- Research article
- Open Access
Large-scale inference of the point mutational spectrum in human segmental duplications
© Nakken et al; licensee BioMed Central Ltd. 2009
- Received: 02 September 2008
- Accepted: 22 January 2009
- Published: 22 January 2009
Recent segmental duplications are relatively large (≥ 1 kb) genomic regions of high sequence identity (≥ 90%). They cover approximately 4–5% of the human genome and play important roles in gene evolution and genomic disease. The DNA sequence differences between copies of a segmental duplication represent the result of various mutational events over time, since any two duplication copies originated from the same ancestral DNA sequence. Based on this fact, we have developed a computational scheme for inference of point mutational events in human segmental duplications, which we collectively term duplication-inferred mutations (DIMs). We have characterized these nucleotide substitutions by comparing them with high-quality SNPs from dbSNP, both in terms of sequence context and frequency of substitution types.
Overall, DIMs show a lower ratio of transitions relative to transversions than SNPs, although this ratio approaches that of SNPs when considering DIMs within most recent duplications. Our findings indicate that DIMs and SNPs in general are caused by similar mutational mechanisms, with some deviances at the CpG dinucleotide. Furthermore, we discover a large number of reference SNPs that coincide with computationally inferred DIMs. The latter reflects how sequence variation in duplicated sequences can be misinterpreted as ordinary allelic variation.
In summary, we show how DNA sequence analysis of segmental duplications can provide a genome-wide mutational spectrum that mirrors recent genome evolution. The inferred set of nucleotide substitutions represents a valuable complement to SNPs for the analysis of genetic variation and point mutagenesis.
- Mutational Event
- Segmental Duplication
- Paralogous Sequence
- RefSeq Transcript
- Recent Segmental Duplication
Single point mutations represent a fundamental driving force for the evolution of any vertebrate genome. Mutations create DNA sequence variation that may alter gene function as well as DNA conformation and protein binding [1, 2]. The spectrum of nucleotide substitutions occurring in human DNA sequences is the result of actions of various mutational sources of both endogenous and exogenous origin. An increasing body of evidence supports the idea that the majority of mutations are generated by error-prone intracellular processes that operate in a DNA sequence-dependent manner [3, 4]. Examples of endogenous mutagenic processes are DNA replication (i.e. polymerase fidelity and replication slippage), post-replicative DNA mismatch repair and methylation-mediated deamination of cytosines in CpG dinucleotides [5–9]. The sequence dependence of these processes is reflected in a biased distribution of point mutations and their sequence neighbourhoods, as shown by previous analyses of pseudogene mutations, germline disease mutations and single nucleotide polymorphisms (SNPs) [3, 10–13]. The nature of the observed point mutational bias is by far dominated by the hypermutability of the CpG dinucleotide [14, 15]. The extent of CpG depletion in mammalian DNA attributable by methylation-mediated mutation (i.e. 5mC→T) is however a matter of debate [16–21]. The deficiency of CpG seen in unmethylated vertebrate DNA viruses and observations that CpG sequences are favored targets for specific exogenous mutagens suggest that other mutational and selectional mechanisms might contribute to CpG depletion [22–24]. With the exception of CpG mutations, linking the observed non-randomness of human mutations to known sequence-dependent mutational mechanisms remains challenging.
So far, large-scale genome-wide analyses of the DNA context of point mutational events have relied on either disease-causing mutations or SNP data from NCBI's dbSNP . As of February 2007, dbSNP contains more than 9 million polymorphic (biallelic only) positions in the human genome. However, studies have shown that a substantial fraction of entries in dbSNP have been erroneously submitted (e.g. as a result of DNA sequencing errors), and are most likely monomorphic alleles in human populations [26, 27]. Comprehensive computational analyses of SNPs may thus easily get corrupted unless a careful discrimination between validated and non-validated entries in dbSNP is undertaken.
A valuable source of information on vertebrate point mutagenesis that to our knowledge has not been thoroughly investigated is contained within human segmental duplications. Recent segmental duplications are large (≥ 1 kb) regions of high sequence identity (≥ 90%) that constitute all types of genomic elements, such as high-copy repeats and gene sequences with exon-intron structures [28–31]. Approximately 4–5% of the human genome is covered with recent duplications, being enriched in pericentromeric and subtelomeric regions of the chromosomes [32–34]. Owing to their high degree of sequence identity, a large number of mutational events can be inferred with high confidence using only pairwise DNA sequence alignments. Knowing that duplications were once identical during evolution, point mutational events correspond to mismatches in the aligned sequences. This simple approach is thus powerful for detection of a mutational spectrum in recent mammalian evolution. A proper classification of the allelic fate of newly derived alleles in segmental duplications is a different matter, however. An allele created by a point mutation in one duplication copy may be subject to a number of genetic processes that determines its allelic state in duplicated DNA. Allelic drift can take the newly derived allele through a polymorphic state (that is, SNP in a duplication) and further to fixation, in which the new allele and its counterpart in the other duplication copy are termed paralogous sequence variants (PSVs) [29, 35–37]. At the same time, the newly derived allele can be distributed into multiple sequence copies by duplication or gene conversion [38–40]. The latter mechanisms take the initial mutational event into a complex type of sequence variation coined multisite variation (MSV) by Fredman and colleagues . Mutational events in segmental duplications thus result in a mosaic of different genotype patterns. Altogether, data on duplication-inferred mutations generated by our approach both enriches the available pool of known mutational events within recent mammalian evolution and complements the data on disease mutations and SNPs for a contextual DNA sequence analysis of single nucleotide substitutions in humans.
We have developed a computational pipeline for inference of mutational events in segmental duplications in the human genome. The analysis of duplication-inferred mutations (DIMs) was restricted to intergenic regions of duplications, focusing on the mutational spectrum in regions that are believed to be more neutral with respect to selection forces. With the aim of detecting mutational hotspots of DIMs, we conducted a computational analysis of the local DNA sequence context of DIMs. A comparative analysis with a large set of high-quality, intergenic SNPs from dbSNP provides insights into similarities and differences between duplication-inferred variation and ordinary allelic variation in unique regions of the genome. We have also investigated the overlap between reference SNPs in segmental duplications and computationally, duplication-inferred variants. Initial reports concerning the high density of SNPs in duplications suggested that this was due to paralogous variation being misinterpreted as SNPs [28, 36, 37]. A following experimental study of a limited set of SNPs in duplications found that only 23% of the SNPs were consistent with paralogous variation , and that multisite variation appeared to be a common type of variation in these regions. We used a computational, in silico approach for the discovery of positional and allelic overlap between SNPs and DIMs. Our data pinpoints a large number of recorded SNPs in segmental duplications that mimic variation between paralogous sequences, and these may consequently give rise to strange patterns during traditional SNP genotyping.
Distribution of nucleotide substitutions
Substitution frequencies at the CpG dinucleotide context
Non-CpG island: (A/C)G
Non-CpG island: (C/G)G
Non-CpG island: (C/T)G
Non-CpG island: C(A/G)
Non-CpG island: C(C/G)
Non-CpG island: C(G/T
CpG island: (A/C)G
CpG island: (C/G)G
CpG island: (C/T)G
CpG island: C(A/G)
CpG island: C(C/G)
CpG island: C(G/T)
Substitution frequencies at sequence contexts associated with DNA sequencing errors
Sequence contexts of DIMs
We obtained DNA oligomer frequencies at SNPs and DIMs and in their corresponding reference regions to address whether both types of mutations were subject to similar mutational hotspots. Under the assumption that the middle nucleotide of an odd-length oligomer is independent of its surrounding sequence, we computed expected numbers for all oligomers. Finally, we compared the actual number for each oligomer with its expected number, defined as overrepresentation (see Methods).
Overlap between SNPs and DIMs in segmental duplications
Previous analyses of SNPs in segmental duplications have reported an uncertainty about the validity of this particular set of SNPs [28, 36, 37]. The observed SNP enrichment was initially viewed as duplication-induced, representing paralogous rather than allelic variation. More advanced techniques have later shown that the spectrum of sequence variation in duplications appears as a complex combination of PSVs, SNPs in duplications and MSVs . In this work, we have quantified the number of inferred mutational events in segmental duplications that overlap with reference SNPs in segmental duplications.
Fredman et al. conducted an experimental study in which they genotyped predicted SNPs in segmental duplications from fully homozygous genomes of complete hydatidiform moles (CHMs) . They discovered that only 23% gave patterns indicative of PSVs, and 28% behaved differently than SNPs and PSVs, being the sum of individual genotyping signals from similar-sequence duplication copies. They termed the latter category multisite variants (MSV). Among 105 SNPs being targeted in their study, 64 SNPs mapped to the intergenic regions of duplications used in our analysis, of which they experimentally verified 11 as PSVs. We observed all 11 variants among our computationally inferred DIMs. An additional overlap was observed for 25 inferred DIMs that were designated as MSVs by Fredman and colleagues.
An understanding of the contextual patterns of nucleotide substitutions in the vertebrate genome is important for several reasons. The spectrum of mutational events reflect how the genome has been shaped during evolution, the mechanism of substitution mutagenesis, and it can also shed light on fundamental cellular processes such as genome stability, DNA replication and repair.
In this study, we have inferred a large set of point mutations originating within segmental duplications in the human genome. These point mutations were compared with a genome-wide collection of high-quality SNPs to assess whether these two datasets of mutational events show similar patterns in terms of distribution and surrounding sequence contexts. We initially recognized that regions of the genome covered by segmental duplications had a higher GC content than the grand average in non-duplicated regions. A previous study also reported a positive correlation between GC content and segmental duplications . However, the biological interpretation of the strong association between GC content and segmental duplications is not obvious. One part may by attributed to the increased gene density in duplications , as regions containing genes are known to be GC-rich. Biased gene conversion may in addition play a role, a process in which repair of mismatches in heteroduplex recombination intermediates favour the fixation of G and C alleles [42, 43]. Also, duplications are particularly enriched in subtelomeric regions of the chromosomes that are directly linked with GC-rich isochors .
The distribution of nucleotide substitutions observed in segmental duplications displays a pattern that in general is similar to SNPs. Both sets of mutations display an excess of transitional substitutions, a common phenomenon in vertebrate genomes. Among the four different transversions, the greatest difference between SNPs and DIMs were found for C/G substitutions. This finding suggests a potential association between the nucleotide composition of duplications and the frequency of substitutions, given the high GC content found in segmental duplications. Moreover, we observed a notable difference in the overall ratio of transitions to transversions between DIMs and SNPs, and an increased ratio in recently occurring DIMs. These results may reflect the evolutionary time window in which the two sets of substitutions were sampled, as well as differences in nucleotide composition between duplicated and non-duplicated DNA. Substitutions within recent segmental duplications comprise mutational events potentially originating 35–40 million years ago (≥ 90% sequence identity) up until today (100% sequence identity), and will thus include a substitution spectrum beyond the human lineage. SNPs should on the other hand represent point mutational events within the human lineage only, as they represent genetic variation between humans. If one assumes that the rate of transversions and transitions varies over time , one would therefore expect to see stronger long-term effects within the DIM dataset than in the SNP set. Previous studies have shown that the rate of 5mC deamination is limited by local GC content [46, 47]. Thus, the GC richness of segmental duplications may be partly responsible for the fewer observed transitions relative to transversions.
The majority of DNA oligomers at DIM and SNP sites, respectively, displayed similar levels of abundance. This observation implies in essence that the majority of SNPs and DIMs appear to be generated by similar mutational mechanisms. We confirmed the latter in oligomers drawn from reference regions, that is intergenic regions of segmental duplications and intergenic, non-duplicated regions. However, we also discovered that many oligomers that contain substitutions at the CpG dinucleotide are overrepresented at SNPs while underrepresented at DIMs. In the reference regions, these oligomers were less underrepresented in duplications than in nonduplicated regions. As mentioned above, different effects at the CpG dinucleotide may be caused by differences in GC content, which in turn lead to different 5 mC deamination rates. Furthermore, when looking at the total mutational spectrum at the CpG dinucleotide, we observed that the frequency of methylation-related transitions differed significantly in CpG islands and non-island regions (Table 1). Our results henceforth imply that mutational events drawn from paralogous sequences exhibit the same suppression of methylation-dependent deamination in CpG islands as SNPs have been shown to do .
During large-scale computational identification of SNPs, many single nucleotide differences between genomic clones are taken as evidence of allelic variation and submitted to dbSNP. Without proper validation by other means, this form of SNP discovery will inevitably lead to spurious results caused by the duplication content of the human genome [26, 48]. To address this issue, we systematically examined predicted SNP alleles in segmental duplications and mutations inferred from duplication alignments. Our approach revealed that nearly one out of five SNPs in duplications bear resemblance of paralogous sequence variation. Whether these SNPs behave like ordinary SNPs, MSVs or fixed PSVs is yet to be determined. Nonetheless, we suspect that traditional genotyping of the majority of these SNPs will produce misleading allele frequencies and genotype patterns since they will receive additional signals from paralogous sequences. Further, we discovered that SNPs that mirror mutational events in duplications are most prominent in duplications of high (≈97–100%) sequence identity, an observation for which we have no obvious explanation at present. In a comparative analysis with a small set of previously experimentally verified PSVs, we found all designated paralogous sequence variants among our computationally inferred mutations. In addition, we observed an overlap with computationally inferred DIMs and sites that were determined to be MSVs. The type of polymorphisms represented by MSVs involves a variation in duplication copy-number, and presumably indicates that much multisite variation may have originated from point mutational events in paralogous sequences.
Our approach does have some inherent limitations that could affect the reliability of the results obtained. These limitations involve the data source, i.e. detection of segmental duplications and reliability of DNA sequence alignments, the approach for inference of mutational events, and the sample effect. With respect to the source of segmental duplications, we relied on data provided by HGSDB . The detection scheme employed by HGSDB uses BLAST for pairwise comparisons of all assembled chromosomes. Detected duplications will thus depend on the overall quality of the genome assembly, and inferred mutations will rely on correctly determined consensus sequences in the assembly. We reduced some potential assembly (and sequencing) errors by excluding high-copy repeats from the analysis, as assembly programs may fail to distinguish single base differences between repeat copies from erroneous base calls [49, 50]. Since the degree of sequence divergence between duplications in HGSBB are all less than 10%, the resulting alignments are highly significant. Also, we placed restrictions on the alignment window around candidate DIMs to exclude potential alignment artefacts. Altering the alignment restrictions for DIM calling in two other DIM sets did not change the distribution of DIM substitutions to a large extent. In error-prone DNA sequencing contexts we observed a small increase of DIMs relative to high-quality SNPs, suggesting a minor impact of random noise in the DIM set. Altogether, we believe that the sequence alignments did not cause any serious errors.
Computational inference of mutational events leading to DIMs also has limitations. First of all, the directionality of the mutations was not inferred with our approach, i.e. an A→T mutation could not be distinguished from a T→A mutation. Thus, an observed (C/T)G substitution may not necessarily reflect the deamination of a methylated thymine, but rather correspond to a thymine to cytosine transition. A recent study of the directionality of SNPs indicated that most substitutions in intergenic regions have roughly the same amounts of substitutions in either direction . Whether DIMs display the same characteristics is unknown. Secondly, when the same mutational events were found propagated in several duplications (Figure 1B), we excluded them as individual events under the assumption of no multiple substitutions at a single site. This assumption is not likely to be violated in DNA sequences that show as low degree of sequence divergence as recent segmental duplications.
The sample of inferred DIMs were, as mentioned above, retrieved from all human chromosomes in regions where duplications have been found to exist. The total number of DIMs sampled was so large (≈344,000) that we believe they can provide a general pattern of substitutions in segmental duplications. In contrast to unique DNA sequences, duplicated sequences frequently undergo homology-driven mutation when involved in either non-allelic homologous recombination or gene conversion [28, 42]. In the latter process, DNA repair of nucleotide mismatches in heteroduplex DNA intermediates has been shown to be GC-biased, providing a direct link to the GC-richness of duplications . Investigating the relationship between biased repair and the observed distribution of DIMs requires further work, considering that base mispairs are corrected with different efficiencies and specificities in mammals . The inferred point mutational spectrum was restricted to intergenic regions, excluding all DIMs located within RefSeq transcripts. Among all DIMs inferred, we thus omitted nearly 31.5% in our analyzed sample, as they all originated within UTRs, exons and introns residing in segmental duplications. As shown in early studies of molecular evolution, regions under functional constraints (i.e. human transcripts) show different patterns and rates of substitutions from selectively neutral sequences such as pseudogenes [53, 54]. In order to establish a neutral pattern of point mutations in segmental duplications, minimized with the confounding effects of natural selection, we excluded any mutational event in which either of the nucleotides were found inside RefSeq transcripts. Since the point mutational spectrum in coding regions of segmental duplications may display different characteristics than what we found in intergenic regions, we suggest that these nucleotide substitutions should be explored in further work.
Most important, our computational analysis of segmental duplications in the human genome suggests that they can be utilized as a novel data source for the analysis of vertebrate point mutagenesis. There are essentially two different observations that support this claim. First, the distribution and context of computationally inferred DIMs and a set of high-quality set of SNPs in intergenic regions of the genome were largely similar (Figures 3, 5 and 6). Second, we found that a large fraction of the inferred DIMs overlap with verified SNPs, which provides evidence that our inference strategy is able to retrieve actual mutational events that lead to genetic variation. Moreover, our inferred set of nucleotide substitutions originates from regions in all human chromosomes, as segmental duplications are not restricted to any particular chromosome, but rather distributed in a genome-wide fashion. We believe that the inferred dataset of point mutations may be a valuable complement to SNPs for the analysis of human genetic variation.
Segmental duplication data
The Human Genome Segmental Duplication Database (HGSDB, http://projects.tcag.ca/humandup) has been reported to contain chromosomal coordinates of all segmental duplications (length ≥ 5 kb and sequence identity ≥ 90%) in the human genome, based on a computational detection scheme . In total, 12589 unique pairwise sequence alignments of duplication copies were downloaded from HGSDB (build hg17). The two sequences in any pairwise sequence alignment of duplications were denoted as source and target sequences. 6587 alignments had both source and target sequences located on the same chromosome (intrachromosomal duplications), the remaining 6002 alignments had their duplication copies on nonhomologous chromosomes (interchromosomal duplications). Several regions were involved in both inter- and intrachromosomal duplications. The average alignment length was approximately 20.5 kb. The total nonredundant content of recent segmental duplications was found to be 133.9 Mb, comprising 4.7% of the non-gap length (2851.3 Mb) of the human genome. Chromosomal coordinates of RefSeq transcripts and CpG islands annotated to hg17 were downloaded as flat files from the UCSC genome browser http://genome.ucsc.edu and mapped to segmental duplications from HGSDB. High-copy repeats in segmental duplications were identified as lower-case nucleotides (output from RepeatMasker) within alignments downloaded from HGSDB.
Inference of mutational events in segmental duplications
Mutational events were inferred using DNA sequence alignments from HGSDB only. Figure 1A illustrates the basic inference principle. Since no other mammalian genome was used in our analysis, we did not attempt to infer the directionality of the mutational events or separate events that originated within different vertebrate lineages. We merely inferred that mutational events had occurred since the duplication event took place. Two other factors related to the nature of segmental duplications had further impact on how DIMs were recorded (see Figure 1B). We wrote software for the traversal of pairwise DNA sequence alignments and recording of all mutational events along with their neighbouring sequence context (total entries n = 800,649). The dataset was reduced by excluding DIMs occurring in RefSeq transcripts as well as high-copy repeats as masked by RepeatMasker (n = 548,088). An alignment window of length 40 around each candidate DIM was extracted. To ensure that inferred DIMs were results of actual point mutational events rather than alignment artefacts, we only kept DIMs where the 40 bp alignment window satisfied the following criteria: (1) maximum four mismatches, (2) maximum two gaps (indels) and (3) no mismatches in the three immediate positions upstream and downstream of the candidate DIM site. With these criteria, the total number of intergenic inferred DIMs was 343,864. To test whether these alignment criteria induced any bias in the distribution of DIM types, we established two control sets in which DIMs were inferred in a stricter manner. In the first control set, we required a minimum of seven non-variant bases upstream and downstream of the candidate DIM site (258,612 DIMs), and in the second control set we increased this number to fifteen (108,117 DIMs).
To ensure that substitutions were sampled consistently across alignments with different sequence identity, we calculated the overall transition to transversion ratio for DIMs as a weighted sum of ten different bin ratios. DIMs were initially put in ten bins according to the sequence alignment identity in which they originated (i.e. 90 to 100), and a ratio for each bin was calculated without weighting. Each bin was then assigned a weight, representing the expected fraction of all substitutions that originated from alignments in the given bin. The expected number of substitutions in an alignment was estimated as alignment length multiplied by the fraction of nonidentical bases (the expected number in a bin was found by summing over all bin alignments).
The human dbSNP database (build 126) was downloaded as XML files and parsed with Perl scripts for retrieval of biallelic RefSNP entries (reference SNPs). We established two different sets of SNP data. The first set contained a high-quality set of SNPs in non-duplicated regions of the genome, used for a comparative sequence context analysis with DIMs. The second set contained all reference SNPs in segmental duplications.
In the high-quality set of SNPs, we decided to only keep entries that were validated within the HapMap project . We excluded all ambiguously mapped SNPs, that is, polymorphic sites where the flanking sequences did not map to a unique region in the genome with an alignment identity of at least 99% (total entries n = 2,160,150). The fraction of SNPs where allele frequencies in none of the four HapMap populations satisfied the basic SNP definition, that is, minor allele frequency ≥ 1%, were also omitted (as these may not mirror true SNP sites). The number of SNPs was further reduced by excluding SNPs that mapped within RefSeq transcripts (n = 1,337,235), SNPs where the flanking sequence (100 bp) fell inside high-copy repeats as masked by RepeatMasker (n = 1,131,893), and finally SNPs inside segmental duplications (n = 1,115,692).
A second set of SNPs was established by fetching all reference SNPs located within intergenic regions of segmental duplications, both validated and nonvalidated (n = 458,811). A SNP was classified as nonvalidated within dbSNP if it did not satisfy any of the following criteria: 1) allele frequencies in a given population, 2) multiple independent submissions, or 3) both alleles seen in at least two chromosomes. An overlap between a SNP and a DIM was considered valid if the chromosomal position of the SNP matched either the source or the target position associated with the DIM, and that the alleles at the SNP and DIM site matched (either directly or in a complementary manner if the SNP and DIM were recorded on different strands).
Sequence context of nucleotide substitutions
We determined whether similar mutational mechanisms act upon segmental duplications as in non-duplicated genomic regions by quantifying the frequencies of DNA oligomers at DIMs and high-quality SNPs. For comparison, we counted reference oligomer frequencies in the surrounding regions of DIMs (intergenic, duplicated DNA) and SNPs (intergenic, non-duplicated DNA).
Let uxv represent a k-mer where x is the middle nucleotide and u and v are surrounding nucleotides, and u[xy]v represent a k-mer where the middle nucleotide is a substitution pair x/y. Let n(uxv) count the number of k-mers that are either uxv or its reverse complement, and define n(u[xy]v) similarly. We count SNPs and DIMs separately.
The nucleotide and substitution pair probabilities are p(x) = n(x)/n and p([xy]) = n([xy])/n for reference region and substitution respectively, with n the corresponding total number of nucleotides. Note that by this definition f.ex. p(A) = p(T) is the probability of any nucleotide being either A or T, each with a 1/2 probability of being on either strand. If the middle nucleotide, x or [xy], is independent of the surrounding nucleotides, the expected numbers in the reference regions are
μ(uxv) = n(u*v)·p(x)/2
where n(u*v) is the sum of all n(uxv) for different x, and the division by two is because there is a 1/2 chance that x is on the same strand as u*v. For substitutions,
μ(u[xy]v) = n(u[**]v)·p(xy)/2
except that if either [xy] or u*v are their own reverse complements one should not divide by 2. The overrepresentation (or abundance) is defined as R(uxv) = n(uxv)/μ(uxv), and R(u[x*]v) = n(u[x*]v)/μ(u[x*]v) where u[x*]v indicates the sum over all matching u[xy]v for n and μ.
We thank various people (Razi Khaja, Jeff MacDonald and Dr. Steven W. Scherer) working at the Centre for Applied Genomics in Toronto for assistance with data from the Human Genome Segmental Duplication Database . We also wish to thank Dr. Anthony J. Brookes and Dr. Evan E. Eichler for providing the rsIDs of SNPs analyzed in their study of sequence variation in segmental duplications .
- Gartenberg MR, Crothers DM: DNA sequence determinants of CAP-induced bending and protein binding affinity. Nature. 1988, 333 (6176): 824-829.View ArticlePubMedGoogle Scholar
- Sims J, Rabbitts TH, Estess P, Slaughter C, Tucker PW, Capra JD: Somatic mutation in genes for the variable portion of the immunoglobulin heavy chain. Science. 1982, 216 (4543): 309-311.View ArticlePubMedGoogle Scholar
- Krawczak 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 (2): 474-488.PubMed CentralView ArticlePubMedGoogle Scholar
- Thilly WG: Have environmental mutagens caused oncomutations in people?. Nat Genet. 2003, 34 (3): 255-259.View ArticlePubMedGoogle Scholar
- Aquilina G, Bignami M: Mismatch repair in correction of replication errors and processing of DNA damage. J Cell Physiol. 2001, 187 (2): 145-154.View ArticlePubMedGoogle Scholar
- Ehrlich M, Wang RY: 5-Methylcytosine in eukaryotic DNA. Science. 1981, 212 (4501): 1350-1357.View ArticlePubMedGoogle Scholar
- Kunkel TA: Misalignment-mediated DNA synthesis errors. Biochemistry. 1990, 29 (35): 8003-8011.View ArticlePubMedGoogle Scholar
- Kunkel TA, Loeb LA: Fidelity of mammalian DNA polymerases. Science. 1981, 213 (4509): 765-767.View ArticlePubMedGoogle Scholar
- Lindahl T, Nyberg B: Heat-induced deamination of cytosine residues in deoxyribonucleic acid. Biochemistry. 1974, 13 (16): 3405-3410.View ArticlePubMedGoogle Scholar
- Blake RD, Hess ST, Nicholson-Tuell J: The influence of nearest neighbors on the rate and pattern of spontaneous point mutations. J Mol Evol. 1992, 34 (3): 189-200.View ArticlePubMedGoogle Scholar
- Jiang C, Zhao Z: Mutational spectrum in the recent human genome inferred by single nucleotide polymorphisms. Genomics. 2006, 88 (5): 527-534.View ArticlePubMedGoogle Scholar
- Zhao Z: Neighboring-Nucleotide Effects on Single Nucleotide Polymorphisms: A Study of 2.6 Million Polymorphisms Across the Human Genome. Genome Res. 2002, 12 (11): 1679-1686.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhao Z, Zhang F: Sequence context analysis of 8.2 million single nucleotide polymorphisms in the human genome. Gene. 2006, 366 (2): 316-324.View ArticlePubMedGoogle Scholar
- Cooper DN, Youssoufian H: The CpG dinucleotide and human genetic disease. Hum Genet. 1988, 78 (2): 151-155.View ArticlePubMedGoogle Scholar
- Tomso DJ, Bell DA: Sequence context at human single nucleotide polymorphisms: overrepresentation of CpG dinucleotide at polymorphic sites and suppression of variation in CpG islands. J Mol Biol. 2003, 327 (2): 303-308.View ArticlePubMedGoogle Scholar
- Bird AP: DNA methylation and the frequency of CpG in animal DNA. Nucleic Acids Res. 1980, 8 (7): 1499-1504.PubMed CentralView ArticlePubMedGoogle Scholar
- Cooper DN, Krawczak M: Cytosine methylation and the fate of CpG dinucleotides in vertebrate genomes. Hum Genet. 1989, 83 (2): 181-188.View ArticlePubMedGoogle Scholar
- Duret L, Galtier N: The covariation between TpA deficiency, CpG deficiency, and G+C content of human isochores is due to a mathematical artifact. Mol Biol Evol. 2000, 17 (11): 1620-1625.View ArticlePubMedGoogle Scholar
- Jabbari K, Bernardi G: Cytosine methylation and CpG, TpG (CpA) and TpA frequencies. Gene. 2004, 333: 143-149.View ArticlePubMedGoogle Scholar
- Simmen MW: Genome-scale relationships between cytosine methylation and dinucleotide abundances in animals. Genomics. 2008, 92 (1): 33-40.View ArticlePubMedGoogle Scholar
- Sved J, Bird A: The expected equilibrium of the CpG dinucleotide in vertebrate genomes under a mutation model. Proc Natl Acad Sci USA. 1990, 87 (12): 4692-4696.PubMed CentralView ArticlePubMedGoogle Scholar
- Karlin S, Doerfler W, Cardon LR: Why is CpG suppressed in the genomes of virtually all small eukaryotic viruses but not in those of large eukaryotic viruses?. J Virol. 1994, 68 (5): 2889-2897.PubMed CentralPubMedGoogle Scholar
- Pfeifer GP: Mutagenesis at methylated CpG sequences. Curr Top Microbiol Immunol. 2006, 301: 259-281.PubMedGoogle Scholar
- Shackelton LA, Parrish CR, Holmes EC: Evolutionary basis of codon usage and nucleotide composition bias in vertebrate DNA viruses. J Mol Evol. 2006, 62 (5): 551-563.View ArticlePubMedGoogle Scholar
- Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001, 29 (1): 308-311.PubMed CentralView ArticlePubMedGoogle Scholar
- Nelson MR, Marnellos G, Kammerer S, Hoyal CR, Shi MM, Cantor CR, Braun A: Large-scale validation of single nucleotide polymorphisms in gene regions. Genome Res. 2004, 14 (8): 1664-1668.PubMed CentralView ArticlePubMedGoogle Scholar
- Platzer M, Hiller M, Szafranski K, Jahn N, Hampe J, Schreiber S, Backofen R, Huse K: Sequencing errors or SNPs at splice-acceptor guanines in dbSNP?. Nat Biotechnol. 2006, 24 (9): 1068-1070.View ArticlePubMedGoogle Scholar
- Bailey JA, Gu Z, Clark RA, Reinert K, Samonte RV, Schwartz S, Adams MD, Myers EW, Li PW, Eichler EE: Recent segmental duplications in the human genome. Science. 2002, 297 (5583): 1003-1007.View ArticlePubMedGoogle Scholar
- Bailey JA, Yavor AM, Massa HF, Trask BJ, Eichler EE: Segmental duplications: organization and impact within the current human genome project assembly. Genome Res. 2001, 11 (6): 1005-1017.PubMed CentralView ArticlePubMedGoogle Scholar
- Eichler EE: Recent duplication, domain accretion and the dynamic mutation of the human genome. Trends Genet. 2001, 17 (11): 661-669.View ArticlePubMedGoogle Scholar
- Samonte RV, Eichler EE: Segmental duplications and the evolution of the primate genome. Nat Rev Genet. 2002, 3 (1): 65-72.View ArticlePubMedGoogle Scholar
- Linardopoulou EV, Williams EM, Fan Y, Friedman C, Young JM, Trask BJ: Human subtelomeres are hot spots of interchromosomal recombination and segmental duplication. Nature. 2005, 437 (7055): 94-100.PubMed CentralView ArticlePubMedGoogle Scholar
- She X, Jiang Z, Clark RA, Liu G, Cheng Z, Tuzun E, Church DM, Sutton G, Halpern AL, Eichler EE: Shotgun sequence assembly and recent segmental duplications within the human genome. Nature. 2004, 431 (7011): 927-930.View ArticlePubMedGoogle Scholar
- Zhang L, Lu HH, Chung WY, Yang J, Li WH: Patterns of segmental duplication in the human genome. Mol Biol Evol. 2005, 22 (1): 135-141.View ArticlePubMedGoogle Scholar
- Bailey JA, Eichler EE: Primate segmental duplications: crucibles of evolution, diversity and disease. Nat Rev Genet. 2006, 7 (7): 552-564.View ArticlePubMedGoogle Scholar
- Cheung J, Estivill X, Khaja R, MacDonald JR, Lau K, Tsui LC, Scherer SW: Genome-wide detection of segmental duplications and potential assembly errors in the human genome sequence. Genome Biol. 2003, 4 (4): R25-PubMed CentralView ArticlePubMedGoogle Scholar
- Estivill X, Cheung J, Pujana MA, Nakabayashi K, Scherer SW, Tsui LC: Chromosomal regions containing high-density and ambiguously mapped putative single nucleotide polymorphisms (SNPs) correlate with segmental duplications in the human genome. Hum Mol Genet. 2002, 11 (17): 1987-1995.View ArticlePubMedGoogle Scholar
- Bosch E, Hurles ME, Navarro A, Jobling MA: Dynamics of a human interparalog gene conversion hotspot. Genome Res. 2004, 14 (5): 835-844.PubMed CentralView ArticlePubMedGoogle Scholar
- Hurles ME: Gene conversion homogenizes the CMT1A paralogous repeats. BMC Genomics. 2001, 2 (1): 11-PubMed CentralView ArticlePubMedGoogle Scholar
- Rozen S, Skaletsky H, Marszalek JD, Minx PJ, Cordum HS, Waterston RH, Wilson RK, Page DC: Abundant gene conversion between arms of palindromes in human and ape Y chromosomes. Nature. 2003, 423 (6942): 873-876.View ArticlePubMedGoogle Scholar
- Fredman D, White SJ, Potter S, Eichler EE, Den Dunnen JT, Brookes AJ: Complex SNP-related sequence variation in segmental genome duplications. Nat Genet. 2004, 36 (8): 861-866.View ArticlePubMedGoogle Scholar
- Chen JM, Cooper DN, Chuzhanova NA, Férec C, Patrinos GP: Gene conversion: mechanisms, evolution and human disease. Nat Rev Genet. 2007, 8 (10): 762-775.View ArticlePubMedGoogle Scholar
- Galtier N: Gene conversion drives GC content evolution in mammalian histones. Trends Genet. 2003, 19 (2): 65-68.View ArticlePubMedGoogle Scholar
- Costantini M: An isochore map of human chromosomes. Genome Res. 2006, 16 (4): 536-541.PubMed CentralView ArticlePubMedGoogle Scholar
- Kimura M: A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980, 16 (2): 111-120.View ArticlePubMedGoogle Scholar
- Fryxell KJ, Moon W: CpG mutation rates in the human genome are highly dependent on local GC content. Mol Biol Evol. 2005, 22 (3): 650-658.View ArticlePubMedGoogle Scholar
- Zhao Z, Jiang C: Methylation-dependent transition rates are dependent on local sequence lengths and genomic regions. Mol Biol Evol. 2007, 24 (1): 23-25.View ArticlePubMedGoogle Scholar
- Reich DE, Gabriel SB, Altshuler DA: Quality and completeness of SNP databases. Nat Genet. 2003, 33 (4): 457-458.View ArticlePubMedGoogle Scholar
- Batzoglou S, Jaffe D, Stanley K, Butler J, Gnerre S, Mauceli E, Berger B, Mesirov JP, Lander E: ARACHNE: a whole-genome shotgun assembler. Genome Res. 2002, 12 (1): 177-189.PubMed CentralView ArticlePubMedGoogle Scholar
- Tammi MT, Arner E, Kindlund E, Andersson B: Correcting errors in shotgun sequences. Nucleic Acids Res. 2003, 31 (15): 4663-4672.PubMed CentralView ArticlePubMedGoogle Scholar
- Marais G: Biased gene conversion: implications for genome and sex evolution. Trends Genet. 2003, 19 (6): 330-338.View ArticlePubMedGoogle Scholar
- Brown TC, Jiricny J: Different base/base mispairs are corrected with different efficiencies and specificities in monkey kidney cells. Cell. 1988, 54 (5): 705-711.View ArticlePubMedGoogle Scholar
- Gojobori T, Li WH, Graur D: Patterns of nucleotide substitution in pseudogenes and functional genes. J Mol Evol. 1982, 18 (5): 360-369.View ArticlePubMedGoogle Scholar
- Imanishi T, Gojobori T: Patterns of nucleotide substitutions inferred from the phylogenies of the class I major histocompatibility complex genes. J Mol Evol. 1992, 35 (3): 196-204.View ArticlePubMedGoogle Scholar
- The International HapMap Consortium: The International HapMap Project. Nature. 2003, 426 (6968): 789-796.View ArticleGoogle Scholar
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