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LETTER Coexpression of Neighboring Genes in Caenorhabditis Elegans Is Mostly Due to Operons and Duplicate Genes1Department of Biology and Biochemistry, University of Bath, Bath BA2 7AY, UK; 2Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Denver, Colorado 80262, USA
In many eukaryotic species, gene order is not random. In humans, flies, and yeast, there is clustering of coexpressed genes that cannot be explained as a trivial consequence of tandem duplication. In the worm genome this is taken a step further with many genes being organized into operons. Here we analyze the relationship between gene location and expression in Caenorhabditis elegans and find evidence for at least three different processes resulting in local expression similarity. Not surprisingly, the strongest effect comes from genes organized in operons. However, coexpression within operons is not perfect, and is influenced by some distance-dependent regulation. Beyond operons, there is a relationship between physical distance, expression similarity, and sequence similarity, acting over several megabases. This is consistent with a model of tandem duplicate genes diverging over time in sequence and expression pattern, while moving apart owing to chromosomal rearrangements. However, at a very local level, nonduplicate genes on opposite strands (hence not in operons) show similar expression patterns. This suggests that such genes may share regulatory elements or be regulated at the level of chromatin structure. The central importance of tandem duplicate genes in these patterns renders the worm genome different from both yeast and human. [Supplemental material is available online at http://www.genome.org.]
It is often presumed that, aside from clusters of tandem duplicates, gene order within the eukaryotic genome is random. However, there is increasing evidence that this is not always the case. In species as diverse as humans (Lercher et al. 2002  ), flies (Spellman and Rubin 2002), and yeast (Cohen et al. 2000),
neighboring genes show similar expression patterns, even when
accounting for the coexpression of duplicated genes.
In the worm Caenorhabditis elegans, the tendency for similarly
expressed genes to be linked is taken one step further, in that
The worm genome is also potentially unusual in that it has been
considered to be broken into genomic compartments (The C.
elegans Sequencing Consortium 1998
The availability of both sequence (The C. elegans Sequencing
Consortium 1998
Compartmental Heterogeneity When comparing microarray expression profiles for genes located in different autosomal genomic compartments (autosome arms or central regions), we find that genes are not randomly distributed relative to their expression patterns. We observe significant heterogeneity (P < 0.05) for 31 out of the 44 clusters (‘mounts’) of coexpressed genes defined by Kim et al. (2001) . This includes all 24
mounts with n > 50 (detailed results available as
supplemental data). A similar result is obtained when we define
expression by sorting genes into functional classes: We find
significant compartmental heterogeneity for almost all such classes
(Kim et al. 2001) with large enough sample sizes (31 out of 55,
including 23 of 25 classes with n > 50; see supplemental
data). In these analyses, we independently assess statistical
significance for n = 44 mounts (or n = 55
classes) simultaneously. As this increases the probability of finding
at least one ‘significant’ result even under the null hypothesis of
an equal distribution, we repeated the tests with a more stringent
significance level of P < 0.05 / n
(Bonferroni correction). After this correction, the heterogeneity is
still significant for 21 mounts and for 18 functional classes.
Level of Coexpression
Coexpression of Genes in Operons We measured the level of coexpression of neighboring genes in operons as Pearson's correlation coefficient r of the normalized microarray data (Kim et al. 2001 ). In operons, the distance
between the 3' end of one open reading frame (ORF) and the 5' end of
the next ORF is on average 672 bp (median 446 bp). To test whether
coexpression in operons is just a consequence of the proximity of
genes, we also analyzed all neighboring gene pairs closer than 500 bp
that were not identified as part of operons. As shown in Table
1, the level of coexpression r for
close neighbors either on the same or on opposing strands is
significantly lower compared to gene pairs sharing the same operon. For
all three classes of close neighbor pairs, we found strong coexpression
compared to randomly paired genes. All classes in Table 1 are
significantly different from each other (including Bonferroni
correction for multiple tests; P < 10–19 from
one-sided t-tests), except when comparing close neighbors on
the same and on opposing strands (P = 0.066 from two-sided
t-test).
If genes organized into the same operon are always 100% coexpressed (and the low r value in Table 1 is due to random error in the microarray experiments), then we would expect no distance dependence of r within operons. To test this, we calculated the level of coexpression for all possible gene pairs within operons (Fig. 2). Contrary to the prediction, rdecreases significantly with increasing physical gene distance (R2 = 0.79 from linear regression for 0–13 kb, with P = 0.00003 from 106 random data pairings). This is qualitatively unchanged when measuring distance by counting (0–3) intervening genes, or when restricting the analysis to operons (Blumenthal et al. 2002 ) whose structure has been confirmed by
microarray data or cDNA clones (data not shown).
Coexpression of Duplicated Gene Pairs It is known that the genome of C. elegans contains many pairs of duplicated genes (Semple and Wolfe 1999 ), with a strong bias
towards intrachromosomal duplication, and with an excess of duplicates
that are located close to the original gene (distance  30 kb). It
appears likely that in many gene duplication events, control regions
are duplicated together with the coding sequence. Initially, many
duplicated gene pairs will then show similar expression patterns,
although mutations in the control regions will cause a divergence over
time (C. Pal, pers. comm.). Are then the patterns of local coexpression
mainly a consequence of the nonrandom distribution of duplicated gene
pairs? If this is the case, we expect two consequences: (1) when
removing duplicate gene pairs, the level of coexpression (Table 1; Fig.
1) should be greatly reduced; and (2) the probability of finding
duplicates and/or the degree of similarity of duplicated gene pairs
should show a similar distance dependence as the level of coexpression
(Fig. 1). We tested prediction (1) by removing one gene of each pair of duplicated genes. Table 1 shows the resulting level of coexpression for gene pairs in operons, close gene pairs not in operons, and for random gene pairs. While coexpression is reduced in each case compared to the inclusion of all genes, this reduction is nonsignificant (after Bonferroni correction for multiple tests) for genes in operons and for neighboring pairs on opposing strands (Table 1). The reduction is significant for nonoperon neighbors on the same strand and for random gene pairs. As before, all classes of pairs are significantly different from each other (P < 10–21 from one-sided t-tests) except for the comparison of close neighbors on the same to those on opposing strands (P = 0.059 from two-sided t-test). After the exclusion of duplicates, random gene pairs show no correlation of expression, as is expected. The removal of duplicate gene pairs does not change the negative correlation of coexpression with distance when comparing genes within operons (Fig. 2; R2 = 0.67, P = 0.0005). This suggests that some local coregulation occurs even within operons. The level of coexpression beyond operons after excluding duplicate gene pairs is shown in Figure 3 for microarray data (A) and for functional classes (B). For both measures, the level of local coexpression is greatly reduced compared to Figure 1, and is significant only for the closest neighbors (distance < 20 kb) when taking the nonrandom distribution across compartments into account. This is not due to the reduced sample size: When calculating our similarity measures (rd and ICFd) for random subsets of all genes of the same sample sizes, we find values similar to the full data sets (see Fig. 3).
Distribution of Duplicated Gene Pairs The above results suggest that the local similarity in expression beyond operons is largely due to the nonrandom distribution of duplicated gene pairs. How then does the distribution of such gene pairs compare to the distance dependence of the level of coexpression (see prediction [2] above)? Figure 4A shows the probability of finding duplicate gene pairs at distance d ± 10 kb on the same chromosome (corrected for the total number of gene pairs in this distance bracket; this analysis is for 19,325 genes in Wormbase WS78). In Figure 4B, we plot a measure of the degree of sequence similarity (BLAST expect value) of duplicate gene pairs for different distance brackets. Both the fraction of duplicate genes and the degree of sequence similarity decrease exponentially for distances up to  20 kb, and decrease linearly above 200 kb
(duplicate fraction: R2 = 0.70, log(expect):
R2 = 0.60, between 0.5 and 5 Mb). Thus, there
are not only a higher number of similar genes at close distances, but
they are also much more similar than duplicates further apart. In
summary, all features of the local similarity in expression (Fig. 1)
are compatible with the distribution of duplicate genes beyond operons:
the extreme degree of similarity at very small distances
(d < 20 kb), the steep decrease for small distances
(d < 200 kb), and the linear decrease for larger distances.
The worm genome, like other closely analyzed eukaryotic genomes, is not the random array of genes that is often supposed. It is remarkable, for example, that although genes in operons show the strongest coexpression, neighboring genes on the same strand, as well as on opposing strands, show much stronger coexpression compared to genes that are paired at random. This feature remains after the exclusion of duplicate gene pairs. Although we may not have identified some operons with genes expressed at very low levels, this cannot explain the coexpression of neighbors located on opposing strands. This would be consistent either with a chromatin-based level of gene expression, with certain chromosomal regions being accessible to transcription factors in any given tissue, or with gene pairs sharing regulatory elements (Fig. 5). Chromatin-level regulation has also been proposed as an explanation for the clustering of C. elegans muscle-expressed genes (Roy et al. 2002 ). The latter
analysis included at most one gene from each operon and each
family of duplicates. Consistent with what we found here, significant
clustering of such coexpressed genes was restricted to distances <25
kb.
The putative existence of shared regulatory elements could explain the variation of coexpression level within operons shown in Figure 2. Alternatively, this variation could be caused by common errors in operon transcription. Ideally, all genes within an operon are transcribed together, and the individual transcripts are then separated by trans-splicing. Coregulation affecting only part of an operon must then happen after transcription, but before the trans-splicing which separates the individual genes. In the absence of such coregulation, all genes in the same operon should be perfectly coexpressed. Sometimes however, transcription may terminate prematurely, or trans-splicing may not be achieved successfully. In this situation, the probability of two genes to be coexpressed will decrease with increasing distance between them. Furthermore, genes in operons sometimes may appear not to be coregulated because their mRNAs may be subject to differential mRNA destabilization.
Longer-range patterns of similarity of expression are also found. At
the grossest level, genomic compartments themselves differ in their
expression patterns. Most strikingly however, we have shown a general
correlation between pair distance and coexpression level, with the
similarity in expression decreasing linearly over the range of whole
genomic compartments. This pattern can be explained by a simple model
of tandem duplication of both coding and regulatory regions (Fig. 5),
followed by divergence in sequence and expression over time. We may
suppose that at the point of tandem duplication the sequences (both
coding and regulatory), and consequently their expression, are near
identical. Over time, the sequences diverge, the expression pattern
diverges and—owing to random rearrangements—the physical distance
between the duplicates tends to increase. As support for this model, we
find that local coexpression beyond
A nonrandom distribution of duplicates was first demonstrated by Semple
and Wolfe (1999) Although the above four reasons for local similarity—tandem duplicates, operons, putative chromatin-level regulation, and shared regulatory elements—present a complex portrait of the nonrandom relationship between gene location and gene expression (Fig. 5), it is perhaps surprising how weak some of the local similarity in expression appears to be. Most notably, for confirmed operons, it is striking that the correlation of expression is not higher, that is, why is r in Table 1 not close to 1? To some extent, this may represent noise in the data. Indeed, in comparable experiments in yeast, the correlation between the results of identical assays is often even lower than this figure. Thus, a correlation coefficient of r = 0.23 may in fact be relatively large. However, the demonstrated distance dependence of coexpression within operons indicates that coexpression in operons is not perfect, and is affected by additional, distance-dependent factors.
The results presented here contrast with those found in humans (Lercher
et al. 2002 Taken together, our findings suggest that the genome organization of C. elegans differs from the genomes of other eukaryotes not only by the existence of operons, but also by the relative role played by recent gene duplications. Could there be a link between these two genomic characteristics? Interestingly, we found that duplicated genes are located outside of operons more often than expected if there was no correlation between the two features. Of all duplicate pairs, 29,089 had both genes outside of operons, whereas only 2101 pairs (6.7%) had one or both genes within an operon. Using the finding that 2208 of 19,325 genes in our data set (=11.4%) are found in operons, we would have predicted this number to be 1 – (1 – 0.114)2 = 21.5%. These figures are for a definition of "duplicates" as having pairwise BLAST expect value <10–50; qualitatively similar results are obtained for other cut-off values (data not shown). If the duplication of genes is selectively favorable by allowing the evolution of new functions, then the underrepresentation of operonic genes may not be unexpected. Such new functions may require a changed expression pattern of individual genes. However, genes organized in operons are effectively "frozen" in the expression pattern of their operon; to be expressed, such genes need to be duplicated together with the operon's 5' regulatory elements, and thus with all intervening genes. Conversely, genes outside of operons can easily be duplicated individually together with their control regions.
This places a constraint on the evolution of new functions in C.
elegans. Due to the "frozen operons," only a subset of all
genes are available both for individual changes in expression pattern,
and for individual duplication together with their control elements.
The worm may thus be forced to choose new metabolic pathways that are
more complex than they would be if it could recruit all genes equally.
It is noteworthy that this speculative argument not only suggests an
explanation for the many recent gene duplications found in C.
elegans (Semple and Wolfe 1999
Expression and Genome Data We took expression data from a recent meta-analysis of 553 microarray experiments (Kim et al. 2001 ). Certain experiments (expt463,
expt546, expt547, expt548, expt549) were targeted specifically at
operons (Blumenthal et al. 2002), and were thus excluded to avoid
potential bias. In addition to the raw data, we use two definitions of
genic expression profiles by Kim et al. (2001): (1) the expression in
55 nonexclusive functional groups, and (2) 44 exclusive coexpression
clusters (coined "mounts") that are automatically built from
correlations of the raw data.
We located 15,924 genes with raw expression profile, 5630 genes with
known functional profile, and 15,262 genes with unambiguous mount
assignment on the genome map of Wormbase (WS78, available at
ftp://ftp.wormbase.org). Of these, 13,511, 5015, and 12,949,
respectively were positioned on autosomes. Gene position was defined as
the midpoint between the 3' and 5' ends of the unspliced coding
sequence. A list of approximately 2500 genes organized in operons was
obtained from Blumenthal et al. (2002)
Identification of Tandem Duplicates
Compartmental Heterogeneity
 f2 was compared to the corresponding
values from 10,000 random genomes, each obtained by permuting the
compartmental assignments of all genes.
Level of Coexpression/Cofunction
http://www.sanger.ac.uk; The Wellcome Trust Sanger Institute. ftp://ftp.wormbase.org; Wormbase database.
We thank Csaba Pal for discussions, and two anonymous referees for suggestions on the manuscript. We acknowledge support by the Wellcome Trust (M.J.L.) and the Biotechnology and Biological Sciences Research Council (L.D.H.). The publication costs of this article were defrayed in part by payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 USC section 1734 solely to indicate this fact.
3 Corresponding author.  E-MAIL M.J.Lercher{at}bath.ac.uk; FAX 44-1225-386779. Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.553803.
Received June 24, 2002; accepted in revised format November 18, 2002. 13:238-243 © by 2003 Cold Spring Harbor Laboratory Press ISSN 1088-9051/03 $5.00  CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati What's this?
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ABSTRACT
RESULTS
{0,1} indicates not
expressed/expressed):
