A sequence motif enriched in regions bound by the Drosophila dosage compensation complex.

Abstract

In Drosophila melanogaster, dosage compensation is mediated by the action of the dosage compensation complex (DCC). How the DCC recognizes the fly X chromosome is still poorly understood. Characteristic sequence signatures at all DCC binding sites have not hitherto been found.
In this study, we compare the known binding sites of the DCC with oligonucleotide profiles that measure the specificity of the sequences of the D. melanogaster X chromosome. We show that the X chromosome regions bound by the DCC are enriched for a particular type of short, repetitive sequences. Their distribution suggests that these sequences contribute to chromosome recognition, the generation of DCC binding sites and/or the local spreading of the complex. Comparative data indicate that the same sequences may be involved in dosage compensation in other Drosophila species.
These results offer an explanation for the wild-type binding of the DCC along the Drosophila X chromosome, contribute to delineate the forces leading to the establishment of dosage compensation and suggest new experimental approaches to understand the precise biochemical features of the dosage compensation system.

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RESEARCH ARTICLEOpen Access
A sequence motif enriched in regions bound by
the Drosophila dosage compensation complex
Miguel Gallach1, Vicente Arnau2, Rodrigo Aldecoa3, Ignacio Marín3*
Abstract
Background: In Drosophila melanogaster, dosage compensation is mediated by the action of the dosage
compensation complex (DCC). How the DCC recognizes the fly X chromosome is still poorly understood.
Characteristic sequence signatures at all DCC binding sites have not hitherto been found.
Results: In this study, we compare the known binding sites of the DCC with oligonucleotide profiles that measure
the specificity of the sequences of the D. melanogaster X chromosome. We show that the X chromosome regions
bound by the DCC are enriched for a particular type of short, repetitive sequences. Their distribution suggests that
these sequences contribute to chromosome recognition, the generation of DCC binding sites and/or the local
spreading of the complex. Comparative data indicate that the same sequences may be involved in dosage
compensation in other Drosophila species.
Conclusions: These results offer an explanation for the wild-type binding of the DCC along the Drosophila X
chromosome, contribute to delineate the forces leading to the establishment of dosage compensation and
suggest new experimental approaches to understand the precise biochemical features of the dosage
compensation system.
Background
In Drosophila, dosage compensation occurs by hyper-
transcription of the genes of the single X chromosome
in males, leading to a level of expression similar to that
found for the copies of those same genes located on the
two female X chromosomes [1-3]. This hypertranscrip-
tion is controlled by a ribonucleoprotein complex,
known as Dosage Compensation Complex (DCC; a. k. a.
MSL complex, compensasome), which includes at least
five proteins, encoded by the male-specific lethal (MSL)
genes [4-8], and two non-coding RNAs, derived from
the roX1 and roX2 genes [9-11]. The DCC, functional
only in males, modifies the chromatin structure of the X
chromosome by altering its pattern of histone acetyla-
tion [12,13]. Immunostaining with antibodies against
MSL proteins demonstrated that the DCC complex spe-
cifically recognizes hundreds of sites along the male X
chromosome [14-20]. How this specificity is achieved is
still poorly understood. Data obtained by hybridizing
chromatin immunoprecipitates obtained from regions
bound by the DCC complex to genomic tiling arrays
(ChIP-chip) have led to the precise characterization of
many binding sites ([21,22]; see also ref. [23]). So far,
however, a common sequence motif shared by those
regions has not been described. Just a slight enrichment
for some very short sequences has been detected in
those experiments, as well as with related techniques
[21-25]. Partial DCCs are still generated in flies that are
mutant for some of the genes encoding proteins of the
complex. These incomplete DCCs are also able to
recognize the X chromosome, but only in a limited
number of places, first described by cytological analyses
[16]. These places were suggested to be “entry sites”,
high-affinity binding sites from which the DCC would
epigenetically spread to the rest of the chromosome
[26]. Later, convincing evidence was obtained against
generalized spreading from the few cytologically charac-
terized sites as the only determinant for the wild-type
pattern of DCC binding [27,28]. Recent data support
however that the complex indeed has a higher affinity
for those sites than for the rest of the X chromosome
[29] and that these sites are more abundant than the
cytological data suggested [29,30]. Therefore, they may
* Correspondence: imarin@ibv.csic.es
3Instituto de Biomedicina de Valencia, Consejo Superior de Investigaciones
Científicas (IBV-CSIC), Valencia, Spain
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© 2010 Gallach et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
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contribute to spreading at a local scale [30-32]. A
sequence motif, containing several GA/TC dinucleo-
tides, has been found to be enriched in high affinity
binding sites of the DCC ([29,30]; we will refer to this
motif throughout the text as [GA/TC]n).
All these results are compatible with a genetic model
in which the X chromosome is enriched for two differ-
ent types of sequences. One kind of sequences, charac-
terized by the (GA/TC)nmotif, would be required for
the complex to bind the high affinity sites. The other
type, which is yet to be characterized, would be needed
to achieve wild-type pattern of DCC binding. However,
the characterization of epigenetic marks, often asso-
ciated to gene transcription, which contribute to DCC
binding, and the discovery of acquisition of DCC bind-
ing by some transcribed autosomal genes transposed to
the X chromosome, has led to an alternative model: the
DCCs would spread from the high affinity sites largely
or even exclusively by following epigenetic signals
[31,33-36]. These models are not in contradiction and
formulating a combined model is possible (summarized
in refs. [37,38]). On one hand, the Drosophila X chro-
mosome may contain a large number of sites, with char-
acteristic sequences able to attract the DCC with
variable strengths. On the other hand, transcriptional
status and epigenetic signals may influence the binding
and/or the spreading of the complex. Obviously, this
hybrid model could be possible only if a certain type of
sequences is found to be enriched at all DCC binding
sites and not only at the high affinity ones.
We recently developed a new type of DNA sequence
analysis, called oligonucleotide profiling, which allows for
the rapid detection of singular features in chromosomes
[39,40]. Using this method, we showed that the X chromo-
somes of drosophilid species are less complex than the
autosomes and that such a pattern correlates with the
acquisition of dosage compensation by neo-X chromo-
somes [39]. These results suggested that simple sequences
may be linked to dosage compensation and that oligonu-
cleotide profiling may be used to detect X chromosome-
specific sequences involved in the recognition of that
chromosome by the DCC. In this paper, we demonstrate
that indeed our method allows for the detection of a pecu-
liar type of sequences, hitherto uncharacterized, which is
enriched at the DCC binding regions. We define a repeti-
tive sequence motif that may be involved in X-chromo-
some detection or in spreading of the DCC along the X
chromosome of Drosophila species.
Methods
Sequences, sequence analyses and genomic data
representation
D. melanogaster chromosomes (Release 4.3) were
obtained from the National Center for Biotechnology
Information (NCBI; http://www.ncbi.nlm.nih.gov/).
Accession numbers were as follows: X: NC_004354.2;
2L: NT_033779.3; 2R: NT_033778.2; 3L: NT_037436.2;
3R: NT_033777.2. All Blast analyses were also per-
formed online at the corresponding NCBI web page
http://blast.ncbi.nlm.nih.gov/Blast.cgi. Figures containing
Drosophila melanogaster genomic regions were drawn
with GBrowse [41].
Definition of DCC binding regions
For our analyses comparing the DCC binding sites with
X chromosome-specific sequences, we used the results
obtained by Gilfillan et al. ([22]; kindly provided by the
authors) as primary data. These data refer to punctual,
quantitative signal values in ChIP-chip experiments for
multiple probes tested along the X chromosome. We
wanted instead to define qualitative DCC binding
regions which could be compared with X-specific
regions. To do so, we needed to define a minimum sig-
nal level and also when two adjacent positive probes
could be considered part of the same binding region.
After some tests with Gilfillan et al. [22] data, we
decided to choose a minimum value of signal equal to 2
(i. e., a stringent condition, well above background
levels) and a maximum distance between consecutive
significant values of 1 Kb to be considered part of the
same region. This maximum distance was chosen con-
sidering that consecutive oligonucleotides in the tiling
arrays are separated in the genome by 50 - 100 nucleo-
tides and that repeats are excluded, leading to significant
gaps [21,22].
Oligonucleotide profiling and definition of X-specific
regions
We searched along the X chromosome for regions con-
taining X-specific sequences using oligonucleotide pro-
filing, implemented in our program UVWORD [39,40].
The UVWORD algorithm is simple: the program first
reads a selected sequence (source sequence), one
nucleotide at a time, and establishes the frequencies of
all oligonucleotides of size k nucleotides present in that
sequence. Then, it reads a second DNA sequence (tar-
get sequence), again one nucleotide at a time, and
associates each DNA word present in the target
sequence with the frequency in the source sequence. By
using a single target sequence and two source
sequences, relative ratios of frequencies of oligonucleo-
tides in the source sequences can be obtained [39,40].
Here, given that we wanted to establish X-specific
regions, the target sequence was the X chromosome
and the two source sequences were the X chromosome
itself and an autosome, the 2L chromosome arm. In
Gallach et al. [39], we demonstrated that all D. melano-
gaster major autosomal arms have essentially identical
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oligonucleotide compositions. Therefore, it is only
necessary to use one autosome for comparing with the
X chromosome.
The characterization of X-specific regions was there-
fore performed as follows: for each word of the X chro-
mosome (target), its frequency was determined on the
X chromosome (source 1) and on the 2L arm (source
2) and these values were then combined to obtain an
X/2L ratio (for words present on the X, but absent on
2L, we fixed a 2L value = 0.5). This X/2L ratio was then
corrected for the relative sizes of the X and 2L chromo-
somes. The final corrected X/2L ratio provides a mea-
sure of X-specificity for each word on the X
chromosome [39]. However, here our interest was not
to establish how X-specific particular words were, but
to detect X-specific regions which could be compared
to DCC binding sites. Therefore, we decided to average
the values of a certain number R of adjacent words of
size k to obtain smoothed profiles of X-specificity. In
this study, we used the parameters k = 13 and R = 5.
The reasons for choosing words of 13 nucleotides,
which are optimal for Drosophila chromosome analyses,
are described in Gallach et al. [39]. We chose R = 5 in
order to allow the analysis of small X-specific regions.
In summary, the two parameters, k = 13 and R = 5,
define loci consisting on 5 adjacent words of size k = 13
of the X chromosome (total size of a locus = 17 nucleo-
tides) for which average X/2L ratios are calculated.
Notice that, with each nucleotide that the program
reads in the target sequence, a new locus of 17 nucleo-
tides is established, which overlaps k + R - 2 = 16
nucleotides with the previous one, and a new average is
calculated.
After obtaining the average X/2L ratios, the next step
was to establish when a region of the X (i.e., a single
locus, or oftentimes, a set of adjacent, overlapping loci)
was significantly X-specific. We explored what the effect
was of using different threshold values of the average
X/2L ratios with respect to their ability to explain DCC
binding regions. As shown in the Results section, the
best results were obtained with an average X/2L ratio of
6.8 (i. e., when the region contained oligonucleotides
that were present on average at least 6.8 times more
often on the X than on the 2L arm). Therefore, we
eliminated all regions below the 6.8 cutoff and retained
the rest for comparison with the DCC binding regions.
Comparison of DCC binding regions and X-specific
regions and characterization of motifs
After the DCC binding regions and the X-specific
regions were specified, we compared them in order to
select a set of overlapping sequences. The selected
sequences, which are at the same time able to strongly
bind the DCC and significantly X-specific, were analyzed
with five of the best available programs designed to
detect motifs from sets of sequences. These programs
were MEME [42], ALIGNACE [43], WEEDER [44],
MOTIFSAMPLER [45] and GLAM2 [46]. The logic for
using several programs, with very different algorithms,
was to increase the likelihood of finding a set of com-
mon motifs in our sequences (see discussion of the pro-
grams and strategy in [47-49]). Before using the
programs and to avoid biasing their analyses, we elimi-
nated all sequences which were repeated. We checked
multiple alternative parameters for each program, and
the conditions finally chosen were those which provided
the most significant statistical value. When similar
scores were obtained with different parameters, we
chose the ones that generated the largest number of
positive motifs. All sequences which were detected as
containing a particular motif in at least four of the five
programs were selected for further analysis. We discov-
ered that all of them could be grouped together in a sin-
gle motif, easily defined using MEME. We then used the
applications Prophecy and Profit from EMBOSS [50] to,
respectively, generate a frequency matrix from our
motifs and to map the motifs along the D. melanogaster
chromosomes (see raw data in Additional File 1). Aver-
age densities and their standard errors were calculated
as number of copies of the motif in both DNA chains
divided by number of base pairs for 2 Mb-long
Figure 1 Frequency matrix of nucleotides and relative entropy-
based logo of the detected motif.
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chromosome fragments. The program enoLOGOS [51]
was used to draw the DNA logo shown in Figure 1.
Once the motif enriched in the DCC binding sites based
on Gilfillan et al. [22] data was characterized, we
decided to map it not only against data obtained from
that paper, but also against a consensus dataset of DCC
binding regions obtained by combining data from Gilfil-
lan et al. [22] and Alekseyenko et al. [21]. This consen-
sus dataset was obtained as follows: for the three
datasets from Alekseyenko et al. [21], corresponding to
SL2 cells, clone 8 cells and embryos, we characterized
regions containing probes with signal values above or
equal to 2 in each of the three experiments and sepa-
rated by at the most 1 Kb (i. e., the same criteria used
for the Gilfillan et al. [22] dataset in the previous ana-
lyses). These regions were then compared to those
obtained previously from the Gilfillan et al. [22] dataset.
When the regions derived from Alekseyenko et al. [21]
and Gilfillan et al. [22] results were separated by less
than 1 Kb, they were merged in order to generate the
final consensus regions. Given that this way of obtaining
the consensus regions led in some cases to the appear-
ance of small regions detected in single experiments,
data were filtered, keeping only regions that were longer
than 1000 nucleotides.
We checked for the presence of motifs in the autoso-
mal regions shown to be bound by the DCC complex by
Gorchakov et al. [36] using similar methods. As above,
only the regions with signal values above 2 were consid-
ered positive in our analyses of the TrojanElephant
transposon. The TrojanHorse sequences were kindly
provided by the authors.
Evolutionary conservation analyses
To determine whether the motifs were evolutionary
conserved, the sequence corresponding to each motif
plus 100 nucleotides upstream and downstream of it
were selected as queries to perform BLASTN searches
against D. virilis genomic sequences (included in the
NCBI wgs database). For those sequences for which
non-ambiguous homologies were detected (minimal
E-value = 10-3, minimal length of homology = 40
nucleotides), we evaluated the percentage of nucleotide
identity both within and around the motif. All the
sequences for which we found homology in D. virilis
were reexamined in the D. melanogaster genome to
determine whether they corresponded to coding regions.
The codons that corresponded to the conserved motif
sequences included in coding regions were characterized
using TBLASTX analyses.
Coding region analyses
We downloaded the files containing the coding regions
of the D. melanogaster chromosomes (again, from the
4.3 genome release, obtained from Flybase [52]) and
established the frequency of each type of codon. We
also determined to which codons the motifs located in
coding regions of the X chromosome corresponded,
either within or outside the DCC binding regions.
Finally, we established the relative position of the motifs
along the genes by following methods similar to those
described in [22]. Briefly, we obtained from the supple-
mentary material of that paper a list of X chromosome
genes with intense DCC binding (average signal > 0.5).
From them, we selected those which were larger in size
than 2000 base pairs and which also contained at least
one motif. For the 421 genes with those features, we
mapped all motifs present as follows: the central nucleo-
tide of the motif was found on the X chromosome and
a value measuring the relative position along the gene
was assigned to that nucleotide (value = [position of the
nucleotide on the X chromosome - position of the first
(5’) nucleotide of the gene on the X chromosome]/total
length of the gene). We finally used a Kolmogorov-
Smirnov test to establish whether the distribution of
motifs was uniform throughout the sequences of the set
of genes.
Analyses of high affinity binding sites
As explained in detail in the Results section, we also
established the density of our motif in the high affinity
binding sites characterized by Alekseyenko et al. [30]
and Straub et al. [29]. In parallel, we used MEME to
reanalyze the data obtained in those two studies in
order to establish whether there was any sequence rela-
tionship among the motifs detected in the high affinity
sites and our motif.
Sliding-window analyses of motif locations
We determined the nucleotide located at the center of
all DCC binding regions (from Gilfillan et al. [22] data),
in all the HAS (from Straub et al. [29] data), and in
each region of the X where the DCC does not bind
(i. e. the regions that are left along the X chromosome
once we eliminate from it the DCC binding regions).
We also randomly selected 1000 nucleotides from each
large autosomal arm (for a total of 4000 randomly
selected points). The central nucleotides of DCC bind-
ing regions, non-binding regions, HAS and the ran-
domly taken nucleotides of the autosomes were taken
as starting points for sliding-window analyses of motif
densities. Those analyses were performed as follows:
two 500-nucleotide long windows were initiated at
those starting points and then displaced, respectively
upstream and downstream from them, one nucleotide
at a time. Then, for each window and position, its den-
sity of motifs (no. motifs/Mb) was determined. In this
way, we obtained a precise characterization of how the
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density of motifs varies with increasing distances from
the starting points.
Results
Primary definition of DCC binding regions, X-specific
regions and determination of maximal congruence
between both types of regions
Our first goal was to unambiguously define DCC bind-
ing regions and X-specific regions along the X chromo-
some and to establish the overlap among them. We
started by applying the parameters of signal intensity
and proximity between significant probes indicated in
the Methods section to the data obtained by Gilfillan
et al. [22]. We thus defined 559 DCC binding regions.
This first result shows that our criteria were quite strict:
Gilfillan et al. [22] described their data as containing
>700 regions of binding. We then defined X-specific
regions by checking different cutoff values of X-chromo-
some specificity, which establishes the enrichment in the
X chromosome, with respect to the autosomes, of X
chromosome sequences (Table 1). The final X/2L ratio
chosen was 6.8, i. e., words in a region had to be at least
6.8 times relatively more abundant on the X than on an
autosome to be selected. This value was chosen because
it was the one for whose percentage of X-specific
regions that overlapped with DCC binding regions was
maximal (Table 1; X-positive regions). Thus, we charac-
terized 22366 short X-specific regions, corresponding to
2.3% of the X chromosome. The average size of those
regions was 19.6 nucleotides. As indicated also in Table
1, 82% of the DCC binding regions included at least one
of the X-specific regions, the average being of 5.4 X-spe-
cific regions per DCC binding region.
Characterization of an X-enriched motif found in DCC
binding regions
The X-specific regions included in DCC binding regions
(2157, after eliminating duplicates) were analyzed with
five motif-recognition programs to determine whether
they had anything in common. Notably, each of these
five programs indeed detected that many regions had
common motifs, although the number of regions
detected was quite variable (GLAM2: 1057 regions;
MOTIFSAMPLER: 916 regions; MEME: 712 regions;
WEEDER: 490 regions; ALIGNACE: 370 regions). We
checked for congruence among these results, looking for
regions that were detected as significant in at least four
of the five programs. This led to the characterization of
329 different sequences. Given that some of them were
present more than once in our original dataset, they
corresponded to 356 different places along the X chro-
mosome. The expected number of sequences, if the
results generated by the programs were independent,
was just 102. This difference demonstrated that the five
programs often detected the same sequences. Finally, we
used MEME to analyze the 329 different sequences
obtained, establishing that all of them truly contained a
single 12-nucleotide long motif. According to MEME,
the probability of such a motif arising by chance so
many times in that sample was 10-523. In related ana-
lyses, we found that X-specific regions not included in
the DCC binding regions are just slightly enriched in
simple DNA sequences, mainly poly-G/C [53]. These
results demonstrate that there is a common motif in at
least 356 places of the X-chromosome that are both
highly X-specific (X/2L ratio ≥ 6.8) and where the DCC
binds. The motif obtained is shown in Figure 1. It has
an obvious repetitive signature: [G(CG)N/N(CG)C]4.
From now on, we will refer to this motif as [G(CG)N]4.
Chromosomal distribution of sequences related to the
motif
In order to determine all the positions in which
sequences related to the [G(CG)N]4motif were present,
we used the Prophecy and Profit programs of the
EMBOSS suite. We established the maximum score
(= sum of the frequencies of the most frequent nucleo-
tides) for the matrix obtained for our motif from the
329 sequences characterized (Figure 1), and then we
determined all the sequences with a score of at least
Table 1 Results used in the selection of the cutoff value for X-specificity. In bold, data for the chosen value
X/2L cutoff (%)a
X regionsb
X-positive regions (%)c
DCC positive regions (%)d
14 (0.45)
12.5 (0.52)
11 (0.62)
9.5 (0.81)
8 (1.28)
6.8 (2.33)
6.1 (3.55)
2267
2805
3719
5416
10202
22366
36798
229 (10.10)
279 (9.94)
380 (10.22)
551 (10.17)
1030 (10.10)
2475 (11.07)
3948 (10.07)
53 (9.48)
77 (13.77)
112 (20.03)
200 (35.78)
326 (58.31)
461 (82.47)
499 (89.27)
a: Cutoff value for the X/2L ratio and percentage of the X chromosome above that cutoff
b: number of X-specific regions with an X/2L ratio higher than the cutoff
c: number of X-specific regions included in DCC binding regions and percentage respect to the total number of X-specific regions
d: DCC regions including at least one X-specific region. Total number and percentage relative to the 559 DCC binding regions
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90% of that maximum. We then scanned the X chromo-
some for the positions of all the sequences with score
values above the 90% cutoff. This led to the characteri-
zation of 14967 sites. These sites had an average size of
14.4 nucleotides, slightly larger than the original 12
nucleotides-long motif. This was caused by the fact that
the motif is internally repetitive, so positive overlapping
sequences were often detected and merged.
We found that 3082 of the 14967 sites were included
in 449 of the 559 DCC binding regions defined from
Gilfillan et al. [22] data, with an average of 6.9 sites/
DCC region. It is significant that, although we detected
sites in just 80% of the DCC binding regions, the ones
that remained undetected were in general very small.
The total length of the regions lacking motifs was just
6% of the total assigned to DCC binding regions. We
then divided the X chromosome into the 559 DDC
binding regions and the rest, in order to test whether
the sites detected were found at a higher density in
those regions. For the rest of the X chromosome, once
the DCC binding regions were excluded, we determined
an average of 602 ± 24 sites/Mb, a value almost identi-
cal to the one that we found for the autosomes: 590 ±
29 sites/Mb (all large autosomal arms considered). How-
ever, the 449 positive regions had a density of 1582 ± 68
sites/Mb, that is, almost three times higher. Logically,
this leads to these sites being much closer in the DCC
binding regions than in the rest of the chromosomes
(Additional File 2). The median distance between conse-
cutive sites was just 215 bp and 87% of the consecutive
sites were separated by less than 1 Kb. These results
demonstrate that most DCC binding regions contain
multiple sites related to the [G(CG)N]4motif that we
detected in our original searches, that those sites are
relatively close to each other and that they are signifi-
cantly enriched in most DCC binding regions, with
respect to both the rest of the X chromosome and the
autosomes.
To obtain further support for these conclusions, we
repeated these analyses with a consensus dataset, gener-
ated combining data from Gilfillan et al. ([22]; 1 dataset)
and Alekseyenko et al. ([21]; 3 datasets). From the com-
bined data, we characterized 666 DCC binding regions.
These are quite more than in our analysis based on a
single dataset (666 vs. 559), which suggests that the four
datasets were somewhat heterogeneous. Using again the
90% of maximum value of the similarity matrix as a cut-
off, sequences related to our motif were found in 79%
(526/666) of these consensus DCC binding regions. As
previously seen, the DCC binding regions in which the
motif was not detected were small, corresponding all
together to just 4% of all the nucleotides defined as
bound by the DCC in the consensus dataset. The den-
sity of motifs was 1201 ± 39 sites/Mb in the positive
DCC binding regions in this consensus dataset. The
density in the rest of the X chromosome went down to
523 ± 25 sites/Mb in this case, thus being a bit lower
than the average 590 sites/Mb detected in the auto-
somes. These results confirmed the significant enrich-
ment of the motif in the DCC binding regions.
Figure 2 shows a typical example of how motifs are
distributed. The figure shows a 200 Kb region that con-
tains the white gene, half of which exhibits strong DCC
binding while the other half does not. The high concen-
tration of motifs around the DCC binding regions
upstream of white is evident, while the other half
unbound by the DCC, which includes the white gene
itself, shows a significantly lower number of motifs.
We also checked for the presence of our motifs in the
TrojanHorse and TrojanElephant transposons used by
Gorchakov et al. [36] to demonstrate the ability of some
autosomal sequences to acquire de novo DCC binding.
Significantly, we found that the region in TrojanHorse
to which the DCC binds when the transposon is
inserted on the X chromosome (corresponding to posi-
tions 4224822-4228454 in chromosome 2L; genes
CG3702 and Rpl40) has a high motif density (4 sites in
3633 nucleotides, or 1101 sites/Mb) while the rest of the
transposon has a low density (9 sites in 19531 nucleo-
tides; 461 sites/Mb). Similarly, the regions bound by the
DCC in the TrojanElephant transposon (signal > 2; cor-
responding to positions 6908636-6914771 and 6949036-
6955236 in chromosome 2L) have a density of 811 sites/
Mb (10 motifs in 12337 nucleotides) while the rest of
the transposon has a density of motifs of just 623 sites/
Mb. In summary, the density of sites in the regions
bound by the DCC when these transposons are localized
on the X chromosome is much higher than the average
density of sites in the autosomes (590 sites/Mb). This
may contribute to them behaving as typical X chromo-
some sequences when inserted on the X.
Evolutionary conservation of the sites located in DCC
regions
The DCC is acting not only in D. melanogaster, but also
in other drosophilids, including flies of genera other
than Drosophila [54]. Therefore, we decided to explore
whether the sites found were evolutionary conserved,
which would indicate that the same sequences might be
used in different species. Given that the sites are very
small, we decided to locate each site in D. melanogaster
and then add at both sides of the sites a total of 100
extra nucleotides. By doing so, we increased the likeli-
hood of finding the homologous site in a different spe-
cies. The chosen species to compare was D. virilis,
which is a distant relative of D. melanogaster, belonging
to a different subgenus and which genome has been
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fully sequenced [55]. The two lineages split about 63
millions of years ago [56].
Of the 3082 D. melanogaster sites tested, we were able
to characterize the homologous D. virilis sites in 894
cases. The total number of aligned nucleotides was
113225, of which 12214 corresponded to the sites and
the rest to the adjacent sequences added to perform the
analyses. Since we were interested in determining
whether the sites were evolutionary conserved, we
counted the number of differences in both the sites and
the adjacent sequences, which was used as a control of
local conservation in D. virilis. In total, there were
16365 nucleotide differences between D. melanogaster
and D. virilis, and 1448 of them affected the sites. This
means that the percentage of nucleotide identity
between the sequences of the two species was 88.1% for
the sites and just 85.2% for the adjacent sequences. We
used a cumulative hypergeometric distribution to estab-
lish the probability of the sites and adjacent sequences
having the same mutation rate. That probability was 5.0
10-19. We conclude that, in the cases in which it has
been possible to establish homology between D. melano-
gaster and D. virilis, the sites are significantly more con-
served than their immediately adjacent sequences.
When we checked for the positions of the 894 con-
served sites in the D. melanogaster genome, we found
that in 781 cases (87%), the motifs were part of the
coding regions. We examined those 781 motifs to deter-
mine to which codons they corresponded. The rationale
was to establish whether the [G(CG)N]4DNA signature
generated singular amino acidic signatures. The degen-
erate [G(CG)N]4pattern can be converted, depending
on the frame used, into six codon classes, each one of
them corresponding to eight different codons (Table 2).
One of these types of codons, which can be summarized
in the sequence [(CG)NG]n, was found much more
Figure 2 Location of the [G(CG)N]4motif along the region that contains the white gene (w, rectangle). The figure includes the
coordinates in the X chromosome, location of the genes, raw data of binding obtained from Gilfillan et al. [22] and Alekseyenko et al. [21]
experiments, the binding regions derived from Gilfillan et al. [22], the consensus binding regions and the precise positions of the motifs. Notice
the clear difference in motif densities between the left part of the figure, where the DCC binding regions are located, and the right part, in
which DCC binding regions have not been found.
Table 2 Frequency of appearance in the conserved
regions analyzed in D. melanogaster and D. virilis of the
six possible codon classes that can be obtained from the
repetitive [G(CG)N]4signature
Codon classFrequencyAmino acids encoded
[(CG)NG]n
[CN(CG)]n
[N(CG)C]n
[NG(CG)]n
[G(CG)N]n
[(CG)CN]n
495
123
62
39
36
26
Val, Ala, Glu, Gly, Leu, Pro, Gln, Arg
Leu x 2, Pro x 2, Arg x 2, His, Gln
Ser x 2, Cys, Pro, Arg, Thr, Ala, Gly
Arg x 3, Gly x 2, Cys, Trp, Ser
Ala x 4, Gly x 4
Pro x 4, Ala x 4
For each codon class, the [XXX]nnomenclature refers to the n consecutive
codons of the same class produced by the DNA repeat. Given the eight-fold
degeneracy of that pattern, the set of codons in each codon class may
encode for at most 8 amino acids. The amino acids that each codon class
encode are also indicated. Numbers after the x sign indicate how many
different codons encode for a same amino acid, when they are more than
one.
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often that the rest, while several others were very infre-
quent (Table 2). Notably, there was a clear correlation
between the potential different number of encoded
amino acids and the frequency in which the codons
were detected. Thus, the preferred (CG)NG triplet is the
only one among the six possible classes of codons that
encodes for eight different amino acids, while the two
less frequent triplets, G(CG)N and (CG)CN, are the
only ones that encode for just two amino acids (Table
2).
Coding regions analyses
The results detailed in the previous section suggest a
preference for (CG)NG codons to be included in the
motifs found in the coding regions bound by the DCC.
However, those results were constrained to the 894
cases for which we detected homology with D. virilis.
Therefore, we decided to establish whether that was a
general preference, for all the D. melanogaster sites. We
found that a total of 2720 of the 3082 sites detected in
our previous analyses (88%) were included in coding
regions. This is in agreement with the known enrich-
ment of the DCC binding regions in coding sequences
[21,22]. Then, we determined that those 2720 sites cor-
responded to 10701 codons (incomplete codons were
discarded). Just as it occurred with the conserved
sequences described above, the most frequent triplet
was again (CG)NG (6185 codons; 58%). When we per-
formed the same analyses for the motifs not included in
the DCC binding regions, we found that 5767 of the
11885 motifs (49%) were included in coding regions.
We established that 24016 codons were derived from
those 5767 motifs. Notably, the proportion of (CG)NG
triplets was quite smaller than in DCC regions, just at
51%. This difference is statistically highly significant
(p = 1.2 10-41; Chi-square test with 1 degree of free-
dom). Therefore, the DCC binding regions are enriched
in motifs that correspond to (CG)NG codons.
Interestingly, seven of the eight amino acids that the
(CG)NG sequences can generate are among the pre-
ferred ones in D. melanogaster and many other Droso-
phila species [57]. It is known that the D. melanogaster
X chromosome has an increased codon bias respect to
the autosomes [58]. Therefore, it is possible that selec-
tive pressure to keep DCC binding/spreading sites with
[(CG)NG]nsignatures contribute, along with other pro-
cesses, to that X-specific bias. On the other hand, it is
important to demonstrate that the opposite is not true
(i. e. that our results are not simply caused by the differ-
ence in codon bias between the X chromosome and the
autosomes). Given that the DCC binding regions and
coding regions are often coincidental, a very strong
codon bias, or indeed any force causing highly biased
frequencies of particular codons on the X respect to the
autosomes, could often lead to recovering X-specific
codons when using the oligonucleotide profile method
to detect X-specific sequences. However, we have found
that the frequencies of all codons are actually so similar
in the X chromosome and the autosomes that they can-
not explain the 6.8× level of enrichment for sequences
with k = 13 that we have used as cutoff in our searches.
When we analyzed the coding regions of X chromosome
and autosomes, we found that the codon GGC was the
one with the highest X/A relative ratio, which had a
value of 1.18. Therefore, even a sequence formed by six
consecutive GGC codons (remember that 19.6 nucleo-
tides is the average sequence size selected by our
method, see above) would be enriched just 1.186= 2.7
times due to its increased presence in the coding
regions of the X chromosome respect to the coding
regions of the autosomes. It can be deduced that, unless
those same sequences are (obviously by reasons totally
independent to codon bias or any other forces acting on
coding regions) also depleted from the non-coding
regions of the autosomes relative to the non-coding
regions of the X chromosome, they would never achieve
the 6.8× cutoff value required to be detected in our
searches. As a relevant example to ascertain this point,
we established the relative frequencies of [(CG)NG]4
sequences in X chromosome and in autosome genes.
These frequencies were 5.5 10-3(i. e. just 5.5 out of
1000 groups of four consecutive codons had a [(CG)
NG]4signature) and 3.7 10-3respectively, with an X/A
ratio of just 1.5. We conclude that neither codon bias
nor any other force acting solely on coding regions can
explain the selection of these sequences by the oligonu-
cleotide profile searches.
Given that it has been described that the DCC binding
regions are preferentially located at the 3’ ends of the
genes, we explored whether the motifs were similarly
distributed (see Methods). We found a depletion of
motifs at both extremes of the genes, spanning about
the first 5% and the last 5% of their sequences. However,
along the rest of the sequences of the genes, the distri-
bution of motifs was homogeneous, according to a Kol-
mogorov-Smirnov test for departures of the uniform
distribution (p = 0.09; n. s.). Thus, the motifs by them-
selves cannot explain the preference of the DCC to bind
the 3’ ends of the genes.
Analyses of DCC high-affinity sites
A relevant point was to determine whether the [G(CG)
N]4motif found was in some way involved in the DCC
high-affinity sites (HAS). Alekseyenko et al. [30] recently
characterized a motif, which they called “MSL recogni-
tion element” or MRE. This motif was deduced from
150 binding sites detected for the incomplete DCC com-
plex formed in mutant msl-3 flies. These 150 sites were
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considered HAS by those authors. As we already men-
tioned, this 21 bp motif is characterized by containing
(GA/TC)nrepeats and is totally unrelated to the one
that we found. However, using MEME, we detected
three other motifs enriched in the putative HAS charac-
terized by Alekseyenko et al. ([30]; kindly provided by
the authors). Most interestingly, one of the motifs,
found a total of 166 times in 79 of their 150 HAS, was
clearly related with the motif detected in the searches
described above. This motif detected by MEME was 21
base-pairs long and had a consensus sequence which
can be simplified to [G(CG)(AT)]7. This is obviously
very similar to the [G(CG)N]4signature detected in this
study. In fact, when we searched for our 12 bp-long
motif in the 150 HAS (again using a 90% cutoff for the
similarity matrix, as above), we found similar data: 71
HAS contained a total of 138 copies of the motif. Den-
sity in the positive HAS was 1004 sites/Mb, slightly
lower than that found for the whole set of DCC binding
regions, but still higher than that found in the rest of
the X chromosome or the autosomes.
In another analysis, Straub et al. [29] also searched for
HAS, characterized this time by a combination of
experiments in cell lines, using either RNA interference
of genes encoding DCC proteins (msl-3, mle, mof) or
decrease of crosslinking in the ChIP experiments. They
obtained a total of 132 putative HAS, from which they
characterized a 29 bp motif with (GA/TC)nrepeats,
clearly related to the one found by Alekseyenko et al.
[30]. Our own reanalysis of those 132 putative HAS
using MEME led to the characterization of a total of
five motifs, of which the most abundant was roughly
equivalent to, although slightly shorter than, the one
described by Straub et al. [29] (data not shown). None
of those five motifs was clearly related to the one we
characterized. However, when we searched for our
[G(CG)N]4motif in the 132 putative HAS characterized
by Straub et al. [29], we found that 56 of them actually
contain at least one, making a total of 109 motifs. This
corresponds to a density in the positive HAS of 1354
motifs/Mb, similar to that found for all the DCC bind-
ing sites together and again higher than that found for
the rest of the X chromosome and the autosomes (see
above). We can conclude from our analyses of Alek-
seyenko et al. [30] and Straub et al. [29] data that the
[G(CG)N]4motif that we have detected may be contri-
buting to some of the high affinity sites.
We also checked whether the [G(CG)N]4motif was
found in individually characterized HAS, which have
been determined with a higher precision than that pro-
vided by the ChIP-chip experiments. We analyzed the
HAS in roX1 (217 bp; ref. [59]), roX2 (110 bp; ref. [60]),
the 18D10 region (510 bp; ref. [61]), the 8F7 region
(DBF6; 25 bp), the 18D3 region (DBF9; 59 bp) and the
11B13 region (DBF12; 40 bp; these last three character-
ized by Dahlsveen et al. [24] and Gilfillan et al. [25]).
We found that only one of them, the one located in the
18D10 region, contained a copy of the motif (again
using the 90% similarity matrix cutoff). Actually, the
roX1 and roX2 loci, which may be acting as nucleation
Figure 3 Distribution of the motif along the regions that contain roX1 (top) and roX2 (bottom; the precise positions of the two genes
are highlighted). This figure is similar to Figure 2, except that it also includes the positions of the HAS characterized by Straub et al. [29]. The
roX1 and roX2 loci contain a HAS but lack motifs, even although there are many of them in adjacent regions.
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centers for DCC formation [62], lack motifs, although
they are surrounded by “low affinity” DCC binding
regions with a high density of them (Figure 3). We con-
clude from all these results that the [G(CG)N]4motif
may be relevant but is not essential to form the HAS
for the dosage compensation complex.
We then performed a sliding-window analyses of the
average density of motifs along the X chromosome,
both in regions not bound by the DCC, in the DCC-
binding regions and in the regions corresponding to
HAS. The nucleotides at the middle of each of those
regions were taken as starting points to determine the
average density in windows of 500 nucleotides. Those
windows were slided, one nucleotide at a time and in
both directions, to determine how density varied with
progressive distance from the center of the region.
Autosomes were used as negative controls. A total of
1000 random nucleotides per major autosomal arm
were sampled and, from them, the sliding process
repeated. Results are shown in Figure 4. Differences
between DCC binding regions and HAS are striking. In
the DCC binding regions, average density is maximum
at their centers and progressively declines to reach X-
specific background levels (i. e., the level found if we
start the analysis from a region of the X chromosome
not bound by the DCC) at about 2.5 - 3 Kb at each side
of the center of the region. This is reasonable given that
the average size of the DCC binding regions is about 3.8
Kb (Figure 4): once we abandon the DCC binding
regions, we expect the density to substantially diminish.
On the contrary, and surprisingly, the centers of the
HAS have a minimum number of motifs, which is
equivalent to that observed at the center of the regions
not bound by the DCC (Figure 4). Density then
increases to reach maximum levels at about 0.5 - 1 Kb
from the center, i. e., approximately at both ends of an
average-sized HAS. After we further move away from
the center of the HAS, density decreases again, to reach
again X-specific background levels at about 3 Kbs from
the middle point of the HAS. These results demonstrate
that the motifs are placed differently in HAS and DCC
binding regions. The increase at the ends of the HAS
and posterior decrease when we move away from the
end of the HAS can be understood considering the fact
that HAS are commonly included within larger “low
affinity” DCC binding regions, which have many motifs
(see cases in Figure 3). Therefore, a simple explanation
is that the frequency of the motifs increases when we
move from the center of the HAS towards the “low affi-
nity” DCC binding regions that surround the HAS. A
final significant detail is that both the progressive
increase in density when we get away from the center of
regions of the X chromosome not bound by the com-
plex and the fact that those non-bound regions have an
Figure 4 Average densities of the motifs in different regions. Densities are measured as no. motifs/Mb in a window of 500 nucleotides.
Averages were calculated for all DCC-binding regions (blue), HAS (red) and regions not bound by the complex on the X chromosome (green)
and for 4000 randomly sampled regions of the autosomes (1000 per major autosomal arm; in grey). The 500 nucleotides-long windows were
slided (one nucleotide at a time and in both directions) from the center of the regions (position indicated as “0” in the X axis), to determine
how densities vary when we move away from that center. The broad horizontal grey and black lines indicate the average length of DCC-binding
regions and HAS, respectively. All analyses were oriented respect to the positions of the telomeres and centromeres of the chromosomes. Thus,
values at the left of the “0” position are obtained when the windows are moved towards the telomere and those at the right, when they are
slided towards the centromere.
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average density of motifs which is higher than that
found in the autosomes (a result that apparently contra-
dicts the identical average densities mentioned above,
but can be easily observed in Figure 4) are due to the
interspersion of those regions with the motif-rich DCC
binding regions. Once we move along the X chromo-
some from the center of the non-bound regions, we
come upon DCC binding regions, leading to a subse-
quent increase of average density.
Discussion
We have characterized a repetitive sequence motif, [G
(CG)N]4, which is specifically enriched in regions bound
by the Drosophila DCC. Significantly, hexanucleotides
related to the motif that we have described had been
detected already as enriched in DCC binding regions
[22]. Our ability to detect this longer motif critically
depended on a new type of approach, which involved
not only taking into account the similarities among
DCC binding regions but also the local X-specificity of
the sequences within those regions. In this sense, our
application of the oligonucleotide profiling strategy,
which previously demonstrated its power to tackle more
general problems of chromosome differentiation [39,40],
has been fruitful. Further applications of this approach
to related problems can be easily envisaged.
The motif is especially enriched in the DCC binding
regions that do not have a high affinity for the complex
(i. e. those that are not part of the HAS determined so
far), while is less frequent in the HAS, in which, more-
over, the motifs mostly appear in peripheral positions
(see statistical results and Figure 4). This distribution
suggests a significant role in the generation of most
“low affinity” DCC binding regions, including those that
surround the HAS. Its significance within the HAS is
less obvious; it may simply contribute to them in some
cases. This is demonstrated by the facts that many HAS
lack motifs, while the motif tends to be at high densities
adjacent to the HAS (see figures 2, 3 and 4 and numeri-
cal results above). It is significant in this context that
the motifs found here may also contribute to explain
recent results showing acquisition of DCC binding sites
by some short, autosome-derived regions transposed to
the X chromosome [36]. The failure of acquiring DCC
binding by larger regions of autosomal origin [28] may
be simply understood considering that the larger the
region, the closer its density of motifs will be to the
autosomal average, which may be too low to support
binding. Thus, our hypothesis to explain Gorchakov et
al. data [36] is that only particular, short, motif-rich
regions of autosomal origin may acquire dosage com-
pensation when moved to the X chromosome. The
active transcription of genes located in those regions
seems also essential, given that a deletion in
TrojanHorse that abolishes DCC binding [36] does not
eliminate any [G(CG)N]4motif.
With these results in mind, we hypothesize that the
[G(CG)N]4sequences may contribute to the recognition
of the X chromosome by the DCC, to generate the
majority of DCC binding regions observed, and/or to
the spreading of the complex from the HAS to the rest
of the X chromosome. Our results are in agreement
with the combined model that we discussed in the
Introduction, according to which there are multiple
binding/spreading sites with different features and
strengths along the X chromosome. The available data
is compatible with low affinity sites being largely
explained by the presence of multiple, closely located [G
(CG)N]4sequences, while high affinity sites may be due
to a specific combination of sequence motifs among
which the (GA/TC)nmotif would be fundamental and
the [G(CG)N]4motif and probably several others (e. g.
those additional kinds of sequences detected in our
MEME searches as enriched at HAS) of secondary
importance. Our data thus indicate that the high affinity
sites indeed are qualitatively different from the rest in
terms of which sequences are involved in their forma-
tion, as already suggested by Straub et al. [29] and Alek-
seyenko et al. [30] data.
The fact that some small DCC binding regions (which
add up to 4 - 6% of all nucleotides bound by the DCC)
do not contain any obvious motif, can be explained in
different ways. First, it is evident that our analyses do
not exclude that other motifs, so far uncharacterized,
may be significant in DCC binding regions. Our
searches have been quite stringent and focused on
motifs of a certain length (in the range of 10 - 20
nucleotides, given the k and R parameters used), so
some regularities may have been missed. Alternatively, it
is possible that the criterion used to search for motif
sequences (90% of the maximum score of the frequency
matrix) is too strict. Finally, these exceptional regions
may be simply caused by experimental limitations (e. g.,
false positives for DCC binding).
Despite that it was often impossible to establish
whether particular [G(CG)N]4motifs within DCC bind-
ing regions were evolutionary conserved, we were able
to detect 894 sites in D. virilis. We found that 87%
(781/894) of them were included in coding regions. The
higher level of conservation of the [G(CG)N]4motif
with respect to the immediately adjacent sequences
detected in those 781 cases is significant. It may be
interpreted as [G(CG)N]4sequences being part of the
X-recognition/DCC spreading system in multiple Droso-
phila genus species, a result that is in agreement with
the known conservation of DCC binding in drosophilids
[50]. In Gallach et al. [37], we described the most fre-
quent trinucleotides in different Drosophila species.
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Interestingly, one of them was (CAG/CTG)n, which cor-
responds to one of the possible trinucleotides defined by
the [G(CG)N]4motif. This trinucleotide was enriched
on the X chromosomes of all Drosophila species tested,
including the neo-X arm of D. pseudoobscura [37].
These results, together with those found for the high
affinity sites, enriched for (GA/TC)nsequences, offer
support to the old idea that different types of simple
DNA along the Drosophila X chromosome may be key
to the process of dosage compensation (see discussions
in refs. [39,63-65]). It is interesting that Bachtrog [66]
recently characterized positive selection acting on three
HAS in the D. melanogaster lineage, a result that corre-
lates with positive selection of MSL proteins in that
same lineage [67,68]. These results, which contrast with
the evolutionary conservation that we have observed for
our motif in the D. melanogaster/D. virilis comparisons,
suggest that HAS may be, at least in particular lineages,
under peculiar selective regimes, different from the rest
of DCC binding regions, as suggested by Bachtrog [66].
When we established the imprint that the [G(CG)N]4
motif may leave on the protein sequences of Drosophila
genes, we found that the preferred frame was the one
that allowed for the maximum variation in the amino
acids encoded by the nucleotides of the motif. This
result may contribute to explain the apparent paradox
of why the DCC often binds to coding regions of the
genes [21,22]. The adjacent non-coding regions, evolu-
tionary less constrained, would seem better targets to
acquire binding sites for the DCC (see ref. [65] for a dis-
cussion of the process of acquisition of dosage compen-
sation). However, simple, degenerate, repetitive motifs
have a minimal impact on coding regions if they are
able to encode for many different amino acids. Then, it
may be often enough to choose particular codons to
generate the DNA motif without changing the protein
sequence. Only if the motif encodes for just a few
amino acids, its generation would necessarily cause a
repeat of those amino acids in the protein, which may
be more difficult to accommodate. In the case of the
motif that we discovered, the most versatile frame, and
the one that is found most often, is [(CG)NG]n, which
can be converted into eight different amino acids (Table
2). As we indicated above, the acquisition of these
sequences may contribute to codon bias, which is espe-
cially significant in the X chromosome [55].
Conclusions
The analysis of the Chip-ChIP data for DCC binding
with a novel strategy based on oligonucleotide profiling
allowed us to detect a set of DNA sequences that are at
the same time X-specific and included in the DCC bind-
ing regions. These sequences share a common short,
internally repetitive motif which may contribute to the
establishment of the wild-type localization of the dosage
compensation regulators along the X chromosome.
Further experimental confirmation for the role of the
motif detected in DCC binding and/or local spreading is
required. These results open fascinating new possibili-
ties. Among them, the clearest is that it is now possible
to devise experiments to test more precisely the factors
governing the binding or spreading of the DCC com-
plex. Also, the relationships among genetic changes and
epigenetic modifications leading to the wild-type pattern
of DCC binding may be explored in more detail. Finally,
we also may more deeply understand the similarities
and differences of the evolution of the dosage compen-
sation systems of Drosophila, Caenorhabditis, in which a
similar situation of simple, short motifs acting as X
chromosome recognition/spreading marks has been
described [69-71], and mammals, in which several types
of repetitive DNA sequences may influence X chromo-
some inactivation [72,73].
Additional file 1: Tables S1 - S3. Tables with the coordinates on X
chromosome for the DCC binding regions, the 2475 X positive regions
and the copies of the motif.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-2164-11-
169-S1.XLS]
Additional file 2: Cumulative distribution of the proximity among
consecutive sites. Distances are measured in hundreds of nucleotides.
Continuous black line: sites on the DCC binding regions. Continuous
grey line: X chromosome. Dotted black line: X chromosome, outside of
the DCC binding regions. Dotted grey line: autosomes. Microsoft Word
(.doc) file.
Click here for file
[http://www.biomedcentral.com/content/supplementary/1471-2164-11-
169-S2.DOC]
Acknowledgements
The authors would like to thank Esther Betrán and Peter Becker for their
comments on an early version of this paper and Jennifer Gage for
proofreading the manuscript. This work was supported by Ministerio de
Ciencia e Innovación, Spain [grant number BIO2008-05067].
Author details
1Department of Biology, University of Texas at Arlington, Arlington, Texas,
USA.2Departamento de Informática, Universidad de Valencia, Valencia, Spain.
3Instituto de Biomedicina de Valencia, Consejo Superior de Investigaciones
Científicas (IBV-CSIC), Valencia, Spain.
Authors’ contributions
MG contributed to the design and performed most of the analyses
described in the text. He also significantly contributed to the ideas
developed in the manuscript. VA generated the programs required to
implement the oligonucleotide profiling strategy. RA generated the
programs and obtained the results described in the “Coding region
analyses” sections. IM devised and supervised the research and wrote the
manuscript. All authors read and approved the final manuscript.
Received: 16 September 2009 Accepted: 12 March 2010
Published: 12 March 2010
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References
1.Mukherjee AS, Beermann W: Synthesis of ribonucleic acid by the X-
chromosomes of Drosophila melanogaster and the problem of dosage
compensation. Nature 1965, 207:785-786.
2. Hamada FN, Park PJ, Gordadze PR, Kuroda MI: Global regulation of X
chromosomal genes by the MSL complex in Drosophila melanogaster.
Genes Dev 2005, 19:2289-2294.
3. Straub T, Gilfillan GD, Maier VK, Becker PB: The Drosophila MSL complex
activates the transcription of target genes. Genes Dev 2005, 19:2284-2288.
4.Belote JM, Lucchesi JC: Control of X chromosome transcription by the
maleless gene in Drosophila. Nature 1980, 285:573-575.
5.Belote JM, Lucchesi JC: Male-specific lethal mutations of Drosophila
melanogaster. Genetics 1980, 96:165-186.
6.Uchida S, Uenoyama T, Oishi K: Studies on the sex-specific lethals of
Drosophila melanogaster. III. A third chromosome male-specific lethal
mutant. Jpn J Genet 1981, 56:523-527.
7. Lucchesi JC, Skripsky T, Tax FE: A new male-specific mutation in
Drosophila melanogaster. Genetics 1982, 100:s42.
8.Hilfiker A, Hilfiker-Kleiner D, Pannuti A, Lucchesi JC: mof, a putative acetyl
transferase gene related to the Tip60 and MOZ human genes and to the
SAS genes of yeast, is required for dosage compensation in Drosophila.
EMBO J 1997, 2054-2060.
9.Meller VH, Wu KH, Roman G, Kuroda MI, Davis RL: roX1 RNA paints the X
chromosome of male Drosophila and is regulated by the dosage
compensation system. Cell 1997, 88:445-457.
10.Amrein H, Axel R: Genes expressed in neurons of adult male Drosophila.
Cell 1997, 88:459-469.
11. Franke A, Baker BS: The rox1 and rox2 RNAs are essential components of
the compensasome, which mediates dosage compensation in
Drosophila. Mol Cell 1999, 4:117-122.
12.Turner BM, Birley AJ, Lavender J: Histone H4 isoforms acetylated at
specific lysine residues define individual chromosomes and chromatin
domains in Drosophila polytene nuclei. Cell 1992, 69:375-384.
13.Bone JR, Lavender J, Richman R, Palmer MI, Turner BM, Kuroda MI:
Acetylated histone H4 on the male X chromosome is associated with
dosage compensation in Drosophila. Genes Dev 1994, 8:96-104.
14.Kuroda MI, Kernan MJ, Kreber R, Ganetzky B, Baker BS: The maleless protein
associates with the X chromosome to regulate dosage compensation in
Drosophila. Cell 1991, 66:935-947.
15.Palmer MJ, Mergner VA, Richman R, Manning JE, Kuroda MI, Lucchesi JC:
The male-speeific lethal-one (msl- 1) gene of Drosophila melanogaster
encodes a novel protein that associates with the X chromosome in
males. Genetics 1993, 134:545-557.
16.Gorman M, Franke A, Baker BS: Molecular characterization of the male-
specific lethal-3 gene and investigations of the regulation of dosage
compensation in Drosophila. Development 1995, 121:463-475.
17.Kelley RL, Solovyeva I, Lyman LM, Richman R, Solovyev V, Kuroda MI:
Expression of msl-2 causes assembly of dosage compensation regulators
on the X chromosomes and female lethality in Drosophila. Cell 1995,
81:867-877.
18. Bashaw GJ, Baker BS: The msl-2 dosage compensation gene of Drosophila
encodes a putative DNA-binding protein whose expression is sex
specifically regulated by Sex-lethal. Development 1995, 121:3245-3258.
19.Zhou S, Yang Y, Scott MJ, Pannuti A, Fehr KC, Eisen A, Koonin EV, Fouts DL,
Wrightsman R, Manning JE, Lucchesi JC: Male-specific lethal 2, a dosage
compensation gene of Drosophila, undergoes sex-specific regulation and
encodes a protein with a RING finger and a metallothionein-like
cysteine cluster. EMBO J 1995, 14:2884-2895.
20.Gu W, Szauter P, Lucchesi JC: Targeting of MOF, a putative histone acetyl
transferase, to the X chromosome of Drosophila melanogaster. Dev Genet
1998, 22:56-64.
21.Alekseyenko AA, Larschan E, Lai WR, Park PJ, Kuroda MI: High-resolution
ChIP-chip analysis reveals that the Drosophila MSL complex selectively
identifies active genes on the male X chromosome. Genes Dev 2006,
20:848-857.
22. Gilfillan GD, Straub T, de Wit E, Greil F, Lamm R, van Steensel B, Becker PB:
Chromosome-wide gene-specific targeting of the Drosophila dosage
compensation complex. Genes Dev 2006, 20:858-870.
23.Kind J, Vaquerizas JM, Gebhardt P, Gentzel M, Luscombe NM, Bertone P,
Akhtar A: Genome-wide analysis reveals MOF as a key regulator of
dosage compensation and gene expression in Drosophila. Cell 2008,
133:813-828.
Dahlsveen IK, Gilfillan GD, Shelest VI, Lamm R, Becker PB: Targeting
determinants of dosage compensation in Drosophila. PLoS Genet 2006, 2:
e5.
Gilfillan GD, König C, Dahlsveen IK, Prakoura N, Straub T, Lamm R, Fauth T,
Becker PB: Cumulative contributions of weak DNA determinants to
targeting the Drosophila dosage compensation complex. Nucleic Acids
Res 2007, 35:3561-3572.
Kelley RL, Meller VH, Gordadze PR, Roman G, Davis RL, Kuroda MI:
Epigenetic spreading of the Drosophila dosage compensation complex
from roX RNA genes into flanking chromatin. Cell 1999, 98:513-522.
Demakova OV, Kotlikova IV, Gorgadze PR, Alekseyenko AA, Kuroda MI,
Zhimulev IF: The MSL complex levels are critical for its correct targeting
to the chromosomes of Drosophila melanogaster. Chromosoma 2003,
112:103-115.
Fagegaltier D, Baker BS: X chromosome sites autonomously recruit the
dosage compensation complex in Drosophila males. PLoS Biol 2004, 2:
e341.
Straub T, Grimaud C, Gilfillan GD, Mitterweger A, Becker PB: The
chromosomal high-affinity binding sites for the Drosophila dosage
compensation complex. PLoS Genet 2008, 4:e1000302.
Alekseyenko AA, Peng S, Larschan E, Gorchakov AA, Lee OK, Kharchenko P,
McGrath SD, Wang CI, Mardis ER, Park PJ, Kuroda MI: A sequence motif
within chromatin entry sites directs MSL establishment on the
Drosophila X chromosome. Cell 2008, 134:599-609.
Sural TH, Peng S, Li B, Workman JL, Park PJ, Kuroda MI: The MSL3
chromodomain directs a key targeting step for dosage compensation of
the Drosophila melanogaster X chromosome. Nat Struct Mol Biol 2008,
15:1318-1325.
Sun X, Birchler JA: Studies on the short range spreading of the male
specific lethal (MSL) complex on the X chromosome in Drosophila .
Cytogenet Genome Res 2009, 124:158-169.
Kind J, Akhtar A: Cotranscriptional recruitment of the dosage
compensation complex to X-linked target genes. Genes Dev 2007,
21:2030-2040.
Larschan E, Alekseyenko AA, Gortchakov AA, Peng S, Li B, Yang P,
Workman JL, Park PJ, Kuroda MI: MSL complex is attracted to genes
marked by H3K36 trimethylation using a sequence-independent
mechanism. Mol Cell 2007, 28:121-133.
Bell O, Conrad T, Kind J, Wirbelauer C, Akhtar A, Schübeler D: Transcription-
coupled methylation of histone H3 at lysine 36 regulates dosage
compensation by enhancing recruitment of the MSL complex in
Drosophila melanogaster. Mol Cell Biol 2008, 28:3401-3409.
Gorchakov AA, Alekseyenko AA, Kharchenko P, Park PJ, Kuroda MI: Long-
range spreading of dosage compensation in Drosophila captures
transcribed autosomal genes inserted on X. Genes Dev 2009,
23:2266-2271.
Straub T, Becker PB: Dosage compensation: the beginning and end of
generalization. Nat Rev Genet 2007, 8:47-57.
Straub T, Becker PB: DNA sequence and the organization of
chromosomal domains. Curr Opin Genet Dev 2008, 18:175-180.
Gallach M, Arnau V, Marín I: Global patterns of sequence evolution in
Drosophila. BMC Genomics 2007, 8:408.
Arnau V, Gallach M, Marín I: Fast comparison of DNA sequences by
oligonucleotide profiling. BMC Res Notes 2008, 1:5.
Stein LD, Mungall C, Shu S, Caudy M, Mangone M, Day A, Nickerson E,
Stajich JE, Harris TW, Arva A, Lewis S: The generic genome browser: a
building block for a model organism system database. Genome Res 2002,
12:1599-1610.
Bailey TL, Elkan C: Fitting a mixture model by expectation maximization
to discover motifs in biopolymers. Proceedings of the Second International
Conference on Intelligent Systems for Molecular Biology; Menlo Park, California
Edited by AAAI Press 1996, 28-36.
Hughes JD, Estep PW, Tavazole S, Church GM: Computational
identification of cis-regulatory elements associated with groups of
functionally related genes in Saccharomyces cerevisiae. J Mol Biol 2000,
296:1205-1214.
Pavesi G, Mauri G, Pesole G: An algorithm for finding signals of unknown
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
Gallach et al. BMC Genomics 2010, 11:169
http://www.biomedcentral.com/1471-2164/11/169
Page 13 of 14

Page 14

length in DNA sequences. Bioinformatics 2001, 17(Suppl 1):S207-S214.
Thijs G, Lescot M, Marchal K, Rombauts S, De Moor B, Rouze P, Moreau Y: A
higher-order background model improves the detection of promoter
regulatory elements by Gibbs sampling. Bioinformatics 2001, 17:1113-1122.
Frith MC, Saunders NF, Kobe B, Bailey TL: Discovering sequence motifs
with arbitrary insertions and deletions. PLoS Comput Biol 2008, 4:
e1000071.
Hu J, Li B, Kihara D: Limitations and potentials of current motif discovery
algorithms. Nucleic Acids Res 2005, 33:4899-4913.
Tompa M, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV,
Frith MC, Fu Y, Kent WJ, Makeev VJ, Mironov AA, Noble WS, Pavesi G,
Pesole G, Régnier M, Simonis N, Sinha S, Thijs G, van Helden J,
Vandenbogaert M, Weng Z, Workman C, Ye C, Zhu Z: Assessing
computational tools for the discovery of transcription factor binding
sites. Nat Biotechnol 2005, 23:137-144.
Das MK, Dai HK: A survey of DNA motif finding algorithms. BMC
Bioinformatics 2007, 8(Suppl 7):S21.
Rice P, Longden I, Bleasby A: EMBOSS: The European Molecular Biology
Open Software Suite. Trends Genet 2000, 16:276-277.
Workman CT, Yin Y, Corcoran DL, Ideker T, Stormo GD, Benos PV:
enoLOGOS: a versatile web tool for energy normalized sequence logos.
Nucleic Acids Res 2005, , 33 Web Server: W389-392.
Flybase: D melanogaster 4.3 genome release [ftp://ftp.flybase.net/genomes/
Drosophila_melanogaster/dmel_r4.3_20060303/fasta/].
Gallach M: Análisis de patrones globales de evolución genómica. PhD
Thesis Universidad de Valencia 2008.
Marín I, Franke A, Bashaw GJ, Baker BS: The dosage compensation system
of Drosophila is co-opted by newly evolved X chromosomes. Nature
1996, 383:160-163.
Drosophila 12 Genomes Consortium: Evolution of genes and genomes on
the Drosophila phylogeny. Nature 2007, 450:203-218.
Tamura K, Subramanian S, Kumar S: Temporal patterns of fruit fly
(Drosophila) evolution revealed by mutation clocks. Mol Biol Evol 2004,
21:36-44.
Vicario S, Moriyama EN, Powell JR: Codon usage in twelve species of
Drosophila. BMC Evol Biol 2007, 7:226.
Singh ND, Davis JC, Petrov DA: X-linked genes evolve higher codon bias
in Drosophila and Caenorhabditis. Genetics 2005, 171:145-155.
Kageyama Y, Mengus G, Gilfillan G, Kennedy HG, Stuckenholz C, Kelley RL,
Becker PB, Kuroda MI: Association and spreading of the Drosophila
dosage compensation complex from a discrete roX1 chromatin entry
site. EMBO J 2001, 20:2236-2245.
Park Y, Mengus G, Bai X, Kageyama Y, Meller VH, Becker PB, Kuroda MI:
Sequence-specific targeting of Drosophila roX genes by the MSL dosage
compensation complex. Mol Cell 2003, 11:977-986.
Oh H, Bone JR, Kuroda MI: Multiple classes of MSL binding sites target
dosage compensation to the X chromosome of Drosophila. Curr Biol
2004, 14:481-487.
Park Y, Kelley RL, Oh H, Kuroda MI, Meller VH: Extent of chromatin
spreading determined by roX RNA recruitment of MSL proteins. Science
2002, 298:1620-1623.
Lowenhaupt K, Rich A, Pardue ML: Nonrandom distribution of long
mono- and dinucleotide repeats in Drosophila chromosomes:
correlations with dosage compensation, heterochromatin, and
recombination. Mol Cell Biol 1989, 9:1173-1182.
Baker BS, Gorman M, Marín I: Dosage compensation in Drosophila. Annu
Rev Genet 491-521.
Marín I, Siegal ML, Baker BS: The evolution of dosage-compensation
mechanisms. Bioessays 2000, 22:1106-1114.
Bachtrog D: Positive selection at the binding sites of the male-specific
lethal complex involved in dosage compensation in Drosophila. Genetics
2008, 180:1123-1129.
Levine MT, Holloway AK, Arshad U, Begun DJ: Pervasive and largely
lineage-specific adaptive protein evolution in the dosage compensation
complex of Drosophila melanogaster. Genetics 2007, 177:1959-1962.
Rodriguez MA, Vermaak D, Bayes JJ, Malik HS: Species-specific positive
selection of the male-specific lethal complex that participates in dosage
compensation in Drosophila. Proc Natl Acad Sci USA 2007,
104:15412-15417.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.McDonel P, Jans J, Peterson BK, Meyer BJ: Clustered DNA motifs mark X
chromosomes for repression by a dosage compensation complex. Nature
2006, 444:614-618.
Ercan S, Giresi PG, Whittle CM, Zhang X, Green RD, Lieb JD: X chromosome
repression by localization of the C. elegans dosage compensation
machinery to sites of transcription initiation. Nat Genet 2007, 39:403-408.
Blauwkamp TA, Csankovszki G: Two classes of DCC binding elements
facilitate binding and spreading of the DCC along C. elegans X-
chromosomes. Mol Cell Biol 2009, 29:2023-2031.
Carrel L, Park C, Tyekucheva S, Dunn J, Chiaromente F, Makova KD:
Genomic enviroment predicts expression patterns on the human
inactive X chromosome. PloS Genet 2006, 2:e151.
Wang Z, Willard HF, Mukherjee S, Furey T: Evidence of influence of
genomic DNA sequence on human X chromosome inactivation. Plos
Comput Biol 2006, 2:e113.
70.
71.
72.
73.
doi:10.1186/1471-2164-11-169
Cite this article as: Gallach et al.: A sequence motif enriched in regions
bound by the Drosophila dosage compensation complex. BMC Genomics
2010 11:169.
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