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Dependence of Mutational Asymmetry on Gene-Expression Levels in the Human Genome

2003; Elsevier BV; Volume: 73; Issue: 3 Linguagem: Inglês

10.1086/378134

1537-6605

Jacek Majewski,

Genetic Mapping and Diversity in Plants and Animals

A great deal of effort has been devoted to measuring the rates of different types of nucleotide substitutions. Mutation rates are known to depend on factors such as methylation status and nearest-neighbor nucleotide effects. However, until recently, in eukaryotes, the rates have not been considered to be strand specific. In a recent analysis of mammalian lineages, Green et al. (Green et al., 2003Green P Ewing B Miller W Thomas PJ Green ED NISC Comparative Sequencing Program Transcription-associated mutational asymmetry in mammalian evolution.Nat Genet. 2003; 33: 514-517Crossref PubMed Scopus (210) Google Scholar) uncovered an asymmetry in the frequencies of substitutions on the coding and noncoding strands of genes and showed that this resulted in a nucleotide-content asymmetry within most genes. The authors argue that this bias may be caused by the mammalian transcription-coupled repair in germ cells, but they did not demonstrate an association with germ-cell gene expression. In this work, I analyze nucleotide contents in genes with known expression patterns and levels and provide evidence that the observed asymmetry in mutation rates is, in fact, caused by transcription. The results also imply that germline transcription may occur in a large percentage, 71%–91%, of all human genes. A great deal of effort has been devoted to measuring the rates of different types of nucleotide substitutions. Mutation rates are known to depend on factors such as methylation status and nearest-neighbor nucleotide effects. However, until recently, in eukaryotes, the rates have not been considered to be strand specific. In a recent analysis of mammalian lineages, Green et al. (Green et al., 2003Green P Ewing B Miller W Thomas PJ Green ED NISC Comparative Sequencing Program Transcription-associated mutational asymmetry in mammalian evolution.Nat Genet. 2003; 33: 514-517Crossref PubMed Scopus (210) Google Scholar) uncovered an asymmetry in the frequencies of substitutions on the coding and noncoding strands of genes and showed that this resulted in a nucleotide-content asymmetry within most genes. The authors argue that this bias may be caused by the mammalian transcription-coupled repair in germ cells, but they did not demonstrate an association with germ-cell gene expression. In this work, I analyze nucleotide contents in genes with known expression patterns and levels and provide evidence that the observed asymmetry in mutation rates is, in fact, caused by transcription. The results also imply that germline transcription may occur in a large percentage, 71%–91%, of all human genes. Numerous efforts have been undertaken to determine the rates of mutation that occurred during evolution and the more recent history of individual species. Some early studies (Gojobori et al. Gojobori et al., 1982Gojobori T Li WH Graur D Patterns of nucleotide substitution in pseudogenes and functional genes.J Mol Evol. 1982; 18: 360-369Crossref PubMed Scopus (292) Google Scholar; Bulmer Bulmer, 1986Bulmer M Neighboring base effects on substitution rates in pseudogenes.Mol Biol Evol. 1986; 3: 322-329PubMed Google Scholar) demonstrated that mutation rates are specific to each type of nucleotide substitution. It is important to note that the rates of forward and back mutations are generally not equal; in mammals, the C:G→T:A base-pair transition is usually the most frequently occurring substitution, and its frequency is significantly higher than that of the reverse T:A→C:G transition. Thus, accumulation of neutral substitutions results in a generally GC-poor composition of mammalian genomes. We now also recognize that mutation rates are usually species specific and depend on numerous additional factors, such as nearest neighbor nucleotide effects (Hess et al. Hess et al., 1994Hess ST Blake JD Blake RD Wide variations in neighbor-dependent substitution rates.J Mol Biol. 1994; 236: 1022-1033Crossref PubMed Scopus (87) Google Scholar; Krawczak et al. Krawczak et al., 1998Krawczak M Ball EV Cooper DN Neighboring-nucleotide effects on the rates of germ-line single-base-pair substitution in human genes.Am J Hum Genet. 1998; 63: 474-488Abstract Full Text Full Text PDF PubMed Scopus (235) Google Scholar) and base modification (Bulmer Bulmer, 1986Bulmer M Neighboring base effects on substitution rates in pseudogenes.Mol Biol Evol. 1986; 3: 322-329PubMed Google Scholar). The most notable example is the process of deamination of methylated cytosines—usually present in CpG dinucleotides—which results in a significant CpG underrepresentation in mammalian genomes. Mutations are usually detected as base-pair substitutions, but the underlying mutational mechanisms—which, in most cases, are still poorly understood—act on single bases. A base may be altered by DNA-damaging processes (such as, for example, deamination) or misincorporated during replication. If the damaged base is correctly repaired by DNA-repair systems, or if the mismatched base is correctly resolved by mismatch repair, no mutation is recovered. However, if the mutation escapes repair, an incorrect base is later synthesized on the complementary DNA strand, and the mutation is detected as a base-pair difference from the ancestral sequence. It is important to note that, since mutation acts on single bases, it is possible for mutation rates to be “strand specific.” In fact, in some simple organisms, it has been demonstrated that the rates may vary with respect to the polarity of transcription and replication (Tanaka and Ozawa Tanaka and Ozawa, 1994Tanaka M Ozawa T Strand asymmetry in human mitochondrial DNA mutations.Genomics. 1994; 22: 327-335Crossref PubMed Scopus (139) Google Scholar; Beletskii and Bhagwat Beletskii and Bhagwat, 1996Beletskii A Bhagwat AS Transcription-induced mutations: increase in C to T mutations in the nontranscribed strand during transcription in Escherichia coli.Proc Natl Acad Sci USA. 1996; 93: 13919-13924Crossref PubMed Scopus (189) Google Scholar; Lobry Lobry, 1996Lobry JR Asymmetric substitution patterns in the two DNA strands of bacteria.Mol Biol Evol. 1996; 13: 660-665Crossref PubMed Scopus (577) Google Scholar; Kano-Sueoka et al. Kano-Sueoka et al., 1999Kano-Sueoka T Lobry JR Sueoka N Intra-strand biases in bacteriophage T4 genome.Gene. 1999; 238: 59-64Crossref PubMed Scopus (17) Google Scholar). If the mutation rates of two complementary DNA strands were identical, over a sufficiently long interval the frequencies of complementary bases should approach equality (i.e., A=T and C=G). This is known as Chargaff’s second parity rule (PR2) (Chargaff Chargaff, 1951Chargaff E Structure and function of nucleic acids as cell constituents.Fed Proc. 1951; 10: 654-659PubMed Google Scholar). Deviations from PR2 in simple organisms have been described elsewhere. Such asymmetries may result from the processes of transcription and replication, both of which distinguish between complementary DNA strands. During transcription, the antisense strand is thought to be stabilized by the transcription machinery, whereas the sense strand is exposed and prone to undergoing mutational processes, such as deamination. Hence, in enterobacteria, the rate of deamination of cytosine, which results in C→T transitions, is increased on sense-DNA strands (Beletskii and Bhagwat Beletskii and Bhagwat, 1996Beletskii A Bhagwat AS Transcription-induced mutations: increase in C to T mutations in the nontranscribed strand during transcription in Escherichia coli.Proc Natl Acad Sci USA. 1996; 93: 13919-13924Crossref PubMed Scopus (189) Google Scholar). During replication, the lagging and leading DNA strands are subject to different frequencies of base misincorporation, and replication-associated biases may result in an excess of G over C and T over A on the leading strands. Such biases exist in most genomes that possess single origins of replication: bacteria, many viruses, mitochondria, and chloroplasts (reviewed by Frank and Lobry [Frank and Lobry, 1999Frank AC Lobry JR Asymmetric substitution patterns: a review of possible underlying mutational or selective mechanisms.Gene. 1999; 238: 65-77Crossref PubMed Scopus (222) Google Scholar]). In eukaryotic genomes, where multiple origins of replication exist, replication-associated biases are generally not observed. In the proximity of known origins of replication, such effects have been suggested (Wu and Maeda Wu and Maeda, 1987Wu CI Maeda N Inequality in mutation rates of the two strands of DNA.Nature. 1987; 327: 169-170Crossref PubMed Scopus (80) Google Scholar) but have not been confirmed, in general (Bulmer Bulmer, 1991Bulmer M Strand symmetry of mutation rates in the β-globin region.J Mol Evol. 1991; 33: 305-310Crossref PubMed Scopus (23) Google Scholar). Similarly, transcription-associated biases have not been suggested until recently (Green et al. Green et al., 2003Green P Ewing B Miller W Thomas PJ Green ED NISC Comparative Sequencing Program Transcription-associated mutational asymmetry in mammalian evolution.Nat Genet. 2003; 33: 514-517Crossref PubMed Scopus (210) Google Scholar). In this work, I investigate the bias, measured as B=[(G+T)-(A+C)]/(A+C+G+T), in all known human genes (a total of 13,870 unique genes, from the RefSeq track of the UCSC genome annotation database, Hg14 November 2002 [Kent et al. Kent et al., 2002Kent WJ Sugnet CW Furey TS Roskin KM Pringle TH Zahler AM Haussler AD The human genome browser at UCSC.Genome Res. 2002; 12: 996-1006Crossref PubMed Scopus (5921) Google Scholar]). In the absence of mutational asymmetry, this bias is expected to equal zero (Sueoka Sueoka, 1995Sueoka N Intrastrand parity rules of DNA base composition and usage biases of synonymous codons.J Mol Evol. 1995; 40: 318-325Crossref PubMed Scopus (229) Google Scholar). Within each gene, the average bias was determined from all noncoding intronic sequences, excluding the first and last 50 bp of each intron, since those regions are most likely to contain control elements and evolve in a nonneutral fashion (Majewski and Ott Majewski and Ott, 2002Majewski J Ott J Distribution and characterization of regulatory elements in the human genome.Genome Res. 2002; 12: 1827-1836Crossref PubMed Scopus (232) Google Scholar). It is important to exclude potentially functional regions, since I am interested in investigating sequences that evolve neutrally and are under no selective pressure. To exclude repetitive elements that might have inserted recently and would not reflect long-term evolutionary patterns, I used the repeat-masked version of the genome. However, similar results are obtained with the unmasked sequence. Transcription-associated, neutral asymmetric patterns should be heritable only in genes that are expressed in the germline. Hence, I expect such genes to have higher average biases than tissue-specific genes. In addition, if the asymmetric substitutions occur during transcription, highly expressed genes should have larger deviations from symmetry than genes with low average expression levels. I used the HuGE Index Database (Haverty et al. Haverty et al., 2002Haverty PM Weng Z Best NL Auerbach KR Hsiao LL Jensen RV Gullans SR HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues.Nucleic Acids Res. 2002; 30: 214-217Crossref PubMed Google Scholar) to categorize genes by tissue specificity and expression levels. I used the subset of ubiquitously expressed housekeeping genes (n=374) to represent genes that are very likely to be transcribed in the germline. Although exact expression levels of those genes throughout their germline history are not known, I assume that their average expression over 19 different tissue types should be representative of their mean expression in the germline. Using the average values minimizes tissue-specific variations. The values were log-transformed to ensure a better approximation to normality. Within the housekeeping set, I demonstrate a highly significant Pearson correlation between expression intensity and the mutational bias (B) (r=0.28; P<10−7). This result, shown in figure 1, is also significant under the nonparametric Spearman rank correlation test (r=0.29; P<10−7). The correlation is even stronger for the subset of genes with lowest variability (as measured by the coefficient of variation) across tissues; that is, genes for which tissue-averaged expression should be a particularly good estimate of germline activity. For the set of the 30 least-variable genes, Spearman correlation increases to r=0.46. I also investigated the individual components of the overall compositional bias: the GC skew, which can be measured as (G-C)/(G+C), and the AT skew, measured as (T-A)/(A+T). Within the housekeeping-gene sample, both the GC skew (Pearson r=0.25; P=7.10−7) and the AT skew (r=0.17; P=8.10−4) are significantly correlated with the expression level. As a control, I used a set of brain-specific genes: 431 genes that are highly expressed in the brain but not in any other tissue in the database (Hsiao et al. Hsiao et al., 2001Hsiao LL Dangond F Yoshida T Hong R Jensen RV Misra J Dillon W Lee KF Clark KE Haverty P Weng Z Mutter GL Frosch MP Macdonald ME Milford EL Crum CP Bueno R Pratt RE Mahadevappa M Warrington JA Stephanopoulos G Gullans SR A compendium of gene expression in normal human tissues.Physiol Genomics. 2001; 7: 97-104Crossref PubMed Scopus (177) Google Scholar). Although some of those genes may still be expressed in germ cells, there should be no correlation between brain-specific expression levels and B. In fact, no such correlation exists (Spearman r=0.02; P=.53). Having established the correlation between gene expression and strand asymmetry, it is of interest to compare average biases across different groups of genes (table 1). Within the entire human genome (13,870 genes), B=4.3%. Within the brain-specific sample, the bias is close to this genomewide average (B=4.0%). However, within the housekeeping-gene sample, the mean bias is significantly elevated (B=6.4%; χ21=1,699; P<10−16). Similarly, in an independently assessed sample of 675 oocyte-expressed genes (Stanton and Green Stanton and Green, 2001Stanton JL Green DP A set of 840 mouse oocyte genes with well-matched human homologues.Mol Hum Reprod. 2001; 7: 521-543Crossref PubMed Scopus (37) Google Scholar), the bias is also significantly elevated (B=5.8%; χ21=3,092; P<10−16), which demonstrates that genes that are known to be expressed in germ cells have a higher average bias. The bias remains elevated (B=5.7%) even after removing all known housekeeping genes from the oocyte sample. Finally, there also exist variations in mean bias levels across chromosomes, with the largest bias (B=6.2%) observed on the Y chromosome, which is consistent with the involvement of Y-linked genes in reproductive functions.Table 1Average Mutational Biases within Functional Divisions of Human GenesSampleNo. of GenesBCompared with MeanaAll differences are highly significant under a χ2 test of homogeneity that compares G+T and A+C counts within each sample with those within the entire RefSeq gene complement.RefSeq13,870.043=Housekeeping374.064Oocyte675 (545)bThe values in parentheses refer to a subset of the oocyte-expressed genes from which all known housekeeping genes have been removed..058 (.057)bThe values in parentheses refer to a subset of the oocyte-expressed genes from which all known housekeeping genes have been removed.Y chromosome54.062Brain431.040 0. Within the oocyte-expressed sample, this value is even higher (97%). One may expect that this leads to a bimodal distribution of individual B values within the entire gene complement, genes absent in the germline with biases clustered around B=0, and germline-expressed genes distributed with a positive mean. However, if we examine all known genes with total nonrepetitive intronic lengths >10,000 nucleotides (n=7,054, selected for length to increase statistical power), 91% have positive biases; in 83%, the asymmetry is significant at the P<.05 level (χ2 test for deviation from G+T=A+C); and in 71%, it is significant at the Bonferroni-corrected P 71% and possibly as high as 91%, of all genes are transcribed in reproductive cells, which reflects the great complexity of processes required for reproduction and early development. However, it should be noted that transcriptional activity does not necessarily imply functionality; some of the genes may not be essential for germline function but may still be transcribed at low, residual levels (Chelly et al. Chelly et al., 1989Chelly J Concordet JP Kaplan JC Kahn A Illegitimate transcription: transcription of any gene in any cell type.Proc Natl Acad Sci USA. 1989; 86: 2617-2621Crossref PubMed Scopus (557) Google Scholar). The above analysis implies that mutational asymmetry in human genes is caused by transcription. In bacteria, such biases may be caused by deamination of cytosine. A similar mechanism has been proposed to explain some features of codon bias in human genes (Duret Duret, 2002Duret L Evolution of synonymous codon usage in metazoans.Curr Opin Genet Dev. 2002; 12: 640-649Crossref PubMed Scopus (341) Google Scholar) and may be applicable here. However, Green et al. (Green et al., 2003Green P Ewing B Miller W Thomas PJ Green ED NISC Comparative Sequencing Program Transcription-associated mutational asymmetry in mammalian evolution.Nat Genet. 2003; 33: 514-517Crossref PubMed Scopus (210) Google Scholar) argue that, in mammals, the bias is more likely to be caused by the action of transcription-coupled repair (TCR). The results presented here are consistent with both hypotheses. Increased levels of transcription should result in longer periods of separation for the two DNA strands, which may lead to increased deamination of cytosine. On the other hand, Leadon and Lawrence (Leadon and Lawrence, 1991Leadon SA Lawrence DA Preferential repair of DNA damage on the transcribed strand of the human metallothionein genes requires RNA polymerase II.Mutat Res. 1991; 255: 67-78Crossref PubMed Scopus (91) Google Scholar) have also shown that the efficiency of TCR is dependent on the intensity of transcription. Thus, TCR may also cause the covariation of mutational asymmetry and intensity of transcription. Also, the fact that both the GC skew and AT skew are correlated with transcription does not offer a conclusive argument in favor of either mechanism. Whereas TCR may alter various mutation rates and hence affect both the GC and AT skews, deamination of cytosine would directly cause the GC skew by depleting the cytosine pool, but it would also result in the AT skew by converting cytosines into thymines. Although this work is not able to distinguish between the two hypotheses, the study of Green et al. (Green et al., 2003Green P Ewing B Miller W Thomas PJ Green ED NISC Comparative Sequencing Program Transcription-associated mutational asymmetry in mammalian evolution.Nat Genet. 2003; 33: 514-517Crossref PubMed Scopus (210) Google Scholar) provides two strong arguments in favor of TCR: in primates, the C→T transition rate is not elevated on the sense-DNA strand, and the overall frequency of neutral mutations does not vary between transcribed and nontranscribed sequences. Since both of the above effects would be expected under the deamination hypothesis, the action of TCR remains the preferable explanation for the observed mutational asymmetry. Whereas experimental verification of the above hypothesis should be a welcome development in the future, the analysis presented here provides the strongest evidence to date that, in the human genome, transcription is the cause of strand-specific mutational asymmetry. The knowledge of such issues is crucial to the understanding of mutational processes that occur in the human genome. I thank Dr. Loydie Majewska, Dr. Lilia Iakoucheva, Mark Levenstien, Dr. Phil Green, and an anonymous reviewer for helpful comments on the manuscript. This work was supported by grant HG00008 from the National Human Genome Research Institute, Bethesda.