Human gene organization driven by the coordination of replication and transcription.
ABSTRACT In this work, we investigated a large-scale organization of the human genes with respect to putative replication origins. We developed an appropriate multiscale method to analyze the nucleotide compositional skew along the genome and found that in more than one-quarter of the genome, the skew profile presents characteristic patterns consisting of successions of N-shaped structures, designated here N-domains, bordered by putative replication origins. Our analysis of recent experimental timing data confirmed that, in a number of cases, domain borders coincide with replication initiation zones active in the early S phase, whereas the central regions replicate in the late S phase. Around the putative origins, genes are abundant and broadly expressed, and their transcription is co-oriented with replication fork progression. These features weaken progressively with the distance from putative replication origins. At the center of domains, genes are rare and expressed in few tissues. We propose that this specific organization could result from the constraints of accommodating the replication and transcription initiation processes at chromatin level, and reducing head-on collisions between the two machineries. Our findings provide a new model of gene organization in the human genome, which integrates transcription, replication, and chromatin structure as coordinated determinants of genome architecture.
- SourceAvailable from: sciencedirect.com[Show abstract] [Hide abstract]
ABSTRACT: Transcription during Sphase needs to be spatially and temporally regulated to prevent collisions between the transcription and replication machineries. Cells have evolved a number of mechanisms to make compatible both processes under normal growth conditions. When conflict management fails, the head-on encounter between RNA and DNA polymerases results in genomic instability unless conflict resolution mechanisms are activated. Nevertheless, there are specific situations in which cells need to dramatically change their transcriptional landscape to adapt to environmental challenges. Signal transduction pathways, such as stress-activated protein kinases (SAPKs), serve to regulate gene expression in response to environmental insults. Prototypical members of SAPKs are the yeast Hog1 and mammalian p38. In response to stress, p38/Hog1 SAPKs control transcription and also regulate cell cycle progression. When yeast cells are stressed during S phase, Hog1 promotes gene induction and remarkably, also delays replication by directly affecting early origin firing and fork progression. Therefore, by delaying replication, Hog1 plays a key role in preventing conflicts between RNA and DNA polymerases. In this review, we focus on the genomic determinants and mechanisms that make compatible transcription with replication during S phase to prevent genomic instability, especially in response to environmental changes.Journal of Molecular Biology 09/2013; · 3.91 Impact Factor
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ABSTRACT: DNA damage leads to heritable changes in the genome via DNA replication. However, as the DNA helix is the site of numerous other transactions, notably transcription, DNA damage can have diverse repercussions on cellular physiology. In particular, DNA lesions have distinct effects on the passage of transcribing RNA polymerases, from easy bypass to almost complete block of transcription elongation. The fate of the RNA polymerase positioned at a lesion is largely determined by whether the lesion is structurally subtle and can be accommodated and eventually bypassed, or bulky, structurally distorting and requiring remodeling/complete dissociation of the transcription elongation complex, excision, and repair. Here we review cellular responses to DNA damage that involve RNA polymerases with a focus on bacterial transcription-coupled nucleotide excision repair and lesion bypass via transcriptional mutagenesis. Emphasis is placed on the explosion of new structural information on RNA polymerases and relevant DNA repair factors and the mechanistic models derived from it.Cellular and Molecular Life Sciences CMLS 06/2013; · 5.62 Impact Factor
- 08/2011; , ISBN: 978-953-307-593-8
Human gene organization driven by the
coordination of replication and transcription
Maxime Huvet,1Samuel Nicolay,2,5Marie Touchon,1,3,4Benjamin Audit,2
Yves d’Aubenton-Carafa,1Alain Arneodo,2and Claude Thermes1,6
1Centre de Génétique Moléculaire (CNRS), 91198 Gif-sur-Yvette, France;2Laboratoire Joliot Curie
et Laboratoire de Physique, Ecole Normale Supérieure de Lyon, CNRS, 69364 Lyon, France;
3Génétique des Génomes Bactériens, CNRS URA2171, Institut Pasteur, 75015 Paris, France;
4Atelier de Bioinformatique, Université Pierre et Marie Curie-Paris 6, 75005 Paris, France
In this work, we investigated a large-scale organization of the human genes with respect to putative replication
origins. We developed an appropriate multiscale method to analyze the nucleotide compositional skew along the
genome and found that in more than one-quarter of the genome, the skew profile presents characteristic patterns
consisting of successions of N-shaped structures, designated here N-domains, bordered by putative replication
origins. Our analysis of recent experimental timing data confirmed that, in a number of cases, domain borders
coincide with replication initiation zones active in the early S phase, whereas the central regions replicate in the late
S phase. Around the putative origins, genes are abundant and broadly expressed, and their transcription is
co-oriented with replication fork progression. These features weaken progressively with the distance from putative
replication origins. At the center of domains, genes are rare and expressed in few tissues. We propose that this
specific organization could result from the constraints of accommodating the replication and transcription initiation
processes at chromatin level, and reducing head-on collisions between the two machineries. Our findings provide a
new model of gene organization in the human genome, which integrates transcription, replication, and chromatin
structure as coordinated determinants of genome architecture.
[Supplemental material is available online at www.genome.org.]
It has long been known that genes are nonrandomly distributed
in eukaryote genomes (gene-dense regions alternating with gene
deserts) (Mouchiroud et al. 1991; Zoubak et al. 1996). Over the
past few years, complete genome sequences have confirmed this
striking nonrandomness in several species (Lander et al. 2001;
Hurst et al. 2004). In the human genome, statistical studies have
shown that highly expressed genes have a tendency to form clus-
ters (Caron et al. 2001; Versteeg et al. 2003). However, it has also
been reported that these clusters, in fact, result from the cluster-
ing of genes coexpressed in a large number of tissues (housekeep-
ing genes); although individual expression rates may vary from
tissue to tissue, the overall expression pattern remains similar
(Lercher et al. 2002). Several hypotheses have been advanced to
explain the formation and/or maintenance of this organization.
On the one hand, short-range regulatory mechanisms can be
responsible for small clusters of coexpressed genes. A gene might
be turned on solely because of its proximity to signals regulating
neighboring genes (Cajiao et al. 2004). On the other hand, long-
range mechanisms could maintain large-size clusters of coex-
pressed genes, and it has often been argued that the chromatin
structure could play such a role. When chromatin is in open
conformation during gene transcription, this conformation can
extend to neighboring genes. The presence in a region of a high
proportion of genes active in most tissues would keep chromatin
in an open structure in most cell types, thus leading to the ob-
served coexpressed gene clusters (Spellman and Rubin 2002; Gil-
bert et al. 2004; Hurst et al. 2004; Sproul et al. 2005). Compara-
tive analysis of clusters of coexpressed genes in human and
mouse indicate that they are found together in both species more
often than expected by chance, suggesting that clustering could
result from natural selection (Singer et al. 2005). This process
could contribute to a high degree of organization of human chro-
mosomes. However, these observations were challenged by a re-
cent study showing that most clusters of coexpressed genes seem
to contain only two to three genes, the number of clusters only
slightly exceeding the number expected by chance, which limits
their impact on global genome organization (Sémon and Duret
2006). Moreover, these clusters seem to be held together by
short-range effects resulting from promoters sharing common
regulatory elements or transcriptional read-through.
Here, we address the question of gene organization with
respect to replication. Previous studies have shown that the hu-
man genome displays nucleotide compositional strand asymme-
tries that probably result from asymmetric mutation and repair
processes associated with replication and transcription (Green et
al. 2003; Touchon et al. 2003, 2004, 2005; Brodie of Brodie et al.
2005). Genome-wide analyses of these skews allowed us to pre-
dict a large number of putative human replication origins (Brodie
of Brodie et al. 2005; Touchon et al. 2005). These analyses also
suggested that genes in the immediate vicinity of these putative
origins displayed a characteristic organization, which prompted
us to extend this analysis to a larger scale. We devised a new
methodology to identify large genome domains bordered by pu-
tative replication origins and found that, within these domains,
genes are highly ordered according to their breadth of expres-
5Present address: Département de Mathématique, Université de
Liège, 12 Grande Traverse, 4000 Liège, Belgium.
E-mail email@example.com; fax 33-1-69-82-38-77.
Article published online before print. Article and publication date are at http://
17:1278–1285 ©2007 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/07; www.genome.org
sion, orientation, and position. The data allowed us to propose a
model suggesting that replication and transcription are essential
and coordinated determinants of gene organization, leading to a
new vision of the human genome architecture.
In order to predict putative replication origins, in previous stud-
ies we explored the large-scale behavior of nucleotide strand
compositional asymmetries defined as the skew S = (G ? C)/
(G + C) + (T ? A)/(T + A) (i.e., the relative excess of G over C and
T over A) (Brodie of Brodie et al. 2005; Touchon et al. 2005).
Among the well-known, experimentally determined human rep-
lication origins (very few due to experimental difficulties), most
(six of nine) are associated with a specific property of the skew S:
as it crosses a replication origin, the sign of S changes abruptly,
producing a sharp upward transition of the S profile. This prop-
erty allowed us to identify ∼1000 putative replication origins in
the human genome. Remarkably, successive transitions are con-
nected to each other by DNA segments in which the S values
decrease in the 5? to 3? direction, thereby displaying a character-
istic serrated pattern reminiscent of factory roofs (Fig. 1A). We
propose as a working model that this N-like shape results from
the superimposition of two patterns. One decreases steadily in
the 5? to 3? direction and would be attributable to replication
initiating at two fixed adjacent origins (associated with two up-
ward transitions) and terminating during the successive germ-
line cell divisions at various positions randomly dispersed be-
tween these origins (Fig. 1B,C). The other pattern would result
from transcription-associated strand asymmetries that generate
step-like blocks corresponding to (+) and (?) genes (Touchon et
al. 2003, 2004) (Fig. 1D). When the two profiles are superim-
posed, this leads to the factory-roof pattern (Fig. 1E). We define
as an “N-domain” any DNA segment for which the S profile dis-
plays the characteristic factory-roof pattern. This model implies
that no other fixed replication origin active in germ-line cells can
be located within the N-domains (since any additional origin
would disrupt the N-shape of the domains). We set out to detect
these domains in the human genome and to study gene organi-
zation within these domains.
along a DNA fragment containing the experimentally determined replication origin associated with the MYC gene (Vassilev and Johnson 1990) (red
arrow). S is computed in 1-kbp adjacent windows of masked sequences; (red) + genes (coding strand identical to the Watson strand); (blue) ? genes
(opposite direction); (black) intergenic regions (the color of each point is defined by the majority rule). In abscissa, the position on the sequence; in
ordinate, the skew, S, in percent. (Red vertical lines) Putative replication origins associated with upward transitions of the S profile. (B–E) Working model
of the factory-roof pattern of the S profile. We propose that this pattern results from the superimposition, in germ-line cells, of strand asymmetries
associated with replication and transcription. (B) Model of the replication-associated skew profiles corresponding to two fixed putative adjacent
replication origins, Ori1 and Ori2, and to a replication termination site (Ter) occurring with equal probability between Ori1 and Ori2 (adapted from
Touchon et al. 2005). Upward or downward jumps of the S profile correspond to the origin and termination positions, respectively. (Left) Three
elementary skew profiles, Si, Sj, and Sk, are associated with three successive replication cycles and display three different Ter positions. (Middle)
Superimposition of the Si, Sj, and Skprofiles. (Right) Superimposition of a large number of elementary skew profiles, ultimately leading to a pattern
decreasing linearly in the 5? to 3? direction; note that reverse complementation of the sequence leaves the factory roof structure intact. (C) Final
replication-associated skew profile. (D) Transcription-associated skew profile showing positive step-like blocks at + gene positions and negative step-like
blocks at ? gene positions. (E) Superimposition of the replication- and transcription-associated skew profiles producing the final factory-roof pattern that
defines the N-domains.
Factory-roof pattern of the skew profile. (A) Skew (S) profile around an experimentally identified replication origin. The skew is computed
Human gene organization by replication
Detecting the N-domains
To extract the N-domains from the noisy S profile of the genome,
we developed an adapted wavelet-based multiscale methodology
to identify segments of variable length and position displaying a
factory-roof pattern (Methods; Supplemental Figs. S1, S2). Ac-
cording to the model, the selection involves (1) searching for
segments that decrease between two large upward jumps, and (2)
retaining those containing both intergenic regions with a lin-
early decreasing S profile (possibly induced by replication) and
genes associated with step-like blocks (possibly induced by tran-
scription) superimposed over this linearly decreasing profile. This
amounts to disentangling the components of the skew attributed
to replication and to transcription (Methods; Supplemental Fig.
S3). When applied to the human genome, the method detected
678 N-domains bordered by 1060 putative replication origins.
These domains are evenly distributed in most chromosomes,
spanning 28.3% of the genome with a mean length L = 1.2 ? 0.6
Mbp (Fig. 2A; Methods; Supplemental Fig. S4).
During the selection process, a number of candidate struc-
tures were examined that were not finally retained as N-domains
since they display some departure from symmetry of the skew
with respect to the center of the domain. However, these struc-
tures, which span approximately another 30% of the genome,
can be considered as N-domain-like structures, and do display a
type of gene organization reminiscent of that observed in the
bona-fide N-domains (described below). In most of the remain-
ing genome regions, two types of S profile were observed. The
first type, observed in regions with high gene density, small gene
size, and high GC content (Lander et al. 2001) displayed a high
density of large upward and downward jumps (they span ∼20%
of the genome). These complex S profiles hampered the detec-
tion of the N-domains. For example, both small domain density
and small chromosome coverage were observed in chromosome
19, which contains a high proportion of gene-rich and GC-rich
regions (Supplemental Fig. S5c,d). The second type, observed in
gene-poor regions with low GC content did not display large
upward jumps, but rather flat patterns, suggesting that replica-
tion origins are not fixed. These regions span ∼15% of the ge-
nome and correspond to gene deserts (Lander et al. 2001;
Ovcharenko et al. 2005).
Analysis of the S profile of the N-domains
The mean S profile of the selected N-domains decreases steadily
between opposed values to form a jagged pattern with rather
symmetrical left (5?) and right (3?) halves (the mean S values at
the 5? and 3? extremities are 6.8 ? 0.2% and ?7.1 ? 0.2%, re-
spectively) (Fig. 2B). Between these extreme values, the mean S
profile decreases fairly linearly (Fig. 2C) and accordingly, the
slope of the domains varies approximately as ?1/L (hyperbolic
curve in Fig. 2E, orange dots). On average, genes and intergenic
regions both display linear S profiles (Fig. 2D) that parallel the
profiles of the corresponding domains (Fig. 2E). The fact that the
S values for gene sequences were larger than those for intergenic
sequences (Fig. 2D) reflects the contribution of transcription.
These results strongly support our hypothesis that the skew pro-
file corresponds to the superimposition of replication- and tran-
scription-associated profiles (Fig. 1C–E).
To what extent could the specific S profile of the N-domains
be expected to result from chance? We first examined the human
S profile, looking for structures presenting an inverted factory-
roof pattern, i.e., two downward jumps separated by a steadily
increasing skew. We adapted our method to detect such struc-
tures (the method is the same as that described above apart from
the analyzing wavelet; Supplemental Fig. S1b). When this
method was applied to human autosomes, it detected no more
than 27 inverted structures (vs. 678 N-domains) spanning only
0.6% of the genome. N-domains therefore very significantly out-
(A) Examples of N-domains detected in the chromosome 13. S values are
computed in 1-kbp windows (without repeats); (red) + genes; (blue) ?
genes; (black) intergenic regions; the N-domain borders are indicated by
red vertical lines. In abscissa, the window position is in megabase pairs; in
ordinate, the skew, S, in percent. (B) Mean S profile of the N-domains.
The mean S values are computed along the N-domains of length L ? 1.2
Mbp. In abscissa, the region used for analysis extends from the extremity
to the center of each domain. In ordinate, the mean skew, S, in
percent ? SEM. (C) Mean S profile of the half-domains for L < 0.75 Mbp
(red), 0.75 < L < 1.2 Mbp (blue), 1.2 < L < 2 Mbp (purple), and L > 2
Mbp (green). The sequences of the 3? halves of the domains are reverse-
complemented and analyzed together with the 5? halves. (D) Mean skew
profile of + genes located in 5? half-domains analyzed together with ?
genes (reverse-complemented) located in 3? halves (red) and intergenic
regions (black) (both larger than 400 kbp, and situated in domains with
L > 1 Mbp). In abscissa, the distance ? to the 5? end of genes or intergenic
regions. (E) Mean slope of the domains versus their length L; domains are
ranked by L values and grouped by bins of 20 domains; in ordinate, the
mean (?SEM) of the slopes in percent/megabase pair (orange); the or-
ange hyperbolic curve is obtained by a linear regression fit of ?1/slope
versus L (Supplemental Fig. S5f). In red, the genes with a length >400 kbp
are ranked by length of their domain, and grouped by constant bins; the
mean slope is computed for each bin. The same is true for the intergenic
regions (>400 kbp) (black). In abscissa, the mean length of the corre-
Properties of the N-domains detected in the human genome.
Huvet et al.
number inverted structures (P < 10?15). Secondly, we looked for
N-domains in sequences obtained after shuffling the order of
genes and intergenic regions (Methods), and found that they
were significantly less frequent than in the native sequences
(P < 10?15). This observation also provides the first indication
that the existence of N-domains does indeed reflect some specific
Replication timing profile of the N-domains
Using a high-resolution replication timing map of human chro-
mosome 6 (Woodfine et al. 2005), we determined the timing
profile along the corresponding N-domains identified by our
method. On average, this profile displays maxima at positions
corresponding to the domain extremities, and decreases regularly
on both sides, revealing that (1) a significant number of domain
extremities correspond to early replicating sequences, (2) they
are replicated earlier than their surroundings, and (3) the central
region of large N-domains replicate late in the S phase (Fig. 3).
These results provide experimental evidence that at the degree of
resolution of the timing map, a number of N-domain extremities
correspond to bona-fide replication initiation zones that are ac-
tive rather early in the S phase.
Gene organization in the N-domains
Gene shuffling experiments revealed an underlying gene organi-
zation in the N-domains (see above). In order to decipher this
organization, we analyzed the gene patterns. Most putative ori-
gins (domain borders) are intergenic (77%) and located near a
gene promoter more often than would be expected by chance
(Supplemental Fig. S6a,b). The N-domains contain approxi-
mately equal numbers of genes oriented in each direction (1511
+ genes and 1507 ? genes). Gene distributions in the 5? halves of
domains contain more + genes than ? genes, regardless of the
total number of genes located in the half-domains (Supplemental
Fig. S6c). Symmetrically, the 3? halves contain more ? genes
than + genes (Supplemental Fig. S6d). A total of 32.7% of half-
domains contain one gene, and 50.9% contain more than one
gene. For convenience, + genes in the 5? halves and ? genes in
the 3? halves are defined as R+ genes (Fig. 4A): their transcription
is, in most cases, oriented in the same direction as the putative
replication fork progression (genes transcribed in the opposite
direction are defined as R? genes). The 678 N-domains contain
significantly more R+ genes (2041) than R? genes (977)
(?2= 375, P < 10?15, Supplemental Table S2a). Within 50 kbp of
putative replication origins, the mean density of R+ genes is 8.2
times greater than that of R? genes. This asymmetry weakens
progressively with the distance from the putative origins, up to
∼250 kbp (Fig. 4b). A similar asymmetric pattern is observed
when the domains containing duplicated genes are eliminated
from the analysis, whereas control domains obtained after ran-
domization of domain positions (Methods) present similar R+
and R? gene density distributions (Supplemental Fig. S7a–a?).
The mean length of the R+ genes near the putative origins is
significantly greater (∼160 kbp) than that of the R? genes (∼50
kbp); however, both tend toward similar values (∼70 kbp) at the
center of the domain (Fig. 4C). A similar pattern is observed after
eliminating duplicated genes, whereas, in contrast, the control
domains display fairly constant gene length (Supplemental Fig.
S7b–b?). Within 50 kbp of the putative origins, the ratio between
the numbers of base pairs transcribed in the R+ and R? direc-
tions is 23.7; this ratio falls to ∼1 at the domain centers (Fig. 4D).
A similar pattern is observed after eliminating duplicated genes;
lication timing values (?SEM) determined around the extremities of the
domains located in chromosome 6; in abscissa, the distance to the indi-
cated 5? (left) or 3? (right) closest domain extremity; in ordinate, the
mean timing ratio value; data are retrieved from Woodfine et al. (2005).
(B) Example of replication timing profile along a complete N-domain.
Horizontal bars indicate the DNA probes (∼94 kb) used in the microarray
experiments (Woodfine et al. 2005).
Replication timing profile of the N-domains. (A) Average rep-
indicate the R+ orientation i.e., the same orientation as the most frequent
direction of putative replication fork progression; R? orientation (op-
posed direction); (red) + genes; (blue) ? genes. (B) Gene density. The
density is defined as the number of 5? ends (for + genes) or of 3? ends (for
? genes) in 50-kbp adjacent windows, divided by the number of corre-
sponding domains. In abscissa, the distance, d, in megabase pairs, to the
closest domain extremity. (C) Mean gene length. Genes are ranked by
their distance, d, from the closest domain extremity, grouped by sets of
150 genes, and the mean length (kilobase pairs) is computed for each set.
(D) Relative number of base pairs transcribed in the + direction (red), ?
direction (blue), and nontranscribed (black) determined in 10-kbp adja-
cent sequence windows.
Analysis of the genes located in the N-domains. (A) Arrows
Human gene organization by replication
this ratio is constant in the control domains (Supplemental Fig.
S7c–c?). This strong transcriptional polarity could be mainly at-
tributable to the preferential R+ orientation of the first gene (clos-
est to the extremity). However, polarity is still observed for half-
domains harboring various gene numbers even after the first
gene has been eliminated (Supplemental Fig. S8).
Gene expression in the N-domains
We analyzed the breadth of expression, Nt(number of tissues in
which a gene is expressed), of genes located within the N-
domains. We found that it significantly decreases from the ex-
tremities to the center, regardless of whether it is measured by
EST, SAGE, or microarray data (?2= 29, P = 10?8for EST data).
The distribution is symmetrical in the 5? and 3? half-domains
(Fig. 5A,B). Significantly decreasing mean Ntvalues are also ob-
served after eliminating duplicated genes, whereas they remain
constant within the control domains obtained after randomizing
the domain positions (Methods; Supplemental Fig. S7d-f?). The
distribution of Ntvalues (determined using ESTs) displays a bi-
modal pattern for the genes located in the domains (Fig. 5C),
with one mode (peak at Nt< 5) corresponding to the genes ex-
pressed in only a few tissues, and a second mode (a wide bump
centered at Nt∼ 15) corresponding to widely expressed genes. It is
noteworthy that this distribution is similar to that found for the
complete set of human genes (Supplemental Fig. S9d). Genes
located near the putative replication origins tend to be widely
expressed (Fig. 5D), whereas those located far from them are
mostly tissue specific (Fig. 5E). We checked that the decrease in
both Ntvalues and gene length L, from the N-domain border to
its center (Fig. 4C), did not reflect a correlation between these
factors: no correlation was observed between gene length and
expression breadth measured using EST, SAGE, or microarray
data (Supplemental Fig. S9a–c). In addition, no significant corre-
lation was observed between the transcription rate of a gene and
its position within an N-domain, whether or not duplicated genes
are eliminated from the analysis (data not shown).
This study shows that some features of human genome organi-
zation can be unraveled by examining the properties of the
nucleotide compositional skew. The S profile exhibits a highly
significant number of occurrences of so-called N-domains, spe-
cific structures consisting of two sharp upward transitions con-
nected by a downward-sloping segment. These large structures
are recognizable along all chromosomes. They are unambigu-
ously detected by our methodology in more than one-quarter of
the genome. Could these structures be generated solely by tran-
scription? Transcription generates strand asymmetries along
gene sequences, leading to step-like blocks in the S profile (Green
et al. 2003; Touchon et al. 2003, 2004). Premature termination of
RNA polymerase elongation could occur during transcription,
leading to S profiles that decrease along the gene sequence. How-
ever, it would be unlikely to produce linear downward profiles
(termination at random positions would generate exponentially
decreasing S profiles). Moreover, this cannot account for the shift
from positive to negative S values observed along gene profiles
(Supplemental Fig. S4c–f), since transcription always generates
positive S values on the coding strand (and negative ones on the
noncoding strand) (Green et al. 2003; Touchon et al. 2003, 2004).
Recent studies have revealed the existence of complex networks
of unannotated transcripts (Cheng et al. 2005; Kapranov et al.
2005). Superimposition of sense and antisense transcription
could also generate decreasing S profiles, but it is unlikely that
these transcripts would display the specific organization required
to produce linear profiles that are, moreover, parallel in genes
and intergenic regions. In addition, most of these unannotated
transcripts are weakly expressed (Cheng et al. 2005), so that their
transcription would not generate significant compositional skew.
These data are compliant with our hypothesis that the factory-
roof pattern is produced by the superimposition of a jagged pro-
file, resulting from replication, over a crenellated profile resulting
from transcription (Fig. 1B–E).
The replication timing profile of the N-domains shows that,
on average, the extremities replicate earlier than the neighboring
regions, which is consistent with these regions being true repli-
cation origins, active early in the S phase. This profile was estab-
lished using replication timing data obtained from lymphoblas-
toid cells (Woodfine et al. 2005), suggesting that a number of
putative replication origins detected by our method (i.e., active
in germ-line cells) are also active in these cells in the early S
phase. We therefore propose that the putative replication origins
detected by our approach are, at least in part, early, well-
positioned replication origins active in most cell types. This
proposition is supported by earlier studies of replication timing
in various cell types that suggested some conservation of timing
between tissues (White et al. 2004). It is also consistent with
domains. (A) Mean expression breadth calculated using EST data (red). In
abscissa, the distance, d, in megabase pairs, to the closest domain ex-
tremity. (B) Same as in A with SAGE data (red) and microarray data
(black). (C) Histogram of the expression breadth (determined with EST
data) of the genes located in the domains. (D) Histogram of the expres-
sion breadth of the genes with an extremity (5? for R+ genes, 3? for R?
genes) located at distance d from the putative replication origins where
d < 5% of the length of the half-domain. (E) Same as in D, but with
70% < d < 100%.
Expression breadth, Nt, of the genes located in the N-
Huvet et al.
previous analyses of the S profile, showing that most well-
known, experimentally determined replication origins coincide
with sharp upward transitions of the S profile (Brodie of Brodie et
al. 2005; Touchon et al. 2005), indicating that these origins,
which were all identified in somatic cells, are also likely to be
active in germ-line cells.
According to our model, replication units would be better
described by N-domains, as defined in this study, than by the
usual replicons. Indeed, the fixed terminators of the replicons
would not be suitable for describing the putative variable termi-
nation sites within the N-domains. The length of the N-domains
matches the large, ∼1 Mbp-long replicons (Yurov and Liapunova
1977; Berezney et al. 2000) rather than the usually 50–300 kbp-
long replicons (Edenberg and Huberman 1975), and is consistent
with the large replication units observed in meiotic chromo-
somes (Callan 1972). In somatic cells, additional origins may be
activated within the N-domains, thus leading to the commonly
observed shorter replication units.
We then asked whether these N-domains correspond to a
specific gene organization pattern. Most putative replication ori-
gins located at domain extremities are intergenic and located
close to promoters of widely expressed genes (housekeeping
genes) oriented toward the domain center. Gene density, breadth
of expression, and transcription polarity all tend to decrease pro-
gressively from the extremities of the domain toward its center.
In the central region, genes are few in number, tissue specific,
and have no preferential orientation (Fig. 6). We propose that
coordination between replication and transcription is the key to
this complex architecture. The putative replication origins would
mostly be active early in the S phase in most tissues. Their activ-
ity could result from particular genomic context involving tran-
scription-factor binding sites and/or from the transcription of
their neighboring housekeeping genes. This activity could also be
associated with an open chromatin structure, permissive to early
replication and gene expression in most tissues (Gilbert et al.
2004; Hurst et al. 2004; Chakalova et al. 2005; Sproul et al. 2005).
This open conformation could extend along the first gene, pos-
sibly promoting the expression of further genes. This effect
would progressively weaken with the distance from the putative
replication origin, leading to the observed decrease in expression
breadth. This model is consistent with a number of data showing
that in metazoans, ORC and RNA polymerase II colocalize at
transcriptional promoter regions (MacAlpine et al. 2004), and
that replication origins are determined by epigenetic informa-
tion such as transcription-factor binding sites and/or transcrip-
tion (Lin et al. 2003; Danis et al. 2004; Ghosh et al. 2004; De-
Pamphilis 2005). It is also consistent with studies in Drosophila
and humans that report correlation between early replication
timing and increased probability of expression (Schubeler et al.
2002; MacAlpine et al. 2004; White et al. 2004; Jeon et al. 2005;
Woodfine et al. 2005). The data we report here provide the first
demonstration of quantitative relationships in the human ge-
nome between gene expression, orientation, and distance from
putative replication origins.
Near the putative origins bordering the N-domains, tran-
scription is preferentially oriented in the same direction as rep-
lication fork progression. We propose that this co-orientation
would reduce head-on collisions between the replication and
transcription machineries, which could induce deleterious re-
combination events either directly or via stalling of the replica-
tion fork (Deshpande and Newlon 1996; Takeuchi et al. 2003). In
bacteria, co-orientation of transcription and replication has been
observed for essential genes, and has been associated with a re-
duction in head-on collisions between DNA and RNA polymer-
ases (Rocha and Danchin 2003). Recent results support the hy-
pothesis that co-orientation bias of replication and transcription
in Bacillus subtilis results from deleterious effects on replication
caused by head-on transcription (Wang et al. 2007). It is note-
worthy that in human N-domains such co-orientation usually
occurs in widely expressed genes located near putative replica-
tion origins. Near domain centers, head-
on collisions may occur in 50% of repli-
cation cycles, regardless of the transcrip-
tion orientation, since there is no
preferential orientation of the replica-
tion fork progression in these regions.
However, in most cell types, there
should be few head-on collisions, due to
the low density and expression breadth
of the corresponding genes. Selective
pressure to reduce head-on collisions
may thus have contributed to the simul-
taneous and coordinated organization of
gene orientation and expression breadth
along the N-domains (Fig. 6).
The data presented here strongly
suggest the existence in the human ge-
nome of regions bordered by putative
early replication origins in which gene
position, orientation, and expression
breadth present a high level of organiza-
tion, possibly mediated by the chroma-
tin structure. This allows us to propose
a model of gene order that relates tran-
scription and replication as coordi-
nated determinants of genome organiza-
putative replication origins (ORI) delineate a replication N-domain. (Open chromatin) Arrows illustrate
an open chromatin state at replication origin position; (replication timing) the triangles figure the
replication timing values along the N-domain. Replication fork orientation: the triangles indicate the
proportion of replication forks progressing from each extremity to the other extremity along the
domain (during the successive cell cycles, replication terminates at random sites within the domain).
Breadth of expression is maximum near the replication origins and decreases toward the domain
center (gray triangles). Transcription orientation: it is preferentially co-oriented with the replication fork
progression; the colored triangles indicate the proportion of base pairs along the domain transcribed
in the + direction (red) and – direction (blue). Gene organization: red (resp. blue) arrows indicate +
(resp. ?) genes in the domains.
Model of gene organization coordinated by replication and transcription. Two successive
Human gene organization by replication
Sequence and expression data
Sequence and annotation data were retrieved from the Genome
Browser of the University of California Santa Cruz (UCSC, hg17).
To obtain gene sequences, we used the RefSeq annotation (con-
taining only protein-coding transcripts). When two genes pre-
senting the same orientation overlap, the largest gene was re-
tained. For the detection process of N-domains, sequences
masked with REPEATMASKER were retrieved from the UCSC
browser to avoid the biases intrinsic to repeated elements. In all
other analyses, sequences were not masked. The skew, S, was
computed in nonoverlapping, 1-kbp windows. EST, SAGE, and
microarray data were provided by M. Sémon and L. Duret (Sémon
et al. 2005). Among the 3018 genes located in the N-domains,
EST (Expressed Sequence Tags) data were available for 2514 genes
in 50 normal tissues, SAGE (Serial Analysis of Gene Expression)
data were available for 2668 genes in 22 normal tissues, and
microarray data were available for 1276 genes in 22 normal tis-
Detection of N-domains using the wavelet transform
Using the wavelet transform (WT) as multi-scale shape detector,
we search at every sequence position for segments of variable
length presenting a factory-roof skew pattern (space-scale analy-
sis) (Supplemental Section S1). In the first step, we used as the
analyzing wavelet the function, ?,constituted by a linearly de-
creasing segment between two upward jumps (Supplemental Fig.
S1), and computed the WT of the strand compositional asymme-
try S measured in 1-kbp windows (Supplemental Fig. S2). The
space-scale locations of significant maximum values in this two-
dimensional decomposition (red areas in Supplemental Fig. S2b)
indicate the middle position (spatial location, abscissa in Supple-
mental Fig. S2b) of candidate N-domains, the size of which is
shown by the scale location (ordinate in Supplemental Fig. S2b).
In order to avoid false positives, we then checked that there was
indeed a well-defined upward jump at each domain extremity
(Supplemental Fig. S2b). Because the mean value of the analyzing
wavelet was zero, the WT decomposition was insensitive to (glo-
bal) asymmetry offset. Hence, in order to enforce strong compat-
ibility with the working model of replication (Fig. 1B–E), we re-
tained from the set of candidate domains obtained at the previ-
ous step, only those where the two upward jumps corresponded
to a transition from a negative S value < ?3% to a positive S
value > +3%. In the second step, we disentangled two compo-
nents of the skew profile possibly associated with replication and
transcription. Ignoring transcription bias, the asymmetry profile
SRin one N-domain can be expressed as follows:
SR?t? = −2? × ?t −1⁄2?,
where position t within the domain has been rescaled between 0
and 1, and ? > 0 is the replication bias. If we now take into ac-
count the contribution of transcription STto the bias in a gene-
containing domain, the asymmetry profiles can be written as:
S?t? = SR?t? + ST?t? = −2? × ?t −1⁄2? +?
where ?gis the characteristic function for the gthgene (1 when
there are t points within the gene, and 0 elsewhere), and cgis its
transcriptional bias calculated on the Watson strand (likely to be
positive for + genes and negative for ? genes). For each domain
identified in the previous step, we used a least-square fitting pro-
cedure to estimate the replication bias, ?, and each value of the
gene transcription bias, cg. The resulting ?2value was used to
select the domains where the S noisy profile is well described by
Equation 2. As illustrated in Supplemental Figure S3 and Supple-
mental Table S1 for a fragment of human chromosome 6 that
contains three adjacent N-domains (Supplemental Fig. S3a), this
method provides a very efficient way of disentangling the step-
like component of strand asymmetry associated with transcrip-
tion (Supplemental Fig. S3b) from the jagged component associ-
ated with replication (Supplemental Fig. S3c).
Applying this procedure to the 22 human autosomes, we
detected 678 N-domains and predicted 1060 putative origins of
replication (in 296 cases, the right origin of a domain is also the
left origin of the following domain). Examples of such N-
domains are illustrated in Figure 2A and Supplemental Fig. S4.
The domain length ranges between ∼300 kbp and ∼2.8 Mbp, with
an average domain density of 0.22 ? 0.07 domain/Mbp (Supple-
mental Fig. S5a). The distribution of the domain GC content
(39.8 ? 4.1%) is narrower than that of the whole genome
(41.0 ? 5.1%) indicating some degree of under-representation of
regions presenting high GC contents (Supplemental Fig. S5b).
The mean values of several characteristics decrease as the GC
content increases: the density of N-domains, the proportion of
the chromosome length covered by the domains, and the do-
main length (Supplemental Fig. S5c–e).
Randomization of gene order
In order to compare the N-domains detected in human chromo-
somes to those detected in sequences obtained after randomiza-
tion of gene order, we randomly permuted genes and intergenic
regions without any change in orientation (genes and intergenic
regions alternate in the shuffled chromosomes). The process was
performed 100 times using chromosome 3 (this chromosome has
domain properties representative of those of the whole genome,
Supplemental Fig. S5c,d). The process detected, on average, 12.8
control domains per shuffled chromosome, compared with 56
putative replication domains detected in native chromosome 3.
Control domains have a mean length of 1.0 ? 0.5 Mbp, a density
of 0.065 ? 0.02 domain/Mbp (to be compared with 0.22 ? 0.07
N-domain/Mbp in native sequences), and correspond to only
6.9% of the shuffled sequences.
Randomization of N-domain positions
In this control test, we studied the gene characteristics in DNA
segments chosen at random along the chromosome sequences.
These segments are considered as control domains. In each chro-
mosome, the length and number of these control domains are
equal to those of the previously detected N-domains in the cor-
responding chromosome. This operation was repeated 10 times
on the 22 autosomes (leading to 6780 control domains).
Detection of duplicated genes
Genes displaying a high level of sequence identity were identi-
fied using BLASTP. Two genes were considered duplicates if they
presented E-values of <0.2 (Lercher et al. 2002) and a number of
identical amino acids >30% of the shortest protein length (Li et
al. 2001). This led to the identification of 322 genes displaying a
duplicated gene in the same domain, among the 3018 genes con-
tained in all the domains; 94 domains contained at least two
To assess correlations, Pearson’s correlation coefficients were
computed. To evaluate the statistical significance of the decreas-
ing Ntpattern observed along N-domains, we used the following
Huvet et al.
procedure. A linear fit of the Ntprofile was performed in each
half-domain containing more than one gene. The numbers of fits
with negative and positive slopes were compared with the corre-
sponding numbers obtained with the control domains (random-
ization of N-domain positions, see previous section).
The positions of the N-domains and of the inverted N-
domains are available as Supplemental material.
We thank M. Sémon and L. Duret for providing the expression
data for human genes, S. Camier, L. Duquenne, and M. Ghosh for
their careful reading of the manuscript, and O. Hyrien and B.
Michel for helpful discussions. This work was supported by the
Centre National de la Recherche Scientifique (CNRS), the Agence
Nationale de la Recherche (NT05-3_41825), the ACI IMPBIO
2004, the French Ministère de l’Education et de la Recherche, and
the PAI Tournesol. B.A. acknowledges support from the European
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Received March 22, 2007; accepted in revised form June 10, 2007.
Human gene organization by replication