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Genetics, Vol. 175, 421-428, January 2007, Copyright © 2007
doi:10.1534/genetics.106.064386
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Institut für Humangenetik, Universität Ulm, D-89081 Ulm, Germany
1 Corresponding author: Institut für Humangenetik, Universität Ulm, Albert-Einstein-Allee 11, D-89081 Ulm, Germany.
E-mail: guenter.assum{at}uni-ulm.de
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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On a fine scale, the correlation between DNA-sequence composition and functional genomic features has been demonstrated for a few regions in which the long-range GC content changes abruptly. In humans, GC-content transitions located in the NF1 gene region on chromosome 17 and in the MN1/PITPNB gene region on chromosome 22 are also demonstrated to be boundaries between regions showing high and low recombination frequencies (EISENBARTH et al. 2000, 2001). Boundaries between early- and late-replicating sequences were found to coincide precisely with GC-content transitions in the human MHC locus (TENZEN et al. 1997) and again in the NF1 gene locus (SCHMEGNER et al. 2005a). Interestingly, both the replication timing during S phase and the recombination frequency of a sequence are supposed to influence the composition of DNA sequences (EYRE-WALKER and HURST 2001), the former through changes in the spectrum of base misincorporations during S phase and the latter through two possible mechanisms. The first is based on a postulated correlation between the recombination frequency in a genomic region, the mutation rate, and perhaps the mutation spectrum. The second mechanism derives from the following fact: Recombination and gene conversion are mechanistically connected in a manner by which sequences with different recombination rates ought also to have different conversion rates. Since gene conversion has been shown to be a biased process (GALTIER 2003), regional variation of conversion rates probably results in regionally varying patterns of evolutionarily fixed mutations. In summary, it can be assumed that the analysis of genetic variability patterns within a species and of fixed differences between species not only reveals whether GC-rich and GC-poor sequences are in a compositional equilibrium, but also allows for the differentiation between the actions of the stabilizing forces mentioned above. Moreover, the variability patterns, if they result from processes relevant for the local differentiation of the GC content, probably differ according to the GC content of DNA sequences and change at GC-content transitions. For this reason, we analyzed the frequency and the spectrum of polymorphic sites in the human and of fixed mutational differences between human and chimpanzee in DNA sequences located around the GC-content transition in the NF1 gene region.
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MATERIALS AND METHODS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Resequencing:
Overlapping primers for PCR were designed to span four different, mainly intronic, parts of the NF1 gene, which altogether comprised 24.9 kb, plus two intronic parts of the neighboring RAB11FIP4 gene, which comprised 19.8 kb. The locations of the sequenced regions within the NF1 and the RAB11FIP4 gene are given in Figure 1A. The average amplicon size used was 2.5 kb, and the average overlap between neighboring amplicons was 100 bp. These PCRs were performed using genomic DNA from all 29 human probands, as well as genomic DNA of one chimpanzee, one gorilla, and one orangutan. Samples were sequenced using Big-Dye Terminator chemistry (Applied Biosystems, Foster City, CA) on an ABI 3100 analyzer. Each PCR amplicon was sequenced from both ends and with at least eight additional internal primers to cover the whole 2.5 kb. Sequence data were assembled and compared using the SeqScape software (Applied Biosystems), and the entire sequence chromatograms were visually inspected.
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One-way chi-square tests were used to compare frequencies of mutations to a model distribution. This model distribution was either 0.5:0.5, when investigating if the frequencies of two types of mutations were equal, or the actual GC:AT content of a sequence, i.e., 0.37:0.63 in the GC-poor domain and 0.51:0.49 in the GC-rich domain. To compare the ratio of AT > GC and GC > AT mutation frequencies (mutations that change an AT into a GC base pair or vice versa) between the domains which is adjusted for the AT contents and the GC contents of the underlying sequences, a test based on the logarithm of the odds ratio for an AT > GC mutation between the domains was used. For adjustment, the model under the null hypothesis claimed an odds ratio of (0.63:0.37)/(0.49:0.51) between the domains. The same procedure was applied to compare SNPs and fixed mutations, with a model odds ratio of 1.
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RESULTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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4.5 difference percentage points each). The differences are due to an adenylate kinase 3 pseudogene, present in one window of the human but not found in the chimpanzee genome, in addition to a 1.3-kb gap in the other window of the chimpanzee sequence. In addition to the GC content, the relative frequency of divergent sites was calculated for each window. The values obtained are given graphically in Figure 1A. For this analysis, only intergenic and intronic sequences with a distance of >50 bp to the next coding exon were used. Nevertheless, varying sequence lengths between the windows are supposed to be negligible, since only the homologous sequences of each window were compared. Regarding the GC-content curves in Figure 1A, the sharp GC-content transition located in the intergenic region between NF1 and RAB11FIP4 is clearly visible. In the same region, a transition from low to high values of sequence divergence occurs, with an average divergence of 0.82% in the GC-poor and 1.19% in the GC-rich region. To decide whether the observed distributional changes of GC content and divergence along the sequence are compatible with random variation and, if not, to specify a region where a change takes place, a statistical change-point analysis was performed. The advantage of this method is that, in addition to no prespecified regions being compared, a candidate position for a change between regions is estimated. For the GC content in human and chimpanzee, and for the divergence, change points were observed, which represent actual changes on the 5% level. Visual inspection of the t-value curves given in Figure 1B actually results in the detection of a transition zone of 20 kb where changes of both features, the GC content of the sequences and the interspecies divergence, might occur. The strongest change in the GC content could be assigned to the window around nucleotide position 212.5 kb; this coincides precisely with the strongest change in the interspecies divergence and hence in the substitution rates between GC-poor and GC-rich sequences immediately contacting each other. The boundaries between the GC-content domains and the domains with differing divergences coincide precisely. Under the assumption of a neutral evolution (the reasons for this assumption are discussed below), the observed regional differences in the substitution frequencies can be interpreted as the result of regionally differing mutation rates. When neutrally evolving sequences are analyzed in a homogeneous population, mutation-rate differences are expected to result in differing SNP densities. To elucidate the SNP densities in both GC-content domains, we resequenced 24.9 kb of intronic sequences from the GC-poor and 19.8 kb from the GC-rich regions in 29 randomly chosen probands of German origin. The sequenced regions (depicted in Figure 1A) were chosen without prior knowledge of GC content or interspecies divergence. The process of resequencing was chosen because reliable SNP densities can hardly be obtained from SNP databases due to varying methods of SNP ascertainment used by the submitters. All told, in our sample of 58 chromosomes, 47 variable sites were detected in the 24.9 kb of NF1 and 71 variable sites in the 19.8 kb of RAB11FIP4. This results in SNP densities of 1.89 SNPs/kb in NF1 and 3.58 SNPs/kb in RAB11FIP4, a difference that also points to mutation-rate differences between the GC-rich and the GC-poor domains.
Next, we wanted to analyze whether or not the spectrum of base pair-changing mutations differs between the two GC-content domains. As it is not possible to directly observe the spectrum of mutations by which a DNA sequence is affected, the spectrum of SNPs found in the human population was used in place of the mutation spectrum. SNPs represent evolutionarily young mutation events. The SNP spectrum is therefore supposed to resemble the mutation spectrum with only minor disturbances. For the analysis we used validated noncoding SNPs, from the dbSNP database, located in a 320-kb region around the GC-content transition at the NF1 locus. The ancestral allele for each SNP was determined through comparisons with the chimpanzee sequence. All SNPs were categorized into four groups: SNPs resulting from mutations that changed an AT base pair into a GC base pair (AT > GC), a GC into an AT (GC > AT), an AT into an TA (AT > TA), and a GC into a CG (GC > CG). GC-rich and GC-poor sequence domains were analyzed separately. As a boundary between the domains, the 5-kb window with the peak in the t-value curve of the GC content (window around nucleotide position 212.5 kb in Figure 1) was used. The results given in Table 1 demonstrate that the SNP pattern is clearly dominated by AT > GC and GC > AT SNPs, which together are called GC-content-changing SNPs in the following text. Henceforth, only this category of SNPs is regarded, because this is the only one that is relevant for the evolution of the GC content of a sequence.
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DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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The analysis of the GC content and the human–chimpanzee divergence in a sliding window of 5 kb showed that both characteristics change abruptly within the same narrow transition region. Results published earlier and the inspection of HapMap data (INTERNATIONAL HAPMAP CONSORTIUM 2005) assigned change points for the recombination frequency (EISENBARTH et al. 2000) and the timing of replication (SCHMEGNER et al. 2005a) to this same transition region. Taken together, these results demonstrate a covariation of all four features—GC content, mutation rate, recombination frequency, and replication timing—on an astonishingly fine scale. On a large scale, various pairwise correlations between these features have been described and a number of causal connections from these correlations have been inferred, especially to explain the mutation-rate variation in the human genome. Covariation of the GC content with the recombination frequency (KONG et al. 2002; MONTOYA-BURGOS et al. 2003; MEUNIER and DURET 2004), with the mutation rate (SMITH et al. 2002), and with the timing of DNA replication (WATANABE et al. 2002; WOODFINE et al. 2004) were described for several chromosomes and the human genome as a whole. The direct influence of the GC content on the mutation rate of a sequence due to a higher rate of cytosine deamination in GC-poor DNA was reported (FRYXELL and ZUCKERKANDL 2000; FRYXELL and MOON 2005). One hypothesis describes the dependency of both the mutation rate and the mutation spectrum of a sequence on the time in S phase, during which the sequence is replicated. The basis for this hypothesis comes from the observation that the concentrations of free deoxyribonucleotides in a cell fluctuate during S phase and affect the fidelity of DNA replication (WOLFE et al. 1989; WOLFE 1991). A correlation between recombination frequency and the mutation rate of a genomic region has been demonstrated by several groups (HELLMANN et al. 2003; HUANG et al. 2005). A causal relationship has been suggested in the sense that the process of recombination itself may be mutagenic (LERCHER and HURST 2002b; FILATOV and GERRARD 2003; FILATOV 2004). Due to the observed covariation of all characters, the results of our work are compatible with all these hypotheses and cannot be used as arguments in favor of or against any of them. Instead, our results suggest that the correlations between structure and function of a genomic region may be more complex than expected from pairwise comparisons of the relevant characters.
To test whether regional variations of the proportions of GC > AT vs. AT > GC mutations were responsible for the creation and the maintenance of the pronounced GC-content differences and the sharp boundary between the sequence domains in the NF1 gene region, the spectrum of base pair exchanges leading to SNPs in the human population was analyzed and taken as a proxy for the mutation spectrum. The results revealed a higher GC > AT than AT > GC mutation rate in both sequence domains, confirming similar observations at the MHC locus, published by EYRE-WALKER (1999) and SMITH and EYRE-WALKER (2001), and for a number of genes on various chromosomes (ALVAREZ-VALIN et al. 2002). Moreover, it turned out that the bias in favor of GC > AT mutations was equally strong in both GC-content domains. These results reject the mutation-bias variation hypothesis as a possible explanation for the compositional heterogeneity of GC-content domains.
A higher rate of GC > AT than AT > GC mutations will lower the GC content of a sequence to <50% over time until an equilibrium is reached, at which both types of mutations occur with the same absolute frequency. This equilibrium appears to be reached for the GC-poor sequences from the NF1 gene locus because the proportions of GC > AT and AT > GC mutations have been found to be equal in this region. As the vast majority of human genomic DNA shows a GC content of <45%, with a peak in the distribution of the GC content in 20-kb windows at 37.5% (LANDER et al. 2001), the GC content of the GC-poor NF1 gene region may be taken as representative of the majority of the genomic sequences. In which case, it can be assumed that the sequence composition of the greatest part of the mammalian genome is a direct result of the mutation-rate bias.
The human–chimpanzee comparison revealed equal proportions of GC > AT and AT > GC substitutions for the GC-poor sequences, further demonstrating the compositional equilibrium for this domain. In the GC-rich domain a higher proportion of GC > AT than AT > GC substitutions was observed, although the difference between the two values was statistically not significant. Hence, we cannot categorically state that this domain is also at an equilibrium or whether the GC content of the GC-rich sequences will decrease over time—a fact that would argue in favor of the vanishing isochore theory, which has been discussed controversially during the last few years (DURET et al. 2002; ARNDT et al. 2003; ALVAREZ-VALIN et al. 2004; BELLE et al. 2004; MEUNIER and DURET 2004; KHELIFI et al. 2006). Irrespective of this discussion, however, our results show a clear discrepancy between the SNP data and the interspecies comparison. This discrepancy may be explained by a change in the mutational biases that occurred after the divergence of the human and the chimpanzee lineages, as suggested by COMERON (2006), or by a fixation bias in favor of AT > GC substitutions, also described earlier (LERCHER and HURST 2002a; LERCHER et al. 2002; WEBSTER and SMITH 2004). Two forces—direct selection on the GC content and biased gene conversion—can explain the proposed fixation bias. The two forces are not mutually exclusive and it is difficult to distinguish between them. In the NF1 gene region, an abrupt regional change in the action of either of the two forces has to be assumed, because the fixation bias has to be postulated only for the GC-rich but not for the GC-poor domain. Intriguingly, a change in the recombination frequencies of the underlying sequences was observed exactly at the boundary between the two GC-content domains, with a low frequency in the GC-poor and a high recombination frequency in the GC-rich region (EISENBARTH et al. 2000). Moreover, HapMap data (INTERNATIONAL HAPMAP CONSORTIUM 2005) revealed not only a higher density of recombination hot spots in the GC-rich than in the GC-poor domain, which actually is completely devoid of hot spots, but also substantially elevated recombination rates in the regions outside of the hot spots in the GC-rich compared to the GC-poor domain. Therefore, it can be assumed that the gene-conversion frequency is also higher in the GC-rich domain, a fact that will result in a stronger fixation bias in this domain, if there is a bias in the conversion rates. This postulated correlation was confirmed by data published recently. KUDLA et al. (2004) showed that paralogous sequences undergoing gene conversion have a higher GC content than sequences not involved in this process. WEBSTER et al. (2005) demonstrated an effect of the recombination rate of a genomic region on the substitution patterns of Alu sequences but not on their polymorphism pattern and explained the differences in the observations by biased gene conversion. This mechanism can lead to regional differences in the GC content only if regional differences in the conversion rates are stable over long periods of time. Whether this condition has really been met cannot be reported upon at present. The exact location of recombination hot spots and the recombination rates measured over short distances (50 kb) are not well conserved between human and chimpanzee (PTAK et al. 2005), but these results tell us little about the conservation of regional differences of recombination frequencies on a scale that is relevant for the evolution of GC-content domains.
In summary, our results suggest a model according to which the GC content of GC-poor sequence domains, representative of the majority of human genomic DNA, is the result of a mutation bias. The higher GC content of the GC-rich domains cannot be explained by actual regional variation of the mutation bias. For this domain, the action of postmutational processes that lead to a preference in the fixation of AT > GC mutations over GC > AT mutations or an evolutionary very recent change in the mutation bias has to be assumed to explain the data.
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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