MBE Advance Access originally published online on May 9, 2008
Molecular Biology and Evolution 2008 25(8):1602-1608; doi:10.1093/molbev/msn110
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Research Articles |
DNA Methylation and Structural and Functional Bimodality of Vertebrate Promoters
School of Biology, Georgia Institute of Technology
E-mail: soojinyi{at}gatech.edu
| Abstract |
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Human promoters divide into 2 classes, the low CpG (LCG) and the high CpG (HCG), based on their CpG dinucleotide content. The LCG class of promoters is hypermethylated and is associated with tissue-specific genes, whereas the HCG class is hypomethylated and associated with broadly expressed genes. By analyzing several chordate genomes separated for hundreds of millions of years, here we show that the divide between low CpG and high CpG promoters is conserved in several distantly related vertebrate taxa (including human, chicken, frog, lizard, and fish) but not in close invertebrate outgroups (sea squirts). Furthermore, LCG and HCG promoters are distinctively associated with tissue-specific and broadly expressed genes in these distantly related vertebrate taxa. Our results indicate that the function of DNA methylation on gene expression is conserved across these vertebrate taxa and suggest that the 2 classes of promoters have evolved early in vertebrate evolution, as a consequence of the advent of global DNA methylation.
Key Words: DNA methylation promoter expression genome evolution vertebrates
| Introduction |
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Analyses of human and mouse promoters have revealed an intriguing structural and functional bimodality (Carninci 2006
In terms of its effect on sequence, DNA methylation is highly mutagenic. In vertebrate genomes, methylation occurs almost exclusively at the cytosines in CpG dinucleotides. Methylated cytosines undergo rapid deamination to become thymines, causing C-to-T transitions (or G-to-A transitions in the complementary strand) (Coulondre et al. 1978
). In the human and chimpanzee genomes, for example, methylation-origin transitions occur almost 15-fold more frequently than other single-nucleotide substitutions (Elango et al. 2008
). As a consequence, CpG dinucleotides are depleted from methylated regions over evolutionary timescale (Bird 1980
). Thus, normalized CpG content (CpG O/E or "CpG content" in the rest of the paper; see Materials and Methods) is an indicator of the level of DNA methylation (low CpG content and high CpG content reflect hypermethylation and hypomethylation, respectively: Suzuki et al. 2007
; Weber et al. 2007
).
In terms of function, at least in mammals, promoter methylation can dampen gene expression. This is achieved either directly by interfering with transcription factor binding or indirectly through recruitment of methyl-CpG–binding proteins to alter chromatin structure (Jones and Takai 2001
; Klose and Bird 2006
). LCG promoters may therefore be associated with (somatic) tissue-specific genes as a consequence of germ line DNA methylation, whereas the promoters of broadly expressed genes remain unmethylated thereby forming the HCG class (Vinogradov 2005
).
Although the role of mammalian promoter methylation and its effect on CpG content and expression breadth is well studied (Antequera 2003
; Carninci 2006
; Saxonov et al. 2006
; Tang and Epstein 2007
; Weber et al. 2007
), the origin and evolution of such phenomenon is little understood. Here we investigated these aspects, by first focusing on the observation that the patterns of DNA methylation differ greatly among diverse taxa. Mammalian genomes exhibit a global DNA methylation pattern (
80% of the CpGs are methylated) in most cell types (Tweedie et al. 1997
and the references therein) and thus are largely depleted of CpG dinucleotides (Bird 1980
). Most of the vertebrate genomes analyzed are similarly globally methylated (Bird 1980
; Tweedie et al. 1997
).
Studies indicate that such "global" genomic methylation is restricted to vertebrates. Invertebrate animals distantly related to vertebrates such as Drosophila and Caenorhabditis elegans generally lack germ line DNA methylation (Tweedie et al. 1997
). Genomes of close outgroup of vertebrates, such as those of invertebrates within the chordate phylum (e.g., urochordate sea squirt and cephalochordate amphixious), and echinoderms (e.g., sea urchin) exhibit a "mosaic" CpG methylation pattern with long methylated regions and equally long unmethylated regions. Based upon these, it is proposed that the transition from mosaic to global methylation pattern have occurred early in vertebrate evolution (Hendrich and Tweedie 2003
).
Interestingly, the aforementioned functional role of promoter DNA methylation may also be unique to vertebrates. A recent study (Suzuki et al. 2007
) showed that methylation at CpG sites in the urochordate Ciona intestinalis, which exhibits a mosaic methylation pattern, is targeted to intragenic regions of a subset of genes. Thus, intragenic regions (in contrast to promoters in humans) fall into low-CpG and high-CpG categories in this genome. Promoters analyzed in Suzuki et al. (2007)
were not preferentially targeted by DNA methylation.
Several questions emerge when we synthesize these observations: does the structural bimodality in mammalian promoters exist in other vertebrates? If yes, does the relationship between structural bimodality and expression breadth hold in those species? When did the promoter bimodality evolve? If the structural bimodality coincides with the functional bimodality in distantly related vertebrate species, we may infer that DNA methylation is the underlying link for both phenomena, and that structural and functional promoter bimodality has evolved early in vertebrate evolution, rather than independently several times. In this study, we provide answers to some of these questions and propose a model for the evolution of bimodal vertebrate promoters.
| Materials and Methods |
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Genome Sequences and Annotations
We analyzed 6 vertebrate and 3 invertebrate genomes, covering substantial phylogenetic depth. The genome build, source, and gene annotations used in the study are shown in Supplementary Table 1 (Supplementary Material online). We present results from the analyses of the following genomes in the main text: zebrafish (Danio rerio), frog (Xenopus tropicalis), chicken (Gallus gallus), human (Homo sapiens), and a sea-squirt (C. intestinalis) because these genomes had relatively large numbers of curated RefSeq (Pruitt et al. 2007
In all the analyses, we removed genes with more than one transcript to avoid errors in TSS annotation. Promoters were defined as 600-bp regions upstream of TSS. Qualitative results of our analyses did not change when we used 1-kb upstream regions as promoters. We also removed promoters that lied within a distance of 3 kb from any other gene.
Because natural selection on coding sequence could potentially confound our results, exons were removed from all the intragenic analyses. First introns were also removed from our analyses because they often encode regulatory elements (Majewski and Ott 2002
).
Non–first introns may still harbor some regulatory sequences; for example, some introns may carry CpG islands (Gardiner-Garden and Frommer 1987
). The presence of intronic CpG islands may have caused the skew toward greater CpG O/E in human and chicken introns (fig. 1I,J).
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Repetitive elements were identified using repeat masker annotations in the UCSC genome browser (Karolchik et al. 2008
Measurement of Normalized CpG Contents
The "normalized CpG content" (CpG O/E) is defined as
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Statistical Test for Bimodal Distribution
The unimodality or bimodality of normalized CpG content distributions was tested using the NOCOM software (Ott 1992
). Briefly, the software uses an expectation maximization algorithm to fit the data to both unimodal and bimodal distribution models and finds the maximum likelihood values (L0 and L1 for unimodal and bimodal models, respectively). To test if the bimodal distribution model is a better fit to the data as compared with the unimodal distribution model, a statistic G2 = 2[ln(L1)–ln(L0)] was calculated. This statistic approximately follows a Chi-square distribution with 2 degrees of freedom.
Analysis of Expression Data
Expression data were obtained from EST counts in the Unigene database (Wheeler et al. 2003
). Genes with EST count
1 in a tissue were considered to be expressed in that tissue. The expression breadth of a gene is the number of tissues in which it is expressed. For the human genome, we additionally analyzed 2 microarray data sets. The first data set contains expression data from 79 tissues measured using 3' arrays (Su et al. 2004
). Genes with average difference value >200 in a tissue were considered expressed in that tissue (Su et al. 2004
; Saxonov et al. 2006
). The second data set contains exon array expression data from 6 tissues (Xing et al. 2007
), namely heart, kidney, liver, muscle, spleen, and testis. The probes in the exon array are evenly spaced and dense (147 probes per gene, compared with 11 probes per gene in the 3' array [Xing et al. 2007
]). Therefore, exon arrays are considered to provide more accurate measures of gene expression compared with the 3' arrays used in Su et al. 2004
(Kapur et al. 2007
; Xing et al. 2007
).
| Results |
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Patterns of Intronic and Promoter Methylation in Invertebrate Genomes Closely Related to Vertebrates
We analyzed patterns of CpG dinucleotide depletion in upstream promoter regions and intragenic regions of several invertebrate and vertebrate genomes and related them to the known patterns of genomic methylation. Previous studies have shown that although most vertebrate genomes are globally methylated in many different tissue types (Tweedie et al. 1997
We compared normalized CpG content (CpG O/E) of upstream promoter regions (defined as 600-bp upstream of the transcription start site [TSS]: results remained the same when 1 kb instead of 600 bp of upstream regions were analyzed) and of introns. Because our purpose is to compare patterns of intragenic methylation versus upstream promoter regions, we did not include promoter regions downstream of TSS, which often includes first exons and introns. Intron CpG O/E serves as an indicator of the level of genome-wide methylation. Intergenic CpG O/E is not used for this purpose because these genomes differ greatly in terms of genome size and the amount of intergenic regions. In the relatively well-annotated human genome, for example, CpG O/E distributions of intergenic and intronic regions are similar (Supplementary text and Figure S1, see Supplementary Material online).
Introns of C. intestinalis show 2 distinctive distributions, one with the mean CpG O/E
1 and the other with the mean CpG O/E around 0.5 (Suzuki et al. 2007
; fig. 1F). This observation is in accord with the finding that the genomic methylation pattern is mosaic in Ciona genome, where intragenic regions of a subset of genes are methylated and others are not methylated (Suzuki et al. 2007
). The introns with high CpG O/E (
1) represents nonmethylated genes, and those with low CpG O/E (
0.5) showcases methylated genes (Suzuki et al. 2007
; fig. 1F). In contrast, we found that CpG content of Ciona promoters follows a unimodal distribution with its mean
1 (CpG occurs at the expected frequency; fig. 1A) indicating that promoters are largely unmethylated in this genome.
We analyzed distributions of CpG O/E in promoters and introns of another sea squirt, Ciona savignyi. Genetic divergence between C. intestinalis and C. savignyi is known to be similar to that between human and chicken (Small et al. 2007
). We obtained similar results (Figure S2, see Supplementary Material online). promoter regions follow a unimodal Gaussian distribution with mean
1, whereas intragenic regions show 2 distinctive curves.
We also analyzed data from sea urchin (Strongylocentrotus purpuratus), which also exhibits a patchy DNA methylation pattern (Tweedie et al. 1997
). There are only 131 RefSeq genes from this species that satisfy the criterion of single transcript. Even with this small sample size, results from the promoter and intronic regions of this species are similar to those in the 2 Ciona genomes (Figure S2, see Supplementary Material online).
This above pattern in invertebrate genomes is opposite to that in the human genome. As discussed earlier, human promoters exhibit bimodality of hypo- and hypermethylated portions (fig. 1E), whereas introns show a unimodal distribution with mean around 0.2, reflecting heavy global methylation (fig. 1J).
Distribution of Promoter CpG Content Is Bimodal in Distantly Related Vertebrate Species
Next we investigated if the pattern of promoter and intron CpG depletion found in humans is conserved in nonmammalian vertebrates. We analyzed the following distantly related vertebrate genomes, in addition to the human genome: fugu (Takifugu rubripes), zebrafish (Danio rerio), frog (Xenopus tropicalis), lizard (Anolis carolinensis), and chicken (Gallus gallus). Among these species, results from fugu and lizard are presented in the Supplementary Material online (Figure S2) because of the potential inaccuracy of annotations. We will focus on results from the 4 remaining vertebrate genomes, which are relatively well annotated and cover sufficient phylogenetic depth (fig. 1).
Intronic CpG content of the 4 vertebrate genomes shows clear unimodal distributions (fig. 1F–J). The mean intronic CpG O/E are all below 1, indicating that these genomes are heavily methylated. The suppression of CpG frequency is most pronounced in the human and chicken introns, where the mean CpG O/E is 0.23 and 0.22, respectively (fig. 1I,J and table 1). In the zebrafish, CpG frequency is approximately 40% of the expected (fig. 1G). The observed interspecies differences in intronic CpG O/E could be due to differences in methylation levels or due to the variability of the efficiency of deamination, which is a key step in methylation-induced CpG mutations (Frederico et al. 1993
).
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In contrast, upstream promoter regions of all 4 vertebrate genomes follow 2 distinctive distributions of LCGs and HCGs (fig. 1 and table 1). We used an expectation–maximization (EM) algorithm to fit the observed distributions to unimodal, bimodal, and trimodal Gaussian distributions and compared the likelihoods (see Materials and Methods, table 1). Bimodality is consistently a far better fit to the observed distributions than unimodal distributions (P < 10–10 using likelihood ratio test in all species). A recent paper suggested a "trimodal" distribution rather than bimodal (Weber et al. 2007
It is known that the G and C nucleotide content (G+C content) and CpG O/E are correlated (Gardiner-Garden and Frommer 1987
; Duret and Galtier 2000
; Fryxell and Zuckerkandl 2000
). However, the bimodality of CpG O/E is not caused by GC content bimodality; for example, Saxonov et al. (2006)
showed that G+C contents in human promoter regions follow a Gaussian distribution with 1 mean. Similarly, we demonstrate that the bimodality of CpG content in promoters is not caused by the underlying distribution of G+C contents (Supplementary text and Figure S3, see Supplementary Material online).
To test whether the observed pattern is caused by inaccurate TSS annotation, we restricted our analyses to experimentally verified TSS only, using the data from DBTSS (Wakaguri et al. 2008
). There are 4,277 human genes in the DBTSS that overlap with our data set. Analyses of this subset of genes show the same results as those from the whole data set (Supplementary Figure S4, see Supplementary Material online). Therefore, our finding is not caused by bias in TSS annotation.
LCGs Are Associated with Tissue-Specific Genes and HCGs Are Associated with Broadly Expressed Genes in Distantly Related Vertebrate Genomes
Next, we investigated the functional implication of the observed bimodality. We first analyzed microarray data from humans to compare with previous results. We analyzed the gene expression data from 79 tissues in gene atlas (Su et al. 2004
). Genes with LCG promoters were expressed in fewer tissues (median: 38 tissues) than those with HCG promoters (median: 58 tissues). This difference is statistically significant (table 2, Mann–Whitney test, P < 10–3) and confirms earlier results (Saxonov et al. 2006
). Analysis of exon array expression data (Kapur et al. 2007
; Xing et al. 2007
) from 6 tissues yielded similar results (Supplementary text and Figure S5, see Supplementary Material online).
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To determine whether the same pattern holds in other species, we chose to analyze EST data because they are available from all the species studied here, allowing a meaningful comparison. We obtained EST data from the Unigene database (Wheeler et al. 2003
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Vinogradov (2005)
| Discussion |
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We have shown that the structural and functional distinctions between LCGs and HCGs are conserved in several distantly related vertebrate genomes. This indicates that the functional role of DNA methylation in gene expression is conserved in these taxa, which were separated for hundreds of millions of years (fig. 1). What is the underlying mechanistic basis of the association of LCG promoters with tissue-specific genes and HCG promoters with broadly expressed genes in these vertebrate genomes? As mentioned earlier, DNA methylation can suppress gene expression directly by interfering with transcription factors or indirectly by recruiting chromatin modification enzymes. A recent study (Vinogradov 2005
6-fold lower than that of HCG genes (fig. 3).
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The invertebrate chordates with mosaic genomic DNA methylation pattern analyzed here exhibit a single class of hypomethylated promoters (fig. 1 and Supplementary Figure S2, see Supplementary Material online). This finding, along with the observation that the structural and functional bimodality in promoters is conserved across several distantly related vertebrate species spanning zebrafish to human, suggests that the bimodality originated early in vertebrate evolution, potentially as a consequence of the transition from mosaic to global methylation of genomes. Hypomethylation of promoters, as found in Ciona, is likely to be the ancestral state because the mosaic DNA methylation pattern in Ciona is typical of methylated chordates (Suzuki et al. 2007
The fact that CpG contents of LCGs are similar to that of the rest of the genome whereas HCGs preserve CpG contents in several distantly related vertebrate genomes (fig. 1 and table 1; also see Supplementary text, see Supplementary Material online) provides a clue to the origin of the vertebrate LCG promoters. Specifically, it indicates that the level of DNA methylation in LCG promoters is similar to the genome-wide level. We propose that LCG promoters, and consequently the bimodal distribution of CpG contents in vertebrate promoters, have originated due to mutational decay of CpG dinucleotides following DNA methylation. Our functional analyses suggest that this process has occurred preferentially in upstream regions of tissue-specific genes.
HCG promoters, on the other hand, maintain high CpG contents despite the global genomic methylation. One possible explanation is that broadly expressed genes have selectively avoided DNA methylation and remained as HCGs because silencing of such genes due to DNA methylation would have been deleterious. For instance, aberrant promoter methylation in the human genome is highly deleterious, often associated with several diseases including cancer (Robertson and Wolffe 2000
; Esteller and Herman 2002
; Egger et al. 2004
).
According to this model, the rate of CpG loss should be greater in LCG promoters than in HCG promoters. This is indeed the case in the human genome (Weber et al. 2007
). Comparing expression patterns in human and mouse genomes has further revealed that CpG islands were preferentially being lost from promoters of tissue-specific genes (Jiang et al. 2007
). These observations provide strong support to the role of DNA methylation on the origin and evolution of the bimodality of vertebrate promoters.
| Supplementary Material |
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Supplementary text, tables, and figures are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/).
| Acknowledgements |
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We thank comments from the Yi laboratory, especially from Brendan Hunt. Comments from anonymous reviewers on the previous versions of the manuscript provided helpful insights. This study is supported by funds from the Blanchard-Milliken Fellowship and the Alfred P. Sloan Foundation to S.Y.
| Footnotes |
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David Irwin, Associate Editor
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