for valid replicates (Tarazona et al. 2011), indi-
cating that there was acceptable sequencing quality and
repeatability among the biological replicates of each
group. The majority of methylation sites of all samples
(77.55%) were the CG type, which was considerably more
than other two types (CHH: 20.5% and CHG: 1.95%
respectively; Fig. S2, Supporting information).
Results
As the age of transplant of the worker larvae increased,
the size and mass of the emergent adult queen decreased
(Fig. 1). QWE had the highest thorax length (4.90 0.24
mm, mean SE), thorax width (4.78 0.21 mm,
mean SE) and weight (267.21 2.49 mg, mean SE),
whereas the QWL3 had lowest, with 4.60 0.13 mm,
4.45 0.26 mm and 226.00 2.82 mg, respectively. All
morphological indices were differed significantly across
the four treatments (P<0.05, ANOVA test followed with
Fisher’s PLSD test).
RNA-Seq analyses comparing gene expression
between QWE and the three larvae-transplanted groups
(QWL1, QWL2 and QWL3) showed that the number of
differentially expressed genes increased as the age of
the transplanted worker larva increased (Fig. 2 and
Fig. S3, Supporting information). In all comparisons, the
differentially expressed genes contained a high propor-
tion of genes involved in immunity, body development,
metabolism, reproductive ability and longevity (Fig. 2
and Table S3, Supporting information). In particular,
one of cytochrome P450 family gene (CYP450 6a14-like)
was significantly upregulated in QWL1 compared
QWE; Six of ten immunity-related DEGs such as
CYP450 6a14-like and CYP450 305a1 were upregulated
in QWL2 compared with QWE, whereas seven of ten
body development-related genes were downregulated
in QWL2; In QWL3 and QWE comparison, 13 of 23
immunity-related DEGs were upregulated in QWL3
while 29 of 41 body development-related genes were
downregulated in QWL3, respectively. Interestingly, the
hormone biosynthesis genes [vitellogenin precursor (Vg),
juvenile hormone esterase precursor (JH), juvenile hormone
esterase-like (JH-like) and ecdysteroid-regulated 16 kDa pro-
tein-like] were upregulated in QWL3 compared with
QWE, whereas the major royal jelly protein 1 (MRJP1)
was downregulated in QWL3 (Table S3, Supporting
information). Similarly, the results of GO enrichment
analysis showed that the number of categories of DEGs
enriched between the QWE group and the other experi-
mental groups increased with the increasing age of the
grafted larva: from 27 categories (QWL1 vs. QWE) to 33
(QWL2 vs. QWE) and 44 (QWL3 vs. QWE), respectively
(Fig. S4S6, Supporting information). Categories of DEG
included growth, development process, reproductive
process and immune system process. The results of
Fig. 1 (A) Mean (+SE) weight of new born queens and 3-day-
old queen larvae, (B) Mean (+SE) thorax width and length of
new born queens, from QWE (open), QWL1 (grey), QWL2
(black) and QWL3 (diagonal stripes). Different letters above
each bar indicate significant differences (P<0.05, ANOVA test
followed with Fisher’s PLSD test).
©2016 John Wiley & Sons Ltd
EPIGENETIC CHANGES IN HONEYBEE QUEEN REARING 1601
COG enrichment analysis showed a similar pattern in
that the number of categories between QWE and QWLs
increased with their grafting age (Fig. S7, Supporting
information).
Furthermore, queens from older grafted worker larvae
had a higher global DNA methylation level than QWE
(Fig. S8 and Table S4, Supporting information). The
QWE vs. QWL3 (totally 146 DMRs) comparison had the
greatest number of differentially methylated regions
(DMRs) than QWE vs. QWL2 (108) and QWE vs. QWL1
(99) comparisons (Fig. 4). Mapping these DMRs to gene
regions identified 2, 6 and 23 differentially methylated
genes in the QWE vs. QWL1, QWE vs. QWL2 and QWE
vs. QWL3 comparisons, respectively, and no gene was
overlapped among these three comparisons. These genes
were different from the DEGs identified by RNA-Seq.
Most of them were involved in substance metabolism
(Table S5, Supporting information). A correlation analy-
sis of gene expression and DNA methylation developed
by (Lou et al. 2014) (Fig. S9, Supporting information)
suggested a very weak correlation between DNA methy-
lation and gene expression in honeybees for all compar-
isons (Pearson correlation values were 0.0018, 0.0016,
0.004 and 0.0034 in QWE, QWL1, QWL2 and QWL3,
respectively, and all P-values were >0.05). We also com-
pared the expression of DGEs involved in immune sys-
tem and hormone biosynthesis and their DNA
methylation among the four treatment groups. The dif-
ference in expression of these genes increased as the dif-
ference in age of the transplanted larvae increased
(Fig. 3) (greater when comparing QWE vs. QWL3 than
when comparing QWE vs. QWL1), but the DNA methy-
lation of very few of these genes showed a clear nega-
tive correlation with expression (Fig. 3 and Table S6,
Supporting information).
Discussion
Honeybee workers and queens are two very different
phenotypes that come about as a result of divergent
developmental pathways. Environmental differences in
growing space and nutrition cause the divergence, and
the two pathways are organized by epigenetic processes
(Haydak 1970; Shi et al. 2011; Foret et al. 2012). Here,
we explored the mechanisms and stability of the queen
developmental path by transplanting worker larvae of
different ages into queen cells causing a redirection of
the worker developmental path onto the queen devel-
opmental path.
Our results speak to both the plasticity and limita-
tions of honey bee phenotypic plasticity. While it is
known that worker larvae that are more than 3.5 days
old when transplanted fail to develop into queens
(Weaver 1966), here we found that transplanting even
3-day-old worker larvae to queen cells resulted in func-
tional adult queens, but with reduced size and weight.
Moreover, our results showed that the number of differ-
entially expressed genes in QWLs compared with QWE
(Fig. 2) increased with the age of the transplanted lar-
vae. Many of these genes were involved in immunity,
body development, metabolism, reproductive ability
and longevity (Fig. 2 and Table S3, Supporting informa-
tion). These are all functions that differentiate queens
from workers and are critical to the quality and longev-
ity of the queen. We also showed that queens raised
from transplanted older worker larvae had a higher glo-
bal genomic DNA methylation level when compared to
QWE (Table S4, Supporting information) identifying a
possible epigenetic mechanism for these differences. In
summary, we could conclude that the queen develop-
mental pathway is quite robust. The queen phenotype
Fig. 2 Significantly differentially expressed genes in three com-
parisons. Genes were identified as differentially expressed if
both the FDR <0.05, and the absolute value of the log2 fold
change was 1. Genes involved in immunity (yellow), body
development (green), reproduction or longevity (purple) and
other functions (open bars) are shown. Top bars represent
upregulated genes in QWE compared with other groups.
Lower bars are downregulated genes.
©2016 John Wiley & Sons Ltd
1602 X. J. HE ET AL.
could be attained even by 3-day-old worker larvae (the
larval developmental period is just 5 days long) and
therefore developmental trajectory is certainly not fixed
until relatively late in larval development. However,
interfering with the normal developmental process by
switching larvae from a worker to a queen path clearly
had consequences for the resulting adults that were
detectable at morphological and genetic levels.
Our study identified many genetic and epigenetic
changes related to the age at which worker larvae were
transplanted to queen cells to be raised as queens
(Figs 2 and 4 and Table S3 and S4, Supporting informa-
tion). Of note, the differentially expressed genes
included insulin-like peptide A chain (ILP-A), a gene
involved in the mTOR pathway. The mTOR pathway is
involved in queen ovary development, and caste differ-
entiation (Patel et al. 2007; de Azevedo & Hartfelder
2008; Mutti et al. 2011). The ILP-A was significantly
downregulated in QWL3 compared with QWE. Hence,
this identifies a candidate pathway for why transplant
age alters adult queen ovariole number and spermath-
eca size (Woyke 1971). The gene MRJP-1 (downregu-
lated in QWL3 compared with QWE), JH (upregulated
in QWL3) and Vg (upregulated in QWL3) were also dif-
ferentially expressed between QWE and QWL3. These
genes are also involved in the regulation of honeybee
caste differentiation and longevity (Amdam & Omholt
2002; Kamakura 2011), perhaps indicating why queens
from late-stage larval grafts are undersized. The GO
enrichment results also confirmed this result that DEGs
between QWE and QWLs were enriched in growth,
reproductive and development processes (Fig. S4S6,
Supporting information).
Previous studies have demonstrated that DNA
methylation is widespread in social Hymenoptera
(Kronforst et al. 2008; Kucharski et al. 2008; Lyko &
Fig. 3 Expression and DNA methylation
of 38 immunity- and hormone-related
genes among QWE, QWL1, QWL2 and
QWL3. These genes were identified by
their functions in immunity or hormone
biosynthesis and were at least signifi-
cantly differentially expressed between
one comparison of QWE and QWLs. The
ratio of gene expression in QWLs against
QWE was used for presenting the
expression level of each gene. Green
indicates downregulation in QWLs com-
pared with QWE, red indicates upregula-
tion, and black indicates no difference.
Left side is the gene ID and gene func-
tion, middle is the ratio of gene expres-
sion of each gene, and right is the ratio
of DNA methylation for each gene. More
detailed information of these 38 refers to
Table S6 (Supporting information).
©2016 John Wiley & Sons Ltd
EPIGENETIC CHANGES IN HONEYBEE QUEEN REARING 1603
Maleszka 2011; Foret et al. 2012). While the level of
DNA methylation in honeybees is quite low compared
with mammals, differential methylation of the genome
has a key role in establishing the divergent worker and
queen developmental pathways (Wang et al. 2006;
Gabor Miklos & Maleszka 2011; Shi et al. 2013; Mal-
eszka 2014). We found that increasing the age at which
worker larvae were transplanted to queen cells resulted
in an increasing number of differentially methylated
regions of the genome. We propose this reflects the epi-
genetic processes underlying the reorientation of a
worker-destined developmental pathway to a queen
developmental pathway.
There was not a strong negative correlation between
the gene expression and DNA methylation in this study
(Fig. S9, Supporting information); however, in honey-
bees most methylation sites are located in gene body
regions rather than the upstream and downstream regu-
latory regions (Fig. S8, Supporting information). Foret
et al. (2012) showed that honeybee DNA methylation is
correlated with gene alternative splicing. Table S7, Sup-
porting information showed that the alternative splicing
also exists in differentially methylated genes. It is still
unclear what role these DNA methylation have for
gene expression, although DNA methylation plays an
important role in the regulation of honeybee caste
differentiation (Wang et al. 2006; Gabor Miklos & Mal-
eszka 2011; Shi et al. 2013; Maleszka 2014). Our results
lend further credence to the view that the functions of
DNA methylation of sites in gene body regions in
hymenoptera have more complex functions than simply
inhibiting expression.
In commercial apiculture, rearing queens from trans-
planted worker larvae is a standard commercial prac-
tice, and the age of the worker larvae used can be
anything up to and including 3 days old. In practice,
there is a preference to use older worker larvae for
transplant as these are more hardy and easier to handle
and give a higher success rate. But these larvae will
have been fed worker jelly (brood food) rather than
queen jelly in their early life. Worker jelly is a very dif-
ferent diet to queen jelly. It differs in sugar content
(Asencot & Lensky 1977), amino acid (Brouwers 1984),
vitamin (Brouwers et al. 1987), juvenile hormone (Asen-
cot & Lensky 1984) and major royal jelly protein content
(Kamakura 2011). Therefore, the commercial queen-rear-
ing practice alters the nutritional environment of the
queen larvae, likely resulting in development and epi-
genetic changes. This is consistent with the previous
studies that nutritional differences control the caste dif-
ferentiation of queen and workers by DNA methylation
(Kucharski et al. 2008; Shi et al. 2011).
Fig. 4 Distribution of significantly differ-
entially methylated regions (DMRs) from
three comparisons for the 16 honeybee
chromosomes. DMRs were deemed sig-
nificantly differentially methylated across
QWE, QWL1, QWL2 and QWL3 with a
false discovery rate (FDR) <0.05 and log2
fold change 1.5 in sequence counts. The
DMRs of QWE/QWL1, QWE/QWL2 and
QWE/QWL3 comparisons are presented
from outer to inner, respectively. Red
plots are upregulated DMRs in QWE
compared with other three groups,
whereas green plots are downregulated
ones. Chromosome name and scale are
indicated on the outer rim.
©2016 John Wiley & Sons Ltd
1604 X. J. HE ET AL.
There have been long-standing concerns about the
consequences of this queen-rearing method for queen
quality and colony productivity (Woyke 1971; Thomas
1998; Rangel et al. 2012). Our results have clearly shown
that queens raised from older worker larvae are smal-
ler, and it is also telling that we found a difference in
expression between several genes involved in immune
function between QWE and QWLs (Fig. 2, Table S3,
and Fig. S4S6, Supporting information for GO enrich-
ment results). These included the Cytochrome P450 fam-
ily (CYP450s, 11 of 15 were upregulated in QWL3
compared with QWE).CYP450s may contribute to both
disease and insecticide resistance in queen honeybees
(Claudianos et al. 2006; Boncristiani et al. 2012). We pro-
pose that queens reared from older larvae may suffer
reduced immune function and insecticide resistance.
Evolutionary theories on the development of eusocial-
ity demonstrated that maternal care (nutrition and
developmental space) dramatically contribute to the
evolution of queenworker dimorphism in honeybees
(Linksvayer et al. 2011; Leimar et al. 2012). Our study
clearly showed that the domestic rearing practice artifi-
cially transformed the nutrition and developmental
space of queen larvae and resulted in a partial inter-
caste between queen and workers. In Leimar’s model
(2012), honeybee caste dimorphism is produced by
maternal care rather than a switch-controlled polyphen-
ism, and our results are consistent with this model. We
also demonstrated that the domestic rearing practice
altered natural honeybee maternal behaviour, inducing
various epigenetic changes. This is particularly interest-
ing as epigenetic changes such as DNA methylation can
introduce environmental effects into the following
generations (Bird 2002; Klironomos et al. 2013) and
potentially influence evolutionary processes (Dickins &
Rahman 2012). If it is possible for epigenetic markers of
the genome to persist through gamete formation and
operate transgenerationally in honeybees, as occurs in
some mammals (Klironomos et al. 2013), then the evolu-
tion of queenworker dimorphism might be influenced
by these mechanisms. Moreover, we propose that the
often used commercial queen-rearing practice results in
queens of lower quality. As a proximal remedy, rearing
queens from eggs or very young larvae may yield a better
outcome for queen performance and colony function.
Acknowledgements
We thank Dr. Ying Wang for suggesting on experimental
design, Mr. Xue Chuan Zhang and Li Sha Huang for helping
on epigenetic data analysis. This work was supported by the
National Natural Science Foundation of China (No. 31572469
and No. 31460641) and the Earmarked Fund for China Agricul-
ture Research System (CARS-45-KXJ12).
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©2016 John Wiley & Sons Ltd
1606 X. J. HE ET AL.
Z.J.Z. designed the experiments; X.J.H., L.B.Z. and
Q.Z.P. performed the experiments; X.J.H., A.B.B. and
W.Y.Y. analysed the data; and X.J.H., A.B.B. and Z.J.Z.
written the paper. We have declared that no conflict of
interests exist.
Data accessibility
The raw data for queen morphology are available from
the Dryad Digital Repository: https://doi.org/10.5061/
dryad.bg4t9. The raw Illumina sequencing data are acces-
sible through NCBI’s database: RNA-Seq and DNA meth
ylation data of QWE: NCBI Bioproject: PRJNA308280/
SAMN04390202. RNA-Seq and DNA methylation data of
QWL1: NCBI Bioproject: PRJNA308280/SAMN04390203.
RNA-Seq and DNA methylation data of QWL2: NCBI
Bioproject: PRJNA308280/SAMN04390236. RNA-Seq
and DNA methylation data of QWL3: NCBI Bioproject:
PRJNA308280/SAMN04390201.
Supporting information
Additional supporting information may be found in the online ver-
sion of this article.
Fig. S1 The saturation curve of RNA-Seq in each sample.
Fig. S2 Average distribution of three methylation types in
3-day-old queen larvae.
Fig. S3 Volcano plots of gene expression in three comparisons.
Fig. S4 Gene ontology classification of DEGs between QWE
and QWL1.
Fig. S5 Gene ontology classification of DEGs between QWE
and QWL2.
Fig. S6 Gene ontology classification of DEGs between QWE
and QWL3.
Fig. S7 COG enrichment analysis of DEGs between QWE and
QWLs.
Fig. S8 DNA methylation level of protein coding genes in four
groups: QWE (blue), QWL1 (green), QWL2 (lavender) and
QWL3 (red).
Fig. S9 Correlation analysis of gene expression and DNA
methylation.
Table S1 Summary of DGE profiles and their mapping to the
reference genes.
Table S2 Pearson correlation coefficient among three biological
replicates of each group.
Table S3 Significantly differentially expressed genes in three
comparisons.
Table S4 Summary of DNA methylation sites of each sample.
Table S5 Differentially methylated genes between QWLs
(QWL1, QWL2 and QWL3) and QWE.
Table S6 Gene expression and DNA methylation of 38 selected
genes in four treatments.
Table S7 The Alternative splicing sites in differentially methy-
lated genes between QWLs and QWE.
©2016 John Wiley & Sons Ltd
EPIGENETIC CHANGES IN HONEYBEE QUEEN REARING 1607
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In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.