Identification of Genes That Promote or Antagonize
Somatic Homolog Pairing Using a High-Throughput
Eric F. Joyce1, Benjamin R. Williams1¤, Tiao Xie2,3, C.-ting Wu1*
1Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America, 2Department of Systems Biology, Harvard Medical School, Boston,
Massachusetts, United States of America, 3Image and Data Analysis Core, Harvard Medical School, Boston, Massachusetts, United States of America
The pairing of homologous chromosomes is a fundamental feature of the meiotic cell. In addition, a number of species
exhibit homolog pairing in nonmeiotic, somatic cells as well, with evidence for its impact on both gene regulation and
double-strand break (DSB) repair. An extreme example of somatic pairing can be observed in Drosophila melanogaster,
where homologous chromosomes remain aligned throughout most of development. However, our understanding of the
mechanism of somatic homolog pairing remains unclear, as only a few genes have been implicated in this process. In this
study, we introduce a novel high-throughput fluorescent in situ hybridization (FISH) technology that enabled us to conduct
a genome-wide RNAi screen for factors involved in the robust somatic pairing observed in Drosophila. We identified both
candidate ‘‘pairing promoting genes’’ and candidate ‘‘anti-pairing genes,’’ providing evidence that pairing is a dynamic
process that can be both enhanced and antagonized. Many of the genes found to be important for promoting pairing are
highly enriched for functions associated with mitotic cell division, suggesting a genetic framework for a long-standing link
between chromosome dynamics during mitosis and nuclear organization during interphase. In contrast, several of the
candidate anti-pairing genes have known interphase functions associated with S-phase progression, DNA replication, and
chromatin compaction, including several components of the condensin II complex. In combination with a variety of
secondary assays, these results provide insights into the mechanism and dynamics of somatic pairing.
Citation: Joyce EF, Williams BR, Xie T, Wu C-t (2012) Identification of Genes That Promote or Antagonize Somatic Homolog Pairing Using a High-Throughput
FISH–Based Screen. PLoS Genet 8(5): e1002667. doi:10.1371/journal.pgen.1002667
Editor: R. Scott Hawley, Stowers Institute for Medical Research, United States of America
Received December 15, 2011; Accepted March 7, 2012; Published May 10, 2012
Copyright: ? 2012 Joyce et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by a Ruth L. Kirschstein National Research Service Award to EFJ from the National Cancer Institute (F32CA157188), a National
Science Foundation Graduate Research Fellowship to BRW, and an NIH/NIGMS grant (RO1GM61936), SPARC Award from the Broad Institute, and Cox Program
Award from Harvard Medical School to C-tW. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
¤ Current address: Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
Pairing of homologous chromosomes is a fundamental aspect of
nuclear organization. Although most well-known for its role in
chromosome segregation during meiosis, studies have also
documented homolog pairing in somatic tissues [1–5]. The most
dramatic examples can be observed in Dipteran insects, such as
Drosophila melanogaster, where homologous chromosomes are
intimately paired in virtually all cell types throughout development
[4,6,7]. Importantly, these pairing interactions have been shown to
affect gene regulation at a number of loci through a process
termed transvection [1,2,8–13] and influence the repair of somatic
DNA double-strand breaks .
In contrast to Drosophila, the homologous pairing of any
particular chromosome or chromosomal region in most organisms,
if it occurs at all, is transient and localized. For example, short-
lived homolog associations have been implicated in both
mammalian X-inactivation [15–19] and immunoglobulin gene
recombination during B cell development . Additionally, there
is evidence that mammalian chromosomes of somatic cells can
colocalize, perhaps even undergo homologous pairing, at specific
stages of the cell cycle [21–25], consistent with observations
indicating that the mammalian nucleus can arrange its chromo-
somes nonrandomly [26–28]. One possible explanation for the
relatively modest level of pairing in mammals as compared to that
found in Drosophila is that mammalian cells support mechanisms
that inhibit interchromosomal interactions throughout most of
development [29,30]. Indeed, identification of the condensin II
subunit, Cap-H2, as a protein in Drosophila that antagonizes
polytene chromosome alignment and transvection supports the
idea that homologous interactions can be actively inhibited ,
perhaps even in a cell-cycle regulated fashion . What remains
unclear is why and how pairing is generally prohibited in most
organisms and yet is so robust and genome-wide in Drosophila.
One strategy to better understand the mechanistic and
functional basis of somatic pairing and its downstream role in
transcriptional regulation is to identify the genes involved. To
date, only two proteins have been directly implicated in promoting
somatic pairing in Drosophila: Suppressor of Hairy Wing (Su(Hw))
 and Topoisomerase II (Top2) . Using fluorescent in situ
hybridization (FISH) targeting euchromatic loci in order to
provide a direct measure of somatic pairing, loss of Su(Hw) and
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inhibition of Top2 have both been shown to partially compromise
homolog pairing in tissues and cell culture, respectively. Intrigu-
ingly, Top2 has been suggested to modulate the activity of Su(Hw)
, indicating that these two proteins may function together.
Aside from these findings, FISH-based searches for pairing factors,
one via a candidate gene approach  and a second entailing a
whole-genome screen in early embryos , have failed to identify
genes whose products control somatic pairing.
Searches for genes involved in somatic pairing have also taken
advantage of transvection-associated phenotypes and, while not a
direct measure of pairing, these phenotypes have enabled genetic
studies to isolate additional candidates. These include genes
encoding proteins that mediate long-range interactions, such as
Zeste and the Polycomb group proteins [2,11–13,37–43], although
direct involvement of such candidates in homolog pairing has yet
to be obtained. What has been observed are correlations between
the cell cycle and relative levels of somatic pairing [2,4,32,43–46].
For example, high levels of somatic pairing may require a long
interphase or an uninterrupted period during which chromosomes
are still decondensed. Pairing may even be disrupted during S-
phase and mitosis, lending further support that pairing is possibly
regulated through the cell cycle, although direct genetic evidence
for such a link is lacking. Cohesin is a protein complex that has
also been implicated in long-range interactions as well as the
tethering of sister chromatids in both mitosis and meiosis [47,48],
and, perhaps most suggestively, the mechanism and control of
meiotic homolog pairing [49–52]. Nevertheless, there is no direct
evidence for the involvement of the cohesin complex in somatic
pairing, and it remains unclear if meiotic pairing and somatic
pairing are mechanistically similar .
Here, we present a genome-wide FISH-based screen in
Drosophila cell culture to identify the factors involved in the
somatic pairing of heterochromatic regions. This screen was made
possible through the development of a high-throughput FISH
technology that permits chromosomal positions to be directly
visualized in a 384-well format. Combined with RNAi, this
approach permitted us to screen two heterochromatic regions
simultaneously for double-stranded RNAs (dsRNAs) that alter the
fidelity and/or strength of somatic homolog pairing. Using an
increased number of FISH signals per nucleus as a readout for
decreased pairing, we report the identification of 40 candidate
‘pairing promoting genes,’ none of which had been previously
associated with pairing functions. Importantly, many of these
genes were also found to influence pairing at euchromatic
regions, revealing a potentially strong mechanistic overlap
between heterochromatic and euchromatic pairing. In addition,
we identified 65 candidate ‘anti-pairing genes,’ which when
knocked down enhance pairing, consistent with a wild-type
function of antagonizing somatic pairing interactions. We propose
a model in which interchromosomal associations are mediated by
a dynamic interplay between groups of proteins with opposing
functions: those that induce or augment pairing and others whose
normal function is to disrupt pairing. This perspective suggests
that the difference between Drosophila and other organisms may
be a shift in the balance of gene function. Finally, in combination
with a variety of secondary assays, the identification of these
proteins has provided insights into the mechanism and dynamics
of somatic pairing, pointing to an intriguing connection between
the progression of the cell cycle and the control of somatic
Heterochromatic pairing in Drosophila cell culture
The design of our studies began with an earlier observation
that the onset of pairing in the Drosophila embryo does not
require the zygotic expression of any particular gene but relies
instead on parental contributions . This finding suggested
that traditional genetic screens for genes involved in pairing
may not be straightforward, arguing for a cell culture- and
FISH-based alternative. For this study, we chose the Drosoph-
ila Kc167 cell line due to its amenability to RNAi  and
capacity to support high levels of pairing, despite being
predominantly tetraploid . In fact, it was in this cell line
that our previous study identified Top2 as a gene important
for somatic pairing .
Our analysis also required chromosomal targets that would
produce robust, reproducible FISH signals. For this reason, we
chose sequences of the centromeric heterochromatin, which make
ideal FISH targets due to their great abundance, simplicity, and
chromosome specificity . We designed FISH probes, 15 to 35
bases in length, against three heterochromatic sequences: the 359,
AACAC, and dodeca repeats of the X, 2nd, and 3rdchromosomes,
respectively (Materials and Methods; Figure 1). Using these
probes, 80, 42, and 58% of Kc167nuclei gave a single FISH
signal at 359, AACAC, and dodeca, respectively, indicating close
homolog alignment (Figure 1). We note that these levels of pairing
are greater than those previously observed for heterochromatic
sequences in Kc167cells , possibly owing to the high specificity
of our probes. However, consistent with this previous study, these
levels of heterochromatic pairing are below those typically found
at euchromatic regions (with the exception of pairing at 359),
raising the possibility that heterochromatic regions may pair less
often, pair more slowly, and/or even rely on mechanisms that
differ from those responsible for pairing at euchromatic regions
. We reasoned that targeting these regions with FISH should
allow us to detect either a reduction or an increase in pairing, thus
identifying heterochromatic and, possibly, euchromatic pairing
factors as well.
In addition to their number and structure, the position and
spatial dynamics of chromosomes are under tight control,
as direct interactions between chromosomes can contrib-
ute to the activation or repression of genes. Here, we focus
on a particular type of interaction, known as somatic
homolog pairing, which occurs between the maternal and
paternal copies of chromosomes. While the role of somatic
pairing on downstream homology-driven processes is
well-established, there is much to be learned about how
homologous chromosome segments find each other,
physically align, and form stable pairing interactions within
somatic cells. Taking advantage of a novel high-through-
put FISH technology and the fact that homologous
chromosomes are intimately paired along their lengths in
the somatic cells of Drosophila, we have conducted a
screen for factors that are important for the fidelity of
somatic pairing. Ultimately, the characterization of these
pairing genes will shed light on the mechanism of pairing,
as well as pairing-mediated processes that have implica-
tions for development and disease. Finally, the efficacy of
our screen for pairing genes suggests that the high-
throughput FISH technology described here will prove
useful for studying forms of nuclear organization and
chromosome positioning beyond pairing.
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Identification of Pav and Cap-H2 as putative regulators of
We next conducted a pilot screen using dsRNA to knock down
transcript levels of genes that had been previously shown to be
important for the pairing of euchromatic regions. For example,
RNAi inhibition of either Top2  or the kinesin-like protein
Pavarotti (Pav) (Williams, BR, unpublished) had been found to
reduce euchromatic pairing levels in cell culture, whereas RNAi
inhibition of Cap-H2 had been shown to antagonize euchromatic
pairing in vivo . Cells were incubated with dsRNA for 4 days, an
extent of time known to reduce protein levels by .80% [55,56],
after which they were fixed, subjected to FISH targeting the dodeca
satellite, and then scored by visual examination. Nuclei were
considered paired when they contained only a single FISH signal or
when the center-to-center distance between all pairs of FISH signals
was #1.0 mm, a threshold selected based on control nuclei (72%
paired). From these analyses, Pav was shown to be important for
heterochromatic pairing, as indicated by a decrease in the number
of paired nuclei to 50% following depletion by RNAi (P,0.005;
Figure 1), while Cap-H2 was shown to antagonize heterochromatic
pairing, as revealed by an increase in the number of paired nuclei to
86% (P,0.05; Figure 1), consistent with the role of condensin II in
vivo . Interestingly, we found that RNAi depletion of Top2 had
no effecton the pairing frequencies observed at theheterochromatic
regions of the X, 2nd, or 3rd chromosomes (data not shown) even
though it reduced pairing at the euchromatic 28B region from 85%
to 58% (P,0.005), confirming efficient knockdown of Top2.
High-throughput FISH screen to identify genes involved
in heterochromatic pairing
The identification of Pav and Cap-H2 in our pilot run argued
that a whole-genome screen in Kc167cells should reveal genes
involved in the somatic pairing of Drosophila heterochromatic
regions. To this end, we developed a high-throughput FISH
technology, allowing FISH assays to be performed in a 384-well
format using a protocol that can be carried out, from fixation to
imaging, within five hours. This strategy also enabled us to target
two different heterochromatic regions simultaneously using probes
against the 359 and dodeca repeated elements (Materials and
Methods). We applied this technique to plates seeded with the
well-characterized dsRNA whole-genome library of the Harvard
Drosophila RNAi Screening Center (Figure 2), which represents
13,912 genes, at an average of 1.7 dsRNAs per gene, in a total of
66 plates. The screen was conducted in duplicate, each plate
including dsRNAs against pav and cap-H2 as positive controls for
increased and decreased FISH signals, respectively. Wells
containing dsRNAs against GFP, lacZ, and no dsRNA were used
as negative controls, with no difference in pairing levels observed
amongst them, suggesting that dsRNA in itself does not affect
pairing (Table S1). A total of 50,668 FISH assays were conducted
in the primary screen.
To automate scoring, we generated a custom MATLAB
program to identify and count the number of FISH signals per
nucleus (Materials and Methods), with an average of 9286185
nuclei being imaged per dsRNA. Computer algorithms were then
used to calculate several parameters of pairing, such as the
percentage of nuclei containing one, two, three, four, and $ five
FISH signals, in order to detect different patterns of pairing as well
as degrees of unpairing. Because we expected the unpairing of
homologs to increase the distance between signals as well, we also
incorporated a parameter that calculates the pairwise distances
between multiple signals. Finally, as aneuploidy may affect the
number of FISH signals per nucleus, the size of DAPI signals was
recorded to monitor both increases and decreases in nuclear
Figure 1. Heterochromatic pairing in Drosophila cell culture. a, Drosophila karyotype (Y and 4th chromosome not shown) and targets of
heterochromatic probes. b, Flattened image of Kc167nucleus stained with DAPI and FISH targeting 359, AACAC, and dodeca. c, Percentage of Kc167
nuclei 6 standard deviation (SD) with the indicated number of signals per nucleus representing 359, AACAC, and dodeca. d, dsRNA directed against
pav reduces the percentage of paired nuclei (one signal or two signals #1 mm apart) at dodeca in Kc167cells (P,0.005), whereas dsRNA directed
against cap-H2 increases the percentage of paired nuclei (P,0.05). The data are from three trials.
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Figure 2. RNAi–mediated FISH–based screen of Drosophila cells for heterochromatic pairing factors. a, Experimental design with
representative image before and after automated identification of nuclei and FISH signals. The screen averages for signals per nucleus obtained with
probes targeting 359 and dodeca. b, Rank-order plot of each dsRNA in the primary screen, where negative z-scores indicate a reduction in paired
nuclei (corresponding to candidate pairing promoters) and positive z-scores indicate an increase in paired nuclei (corresponding to candidate anti-
pairers). c, Functional classifications of the candidate pairing promoters and anti-pairers.
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The screen average for the percentage of nuclei exhibiting a
single FISH signal was 8063% and 7063% at 359 and dodeca,
respectively, with the low variability demonstrating the reproduc-
ibility of the automated FISH counts (Figure 2). As the genes
involved in somatic pairing are not expected to be clustered in any
particular plate, we used the variation within each plate to assign a
z-score (number of standard deviations by which the result differs
from the mean value for the entire plate) to each well. Rank-order
analysis of the primary genome-wide screening results demon-
strated that the majority of dsRNAs had no effect on the number
of FISH signals per nucleus, suggesting that pairing is not
commonly disrupted by RNAi (Figure 2). However, we identified
372 dsRNAs that resulted in a significantly decreased number of
nuclei with a single FISH signal (z-score $2.0), as would be
expected for those that target genes important for somatic pairing.
A second group of 63 dsRNAs resulted in a significantly increased
number of single-signal nuclei (z-score #22.0), as expected for
those that target genes required for suppressing somatic pairing
levels (Table S2). Together, the 435 dsRNAs that affected pairing
targeted 352 annotated genes in the Drosophila genome.
Validation and functional classification of candidate
Because processed dsRNAs can produce off-target effects by
cross-hybridizing with sequences corresponding to more than one
gene , the 352 candidate genes identified in our primary
screen were targeted with 1–2 additional non-overlapping
dsRNAs. The validations were conducted in triplicate in 384-well
plates with FISH probes targeting both the 359 and dodeca loci,
and only those dsRNAs producing a significant increase or
decrease (P#0.05) of the percentage of single-signal nuclei
compared to untreated control wells were considered ‘‘hits’’
(Materials and Methods for specific cut-off criteria). This narrowed
our focus to 105 genes: 40 genes identified as candidate promoters
of pairing, or ‘pairing promoters’, and 65 genes identified as
candidate suppressors of pairing, or ‘anti-pairers’ (Table S3, Table
S4). These data suggest that less than 1% of the Drosophila
genome is directly or indirectly involved in somatic pairing of
RNAi disruption of only 16% of the candidate pairing
promoters significantly affected pairing at the 359-bp repeat on
the X chromosome, estimated to be ,11 Mb in length. Disruption
of 98% of the candidates, however, were found to affect pairing at
the dodeca locus, of unknown size, suggesting dodeca may
represent a sensitized region that is more likely to unpair. Indeed,
control pairing levels were significantly lower at dodeca as
compared to those at 359 (Figure 1). Moreover, a positive
correlation was found between the strongest pairing hits for
dodeca and those that affected 359 (Figure S1).
Further examination of the 40 candidate pairing promoters
revealed that 28 (70%) encode proteins with known or expected
roles in cell division (Figure 2), the large majority of which are
involved in mitotic spindle organization (12), cytokinesis (6) and
the metaphase/anaphase transition (4). Of the remaining 12
(30%), 8 are known components of other cellular processes,
including 3 subunits of the SCF ubiquitin-ligase complex. As for
the 65 candidate anti-pairers, whose knockdown resulted in a
decreased number of FISH signals, we hypothesize that they have
wild-type functions that antagonize somatic pairing interactions.
The most striking enrichments were for gene functions linked to S-
phase progression (16, 26%), including cell cycle factors necessary
for the G1/S transition (9), nucleotide biosynthesis (5), and
replication (2) (Figure 2). Genes associated with transcription (12,
18%) or transcript processing (5, 8%) were also particularly
prominent, with a further 5 (8%) genes encoding zinc finger
proteins with potential roles in transcription (Figure 2). Some of
these proteins could be required for sustained expression of the S-
phase regulators. Of the remaining 32 genes, 5 (8%) are associated
with proteolysis, 3 (5%) are involved in nuclear import, and 5 (8%)
have roles in chromatin organization, including the condensin II
subunits Cap-H2 and Cap-D3 and core condensin subunit SMC2.
These data suggest that somatic pairing of heterochromatic
regions requires a complex network of genes that can promote as
well as antagonize interchromosomal interactions. Below we
describe our candidate pairing promoting and anti-pairing genes,
and address their relationships to both heterochromatic and
euchromatic pairing, aneuploidy, heterochromatin clustering, cell
cycle progression, and each other. Taken together, these
candidates point to an intriguing connection between the
progression of the cell cycle and the control of somatic pairing
as well as reveal an extensive overlap between heterochromatic
pairing factors with those important for pairing at euchromatic
Candidate genes important for somatic pairing
the two strongest hits identifying candidate pairing promoters
(Table S3). We also identified Drosophila SKPA (Table S3), which
physically interacts with SLMB and LIN19 . Together, these
candidates represent three of the four proposed components of the
Drosophila SCF E3 ubiquitin-ligase complex, which targets
signaling molecules and cell cycle regulators for degradation
[58,59]. We found that RNAi knockdown of slmb, lin19, and skpA
reduced the percentage of nuclei with a single dodeca signal from
70% to 30% (P=0.0001), 49% (P=0.0075), and 56% (P=0.002),
respectively (Figure 3). Similar changes were also observed with
probes targeting the 359 repeat (Figure 3, Table S3).
We reasoned unpairing of homologs would also increase the
distance between FISH signals in addition to increasing their
number per nucleus. Of those nuclei with multiple dodeca FISH
signals in SLMB, LIN19, and SKPA-depleted cells, 99% exhibited
two signals .1 mm apart and were therefore considered unpaired.
In fact, 25% of SLMB-depleted cells had two signals .4 mm apart,
a distance rarely observed in control nuclei (4%, P,0.0001;
Figure 3). We further found that, despite an increase in the
number of FISH signals, SLMB-depleted cells also exhibited
reduced nuclear volumes (5876256 mm3) compared to that of
controls (8866439 mm3, P,0.0001). Thus, these data point to a
novel role for the SCF complex in controlling the organization and
structure of interphase nuclei.
Finally, to investigate the contribution of the SCF complex to
euchromatic pairing, we conducted FISH targeting two euchro-
matic regions, 16E and 28B, on the X and 2ndchromosome,
respectively, following slmb RNAi. Pairing was perturbed at both
loci as observed by a reduction in the percentage of single-signal
nuclei from 71 to 32% at 16E and from 85 to 54% at 28B (P,0.05
each; Figure 3), indicating the SCF complex is important for
homologous pairing of both heterochromatic and euchromatic
Complex (APC) contains 11–13 proteins that, similar to SCF,
function together as an E3 ubiquitin ligase, which targets cell cycle
proteins for degradation. Our validation screen identified three
components of the APC as candidate pairing promoters; RNAi
depletion of SHTD (Drosophila APC1), CDC16, and IDA
(Drosophila APC5) each reduced the percentage of single-signal
nuclei (56–59%, P,0.04) and paired nuclei (all signals #1 mm
apart) at dodeca (Figure 3, Table S3). A reduction in pairing, while
dsRNAs targeting slmb and lin19 were
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not significant, was also observed with FISH targeting 359
(Figure 3, Table S3). Euchromatic pairing was also disrupted
following IDA depletion, reducing the percentage of single-signal
nuclei from 71 to 40% at 16E and from 85 to 60% at 28B
(P,0.05), suggesting that, similar to SCF, proper APC function is
important for pairing at both heterochromatic and euchromatic
regions (Figure 3).
Although not confirmed in our validation screen, four
additional members of the APC (FZY, APC10, APC4, and
CDC27) were identified in our primary screen, with depletion of
each causing a significant increase in the number of FISH signals
per nucleus for both 359 and dodeca (Table S2), further
supporting the role of APC in heterochromatic pairing. Our
failure to identify these subunits in our validation screen is most
likely due to the high stringency of the cut-off or inefficiency of the
dsRNAs used in the validation studies. As seen below, different
variants of the APC complex may have different and even
opposing roles in pairing, which may further complicate the RNAi
phenotypes of individual subunits.
The APC targets a different substrate spectrum for degradation
in mitosis and interphase through interactions between the core
APC subunit CDC27 and one of two adaptor proteins, CDC20
(mitotic) and CDH1 (interphase) [60–62]. We were intrigued to
find that depletion of Drosophila CDC20 (FZY) reduced the
percentage of paired nuclei at dodeca to 57% (P=0.0002) (Table
S2), whereas knockdown of Drosophila CDH1 (RAP) had the
opposite effect, increasing pairing levels to 81% (P=0.0097)
Proteins required for microtubule organization and
The organization of microtubules
has well-established roles in chromosome alignment and organi-
zation in both interphase and mitotic cells. We identified three
genes that encode proteins associated with the microtubule
organizing center (MTOC), which is required for proper
microtubule nucleation and establishment of a bipolar spindle:
mcph1, the Dynein motor protein encoding gene dhc64C, and the
Dynein regulator Lis-1. Knockdown of each of these genes
reduced the percentage of single-signal and paired nuclei at
dodeca to 51–58% (P,0.004), while not significantly affecting the
number of signals at 359 (Figure 3, Table S3). Significant increases
in the distances between dodeca FISH signals were also found in
MCPH1, Dhc64C, and LIS-1-depleted cells (P,0.02; Figure 3).
Interestingly, however, euchromatic pairing frequencies at 16E
and 28B were not affected by either mcph1 or dhc64C RNAi
(Figure 3), suggesting these genes may function specifically in
pairing between heterochromatic regions.
Our screen also identified proteins belonging to the well-
described chromosomal passenger complex (CPC), which is
involved in various aspects of mitosis, including chromosome
alignment, spindle assembly, and the completion of cytokinesis
. Specifically, we found that dsRNAs targeting ial (Drosophila
Aurora B), borr, and Incenp all reduced the percentage of single-
signal and paired nuclei at dodeca to 51–66% (P,0.05; Figure 3,
Table S3). These results complement our identification of pav as a
pairing promoter in the pilot run, as pav encodes a kinesin-like
protein required to organize the central mitotic spindle and
contractile ring for cytokinesis . Other functionally related
pairing promoters include major components of microtubules
(aTub84B, bTub56D, bTub85D) and proteins associated with
proper mitotic spindle organization (KLP61F, POLO, MARS)
(Table S3). Additionally, knockdown of genes associated with
chromosome alignment (chb/mast/orbit and cal1) and cytokinesis (pbl,
sti, tsr, scra, and feo) each increased the number of FISH signals per
nucleus as well as the distance between signals (Table S3). FISH
targeting euchromatic 16E and 28B revealed a similar reduction in
single-signal nuclei from 71 to 31–47% at 16E and from 85 to 35–
60% at 28B (P,0.05) following borr, pav, polo, mars, chb, cal1, and sti
RNAi, suggesting these genes are important for pairing at both
heterochromatic and euchromatic regions (Figure 3).
Given the well-established role of these genes in mitosis, we
sought to determine the state of pairing specifically in interphase as
versus that of early mitotic nuclei. FISH targeting dodeca was
performed in combination with immunofluorescent labeling of
cells with an antibody detecting mitotic phosphorylation of histone
H3 on serine 10 (P-H3) to identify and exclude nuclei undergoing
mitosis . Our results confirm that pairing was indeed disrupted
in interphase (P-H3-minus) nuclei following knockdown of mitotic
regulators including borr, ial, polo, mars, chb, cal1, sti, as well as for
mcph1, dhc64C, ida, and slmb (Figure S2). These results suggest that
proper spindle assembly, chromosome segregation, and cytokinesis
are each independently or collectively important for homologous
pairing in interphase nuclei.
Aneuploidy does not necessarily perturb
Many of the candidate pairing promoters described above are
involved in cytokinesis and/or proper chromosome segregation
[66,67], which we reasoned might complicate interpretations of
their FISH phenotype. For example, we cannot rule out the
possibility that increased FISH signals are the result of extra
chromosomes caused by aneuploidy. However, as somatic pairing
has been shown to accommodate polyploidy in a variety of cell
types and tissues [30,68], extra chromosomal copies may not
necessarily be the basis for increased numbers of FISH signals.
Indeed, the Kc167cells used in this study are already tetraploid
(data not shown and ).
To explore the relationship between ploidy and pairing in our
system, we recorded changes in nuclear volume, a reasonable
proxy for chromosomal content. We found that, after knockdown
of borr, CG7236, ial, scra, pav, and klp61f, the volume of .40% of
nuclei was at or above the 95thpercentile of the control volume of
Kc167nuclei (Figure 4), consistent with the frequency of polyploid
cells reported in previous studies [66,67]. Importantly, however,
43% of the candidate pairing promoters did not significantly
increase the population of cells with large nuclear volumes upon
knockdown (Figure 4, section of graph labeled P.0.05), and no
correlation was found between the frequency of large nuclei and
levels of pairing (R2=0.004; Figure 4). Furthermore, despite a
.10-fold increase in the frequency of large nuclei following borr or
Figure 3. RNAi of candidate pairing promoters disrupts pairing. a, Representative FISH images are shown for RNAi knockdown of candidate
pairing promoters (slmb, lin19, shtd, klp61f, dhc64C, mcph1, borr), where the number of FISH signals per nucleus is increased compared to control. The
percentage of single-signal nuclei is noted for both 359 and dodeca. n denotes number of nuclei scored. Scale bars equal 5 mm. b, Relative
frequencies of interhomolog distances (unpaired=two signals .1.0 mm apart) based on dodeca FISH 6 SD for three tests. dsRNA targets are either
grouped based on known interactions (SCF, APC, CPC) or localization patterns of the proteins they encode (MTOC). All significantly reduced the
percentage of paired nuclei compared to control (P,0.05). c, Chromosomal targets of euchromatic FISH probes 16E and 28B and graph displaying
the percentage of single-signal nuclei 6 SD following RNAi. Asterisks denote a significant reduction from control (P,0.05). A minimum number of
100 nuclei were scored for each dsRNA.
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scra RNAi, no correlation was found between the number of FISH
signals and volume for each nucleus (Figure 4). These results argue
that RNAi knockdown of candidate pairing promoters has
consequences in genome organization during interphase that are
independent of ploidy. In line with this observation and discussed
further below, our screen failed to recover any member of the
cohesin complex, which is required to hold sister chromatids
together and maintain proper ploidy .
Cohesin is dispensable for heterochromatic pairing
Considering that separation of sister chromatids should be
detectable by FISH and that ,60% of the Kc167cell population is
in G2 (Figure 5), our candidate pairing genes could formally be
affecting sister chromatid pairing and, in fact, we had anticipated
recovering components of the cohesin complex. Contrary to this
expectation, however, no component was identified. RNAi
depletion of SMC1, CAP (Drosophila SMC3), and VTD
(Drosophila RAD21) resulted in 7560.2 (P=0.0575), 6668
(P=0.4359), and 6169% (P=0.1693) of nuclei with a single
dodeca FISH signal; none of these pairing levels differs signifi-
cantly from the 7063% observed in controls. As these findings
may reflect incomplete knockdown of cohesins, we treated cells
with dsRNA for longer time periods (5 and 6 days) and while
simultaneously targeting two cohesin subunits. We observed no
Figure 4. Relationship between nuclear volume and pairing. a, Rank-order plot of the percentage 6 SD of large nuclei. A nuclei was
considered large if its volume was at or greater than the 95thpercentile volume of control cells. X-axis denotes the RNAi target. P values were
determined by an unpaired t test. Inset, the frequency of single-signal nuclei was plotted against the frequency of large nuclei. The coefficient of
determination R2is a measure of how well the data fit a linear regression, with values close to or exactly one representing a perfect fit. As R2=0.004,
there is no significant correlation between the percentages of paired nuclei and large nuclei. A minimum number of 250 nuclei were scored for each
dsRNA. b, The number of FISH signals was plotted against the volume of each nucleus following borr and scra RNAi. No correlation was found
between the degree of unpairing (number of FISH signals) and the size of the nuclei.
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change in pairing levels in interphase nuclei (data not shown).
Furthermore, depletion of Mei-S332/Shugoshin, required to
protect pericentromeric cohesion from premature separation
, also failed to disrupt pairing in our screen (6960.2%,
P=0.6709). We pursued this unexpected finding by assessing
knockdown of rad21 in mitotic nuclei and observed nearly
Figure 5. RNAi of candidate anti-pairers enhances heterochromatic pairing frequencies. a, Representative FISH images are shown for
RNAi depletion of anti-pairers (cdk8, cap-H2, and orc1), where the number of FISH signals per nucleus is decreased as compared to that of control.
Each resulted in a significant increase in the percentage of single-signal nuclei (noted) for both 359 and dodeca (P,0.05). n denotes number of nuclei
scored. Scale bars equal 5 mm. b, FACS plot (upper) of Kc167cells sorted into G1, early S (S1), late S (S2), and G2/M subpopulations and the percentage
of nuclei producing a single FISH signal 6 SD when targeting 359, AACAC, and dodeca in each. P values were determined by an unpaired t test. A
minimum number of 100 nuclei were scored for each subpopulation. c, Example of a nucleus in which inter-signal distances were measured. Dot-plot
displays the average inter-signal distances per nucleus 6 the standard error of the mean (SEM). Cap-H2, ORC1 and lacZ RNAi results are noted for
reference and red box denotes hits that exhibited a significant shift in the distances per nucleus within the population (P,0.01) based on an unpaired
t test with unequal variance. Insets, relative frequencies of inter-signal distances following Cap-H2 and ORC1 RNAi compared to a lacZ RNAi control. d,
Representative FISH images of a nucleus that produced a single signal for each probe (paired) and a nucleus with partially or fully overlapped 359 and
dodeca signals (clustered). No significant difference in clustering levels was observed by this assay following depletion of any anti-pairer as compared
to control. Graph displays results for the 16 candidate anti-pairers found to produce a significant reduction in inter-signal distances following RNAi in
c (red box). A minimum number of 300 nuclei were scored for each dsRNA.
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complete chromatid separation in the majority of nuclei (Figure
S3), characteristic of sister-chromatid cohesion loss due to efficient
knockdown . We therefore propose that sister-chromatid
cohesion at pericentromeric heterochromatic regions during
interphase can be maintained independent of cohesin or with
reduced amounts of cohesin, possibly due to redundancy with
pairing interactions between homologs (Joyce, EF, unpublished).
Genes identified as candidate suppressors of
Genes required for the G1-S transition.
candidate pairing promoters, our screen identified 65 candidate
anti-pairers, which when depleted decreased the number of FISH
signals per nucleus (Table S4). A large fraction (26%) of these
proteins promote entry into S-phase or are involved in replication,
pointing to the impact of the G1/S transition on pairing (Figure 2).
These included the classical positive G1 regulators of the Cdk/E2f
pathway, including E2f, CYCLIN E, and DM (Drosophila C-
MYC). Depletion of each increased the percentage of single-signal
nuclei from 80 to 86–91% at 359 and from 70 to 79–82% at
dodeca (P,0.05; Table S4). Also identified were the cyclin-
dependent kinase CDK8 and corresponding cyclin CYCC, the
COP9 signalosome subunits CSN4 and CSN5, and the large and
small subunits of ribonucleotide reductase (RNRL, RNRS) that
generate nucleotides for replication (Table S4); depletion of each
has been shown to inhibit S-phase progression and enrich for a
higher G1 population of cells . These results point to the
importance of the cell cycle for heterochromatic pairing.
To further investigate the effect of the cell cycle on heterochro-
matic pairing, we subjected untreated Kc167cells to fluorescence
activated cell sorting (FACS) and directly interrogated pairing
levels in G1, early S, late S, and G2. In unsorted populations,
probes against the 359, AACAC, and dodeca repeats showed
pairing frequencies of 80, 42, and 58%, respectively (Figure 1). We
found that pairing frequencies at 359 remained unchanged
(,80%) throughout interphase, similar to what has been observed
for euchromatic regions . In contrast, we observed higher
pairing frequencies at both AACAC (74%) and dodeca (70%) in
G1 cells compared to early S (47%, AACAC; 42%, dodeca), late S
(45%, AACAC; 40%, dodeca) and G2 cells (53%, AACAC; 52%,
dodeca) (Figure 5). A similar pairing dynamic at all three loci was
obtained in Drosophila S2R+ cells (Figure S4). These results show
that pairing of autosomal heterochromatin is reduced early in
replication, similar to that which has been reported to occur in vivo
. The 359 locus may avoid unpairing during S-phase or,
alternatively, unpair temporarily and subsequently pair with faster
kinetics than do autosomes, possibly avoiding detection in our
analyses of subpopulations. Nevertheless, the reduction in pairing
frequencies at the start of S-phase coupled with our identification
of G1/S regulators as anti-pairing factors is consistent with this
transition representing a critical stage in which pairing interactions
are reduced or become more dynamic.
anti-pairers to include members of the condensin II complex,
given its role in antagonizing pairing interactions in vivo .
Indeed, three subunits of the condensin II complex (Cap-H2, Cap-
D3, and SMC2) were identified (Table S4); RNAi depletion of
Cap-H2, in particular, increased the percentage of single-signal
and paired nuclei from 80 to 87% at 359 and from 70 to 83% at
dodeca (P,0.05; Figure 5). Importantly, we failed to recover any
subunits specific to condensin I, such as cap-D2, cap-G, or barr, the
gene encoding Drosophila Cap-H, suggesting the inhibition of
heterochromatic pairing is a function of condensin II, not
In addition to
We anticipated candidate
The involvement of condensin II in maintaining the higher-
order chromatin state of chromosomes during both mitosis [72,73]
and interphase  has suggested a dichotomy between the level
of chromatin compaction and the paired state of chromosomes
. In line with this model, we also identified HP1a, ORC1, and
SLE as anti-pairers (Figure 5; Table S4). HP1a has been shown to
concentrate at pericentromeric heterochromatin  and is
required for the proper compaction of centromeric satellite repeats
. Depletion of some ORC subunits also results in condensation
defects during mitosis [76,77]. Likewise, SLE is required for
proper compaction of the nucleolus . Therefore, these anti-
pairers may include a class of proteins necessary for the intra-
molecular compaction of heterochromatic regions.
Several anti-pairers may also antagonize
A reduction in the number of FISH signals per nucleus could
represent either a closer alignment of homologs or increased level
of centromere/pericentromeric clustering. Such nonhomologous
associations could increase the frequency of single FISH signals,
yet not necessarily represent homologous pairing. To investigate
the extent of heterochromatic clustering in Kc167cells following
RNAi of candidate anti-pairers, we measured the inter-signal
distances between all signals produced by 359 and dodeca FISH.
We reasoned the average distance would serve as a proxy for how
coalesced the heterochromatic regions were within each nucleus.
In the control, an average inter-signal distance of 1.8 mm per
nucleus was observed between all 359 and dodeca signals. When
compared to the distribution of distances found in the control
population, we found that RNAi of 25% (16/65; see Figure 5d) of
the anti-pairers significantly shifted the population towards smaller
distances (P,0.01, Figure 5), suggesting these genes may have a
role in antagonizing nonhomologous heterochromatic associa-
tions. Included in these 16 ‘anti-clustering’ candidates are
condensin subunit Cap-H2, as well as cell cycle regulators
(CDK8, DM, CYCC), proteins important for nucleotide biosyn-
thesis (RNRL, RNRS, CTPsyn, R), and nuclear import (Fs(2)ket,
NUP214, and NUP358). The remaining 49 anti-pairers, including
HP1a and ORC1, did not significantly change the average inter-
signal distances, possibly reflecting the fact that these proteins
function specifically in antagonizing homologous interactions.
Alternatively, homologous pairing and nonhomologous clustering
may be more mechanistically similar than our results indicate; for
example, we cannot rule out that pairing and clustering require
different levels of activity of the same factors, with pairing being
more sensitive to RNAi depletion.
To investigate whether a reduction in distances between
nonhomologous sequences following RNAi can cause or contrib-
ute to the increased frequency of homologous pairing, we next
analyzed the frequency of overlap between the 359 and dodeca
FISH signals (Figure 5). We reasoned that if an increased
frequency of single FISH signals following RNAi was a direct
consequence of heterochromatin clustering, we would also observe
an increased frequency in colocalization between nonhomologous
sequences (e.g. 359 and dodeca). In the control, we found that
,40% of nuclei that were paired for 359 as well as for dodeca
exhibited complete or partial colocalization of the two signals,
indicating that the pericentromeric regions of the X and 3rd
chromosomes were indeed nonhomologously clustered in a
subpopulation of the cells (Figure 5). Surprisingly, RNAi
knockdown of each of the 65 candidate anti-pairers including
the 16 anti-clustering candidates showed no significant difference
in the frequency of colocalization between the two loci. Even of
those that exhibited a .10% increased level of homologous
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pairing, none were found to increase clustering by more than 4%
(Figure 5). These results suggest that the increased colocalization of
homologous loci following RNAi knockdown of candidate anti-
pairers, such as cap-H2, cannot be fully explained by heterochro-
matic clustering. Instead, the decrease in inter-signal distances
following RNAi of cap-H2 and others suggests that these genes may
have a role in antagonizing nonhomologous associations in
addition to, or perhaps partially contributing to, their role in
antagonizing homologous pairing interactions.
RNAi of a subset of pairing promoters causes Cap-H2–
dependent pairing disruption
Considering that pairing levels are sensitive to the level of
condensin II activity (this study and ), we predicted that some
of the pairing promoters might disrupt pairing upon knockdown
due to misregulated condensin II. To test this model, cells were
depleted for each of the 40 pairing promoters in the presence of
dsRNA targeting cap-H2 and then subjected to FISH targeting
dodeca (Table 1, Table S5). These double knockdown experi-
ments, conducted in triplicate in 384-well plates, revealed three
subsets of pairing promoters: those completely suppressed, those
partially suppressed, and those independent of Cap-H2 co-
Condensin-dependent pairing promoters.
found that 13 (33%) of the pairing hits were completely suppressed
by co-depletion of Cap-H2 (Table 1), suggesting that disruption of
these candidate pairing promoters perturb pairing in a condensin
II-dependent manner. Included in this category was the
Drosophila CRP1 encoding gene, nlp, previously associated with
negatively regulating chromosome condensation ; the per-
centage of nuclei with one dodeca FISH signal was 66% in Nlp-
depleted cells but 78% (P=0.001) in nlp cap-H2 double knock-
downs, the latter being similar to levels found following cap-H2
RNAi alone (P.0.2 compared to cap-H2; Table 1). Similar
suppressions were observed for each component of the SCF
complex; knockdown of slmb, lin19, and skpA reduced the
frequency of single-signal nuclei to 30, 49, and 56%, respectively,
whereas co-depletion of Cap-H2 increased those levels to 76, 79,
and 79%, respectively (P,0.005; Figure 6, Table 1). Additionally,
we found that the reduced nuclear volumes present in SLMB-
depleted cells (5876256 mm3) were suppressed by Cap-H2 co-
depletion (1,0106541 mm3, P,0.0001). Thus, these results reveal
a novel genetic interaction between the SCF ubiquitin-ligase and
condensin II complexes that is important for nuclear organization.
Additional dsRNAs whose FISH phenotypes were dependent
on Cap-H2 included those targeting genes known to be involved in
cytokinesis (pav, scra, and feo) and mitotic spindle organization (polo,
bTub85D, Arp87C, and Cam) (Figure 6, Table 1). Importantly, the
high levels of large nuclei and multi-nucleated cells observed
following pav and polo RNAi was not completely suppressed in cap-
H2 double knockdown experiments (Figure 6). Our examination of
pairing within multi-nucleate cells further revealed that individual
nuclei often produced a single large FISH signal, indicating close
alignment of homologs despite the increased chromosomal content
(Figure 6). This separation of pairing and large nuclei phenotypes
confirms our observation that pairing can accommodate larger
nuclear volumes and extra chromosomal copies.
Condensin-independent pairing promoters.
der of the pairing hits were either partially (12, 30%) or completely
independent (15, 37%) of Cap-H2 co-depletion (Table S5),
perhaps revealing a second, condensin-independent pathway
important for pairing. Those that were partially suppressed
typically restored pairing to control levels, which are, however,
significantly reduced as compared to that produced by cap-H2
RNAi. Proteins corresponding to these hits are involved in
chromosome organization or alignment (e(bx) and tlk) and spindle
organization (aTub84B and mars) and include members of the APC
(shtd and cdc16). We cannot rule out the possibility that some wells
experienced inefficient Cap-H2 depletion, although we consider
this to be unlikely given the low variability between three replicate
tests (Table S5).
Those dsRNAs whose effects were unchanged in the presence of
cap-H2 RNAi targeted genes that encode components of the CPC
(ial and Incenp) and genes associated with MTOC function (mcph1
and dhc64C). dsRNAs targeting genes necessary for cytokinesis (pbl,
sti, and tsr) and chromosome alignment (klp61f and cal1) were also
all found to elicit their pairing effects independent of Cap-H2.
Thus, these data argue that pairing can be influenced by a
complex network of genes, including those that function through
condensin II and those that do not.
In this report, we introduce a high-throughput FISH technology
that enabled a genome-wide RNAi screen for factors involved in
somatic homolog pairing. We identified both candidate pairing
promoting genes as well as candidate anti-pairing genes, support-
ing the idea that homologous pairing is mediated by a balance of
factors with opposing functions (Figure 7). As discussed below,
these results also led to insights into the relationships between
somatic pairing and the cell cycle and condensed state of
Table 1. RNAi of a subset of pairing promoters causes Cap-
H2-dependent pairing disruption.
% of single-signal nuclei1
+ + cap-H23
Chromosome structure nlp 65.862.278.461.30.001
SCF slmb29.960.3 76.360.7
Cytokinesispav 55.764.572.164.4 0.0211
Spindle organization polo56.360.074.464.5 0.0022
bTub85D 64.762.9 74.065.1 0.05
1Data represent the percentage of single-signal nuclei 6 standard deviation for
2N.500 cells for each dsRNA from three trials.
3No dsRNA (blank) or cap-H2 dsRNA was added in addition to dsRNA noted in
4P values determined by unpaired t test by comparing no dsRNA (blank) to cap-
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Somatic pairing may involve multiple mechanisms
Our data are consistent with different regions of the Drosophila
genome exhibiting different levels and stabilities of pairing
[30,33,43,44], suggesting multiple independent mechanisms and/
or different regional sensitivities may contribute to the overall
somatic pairing of homologous chromosomes. For example,
heterochromatin and euchromatin display different pairing fre-
quencies, have different cell cycle dynamics and, as revealed by
studies of Top2, MCPH1, and Dhc64C, might have different
genetic requirements (this study and [30,32,44]). In fact, the
existenceof independent pairing mechanisms might explain whywe
were unable to completely abolish pairing in our screen; ,30% of
nuclei remained paired following dsRNA treatment targeting of our
strongest pairing promoter, slmb, although, of course, this result
could also be a consequence of incomplete RNAi. However, it is
important to note that of the 11 representative heterochromatic
pairing promoting genes we tested, 9 are important for homologous
pairing of euchromatic regions as well. Therefore, the pairing of
same mechanism(s) and maintained independently, vice versa, or,
perhaps, achieved through overlapping forces, with the potential of
each contributing in cis to the proximity of the other.
Figure 6. RNAi of a subset of pairing promoters causes Cap-H2–dependent pairing disruption. a, Representative FISH images are shown
for RNAi knockdown of candidate pairing promoters slmb and pav, where the number of single-signal dodeca FISH signals per nucleus (noted) is
decreased as compared to lacZ RNAi control (P,0.05). Co-depletion of Cap-H2 increases the number of single-signal dodeca FISH signals per nucleus
(P,0.05 compared to slmb and pav RNAi alone). pav RNAi also produces multi-nucleated cells and large nuclei (hashed circles), characteristic of
cytokinesis defects that lead to aneuploidy, which are also observed following pav cap-H2 double RNAi treatment. n denotes number of nuclei
scored. Scale bars equal 5 mm. Also see Table 1. b, Relative frequencies of interhomolog distances (unpaired=two signals .1.0 mm apart) based on
dodeca FISH 6 SD for three tests. Cap-H2 co-depletion also reduces the distances between signals following slmb and pav RNAi (P,0.05), another
indication that pairing is restored. c, The percentage of large nuclei 6 SD following pav and polo RNAi in the presence and absence of cap-H2 RNAi.
Although the frequency of large nuclei in pav cap-H2 is significantly reduced as compared to that of pav (P=0.0072), both were significantly
increased compared to controls (P,0.0001). The frequency of large nuclei in polo cap-H2 was not significantly different as compared to that of polo
(P=0.3791). A minimum number of 500 nuclei were scored for each experiment.
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Our work further indicates that even amongst heterochromatic
regions, different loci may exhibit different stabilities of pairing.
For example, pairing frequencies at the 359-bp repeat locus on the
X-chromosome are higher compared to that of the autosomal
heterochromatic repeated sequences AACAC and dodeca (,80%
compared to ,50%), suggesting that pairing of 359 may be more
difficult to disrupt. Indeed, only 16% of the pairing hits
significantly affected pairing at this locus, and 359 was the only
heterochromatic region tested that did not reveal a drop in pairing
levels during S-phase. We reason the more robust pairing of 359
could be due to structural features, such as the large nature of the
repeated region, estimated to be ,11 Mb in length, and/or the
acrocentric nature of the X-chromosome. Alternatively, the
proximity of the X-linked rDNA gene cluster to 359 may
contribute to pairing via independent forces, as the rDNA locus
is associated with pairing of the X and Y chromosomes during
male meiosis [80–82].
A mechanism for preventing pairing?
Our most striking result was the abundance of candidate anti-
pairers which, similar to Cap-H2 , increased the frequency of
single-signal nuclei when knocked down (Figure 7). If exclusively
or especially effective at heterochromatic regions, anti-pairing
could explain why pairing frequencies are reduced at heterochro-
matic regions compared to that of euchromatic . Thus, the
temporal and spatial regulation of anti-pairing proteins could be
an important aspect of pairing-dependent processes.
The advantages of preventing heterochromatic pairing might
include safeguarding the genome against aberrant repair or
mitotic recombination. Specifically, the unpairing of similar
heterochromatic sequences between homologous and heterologous
chromosomes would preclude either from being used as templates
for repair and therefore prevent loss-of-heterozygosity or chromo-
some rearrangements, respectively. The anti-pairing activity of
HP1a is particularly interesting in this light, as HP1a has been
proposed to contribute to the prevention of aberrant repair
between nonhomologous chromosomes in heterochromatin by
relocalizing broken sites outside the heterochromatic domain .
Our observations suggest that HP1a may facilitate DSB
relocalization by unpairing homologs, which could potentially
increase chromosome mobility. Homolog separation would further
ensure accurate repair by favoring use of the sister chromatid as
the repair template. Anti-pairing could become especially impor-
tant during replication, as spontaneous damage can result from the
passage of replication forks through highly repetitive DNA .
Thus, this viewpoint is consistent with the reduced heterochro-
matic pairing we observed during and immediately after S-phase.
Indeed, a large quantity of anti-pairers included cell cycle
regulators required for entry into S-phase (e.g. e2f and cdk8),
suggesting that homolog unpairing is functionally coupled to the
progression of the cell cycle.
Anti-pairing may also be a potent means to globally, locally,
and/or transiently control gene expression through the cell cycle.
For example, it may be used to inhibit cross-communication
between alleles that are physically paired [30,31] and may explain
why, despite intimate pairing in Drosophila, reports of transvec-
tion are relatively rare throughout the genome. It could even
constitute a conserved form of gene control, a concept in line with
studies of human renal oncocytomas, where the paired state of the
q arm of Chromosome 19 is correlated with misexpression .
Finally, our screen suggests that the mechanism of anti-pairing
involves the maintenance of higher order chromosome structure,
as it recovered several components of the condensin II complex
and ORC1, in addition to HP1a, as anti-pairers. The connection
between anti-pairing and condensin II is particularly intriguing,
given the role of the latter in chromosome compaction. How
might anti-pairing and compaction be mechanistically linked? One
possibility is that the forces of compaction drive the formation of
unpaired loops . Alternatively, anti-pairing may drive com-
paction, where the formation of intermittent unpaired loops pull
flanking chromosomal regions closer together.
Interestingly, the human ORC complex has been implicated in
HP1a recruitment to heterochromatin , and both the ORC
complex and HP1a are required for proper compaction of centric
heterochromatic satellite repeats [86–89]. These observations are
line with compaction being a mechanism by which heterochro-
matic pairing is inhibited, which could be facilitated by the
capacity of arrays of repeated sequences to fold back on themselves
and interact intrachromosomally as versus between homologs 
(Figure 7). The need to preclude heterochromatic pairing, and
hence aberrant repair or recombination, may even provide an
explanation for why heterochromatin remains compacted through
interphase. Intriguingly, ORC1 depletion leads to centromeric
clustering in human cells , possibly reflecting a conserved role
in antagonizing interchromosomal interactions.
A subset of pairing hits are dependent on Cap-H2 activity
Given the role of condensin II in anti-pairing, it is perhaps not
surprising that many of the candidate pairing promoters we
identified had RNAi phenotypes that were dependent on Cap-H2
activity. This ‘condensin-dependent’ subset of pairing promoters
may facilitate pairing indirectly through controlling condensin II
activity (Figure 7). For example, of those completely suppressed by
reduced Cap-H2 activity were three members of the SCF
complex, slmb, lin19, and skpA. Considering that SCF functions
as an E3 ubiquitin-ligase [58,59], it may support pairing by
controlling the level of condensin II during interphase and
targeting this complex for degradation. Consistent with this
Figure 7. Pairing models involving both candidate pairing promoting and anti-pairing factors. a, Summary of candidate pairing factors
identified in the screen. Green boxes denote candidate pairing promoters (hatched green were those identified only in the primary screen) and red
boxes denote candidate anti-pairers. A representative sampling of pairing promoters were tested (italicized) and found (asterisk) to be important for
euchromatic pairing. Proteins are grouped based on either a known function or localization pattern. Candidate pairing promoters found to elicit RNAi
phenotypes dependent on Cap-H2 are presented as potential condensin II regulators (question marks). Note one dsRNA targets both CG42550 and
CG14463 (separated by comma). b, Model for how compaction and intrachromosomal interactions compete with homolog pairing. Although all
chromosomal regions may transiently unpair prior to or during S-phase, homolog pairing (red circles) of heterochromatic centromeric regions (grey
lines) may be in competition with intrachromosomal interactions (black circles), causing pairing to occur less often, more slowly, or with less stability
than homolog pairing of less compacted euchromatic regions (blue lines), where the paucity of repeated sequences reduces the likelihood of
intrachromosomal interactions. This figure is not meant to imply a causal or dependent relationship between heterochromatic and euchromatic
pairing, although such a relationship may exist. c, Model for pairing through the cell cycle. Proper spindle formation and chromosome segregation
during anaphase/telophase of mitosis may bundle centromeric heterochromatic regions to spindle poles and directly facilitate or accelerate homolog
recognition. Such interactions would then be maintained through G1. During S-phase, however, the pairing of regions is perhaps more dynamic,
becoming antagonized and then re-paired subsequently. In this case, not all pairing interactions would be reestablished until the following mitosis.
Euchromatic pairing is not depicted.
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model, slmb RNAi also resulted in smaller nuclear volumes, a
phenotype dependent on Cap-H2 and characteristic of hypercon-
densation. Alternatively, the role of SCF in pairing may be linked
to its role in cell cycle regulation, with knockdown causing an
enrichment of stages where pairing is normally reduced.
Additional dsRNAs whose FISH phenotypes were dependent
on Cap-H2 included those targeting genes known to be involved in
mitotic spindle organization or cytokinesis, such as polo and pav.
Interestingly, while Cap-H2 co-depletion suppressed the pairing
phenotype following polo and pav knockdown, only a mild
reduction in the frequency of large nuclei was observed. Thus,
the increased nuclear volumes and multi-nucleated cells (both
characteristic of cytokinesis defects) in the double knockdowns
confirms that pairing can accommodate larger nuclear volumes
and, likely, extra chromosomal copies. Although the relationship
between cap-H2 and these pairing promoters remains to be
elucidated, our findings argue that these factors may lead to a
disruption in pairing by modulating condensin II activity and/or
inhibiting the activity of proteins necessary for decondensation at
the end of mitosis.
We note an alternative model in which the consequences of
depleting pairing promoters can be countered by the loss of
condensin II. For example, the role of condensin II in resolving
DNA catenations suggests that pairing may involve DNA
catentation and, if so, cap-H2 RNAi may suppress unpairing
simply by precluding paired homologs from decatenating.
Considering that mitotic spindle forces are required for the
resolution of DNA catenations , this interpretation suggests
that co-oriented and catenated homologs attached to the same
spindle pole might remain catenated and therefore paired into the
next cell cycle by escaping antagonizing spindle forces. In light of
this, those gene knockdowns that disrupt spindle stability (e.g. pav
RNAi) could create new antagonizing forces against homologous
chromosomes and thus aberrantly remove any residual catenations
or pairing interactions. In the absence of condensin II, however,
the accumulation of DNA catenations between homologous
chromosomes may enhance pairing and prevent homolog
Potential models for somatic pairing
Of the candidate pairing promoters, 27 had RNAi phenotypes
that were not dependent or only partially dependent on Cap-H2
activity (Figure 7, Table S5). This ‘condensin-independent’ class
includes members of the APC, components of the CPC, and
proteins involved in spindle organization, chromosome alignment,
and cytokinesis. Perhaps the most surprising feature of these results
is the level of conservation among these genes; 25 out of 27 of
these candidate pairing promoters have putative human orthologs
(Table S5), possibly suggesting that eukaryotes have generally
retained the mechanism and therefore ability to pair homologs.
Our identification of mitotic regulators is consistent with a
critical step of pairing occurring during mitosis, with anaphase
and/or telophase being of particular import. Although pairing
may be disrupted at the onset of anaphase [43,44], the drawing of
centromeric regions to spindle poles during late anaphase/
telophase could directly facilitate or accelerate the homolog
interactions by bundling heterochromatic regions into a relatively
small volume (Figure 7). This chromosomal arrangement, in which
centromeres point toward poles with telomeres dragging behind
may resemble a Rabl configuration, which has been proposed to
promote homolog pairing by reducing the nuclear space in which
chromosomes search for their homologs [44,91,92]. This idea is
supported by our identification of pairing promoters essential for
focusing microtubules to spindle poles during anaphase (dhc64C,
lis-1, and mcph1; [93,94]) and many genes that encode proteins
necessary for spindle assembly, chromosome alignment, and/or
the metaphase-anaphase transition; disruption of each would
impair the proper bundling of heterochromatic regions. With the
exception of dhc64C and mcph1, these genes were also found to be
important for euchromatic pairing, suggesting the pairing of
chromosome arms could be facilitated and/or stabilized by a
similar mitosis-driven mechanism, possibly extending, although
not necessarily linearly, from both pericentromeric and interstitial
heterochromatin. A complete understanding of pairing, however,
will require a screen for pairing factors wherein the FISH assay
targets euchromatic loci directly to determine whether there are
pairing factors that are essential only at euchromatin.
An additional, yet not mutually exclusive, model proposes that
at least some pairing promoters function directly in the mainte-
nance of homolog pairing during interphase. For example, kinesin
Klp61F, Dynein motor protein Dhc64C, and microtubule binding
protein CHB also localize to cytoplasmic interphase microtubule
arrays [93,95,96]. Intriguingly, cytoplasmic microtubule-based
movement (involving Dynein) has a wide-spread role in ensuring
proper and timely homolog pairing during meiosis, presumably by
inhibiting incorrect nonhomologous associations, which as we
discussed above, may be in competition with homologous pairing
Lastly, as we identified CPC components INCENP and IAL
(Drosophila Aurora B) as condensin-independent pairing promoters,
an intriguing parallel to our work may be the discovery of DNA
tethers, coated with INCENP and Aurora B, that connect and
 as well as achiasmate homologous chromosomes in Drosophila
female meiosis . These DNA linkages may be a general feature of
Drosophila chromosomes and share genetic properties with somatic
pairing mechanisms. Therefore, additional hits identified in this
screen may also prove to be important for the pairing and accurate
segregation of homologous chromosomes during meiosis.
In sum, this study indicates that somatic homolog pairing may be
mediated by antagonistic mechanisms, possibly involving .100
genes, many of which are highly conserved throughout higher
eukaryotes. Excitingly, a number of these genes have also been
identified as pairing factors through a whole-genome screen
examininglocalization ofthe MSLdosage compensationmachinery
in Drosophila (J. Bateman and E. Larschan, personal communica-
tion). Our work also brings support to long-standing observations
correlating stages of the cell cycle to differing degrees of homolog
pairing [43–46] and further provides a genetic framework
suggesting that progression through the cell cycle can facilitate,
adjust, and thus control pairing-dependent processes. Indeed, cell
cycle progression, per se, may constitute a potent means by which
cells control gene regulatory mechanisms that rely on interchro-
mosomal interactions, with prolonged duration or arrest in G1, S,
G2, or mitosis enhancing or suppressing such interactions .
Homolog pairing may even, in turn, exert some control over cell
cycle progression. A fuller picture of pairing, however, awaits a
parallel screen for factors involved in pairing at euchromatic loci in
Drosophila as well as studies of pairing, in general, in other
organisms. Finally, this report describes a technology for high-
throughput FISH, which can be widely applied to the analysis of
chromosome positioning and nuclear organization.
Materials and Methods
Kc167cells [100,101] obtained from the Drosophila Genome
Resource Center were grown at 25uC following standard
Screen for Somatic Pairing Genes
PLoS Genetics | www.plosgenetics.org15 May 2012 | Volume 8 | Issue 5 | e1002667
protocols. Cultures were grown in sterile filtered Schneider’s
medium (GIBCO) supplemented with heat-inactivated fetal
bovine serum (FBS, to a final concentration of 10% v/v) and
penicillin–streptomycin (50 units/mL penicillin, 50 mg/mL strep-
tomycin; GIBCO). To ensure that experiments were done with
log-phase cells, active cultures were split at a 1:5 ratio, cultured for
3–4 days, and then passaged at 2–46106cells/mL prior to the
Generation of FISH probes
Oligo probes for the 359, AACAC, and dodeca heterochro-
matic repeats [54,102] were synthesized with a 59 Cy5, Tye3, and
FAM488 fluorescent dye, respectively, by Integrated DNA
Technologies (IDT). Probe sequences were designed to be
relatively small in length (15 to 35 bases) for efficient nuclear
integration and have melting temperatures .70uC to withstand
stringent wash conditions. Probe specificity was tested by
hybridization to metaphase spreads (data not shown). Those
sequences found to produce the most robust signal at the lowest
concentration with highest level of specificity were selected for
future analyses. The sequences are as follows: Cy5-359: Cy5-
and FAM488-dodeca: FAM488-ACGGGACCAGTACGG. Oligo
probes were resuspended in 16TE at 100 mM concentration and
stored at 220u.
DNA probes to 16E and 28B were synthesized according to
standard protocols. Bacterial artificial chromosome BACR17D02
RP98-17D2 (AC012163; AE003507) corresponding to 16E1–
16E2 (abbreviated as 16E) and P1 plasmids (Berkeley Drosophila
Genome Project) containing cloned Drosophila genomic DNA
corresponding to chromosomal regions 28B1–28B2 (abbreviated
as 28B; DS01529; ) were synthesized and labeled by nick
translation/direct labeling (Vysis) following the manufacturer’s
Synthesis of dsRNA and application of RNAi to cells was
carried out according to published protocols . Control cells
were treated with a blank of deionized water or, when noted,
dsRNA targeting lacZ. Cells were fixed 4–5 days after treatment.
Standard FISH protocol
Our standard FISH protocol on slides was adapted from
previously published protocols [30,102,103] and involved the
following steps: Cells from log-phase cultures were adhered to
lysine-treated glass slides for 1 hr. Slides were then gently washed
with PBS (pH 7.2), fixed for 5 minutes with 4% formaldehyde in
PBS at room temperature (RT), washed in 26SSCT (0.3 m NaCl,
0.03 m sodium citrate, 0.1% Tween-20) for 5 minutes at RT, and
washed in 26SSCT/50% formamide for 5 minutes. Pre-denatur-
ation steps were carried out as follows: 26SSCT/50% formamide
at 92u for 3 minutes and then 60u for 20 minutes. DNA probe in
hybridization buffer (20% dextran sulfate/26SSCT/50% form-
amide) was then added to the slides, covered with a coverslip, and
denatured on a heat block in a water bath set to 92u for exactly
3 minutes, after which slides were transferred to a humidified
chamber and incubated overnight at RT. Coverslips were then
removed while the slides were being washed (26SSCT at 60u for
10 minutes). For FISH with euchromatic probes (either P1 or
BAC generated), an additional wash at RT in 0.26SSC was
conducted for 10 minutes. A final RT wash in 26SSCT was then
done for 5 minutes, after which Slowfade with DAPI (Invitrogen)
was added. Coverslips were applied and sealed to the slides with
nail polish. Images were collected using an Olympus IX81
fluorescence microscope with a 606, N.A. 1.35 lens. Nuclei were
imaged by collecting optical sections through the entire nucleus.
The data are shown as maximum projections; however, the
analysis of the images was performed by examining one section at
384-well FISH protocol
A 384-well plate containing dsRNA was centrifuged at 1200
RPM for 2 minutes. Log-phase Kc167cells (grown for 3 days) were
centrifuged (1200 RPM for 5 minutes), counted, and diluted in
FBS-free media to 16106cells/mL. Sterile, autoclaved Wellmate
tubing was purged with sterile PBS in a tissue culture hood. After
the Wellmate was primed with the diluted cells, 10 mL were added
to each well. The plate was then spun (1200 RPM, 2 minutes) and
incubated in a 25uC incubator for 30 minutes. With freshly
primed sterile tubing, regular FBS-containing Schneider’s media
was added to each well (30 mL/well) and the plate was then spun
(1200 RPM, 2 minutes) before being transferred to a humidifying
chamber in a 25uC cell culture incubator. Four (primary screen) or
five (validation screen) days after dsRNA treatment, the plates
were removed from the incubator. The cell media was aspirated
and, with a primed Wellmate, wells were quickly washed with PBS
(60 mL/well), which was then immediately aspirated. Plates were
incubated with 4% Formaldehyde (30 mL/well) for 5 minutes,
aspirated, and quickly rinsed (30 mL PBS/well), then washed with
26SSCT (80 mL/well) for 5 minutes. Then, plates were washed
with 50% formamide/26SSCT (80 mL/well) for 5 minutes. The
plates were double-sealed with adhesive aluminum seals, pre-
denatured by being floated in a 91uC waterbath for 3 minutes,
60uC waterbath for 20 minutes, and allowed to cool to room
Probes were prepared in 10 mL of Hybridization Buffer (20%
dextran sulfate/26 SSCT/50% formamide) per plate [the
100 mM stock solution of oligo probes (see above) was diluted
1:10,000 and 1:5,000 for FAM488-dodeca and Cy5-359, respec-
tively]. The plate was aspirated, after which probe mix was added
to each well (20 mL/well). The plates were again double-sealed
with aluminum adhesive seals, centrifuged (1200 RPM for
2 minutes), and denatured in a 91uC waterbath for 20 minutes.
Hybridization was conducted for 30 minutes at 45uC by floating
the plate in prewarmed 45uC wash buffer (50% formamide in
26SSCT) in a Tupperware within an incubator. The plate was
washed by being submerged in 45uC wash buffer while having its
seal removed, allowing buffer to wash immediately into the wells.
The plates, still submerged in 45uC wash buffer, were then placed
on a slow moving shaker. Buffer was vigorously ‘‘flicked’’ out of the
wells after 5 minutes and again after 20 minutes, being quickly
resubmerged after each. The plate was aspirated and washed with
room temperature 50% formamide/26SSCT (80 mL/well) for
5 minutes. Hoechst was diluted 1:1,500 in 26SSCT and added to
each well (30 mL), after which the plate was incubated for
5 minutes. The plate was then washed twice for 10 minutes each
with 26SSCT (60 mL/well). The plate was then sealed with a clear
adhesive seal and centrifuged (1200 RPM for 2 minutes). To
ensure optimal imaging, all plates were prepped and imaged in the
same day. For automated microscopy, the cells were imaged with
an Evotec Opera Confocal Screening Microscope (Perkin-Elmer)
with a 636 water immersion lens. 10 images per well were
acquired, each of which were autofocused prior to taking a single
optical section through the nuclei. Note that the Opera system had
limits as to how many images could be taken per well. Considering
the short depth of nuclei within adhered Drosophila cells and the
brightness of our FISH signals, we chose to take 10 autofocused
Screen for Somatic Pairing Genes
PLoS Genetics | www.plosgenetics.org 16May 2012 | Volume 8 | Issue 5 | e1002667
images per well without Z-slices to maximize the number of cells
Automated data analysis
All the images acquired in this screen were analyzed automat-
ically using a customized algorithm developed in MATLAB. The
analysis was carried out in three main steps: nuclear segmentation,
FISH foci identification, and cell classification/scoring. In the
nuclear segmentation step, the DAPI image was first smoothed
and background corrected. The corrected image was then
segmented by applying a threshold determined by Ridler-Calvard
method . To correct for under-segmentation caused by cell
clustering, large clusters of nuclei were first identified, and then
processed through a shape-based watershed to divide individual
nuclei apart. In the second step, each nucleus was analyzed
individually to identify foci in both red (dodeca, pseudocolored)
and green (359, pseudocolored) channels. To achieve this, an
image patch was cropped out of smoothed green/red image based
on nuclear mask from the first step. For each nucleus, the median
value and standard deviation of intensity were determined in the
nuclear region for both red and green channels. A threshold,
which is two standard deviations higher than the median value,
was then applied to the red/green image crop to pick up all the
bright spots in the nuclear region in both channels. The bright
spots were then filtered based on size criteria to prevent false
detection caused by background noise. Following foci identifica-
tion, we classified/scored cells using three different approaches. In
approach #1, we sorted all cells into six different groups based on
the number of foci they contained in each channel, namely 0, 1, 2,
3, 4, $5 foci. In approach # 2, we measured the pairwise
distances between foci of the same color to further analyze pairing
as well as for both colors to investigate clustering. In the third
approach, we identified cells with colocalized foci of different
colors (one red and one green) by checking whether there were any
overlapping pixels between the foci detected from two different
channels within any given nucleus. Finally, we tried to identify
those dsRNAs from our hit list that caused an abnormal level of
polyploid cells due to failed cell division. For this purpose, we
filtered all the cells based on their size using a cut-off value
determined from the largest 95thpercentile cell sizes of control
wells (data not shown).
Criteria for primary and validation screen cut-offs
In the primary genome-wide screen, a dsRNA was considered a
‘pairing promoting’ hit if, in both replicate plates, the dsRNA
either decreased the percentage of nuclei with a single FISH signal
to a z-score of #22.0 or increased the percentage of nuclei
containing two, three, or four foci to a z-score of $2.0. 374
dsRNAs were considered hits using these criteria. Importantly,
using these cut-offs, greater than 90% of positive control wells
seeded with dsRNA targeting pav or cap-H2 resulted in the
expected increase or decrease in FISH signals per nucleus. In the
validation screen, however, we sought to identify the strongest hits
and, therefore, only listed dsRNAs that significantly (P#0.05)
decreased the percentage of nuclei with a single FISH signal as
compared to control cells. This created a much more stringent cut-
off and reduced the number of gene hits to 40.
For dsRNAs that produced an ‘anti-pairing’ phenotype in the
primary screen, each replicate plate produced an increase in the
percentage of nuclei with a single FISH signal to a z-score of $2.0.
Similarly, the criterion used for hits in the validation screen was
those dsRNAs that significantly (P#0.05) increased the percentage
of nuclei with a single FISH signal as compared to control cells.
Primary antibody against phosphohistone H3 (P-H3; rabbit
used at 1:100; Epitomics) was used for immunofluorescence in a
PBS buffer following FISH reactions. A Cy3-conjugated anti-
rabbit secondary antibody (Jackson ImmunoResearch Laborato-
ries) was used at 1:165 according to the manufacturer’s instruction.
Kc167cells were grown in six-well plates, pipetted onto slides,
exposed to hypotonic solution (1% Sodium Citrate) for 30–
45 minutes and then fixed in 3 Methanol: 1 Acetic acid. Cells were
then dried for a few minutes and DNA was stained with DAPI.
Fixed cells were RNAsed (1 mg/mL), incubated with a 2 mM
solution of Propidium Iodide (PI), and sorted on a Becton
Dickinson FACSAria. The cells were then adhered to lysine-
coated slides for 2–3 hours, and then subjected to FISH. We
confirmed that cells had been successfully sorted into G1, early S,
late S, and G2 subpopulations by assessing nuclear DNA content
as determined by DAPI staining (data not shown).
following RNAi knockdown of pairing promoters. The results
from RNAi of all 40 pairing promoters are plotted. X-axis is the
percentage of single-signal nuclei at 359. The Y-axis is the
percentage of single-signal nuclei at dodeca. The coefficient of
determination R2=0.3586 represents significant fit of the data to a
linear regression, suggesting that pairing levels between the two
chromosomal regions are correlative. A minimum number of 250
nuclei were scored for each dsRNA.
Correlation between 359 and dodeca pairing
interphase nuclei. a, Representative image showing both inter-
phase (PH-3-minus) and mitotic (PH-3-positive) nuclei with
dodeca FISH. b, Following depletion of 11 representative pairing
promoters, the percentage of single-signal nuclei was significantly
decreased compared to control (P,0.05). Error bars denote SD. A
minimum number of 100 nuclei were scored for each dsRNA.
Pairing promoters are important for pairing in
separation during mitosis. Chromosomes from control metaphase
cell with paired sister chromatids and from a RAD21 RNAi
metaphase cell clearly showing separated sister chromatids.
RAD21 depletion leads to premature sister chromatid
S2R+ cells. FACS plot of S2R+ cells with four gates for G1, early S
(S1), late S (S2), and G2 phases of the cell cycle. The frequency 6
SD of paired nuclei when targeting 359, AACAC, and dodeca in
the G1, S1, S2, and G2 subpopulations. Asterisks denote a
significant reduction in paired nuclei at each locus compared to
that of G1 cells (P,0.05). A minimum number of 100 nuclei were
scored for each subpopulation.
Heterochromatic pairing through the cell cycle in
Comparison of pairing levels under different control
listed are those that produced a significant z-score in the primary
screen. Plate and well location are noted along with dsRNA
Pairing candidates isolated in primary screen. dsRNAs
Screen for Somatic Pairing Genes
PLoS Genetics | www.plosgenetics.org17 May 2012 | Volume 8 | Issue 5 | e1002667
amplicon and target gene (if one is annotated). %1 359 and %1
dod denote the percentage of nuclei with a single 359 or dodeca
focus, respectively. Corresponding z-scores are noted.
amplicon, target gene, and well location are noted along with
total cell count (Cell_cnt), the percentage of large nuclei
(Large_nuclei), and the percentage of nuclei with one, two, three,
four, and five or more FISH foci for 359 and dodeca. The
percentage of nuclei with a single focus for both 359 and dodeca
(1R1G_nuclei) as well as the subset of these that exhibit
colocalization (1R1G_touch_nuclei) are also noted. Standard
deviations (stdev) from three replicate tests are presented to the
right of each parameter.
Validated candidate pairing promoters. dsRNA
target gene, and well location are noted along with total cell count
(Cell_cnt), the percentage of large nuclei (Large_nuclei), and the
percentage of nuclei with one, two, three, four, and five or more
FISH foci for 359 and dodeca. The percentage of nuclei with a
single focus for both 359 and dodeca (1R1G_nuclei) as well as the
subset of these that exhibit colocalization (1R1G_touch_nuclei) are
also noted. Standard deviations (stdev) from three replicate tests
are presented to the right of each parameter.
Validated candidate anti-pairers. dsRNA amplicon,
presented for the pairing promoters whose RNAi phenotypes were
either partially or completely independent of Cap-H2 co-
depletion. dsRNA target genes and thier putative human orthologs
are noted as well as the percentage of nuclei with a single dodeca
FISH signal in the presence and absence of Cap-H2 RNAi.
Cap-H2–independent pairing promoters. Data are
We thank the Wu lab, Jack Bateman, Giovanni Bosco, and the reviewers
for insightful comments and critical reading of the manuscript. We also
thank Jack Bateman, Erica Larschan, Mitzi Kuroda, Giovanni Bosco, and
Gregory Rogers for sharing unpublished information and Stephanie Mohr
and the Drosophila RNAi Screening Center at Harvard Medical School
(NIH/NIGMS 2R01GM067761) for providing RNAi libraries, bioinfor-
matics tools, and other support for the screen.
Conceived and designed the experiments: EFJ. Performed the experiments:
EFJ. Analyzed the data: EFJ. Wrote the paper: EFJ. Conceived of and
designed the high-throughput screening technology: BRW. Further
developed the high-throughput screening technology: EFJ. Developed the
script for image analysis: TX EFJ. Participated in all aspects of the project:
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