Properties of overlapping genes are conserved
across microbial genomes
Zackary I. Johnson1,3and Sallie W. Chisholm1,2
1Department of Civil and Environmental Engineering,2Department of Biology, Massachusetts Institute of Technology,
Cambridge, Massachusetts 02139, USA
There are numerous examples from the genomes of viruses, mitochondria, and chromosomes that adjacent genes can
overlap, sharing at least one nucleotide. Overlaps have been hypothesized to be involved in genome size
minimization and as a regulatory mechanism of gene expression. Here we show that overlapping genes are a
consistent feature (approximately one-third of all genes) across all microbial genomes sequenced to date, have
homologs in more microbes than do non-overlapping genes, and are therefore likely more conserved. In addition,
the size, phase (reading frame offset), and distribution, among other characteristics, of overlapping genes are most
consistent with the hypothesis that overlaps function in the regulation of gene expression. The upstream sequences
and conservation of overlapping orthologs of two model organisms from the genus Prochlorococcus that have
significantly different GC-content, and therefore different nucleotide sequences for orthologs, are also consistent
with small overlapping sequence regions and programmed shifts in reading frame as a common mechanism in the
regulation of microbial gene expression.
[Supplemental material is available online at www.genome.org.]
Genomes are often compartmentalized into coding regions
(genes) and noncoding spacer regions. Although functionally re-
lated genes can be closely located, such as in an operon, the
fundamental unit of a gene is generally defined as having a
unique position within a chromosome. However, early sequenc-
ing efforts demonstrated that individual genes can overlap or
share one or more nucleotides with adjacent genes (Barrell et al.
1976; Sanger et al. 1977). Originally discovered in viruses, mi-
tochondria, and other extrachromosomal nuclear elements,
these overlapping genes, which have been shown to be evolu-
tionarily stable, were originally thought to be the result of
evolutionary pressure to conserve sequence length (Miyata
and Yasunaga 1978; Krakauer 2000; Scherbakov and Garber
2000). More recently, overlaps have been identified in chromo-
somal DNA of microbes and higher organisms (Spencer et al.
1986; Williams and Fried 1986; Wellington et al. 1992; Fukuda
et al. 1999). Although there is some speculation that they may
be rare in nonviral genomes (Krakauer and Plotkin 2002),
overlaps have been demonstrated to be potentially important in
transcriptional and translational regulators of gene expres-
sion and to influence the evolution of genes (Keese and Gibbs
1992; Krakauer 2002). Here we seek to understand the prevalence
and properties of overlapping genes across all sequenced micro-
bial genomes, which because of their small size may be influ-
enced by physical size constraints (National Research Council
1999). The characteristics of the overlaps offer insight into the
functional role of overlaps in microbes and possibly other organ-
Results and Discussion
During the genome annotation process, microbial genomes are
assigned to coding and noncoding regions by using gene search-
ing models such as Critica, Glimmer, or Generation or by using
manual assignment often based on similarity indices such as
BLAST (Altschul et al. 1997; Salzberg et al. 1998; Badger and Ol-
sen 1999; http://compbio.ornl.gov/generation). From these de-
fined coding regions, we identified overlapping genes as adjacent
genes, located on either DNA strand, that share one or more
nucleotides in their coding sequence (CDS). For all publicly avail-
able microbial genomes and annotations (ftp://ftp.ncbi.nih.gov/
genomes/Bacteria), we find a strong (r2= 0.96) relationship be-
tween the total number of genes and the number of overlapping
genes (Fig. 1), which is similar to that found by others for smaller
multiorganism data sets (Fukuda et al. 2003) and also consistent
with overlap frequencies for single organisms (Fukuda et al. 1999;
Scherbakov and Garber 2000; Iwabe and Miyata 2001). As would
be expected, there is a similarly robust relationship between the
number of overlapping genes and genome size (base pairs) as well
(data not shown) because there is a strong relationship between
the number of base pairs and number of genes for microbes
(Fukuda et al. 2003). The relationship between overlap and gene
number is consistent across Eubacteria and Archaebacteria do-
mains as well as for plasmids and chromosomal DNA, suggesting
that overlapping genes are a consistent feature across microbial
genomes and their extrachromosomal elements for different lin-
eages, occupying diverse environments.
The slope of the linear relationship between the number of
genes and overlapping gene pairs (overlaps) is 0.16, which indi-
cates that approximately a third of all genes in the genomes are
overlapping because two genes are part of each overlap. It is
possible that some of these overlaps could result from misiden-
tification of coding sequences in the annotation process. If this
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2268 Genome Research
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were the case, we would expect a higher percentage of overlaps in
genes labeled “hypothetical.” To investigate this, we subanalyzed
these hypothetical genes, which canonically connote coding as-
signments with less statistical confidence. Hypothetical genes ac-
count for 53% of all annotated genes and are somewhat less
likely to overlap (P = 0.26) than are the remaining genes. Other
properties of the overlaps, such as size, phasing, and direction,
are similar between hypothetical and nonhypothetical groups.
This evidence, as well as other COG analyses, suggests that pu-
tative overlapping genes are not the result of misannotation
(Fukuda et al. 2003).
We explored whether the relative prevalence of overlapping
genes is related to whole genome features. We found that the
frequency of overlapping genes is not related to genome com-
pactness, as determined from both the average distance between
genes (r2= 0.02, model 2 least-squares linear regression) and
the genome coding percentage (r2= 0.05, model 2) (Supplemen-
tal Fig. 1). The frequency of overlapping genes is also not related
to the percent GC content of the genome (r2= 0.05, model 2),
and the overlapping sequences are not statistically different
in GC content from non-overlapping sequence within a given
genome (P > 0.2). However, based on phylogenetic profiles,
genes that overlap have homologs in more organisms (13% in-
crease, P < 0.001) than do non-overlapping genes. Thus, overlaps
do not appear to be directly related to GC content or reducing
genome size, and it appears that overlapping genes are
more likely to be conserved. This tendency toward conserva-
tion may be the result of shared information (shared base pairs)
resulting in an increased probability of inheritance because
each mutation can potentially negatively affect two genes,
or the overlap feature itself may have adaptive fitness advan-
Previous work has shown that overlaps for a given organism
can have common characteristics such as strand distribution
(Fukuda et al. 1999), phasing (Scherbakov and Garber 2000),
codon usage (Fukuda et al. 1999; Kozlov 2000), or size (Merino
et al. 1994; Iwabe and Miyata 2001), among others. We inves-
tigated these and related properties over all genomes to de-
termine if they are globally conserved. Overlapping genes are
distributed irregularly within a genome such that the majority
(84%) of overlapping genes occur on the same strand (tandem
overlaps, →→) with the remaining (16%) overlaps occurring
on opposite DNA strands (antiparallel overlaps, →← or ←→)
(Table 1.) This global pattern across microbial genomes is con-
sistent with previous findings for individual organisms and
smaller multiple organism data sets showing that antiparallel
overlapping genes can be relatively rare (Fukuda et al. 1999,
2003). Tandem and antiparallel overlaps also have markedly dif-
ferent phase (reading frame offset) distributions (Supplemental
Fig. 2). Antiparallel overlaps are basically evenly distributed
among the three reading frames, whereas tandem overlaps are
most common in the +1 (2 + 3n shared bases) and +2 (1 + 3n
shared bases) reading frames. In-phase (same reading frame) tan-
dem overlaps, which would require an evolutionarily unstable
stop codon read-through (Keese and Gibbs 1992; Krakauer 2000),
are exceedingly rare.
The unequal distribution among the different directions and
reading frame offsets of overlaps across all microbes suggests that
there are selective pressures maintaining this pattern. Krakauer
(2000) has used an in silico analysis that assigns a probable abun-
dance based on the level of selective independence derived from
the plasticity in nucleotide sequence while maintaining a given
amino acid sequence. These predictions, which are based on shared
information content (IC) alone, suggest the following distribution:
antiparallel ?2 reading frame shift (1 + 3n shared bases) > tandem
+1 (2 + 3n shared bases) and +2 (1 + 3n shared bases) shifts > in-
phase antiparallel > antiparallel ?1 shift (2 + 3n shared bases)
(Krakauer 2000). However, we find that there are significantly
more +1 and +2 shift tandem overlaps than for the antiparallel
case, suggesting that additional mechanisms must be acting
(Table 1). Furthermore, there are similar numbers of antiparallel
overlaps in all reading frames, also suggesting that shared IC is
probably not the sole mechanism producing the observed distri-
In addition to phasing, the size distribution of overlaps is
skewed with most overlaps occurring in smaller size classes. More
than 70% of overlaps are <15 bp, and >85% are <30 bp (Fig. 2).
However, this distribution is not smooth as the direction and
reading frame shift of the overlap affect this distribution dramati-
cally. Notably, there are a few special cases that have a dispro-
portionately large number of members. For example, the major-
ity of the +2/?2 shift (1 + 3n shared bases) overlaps are either
single (binary) or four-base overlaps (Fig. 2). The majority of
these small +2/?2 shift observations occur for tandem overlaps,
but this pattern is also generally true for the less frequent anti-
parallel genes. Likely because of IC constraints (number of shared
bases), longer sizes of +2/?2 phase overlaps are significantly less
overlaps identified in all microbial genomes.
Frequency of reading frame offset for the 64,989
Phase offset (reading frame shift)
genome for all genomes in the National Center for Biotechnology Infor-
mation bacteria database (as of May 3, 2003). Plasmids (circles) and
chromosomes (squares) are identified by Eubacteria (black) or Archae-
bacteria (gray) domains. Properties are correlated at r2= 0.96.
Number of overlaps versus the total number of genes in the
Overlapping genes in microbial genomes
common and become monotonically rarer as the length of over-
lap increases. For binary and four-base overlaps, there is a rela-
tively small IC constraint, associated with the overlapping se-
quence. For example, for tandem binary overlaps the leading
stop codon for upstream sequence must either be TAA (TA[A]TG)
or TGA (TG[A]TG). This only prohibits the upstream sequence
from using TAG as stop codon and therefore represents a rela-
tively small IC constraint. For four-base overlaps, tandem over-
laps ([ATGA]) allow the second to last amino acid in the upstream
sequence to be one of 12 amino acids (GALKQESPVIRT) and the
second amino acid in the downstream sequence to be one of
seven different amino acids (MNKITSR) (Kozlov 2000). Both of
the groups, which contain hydrophobic, hydrophilic, and other
amino acids, impose a small IC constraint on the final amino
acid makeup of the two proteins. Similarly, four-base antiparallel
overlapping genes, which are restricted to end-on overlaps (→←),
have the sequence ([T/CTAA/G]) with 14 amino acids possible.
This arrangement also permits a significant degree of flexibility
in the second to last amino acid in the sequence with no effect on
the secondary sequence (and vice versa). As before, this imposes
a relatively small IC constraint and likely accounts for their
large numbers. Aside from the unique one and four-base over-
laps in the +2/?2 shift group, the number of observations de-
creases as the length of the overlap increases, likely due to in-
creasing IC constraints (Fig. 2). In short, tandem and antiparallel
binary and four-base overlaps (phase +2/?1 overlaps) make up
52% of all overlaps most likely because they have relatively small
IC constraints and permit flexibility in the final amino acid com-
Similar to overlaps with +2/?2 shifts in reading frame,
+1/?1 shifted overlaps (2 + 3n shared bases) are generally most
prevalent at smaller overlap sizes but also have some special
cases (Fig. 2). There are only a few observations of tandem
+1 shifted overlaps at 2 or 5 bp because in that orientation and
reading frame shift start and stop codon sequence requirements
prohibit an evolutionarily stable arrangement. At eight bases
and greater, however, there are a significant number of overlaps.
The frequency of this tandem +1 shifted overlap decreases
sharply with overlap size due to increases in shared IC. Antipar-
allel ?1 shifted overlaps have a similar pattern, again with the
5-bp overlap prohibited. In terms of size distribution, the anti-
parallel ?1 shifted overlaps are relatively constant until they
start to decrease monotonically at 17 bases. But overall, as with
the other overlaps with shifts in reading frame, +1/?1 shifted
overlaps are generally small and are less frequent at longer
Regardless of precise shift in reading frame, the majority of
overlapping genes overlap by only a few base pairs, many of
which are the result of unique scenarios that permit a great deal
of flexibility in the final amino acid composition of both pro-
teins. The majority of the remaining overlaps are also relatively
short, with >80% of the total observations overlapping by <30
bp. The observation that the distribution of overlaps is dramati-
cally skewed toward smaller sizes suggests that a reduction in
genome size is not a primary mechanism producing and main-
taining overlaps. Alternatively, these short overlapping se-
quences may be involved in expression regulatory mechanisms
(Normark et al. 1983; Krakauer 2000, 2002; Scherbakov and Gar-
ber 2000). Short tandem overlapping sequences can use transla-
tional coupling via site-specific programmed shifts in reading
frame (PSRF) to express both of the overlapping genes in consis-
tent stoichiometries or to allow inhibitory actions (Oppenheim
and Yanofsky 1980; Das and Yanofsky 1989; Gesteland and At-
kins 1996). Short antiparallel overlaps may also be involved in
expression regulation. Compared with tandem overlaps, the rela-
tive abundance of antiparallel overlaps decreases less quickly as
the length of the overlap increases for the first 20 bases, suggest-
ing that some mechanism is maintaining longer antiparallel over-
laps (Fig. 2). These relatively short antiparallel overlaps, which are
each complementary to the other overlapping gene, may be in-
volved in expression regulatory mechanisms involving RNA anti-
sense effects such as microRNAs and short interfering RNAs that
use small fragments of complementary sequence to regulate
expression (Bartel and Bartel 2003; Carrington and Ambros
We investigated the general properties of overlapping genes
further by using two closely related (as determined from 16S/23S/
ITS sequences) microbial genomes from the marine cyanobacte-
rium Prochlorococcus spp. (MIT9313 and MED4) that have signifi-
cantly different %GC content (50.7 and 30.8, respectively) but
have 1352 orthologs out of their total 2275 and 1716 respective
gene complements as predicted by BLASTP with an e-value
threshold set at 1e ? 10 (Rocap et al. 2003). Out of the 1352
orthologs, which also are significantly different in %GC content
(53.5 and 32.2, respectively), there are 422 and 330 orthologs
which are in-frame (i.e., multiples of three), are indicated with filled
circles and out-of-phase overlaps have open circles, both with a solid line.
The cumulative distribution is plotted as a dashed line. Individual tandem
and antiparallel graphs (data not shown) have nearly identical patterns.
(B) Distribution of tandem overlaps relative to respective phase maxima
above six bases. Tandem in-phase observations were excluded because of
few observations. (C) Distribution of antiparallel overlaps relative to re-
spective phase maxima above six bases.
(A) Size frequency distribution of overlapping genes. Sizes,
Johnson and Chisholm
2270 Genome Research
that are part of an overlapping gene pair in MIT9313 and MED4,
respectively. This is generally consistent with the ∼30% of to-
tal genes overlapping across all sequenced microbial genomes.
Among orthologs that are part of an overlap pair, 292 genes from
MIT9313 and 274 from MED4 genes (69% and 83%, re-
spectively), have both members of the overlap pair as or-
thologs. Thus, the majority of overlapping gene pairs have
dual-ortholog overlaps. This suggests that overlapping gene pairs
are conserved among organisms for specific genes and func-
tion, despite significant differences in the actual base pair
composition of the sequences from the differences in GC
Other properties of the Prochlorococcus genomes are consis-
tent with a regulatory role for overlaps. For example, immedi-
ately upstream of the stop codon in the leading overlapping
gene, both MIT9313 and MED4 each contain multiple, but
unique six-base motifs, including strings of adenines adjacent
the stop codon in MED4. These strings of adenines, which are
found in 19% of the overlapping genes, are twice as likely to be
present for overlapping genes as for non-overlapping genes
(10%). These conserved motifs and strings of repeating bases near
the overlap regions are consistent with the PSRF mechanism and
permit cotranslation of two tandem overlap genes (Scherbakov
and Garber 2000).
We have shown that overlapping genes are abundant
among all microbial genomes, but the number or frequency of
overlaps is not related to genome compactness. Overlapping
genes have more homologs among microbial genomes than do
non-overlapping genes. This property may, in part, be due to
their putative regulatory role as the dominant reading frame
shifts and length of the overlaps suggests. Overlapping genes in
Prochlorococcus spp., which are closely phylogenetically related
yet have significantly different nucleotide sequences for or-
thologs, further support this role.
Because of the small physical size of the organisms, micro-
bial genomes may be under increased pressure to minimize the
size of their genome, but this study suggests that overlapping
genes are not a direct mechanism to substantially reduce genome
size. Nevertheless, regulation of gene expression by overlaps may
result in more efficient control and reduce the need for more
complex regulatory pathways. This reduction in turn could di-
minish the number of proteins (and genes) required and thus be
indirectly involved in sequence conservation. Other patterns of
genomic architecture may also aid in the transcriptional and
translational regulation of protein expression and consequently
enable microbial genomes to have compact sizes yet enable flex-
ible and efficient physiologies.
Genomes, which here are defined as contiguous coding regions
(plastids and chromosomes from the same organisms are separate
“genomes”), were downloaded from the National Institutes of
Health National Center for Biotechnology Information ftp server
(ftp://ftp.ncbi.nih.gov/genomes/Bacteria) on May 3, 2003. This
database included 198 genomes, which are detailed in Supple-
Only fully assembled genomes were used in analyses.
Overlapping genes were defined as adjacent genes, on either
strand, that had coding sequences (CDS regions) that shared
one or more bases. Conserved genomic motifs among parallel
overlapping genes were determined by using the online version
of AlignACE 3.0 by searching for motifs within 15 bases of the
stop codon of the leading sequence and by allowing seven col-
umns to align and expecting seven sites (http://atlas.med.
harvard.edu) (McGuire et al. 2000). Genome compactness was
calculated as both the average distance between adjacent genes
and the fraction of the genome assigned to genes. Gene conser-
vation was estimated by creating protein–protein phylogenetic
profiles by assigning each genome a one or zero based on a mini-
mum BLASTP e-value cutoff of 1e ? 5 and summing the ones
and zeros for all genomes for each query gene (Altschul et al.
1997; Pellegrini et al. 1999). Other analyses were made by using
custom written routines in the MATLAB (version 6.5) program-
This work was supported by grants from NSF and DOE to S.W.C.
The authors would like to thank W. Hess and W.F. Doolittle who
commented on an earlier version of the manuscript and the two
anonymous reviewers and editors whose comments greatly im-
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Received February 9, 2004; accepted in revised form August 12, 2004.
Johnson and Chisholm
2272 Genome Research