Expression in Aneuploid Drosophila S2 Cells
Yu Zhang1, John H. Malone1, Sara K. Powell2, Vipul Periwal3, Eric Spana4, David M. MacAlpine2, Brian
1Laboratory of Cellular and Developmental Biology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland,
United States of America, 2Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, North Carolina, United States of America,
3Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of
America, 4Department of Biology, Duke University, Durham, North Carolina, United States of America
Extensive departures from balanced gene dose in aneuploids are highly deleterious. However, we know very little about the
relationship between gene copy number and expression in aneuploid cells. We determined copy number and transcript
abundance (expression) genome-wide in Drosophila S2 cells by DNA-Seq and RNA-Seq. We found that S2 cells are aneuploid
for .43 Mb of the genome, primarily in the range of one to five copies, and show a male genotype (, two X chromosomes
and four sets of autosomes, or 2X;4A). Both X chromosomes and autosomes showed expression dosage compensation. X
chromosome expression was elevated in a fixed-fold manner regardless of actual gene dose. In engineering terms, the
system ‘‘anticipates’’ the perturbation caused by X dose, rather than responding to an error caused by the perturbation. This
feed-forward regulation resulted in precise dosage compensation only when X dose was half of the autosome dose.
Insufficient compensation occurred at lower X chromosome dose and excessive expression occurred at higher doses. RNAi
knockdown of the Male Specific Lethal complex abolished feed-forward regulation. Both autosome and X chromosome
genes show Male Specific Lethal–independent compensation that fits a first order dose-response curve. Our data indicate
that expression dosage compensation dampens the effect of altered DNA copy number genome-wide. For the X
chromosome, compensation includes fixed and dose-dependent components.
Citation: Zhang Y, Malone JH, Powell SK, Periwal V, Spana E, et al. (2010) Expression in Aneuploid Drosophila S2 Cells. PLoS Biol 8(2): e1000320. doi:10.1371/
Academic Editor: Peter B. Becker, Adolf Butenandt Institute, Germany
Received September 23, 2009; Accepted January 20, 2010; Published February 23, 2010
This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public
domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Funding: This work was supported by the The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Intramural Research Program, National
Human Genome Research Institute (NHGRI) extramural grant HG004279, and a Whitehead Foundation Scholar Award. The funders had no role in study design,
data collection and analysis or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Abbreviations: CGH, comparative genome hybridization; ChIP, chromatin immunoprecipitation; CPA, Bayesian change point analysis; dsRNA, double stranded
RNA; MSL, male specific lethal; RPKM, reads per kb per million reads; RNAi, RNA interference
* E-mail: email@example.com
The somatic cells of multicellular animals are almost exclusively
diploid, with haploidy restricted to post-meiotic germ cells. Having
two copies of every gene has an obvious advantage. Mutations
arise de novo within cells of an organism and within organisms in
populations, such that deleterious mutation-free haploid genomes
are extremely rare. The wild type alleles of genes tend to be
dominant to the recessive loss-of-function alleles, providing a
degree of redundancy allowing diploid organisms to survive even
with a substantial genetic load of deleterious mutations in each
While the dose of most individual genes is of little consequence
to the organism, larger scale genomic imbalance, or aneuploidy, is
detrimental [1–4]. Chromosomal aneuploidy occurs when whole
chromosomes are lost or duplicated and segmental aneuploidy
results from deletions, duplications, and unbalanced transloca-
tions. In Drosophila, a systematic genome-wide segmental aneu-
ploidy study  demonstrated that of all genes (now known to be
about 15,000 ), only about 50 are haploinsufficient and just one
gene is triplo-lethal. However, these same experiments showed
that large deletions and duplications result in reduced viability and
fertility that depends on the extent of aneuploidy, and not on any
particular region or gene . This indicates that the detrimental
effect of aneuploidy is a collective function of multiple small effects,
not a function of particular genes.
Interestingly, while aneuploidy results in inviability at the
organism level, aneuploid cells can out-compete diploid cells for
growth in vivo or in vitro. Human cancer cells are a good example
of proliferating cells characterized by aneuploidy . Most tumors
are nearly diploid or tetraploid with extra or lost chromosomes.
Even tumors with a normal number of chromosomes contain
other rearrangements that result in segmental aneuploidy. It is
likely that aneuploidy results in a systems or gene interaction
defect. Given that a deleterious effect of aneuploidy is likely to
occur at the level of genome balance, understanding the response
to aneuploidy requires the exploration of general control
mechanisms that operate at the network level.
We have turned to widely used Drosophila S2 tissue culture cells
as an aneuploid model [8,9]. These cells are generally tetraploid
 and studies of gene expression and X chromosome dosage
compensation indicate that they are male . As a natural
consequence of chromosomal sex determination in Drosophila,
females have two X chromosomes and two pairs of autosomes
(2X;2A) and males have a single X chromosome (1X;2A) .
Therefore, male cells can be thought of as naturally occurring
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chromosomal aneuploids. The response to altered gene dose
probably occurs at multiple levels, but transcription is an early step
in the flow of information from the genome and is a likely site for
control. For example, X chromosome dosage compensation
clearly occurs at the transcriptional level  and is exquisitely
The Male Specific Lethal (MSL) complex regulates the
balanced expression of X chromosomes in wild type 1X;2A male
flies. MSL is composed of at least four major proteins (Msl1, Msl2,
Msl3, and Mof) and two non-coding RNAs (RoX1 and RoX2)
. Mof is an acetyltransferase responsible for acetylating
H4K16 [11,14,15]. Mof is highly enriched on the male X
chromosome as a component of the MSL complex. However, Mof
also associates with a more limited repertoire of autosomal genes
independently of MSL . H4K16ac is associated with increased
transcription in many systems . Therefore, it is widely believed
that this acetylation results in increased expression of the X
chromosome , although an alternative hypothesis suggests that
MSL sequesters Mof from the autosomes to drive down autosome
expression . Determining which of these mechanisms occurs is
complicated by the very nature of sampling experiments when
much of the transcriptome is altered. The number of X
chromosome transcripts sampled from the transcriptome depends
on the relative abundance of the X chromosome and autosome
transcripts. The salient feature of both models is balanced X
chromosome and autosome expression.
While the term dosage compensation is used to describe X
chromosome expression, dosage compensation is not restricted to
X chromosomes in Drosophila. Autosomes also show significant, but
much less precise, dosage compensation at the expression level
[13,19–21], suggesting that there is a general dose response
genome-wide. Despite the clear role of MSL in X chromosome
dosage compensation, the control system rules for MSL function
and the contribution of global compensation mechanisms to the
specific case of the X chromosome are poorly understood.
There are three basic transcript control mechanisms that could
modify the effect of gene dose: buffering, feedback, and feed-
forward . Here we define buffering as the passive absorption of
gene dose perturbations by inherent system properties. For
example, if transcription obeys mass-action kinetics and the
gene/transcription complex is considered an enzyme , then
one would not expect a one-to-one relationship between mRNA
and gene copy because of the small effect of a change in enzyme
concentration at steady-state . In addition to the enzymatic
properties of transcription, more than a generation of molecular
biologists has elegantly described extensive transcriptional regula-
tion networks controlling key phenotypes . These regulatory
motifs are sensitive to changes in gene dose . Feedback is an
outstanding error-controlled regulator that detects deviations from
the norm and implements corrective action. Feed-forward
regulation differs in that it anticipates the possible effect of
perturbations on the system rather than correcting the perturba-
tion after the deviation occurs. This could operate if cells detect
copy number and correct transcription levels before a quantitative
error in transcript abundance is evident.
In male embryos, the sex determination hierarchy detects X
chromosome number and leads to association of the MSL complex
with the X chromosome before zygotic transcription is activated
, as expected for a feed-forward regulator. However, MSL is
selectively bound to transcribed genes , which is also consistent
with feedback regulation. By examining the response of X
chromosome genes to dose in the presence and absence of MSL,
we show that X chromosome dosage compensation results from a
combination of MSL-dependent feed-forward regulation based on
anticipated effects from unbalanced gene dose and a more general
and dynamic response to perceived gene dose. The latter could be
due to negative feedback, buffering, or both.
Segmental Aneuploidy in S2 Cells
To determine the extent of aneuploidy in S2 cells, we performed
next generation sequencing (DNA-Seq) and comparative genome
hybridization (CGH). These data confirmed the predicted male
genotype of S2 cells, as the average sequence depth of the X
chromosome (reads per kb per million reads, RPKM) was 54% of
the autosome RPKM (Figures 1 and 2A).
We also found that S2 cells exhibit numerous large regions of
segmental aneuploidy (Figure 1, Figure S1, Table S1). Stepwise
deviations from expected dose covered ,42% (,40.0 Mb) of the
autosomes and ,17% (,3.8 Mb) of the X chromosome (Figure
S1). The vast majority of the aneuploid segments showed an extra
or lost copy. There was high congruence between DNA-Seq and
CGH methods. For example, we determined that .93% of calls
for copy numbers between one and five made by DNA-Seq
analysis were confirmed by CGH, even when comparing different
lots of cells grown under slightly different conditions (Figure S2,
Table S2). These data suggest that S2 cells are highly aneuploid
but show a reasonably stable genotype. There was much more
variability seen when copy number was greater than five (30%
agreement between methods and cultures). This could be due to
failure to call short segmental duplications or to repeat expansion/
retraction in different cultures. Regardless of cause, we decided to
focus our subsequent expression analyses on the high-confidence
one to five copy genes (Table S3).
We observed striking differences in DNA-Seq read density
among chromosome arms due to segmental aneuploidy (Figure 2A,
p,10215, KS test). To determine if these DNA differences are also
associated with similar changes at the transcript level, we profiled
transcript expression by next generation sequencing (RNA-Seq).
We validated RNA-Seq data by microarray profiling and found
outstanding agreement (rs=0.87, p=0). Expression analysis
revealed striking dosage compensation. Even though copy number
values significantly differed at the chromosome level (Figure 2A),
we found that expression from autosome arms and the X
While it is widely recognized that mutations in protein
coding genes can have harmful consequences, one can
also have too much or too little of a good thing. Except for
the sex chromosomes, genes come in sets of two in diploid
organisms. Extra or missing copies of genes or chromo-
somes result in an imbalance that can lead to cancers,
miscarriages, and disease susceptibility. We have examined
what happens to gene expression in Drosophila cells with
the types of gross copy number changes that are typical of
cancers. We have compared the response of autosomes
and sex chromosomes and show that there is some
compensation for copy number change in both cases. One
response is universal and acts to correct copy number
changes by changing transcript abundance. The other is
specific to the X chromosome and acts to increase
expression regardless of gene dose. Our data highlight
how important gene expression balance is for cell
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Figure 1. S2 cell DNA copy number. (A–D) DNA density and copy number profiles of the X chromosome (A, B) and chromosome 2L (C, D),
showing copy number of aneuploidy segments along chromosome length. The RPKM DNA-Seq density in nonoverlapping 1 kb windows was plotted
against the chromosome coordinates and the final deduced copy number is indicated (color key). The copy number was determined by Bayesian
change point analysis (CPA) (A, C) and CGH (B, D). The CGH results are projected onto the DNA-Seq data. The average DNA densities of each
aneuploid segment between predicted breakpoints (black lines) are shown.
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chromosome were similar inter se (Figure 2B). In no case was the
expression of a chromosome arm significantly different from all
other arms (p.1022, KS test), indicating that dosage compensa-
tion occurs genome-wide, not just on the X chromosome.
To examine the precision of dosage compensation, we
determined the relationship between expression and copy number.
Compensation was not perfect, as expression increased with copy
number (Figure 2C, p,1024, KS test). This imperfect compen-
sation resulted in a sublinear relationship between copy number
and gene expression, such that per copy expression values
decreased with increased copy number on the autosomes
and especially on the X chromosome (Figure 2D). This
inverse relationship between copy number and expression per
indicatesthat partial dosage compensationoccurs
The X Chromosome
X chromosome dosage compensation was of particular interest.
In wild type males, X chromosome dose (1X) is 50% of autosomal
dose (2A). In S2 cells this relationship occurred at 2X;4A due to
tetraploidy. The precision of X chromosome dosage compensation
in S2 cells was revealed by the indistinguishable expression of two
copy X chromosome genes and four copy autosome genes
(Figure 2C, p=0.15, KS test). Thus X chromosome dosage
compensation shows similar efficacy in diploid 1X;2A flies and in
aneuploid 2X;4A tissue culture cells.
Figure 2. Expression at varying copy numbers. (A, B) Boxplots showing the distribution of DNA-Seq read densities (in non-overlapping 1 kb
windows) mapped to chromosome arms in S2 cells (A) and the distribution of RNA-Seq expression values at the gene-level (B). Pie charts (A, B) show
the distributions of copy numbers on each chromosome arm (for expressed genes only). See Figure 1 for copy number color key. The X chromosome
is in red. (C, D) Boxplots showing the distribution of RNA-Seq expression values by copy number (C) and expression per copy (D). Equivalent
expression medians for two copies on the X and four copies on the autosomes are indicated (dashed line). For all boxplots, the 25th to 75th
percentiles (boxes), medians (lines in boxes), and ranges (whiskers, 1.5 times the interquartile range extended from both ends of the box) are shown.
Asterisks indicate significant differences from all other chromosome arms (A, B) or from the 2X or 4A baseline (C).
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The aneuploid S2 cells also allowed us to examine the effect of
X chromosome dosage compensation when the X chromosome
dose was greater or less than 50%. Precise X chromosome dosage
compensation did not occur at these other gene doses (Figure 2C,
p,1029, KS test). For example, when we compared expression
from three copy genes on the X chromosome and autosomes, X
chromosome gene expression per copy was higher despite identical
copy number (Figure 2D). Thus, we suggest that X chromosome
dosage compensation is error generating when the underlying X
chromosome gene dose is equivalent to the autosomal gene dose.
Similarly, we found under-compensated X chromosome expres-
sion when there was a single copy of an X chromosome segment.
These data indicate that the anticipated or predicted X
chromosome copy number that implements the sex and dosage
compensation pathway determines X chromosome expression.
The actual X chromosome dose is not a factor. This error
generation following perturbation is a property of feed-forward
To evaluate the effect of the MSL complex on appropriate and
error generating X chromosome dosage compensation in S2 cells,
we performed RNA interference (RNAi) experiments to knock-
down expression of two genes encoding key MSL components,
msl2 and mof. If MSL operates via feedback regulation, then
knockdown should differentially alter expression depending on
dose, whereas if MSL is a feed-forward regulator, the effect of
MSL on expression should be X chromosome specific but dose
We selected double stranded RNAs (dsRNA) targeting msl2 and
mof that resulted in greater than 90% knockdown at the mRNA
(not shown) and protein levels (Figure 3A). MSL is a chromatin-
modifying machine. We therefore also determined if RNAi altered
X chromatin. The X chromosome showed high levels of
acetylation at expressed genes (Figure 3B and 3C), and both
msl2 and mof RNAi resulted in markedly reduced H4K16ac levels
on the X chromosome as determined by chromatin immunopre-
cipitation on microarray (ChIP-chip, Figure 3B, 3D, and 3E).
RNAi against mof also resulted in decreased autosomal H4K16ac
(Figure 3B and 3E). All these data suggest that the RNAi
treatments were effective.
We then measured the effect of msl2 and mof RNAi on
expression by RNA-Seq. As in the previous experiments, we
validated expression by microarray expression profiling and found
outstanding agreement (rs=0.87–0.89, p=0, Figure S3). We
observed decreased expression of X chromosome genes following
either RNAi treatment (Figure 4, p,1022, KS test), consistent with
the role of MSL in promoting expression of X chromosome genes
relative to autosomes. For example, in mof RNAi cells we observed
a median expression of 26.4 RPKM for autosomal genes present at
four copies and only 18.6 RPKM for X chromosome genes
present at two copies (p,10215, KS test). The msl2 or mof RNAi
treatments broke the precise equilibration of 2X with 4A
We observed 1.35-fold greater X chromosome expression
attributable to wild type Msl2 or Mof (average RNAi/Mock
expression ratio =0.74, p,10215, KS test), with little to no effect
on autosomal expression (Figure 5A and 5B). If MSL acts as a
strict feed-forward regulator, then MSL would have the same fold
effect on all populations of X chromosome genes at a given copy
number, irrespective of the actual copy number. Indeed, we
observed a similar fold effect on the expression of X chromosome
genes with different copy numbers (Figure 5C and 5D,
0.58,p,0.89 in msl2 RNAi, 0.21,p,0.91 in mof RNAi, KS
test). These data clearly indicate that MSL acts on expression
based on X chromosome gene nature, rather than monitoring
actual copy number.
Drosophila X chromosomes are dosage compensated over the full
range of gene expression values. Given that MSL is bound
selectively to expressed genes, we also asked if there is a
relationship between expression levels and dosage compensation.
We determined that the RNAi treatments had the same effect on
X chromosome gene expression regardless of expression levels
(Figure 5E and 5F). Interestingly, these experiments also showed
only a modest effect of mof on autosomal expression, suggesting
that the proposed autosomal function of Mof  is subtle. The
effect of Mof on autosomes was expression level dependent, as we
observed a greater fold effect at low expression levels. However,
the most overt effect of wild type Msl2 or Mof was a 1.35-fold
increase in X chromosome expression at all expression values.
These data indicate that MSL acts as a feed-forward multiplier
causing a fixed-fold effect on X chromosome expression regardless
of gene copy number and basal gene expression value.
Genome-Wide Sublinear Expression Response to Gene
X chromosome dosage compensation is 2-fold, but we observed
only a 1.35-fold effect of MSL. If MSL is the only contributor to X
chromosome dosage compensation and if knockdown was
complete, we would expect X chromosome and autosome genes
with the same copy number to show the same expression levels
following msl2 or mof RNAi treatment. However, following either
msl2 or mof RNAi, three copy genes on the X chromosome were
still 1.19-fold over-expressed relative to three copy genes on
autosomes (Figure 6A, p,0.01, KS test). This difference between
expected and observed expression could be due to residual MSL
activity exclusively, or due to a combination of residual MSL
activity and an MSL-independent component of X chromosome
dosage compensation. The MSL-independent compensation could
be the same as observed on the autosomes. Given that the fixed-
fold properties of MSL also apply to residual activity, then the
over-expression of X chromosome genes following RNAi treat-
ment should also have a fixed fold effect if there is residual MSL
activity. We observed significantly increased variance in the
expression ratios between the X chromosome and autosomes
following RNAi (p,1022, F test, Figure 6B). This supports the idea
that much of the unexplained X chromosome dosage compensa-
tion is not due to a fixed-fold effect on expression. It is possible that
there are MSL-dose dependent effects on X chromosome
expression due to variable affinity, although the fixed-fold effect
of MSL knockdown on the population of genes makes this less
likely. These data suggest that there is an MSL-independent
component of X chromosome dosage compensation.
To determine if the MSL-independent component is the same
dosage compensation system that operates on autosomes, we
characterized the sublinear expression response to gene dose for
the X chromosome and autosomes with or without RNAi
treatment. There were three distinct trend lines for the relationship
between copy number and expression: one for the autosomes and
one each for the X chromosome with and without RNAi
treatment (Figure 6A). There are an infinite number of possible
sublinear curves. If the nature of the dose response on the X
chromosome differed from the autosomes, or the presence or
absence of MSL, then scaling should not result in a common fit.
However, if the three dose response curves are the result of a
common dosage compensation mechanism, then they should scale
to yield a single curve that fits all three of the absolute dose-
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We set median expression fold change at 2X and 4A to 1.0 for
both copy number and expression (Figure 6C). We found that X
chromosome and autosomes show remarkably similar fold changes
in expression relative to fold changes in copy number. Addition-
ally, the relationship between X chromosome expression and copy
number is MSL independent following scaling. These data suggest
that like the autosomes, the X chromosome is subject to dosage
compensation based on actual gene dose. The gene dose to
Figure 3. msl2 and mof RNAi. (A) Western analysis showing changes in MSL protein abundance following RNAi for msl2 and mof in S2 cells. (B) K-
means clustering (k=3) of H4K16ac ChIP/input ratio for expressed genes on the X chromosome and chromosome 3R in RNAi and mock treated S2
cells. Genes enriched (yellow) and depleted (blue) for H4K16ac are indicated. (C) Boxplots showing the distribution of H4K16ac ChIP/input ratios in
mock treated cells for expressed genes on different chromosome arms. (D–E) Boxplots showing the distribution of H4K16ac ChIP ratios between msl2
RNAi cells (D) or mof RNAi cells (E) and mock treated cells for expressed genes on different chromosome arms. Significant differences (p,1022)
among chromosome arms (C) and between RNAi and mock treated cells (D, E) are indicated by asterisks.
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expression response fits a one parameter model y=x(EC50 +1)/
(EC50 + x), where y is transcript abundance, x is DNA copy
number expressed as a ratio relative to wild type, and EC50 is the
copy number required for half maximal expression (r2.0.99). This
indicates that gene expression is a saturating function of gene dose
regardless of chromosome location or the presence of MSL.
Our data indicate that the MSL complex and general
compensation mechanisms independently contribute to male X
chromosome dosage compensation. The MSL complex recognizes
active X chromosome genes [28–31]. We have shown that MSL
then acts as a simple unidirectional multiplier of expression
regardless of the actual gene dose and gene expression level. In
contrast, buffering and feed-back are dose sensitive and absorb the
expression perturbations caused by unbalanced dose. We suggest
that all these mechanisms are critical for proper X chromosome
Some rough accounting illustrates the composite nature of X
chromosome dosage compensation. In the Drosophila genus, dosage
compensation results in a 2.0- to 2.2-fold increase in X
chromosome expression in males relative to autosomes [13,32].
Similarly, in S2 cells we observed a 2.08-fold increase in X
chromosome expression. The fixed-fold effect of MSL resulted in
at least a 1.35-fold increase in X-chromosome expression. Dose-
responsive compensation also acted to increase X chromosome
expression and was independent of MSL function. We can
estimate the contribution of dose-responsive compensation from
work performed on whole flies and on S2 cells. Autosomal dosage
compensation increases per copy expression by 1.4- to 1.6-fold in
diploid flies with a single copy of tens of genes [13,19]. In
agreement with those reported values, we can project that a 2-fold
change in scaled DNA dose in S2 cells results in about a 1.5-fold
increase in scaled gene expression. Thus, at face value, the layered
effect of dose-responsive compensation and feed-forward dosage
compensation may explain all of the final increase in S2 cell X
chromosome expression (1.50-fold61.35-fold=2.03-fold).
While most work on dosage compensation focuses on the X
chromosome [2,11], other organisms also show dosage compen-
sation on autosomes . For example, mammalian trisomies
show only about a 1.3-fold increase in gene expression as a result
of a 1.5-fold change in gene dose [34,35]. Compensation is likely
to be a universal property of biological systems that enables cells to
avoid deleterious effects of genetic load and other perturbations.
Materials and Methods
Cell Strains and Media
Drosophila S2 cells  (a.k.a. SL2) were obtained from Drosophila
RNAi Screening Center (DRSC, Harvard Medical School,
Boston, MA) and were grown at 25uC in Schneider’s Drosophila
Medium (Invitrogen, Carlsbad, CA) supplemented with 10% Fetal
Bovine serum (SAFC Biosciences, Lenexa, KS) and Penicillin-
Streptomycin (Invitrogen, Carlsbad, CA). These cells were used
for all experiments, except CGH, where S2-DRSC cells were
obtained from the Drosophila Genomics Resource Center (#181,
We extracted S2 cell genomic DNA using a genomic DNA kit
(Qiagen, Valencia, CA). Approximately 2 mg of purified genomic
DNA was randomly fragmented to less than 1,000 bp by 30 min
sonication at 4uC with cycles of 30 s pulses with 30 s intervals
using the Bioruptor UCD 200 and a refrigerated circulation bath
RTE-7 (Diagenode, Sparta, NJ). Sonicated chromatin (see ChIP
protocol) was purified by phenol/chloroform extraction.
We extracted S2 cell total RNA with Trizol (Invitrogen,
Carlsbad, CA) and isolated mRNA using Oligotex poly(A)
(Qiagen, Valencia, CA). The number of cells used for each
extraction was counted using a haemocytometer. The quality of
mRNA was examined by RNA 6000 Nano chip on a Bioanalyzer
Figure 4. Expression following msl2 or mof RNAi. Boxplots showing the distribution of expression RPKM values at indicated copy number on
the X chromosome (left) and autosomes (right) in RNAi and mock treated S2 cells. Equivalent expression of two copy X chromosome genes and four
copy autosomal genes in mock treated cells is shown (dashed line). See Figure 2 for boxplot format. Asterisks indicate significant expression decrease
in RNAi cells compared to mock treated cells.
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Figure 5. Mof and Msl2 effects on expression. (A, B) Boxplots showing the distribution of expression ratios between msl2 RNAi cells (A) or mof
RNAi cells (B) and mock treated cells by chromosome arms. The expected fold decrease in X chromosome expression after RNAi treatment is
indicated (red dashed line). (C, D) Boxplots showing the expression ratios for msl2 (C) and mof (D) RNAi treated cells at indicated gene copy numbers.
The X chromosome (left) and autosomes (right) are shown separately. (E, F) The relation between gene expression and fold expression change in msl2
(E) and mof (F) RNAi treated cells plotted as a moving average (20 gene/window).
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2100 (Agilent, Santa Clara, CA) according to the manufacture’s
protocol. One hundred ng of the extracted mRNA was then
fragmented in fragmentation buffer (Ambion, Austin, TX) at 70uC
for exactly 5 min. The first strand cDNA was then synthesized by
reverse transcriptase using the cleaved mRNA fragments as
template and high concentration (3 mg) random hexamer Primers
(Invitrogen, Carlsbad, CA). After the first strand was synthesized,
second strand cDNA synthesis was performed using 50U DNA
polymerase I and 2U RNaseH (Invitrogen, Carlsbad, CA) at 16uC
for 2.5 h.
Deep sequencing of both DNA and short cDNA fragments were
performed [36,37]. Libraries were prepared according to instruc-
tions for genomic DNA sample preparation kit (Illumina, San
Diego, CA). The library concentration was measured on a
Nanodrop spectrophotometer (NanoDrop products, Wilmington,
DE), and 4 pM of adaptor-ligated DNA was hybridized to the flow
cell. DNA clusters were generated using the Illumina cluster
station, followed by 36 cycles of sequencing on the Illumina
Genome Analyzer, in accordance with the manufacturer’s
protocols. Two technical replicate libraries were constructed for
each DNA-Seq sample. Two libraries were prepared from two
biological replicates of each RNA material (RNAi or mock
dsRNA for RNAi treatment  was produced by in vitro
transcription of a PCR generated DNA template from Drosophila
genomic DNA containing the T7 promoter sequence on both
ends. Target sequences were scanned to exclude any complete 19
mer homology to other genes . The dsRNAs were generated
using the MEGAscript T7 kit (Ambion, Austin, TX) and purified
using RNAeasy kit (Qiagen, Valencia, CA). Two different primer
sets were used for each target gene, and the one with better RNAi
efficiency was used for downstream experiments. The selected
primer sequences for generation of msl2 dsRNA template by PCR
were as follows: forward, 59-taatacgactcactatagggTTGCTCC-
GACTTCAAGACCT-39, and reverse, 59-taatacgactcactatagggG-
CATCACGTAGGAGACAGCA-39 and the selected primer
sequences for generation of mof dsRNA template were as follows:
TG-39, and reverse, 59-taatacgactcactatagggTGCGGTCGCTG-
For RNAi treatment, S2 cells were resuspended in serum free
media at 26106cells/ml. Twenty mg dsRNA was added to 1 ml of
cell suspension and incubated for 45 min at room temperature.
Cells with the same serum free media treatment but without added
dsRNA were used as mock treated controls. After the incubation,
3 ml complete medium was added and the cells were cultured for
another 4 d. Cells were collected and split into three aliquots for
mRNA extraction, chromatin immunoprecipitation, and western
For ChIP , 5–106106S2 cells were fixed with 1%
formaldehyde in tissue culture media for 10 min at room
temperature. Glycine was added to a final concentration of
0.125 M to stop cross-linking. After 5 min of additional incubation
and two washes with ice-cold PBS, cells were collected and
resuspended in cell lysis buffer (5 mM PH 8.0 PIPES buffer,
85 mM KCl, 0.5% Nonidet P40, and protease inhibitors cocktail
from Roche, Basel, Switzerland) for 10 min and then resuspended
in nuclei lysis buffer (50 mM PH 8.1 Tris.HCl, 10 mM EDTA,
1% SDS and protease inhibitors) for 20 min at 4uC. The nuclear
extract was sheared to 200–1,000 bp by sonication on ice for
8 min (pulsed 8 times for 30 s with 30 s intervals using a Misonix
Sonicator 3000; Misonix, Inc. Farmingdale, NY). The chromatin
solution was then clarified by centrifugation at 14,000 rpm for
10 min at 4uC. Five ul anti-H4AcK16 (Millipore, Billerica, MA)
was incubated with the chromatin for 2 h and then was bound to
protein A agarose beads at 4uC overnight. The beads were washed
three times with 0.1% SDS, 1% Trition, 2 mM EDTA, 20 mM
PH 8.0 Tris, and 150 mM NaCl; three times with 0.1% SDS, 1%
Trition, 2 mM EDTA, 20 mM PH 8.0 Tris, and 500 mM NaCl;
and twice with 10 mM PH 8.1 Tris, 1 mM EDTA, 0.25 M LiCl,
1% NP40, and 1% sodium deoxycholate. The immunoprecipitat-
ed DNA was eluted from the beads in 0.1 M NaHCO3 and 1%
SDS and incubated at 65uC overnight to reverse cross-linking.
DNA was purified by phenol-chloroform extraction and ethanol
precipitation. The precipitated DNA for Chromatin immunopre-
cipitation was amplified using a Ligation-mediated PCR (LM-
Figure 6. Characterization of dose-response curves. (A, C) Median expression RPKM values plotted against the DNA copy for X chromosome
and autosome genes in RNAi and mock treated S2 cells based on absolute (A) or scaled (C) data. Fitted trend lines for the X chromosome (red) and
autosomes (black) following mock (solid), msl2 (dashed), and mof (dotted) RNAi treatment are indicated. (B) Boxplots and table showing the
distribution of expression ratios among different copy numbers. Expression fold change values were calculated based on real median RPKM values
(bold) or projected expression values. Asterisks indicate significant variation for the expression fold change between X chromosome and autosome
genes at an equivalent dose in RNAi cells (p,1022).
Expression in Aneuploid Cells
PLoS Biology | www.plosbiology.org9 February 2010 | Volume 8 | Issue 2 | e1000320
PCR) protocol from FlyChip . ChIP was performed on
triplicate biological samples.
Six hundred ng of amplified DNA (ChIP enriched DNA or
input DNA) were labeled using 6ug Cy3- or Cy5-labeled random
nonamers (Trilink Biosciences, San Diego, CA) with 50U Klenow
(New England Biolabs, Ipswich, MA) and 2 mM dNTPs. The
labeled DNA was purified and hybridized to FlyGEM microarrays
. Arrays were scanned on an Axon 4000B scanner (Molecular
Devices Corporation, Sunnyvale, CA) and signal was extracted
with GenePix v.5.1 image acquisition software (Molecular Devices
Two hundred ng aliquots of the same extracted mRNA used for
RNA-Seq were labeled as described  and were hybridized to
NimbleGen custom 12 plex microarrays at 42uC using a MAUI
hybridization station (BioMicro Systems, Salt Lake City, UT)
according to manufacturer instructions (NimbleGen Systems,
Madison, WI). Arrays were scanned on an Axon 4200AL scanner
(Molecular Devices Corporation, Sunnyvale, CA) and data were
captured using NimbleScan 2.1 (NimbleGen Systems, Madison,
Cell lysates were prepared from cells 4 d after dsRNA or mock
treatment by boiling for 5 min in NuPAGE LDS sample buffer
(Invitrogen, Carlsbad, CA). Samples were run by SDS-PAGE
using a 4%–12% Bis-Tris gel (Invitrogen, Carlsbad, CA) and
transferred to PVDF membrane. Blots were incubated with anti-
MSL antibody (1:500), anti-MOF antibody (1:3,000, gifts of M.
Kuroda), or anti-a tubulin antibody (1:10,000, Sigma, St. Louis,
MO) and then with HRP-secondary antibodies in PBS buffer with
0.1% Tween 20. Protein signals were detected by Pierce Super-
Signal West Dura extended Duration Substrate (Thermo Fisher
Scientific, Rockford, IL). Images were captured using a Fuji LAS-
3000 Imager and quantified using the Image Gauge software (Fuji
Film, Tokyo, Japan).
Both DNA-Seq and RNA-Seq sequence reads were compiled
using a manufacturer-provided computational pipeline (Version
0.3) including the Firecrest and Bustard applications .
Sequence reads were then aligned with the Drosophila melanogaster
assembly (BDGP Release 5, dm3) [6,43] using Eland. Only
uniquely mapped reads with less than two mismatches were used.
For DNA-Seq data, we counted the number of reads in the non-
overlapped 1 kb region along each chromosome using all
sequenced reads from two technical DNA-Seq libraries and
calculated the read density by the number of unique mapped reads
per kb per million mapped reads (RPKM) . The breakpoint
positions of aneuploid segments were identified using the Bayesian
analysis of change point (bcp) package from R . Because some
reads mapped to multiple positions in the genome and thus
inappropriately lower the deduced copy number in regions with
low sequence complexity, we removed all the 1 kb windows with
RPKM lower than 2 (RPKM value of one copy =2.29) prior to
change point analysis. Breakpoints with posterior possibility .0.95
were used. Copy number was assigned to segments based on the
fold between average segments RPKM value between breakpoints
(2.2961.15 RPKM =1 copy, 4.5861.15 RPKM =2 copy, etc.).
Genes spanning two segments were not used in gene expression
For RNA-Seq data, we counted the number of unique mapped
reads within all unique exons of Drosophila Flybase  Release
5.12 annotation (Oct. 2008) and calculated the total number of
reads of all unique exons per kb of total length of unique exons per
million mapped reads (RPKM) for each annotated gene. The
RPKM calculation was done for individual RNA-Seq libraries
separately, and then RPKM values were averaged for biological
replicates (r2=0.98 between replicates). Non-expressed genes are
not useful for ratiometric analysis and these were therefore
excluded. We used RPKM values for intergenic regions to
determine expression thresholds. For intergenic regions, the
RPKM values were calculated for total number of reads between
adjacent gene model pairs. Only 5% of intergenic regions in S2
cells have a RPKM value greater than or equal to 4. Therefore, we
called genes with RPKM values no less than 4 in S2 cells as
expressed with an estimated type I error rate of 5%.
All microarray data (except CGH) and statistical tests were
processed and analyzed in R/Bioconductor . For the ChIP-
chip experiments, we used quantile normalization based on the
input channel. The distributions of raw and normalized intensities
were checked to make sure that normalization was appropriate
(i.e., that the skew was maintained). We used the average ChIP/
input ratio from biological replicates (r2=0.40–0.54 between
replicates). The ChIP/input ratios in RNAi and mock treated cells
were used for K-means clustering analysis with 3 nodes using
Euclidean similarity metric and genes on X chromosome and
autosomes were clustered separately using Cluster3.0 and then
visualized using Tree-View . For expression profiling, we
normalized using loess within each 12-plex and quantile between
12-plexes. Average probeset log2 intensities were calculated in
both channels for each gene. Correlations between array
intensities and RPKM values were estimated by Spearman’s rank
correlation coefficient. The comparisons for the distributions of
DNA densities or expression values among different chromosomes
and different copy numbers were performed using two sample
Kolmogorov-Smirnov tests (KS tests).
Normalization is inherently problematic when a large fraction
of the genome changes expression, as in the RNAi experiments.
Given that 20% of the genome is encoded on the X chromosome
(X) and 80% is encoded on autosomes (A), and that one samples
transcripts from a total mRNA pool to generate an expression
profile, and that X chromosome expression is reduced by half and
autosome expression does not change, then autosomal transcripts
must be over-sampled in the experiment. Conversely, if the
autosome expression is doubled, then X chromosome transcripts
must be under-sampled. While it is imprudent to formally state the
precise contribution of X chromosome expression changes and
autosomal expression changes due to MSL-mediated dosage
compensation, we can determine which makes the larger
contribution based on the RPKM, total mRNA, and cell count
measurements. Using this information, we calculated the log-
likelihood value for two hypotheses:
Here hypothesis H0states that the expression of autosomes (A)
remains the same and the expression of the X chromosome (X)
decreases by half after RNAi treatment. Hypothesis H1states that
the expression of autosomes (A) is increased by 2-fold after the
RNAi treatment and the expression of X chromosome (X) remains
the same. The expected sum of expression in the RNAi treated
cells is 90% of wild type for H0 and 180% for H1. E is the
measured mRNA per cell. In the duplicate RNA-Seq experiments,
Expression in Aneuploid Cells
PLoS Biology | www.plosbiology.org10February 2010 | Volume 8 | Issue 2 | e1000320
we obtained mRNA yields of 0.16 pg and 0.17 pg/cell from mock
treated, 0.15 pg and 0.19 pg/cell from Msl2 knockdown, and
0.14 pg and 0.20 pg/cell from Mof knockdown S2 cells.
The log-likelihood of H0 – the log-likelihood of H1 =26.4
suggests that X chromosome expression change contributes more
than autosomal expression change to the observed measurements
of expression in wide type cells relative to RNAi treated cells.
Comparative Genomic Hybridization (CGH)
DNA was isolated from Drosophila S2-DRSC cells obtained from
the Drosophila Genomics Resource Center (#181, Bloomington, IN)
and from w11180–2 h embryos as described previously . The
isolated cell line and embryonic DNA were labeled with either Cy5
or Cy3 conjugated dUTP and subsequently hybridized to a custom
Agilent genomic tiling array (GEO; GPL7787). Changes in copy
number along each of the Drosophila chromosome arms were
detected by a dynamic programming algorithm which divided each
arm into the optimal number of copy number segments .
All Seq and array data sets are available at GEO under
accession number GSE16344. The CGH data set is available at
modENCODE submission ID 596.
Change Point Analysis of DNA-Seq read density.
Found at: doi:10.1371/journal.pbio.1000320.s001 (1.12 MB PDF)
Copy number determination by Bayesian
defined by DNA-Seq copy number calls or CGH copy
Found at: doi:10.1371/journal.pbio.1000320.s002 (0.07 MB PDF)
DNA-Seq densities of each copy number
Found at: doi:10.1371/journal.pbio.1000320.s003 (2.01 MB PDF)
RNA-Seq and array expression profiling.
Found at: doi:10.1371/journal.pbio.1000320.s004 (0.04 MB XLS)
Copy number segments based on DNA-Seq.
Found at: doi:10.1371/journal.pbio.1000320.s005 (0.09 MB
Copy number validation by DNA-Seq and
Found at: doi:10.1371/journal.pbio.1000320.s006 (0.03 MB
The number of genes in each copy number
We thank members of Oliver laboratory and Carson Chow for helpful
discussion and comments on the manuscript, Mathias Beller for help with
cell culture and RNAi experiments, David Clark for help with ChIP
experiments, Mitzi Kuroda for anti-Msl2 and anti-Mof reagents, and the
NIDDK genomics core for assistance with Illumina sequencing.
The author(s) have made the following declarations about their
contributions: Conceived and designed the experiments: YZ SKP ES
DMM BO. Performed the experiments: YZ SKP. Analyzed the data: YZ
JHM SKP VP DMM BO. Contributed reagents/materials/analysis tools:
JHM ES. Wrote the paper: YZ BO.
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