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The Journal of Immunology, 2005, 175: 5170-5177.
Copyright © 2005 by The American Association of Immunologists

Hypermutation at A-T Base Pairs: The A Nucleotide Replacement Spectrum Is Affected by Adjacent Nucleotides and There Is No Reverse Complementarity of Sequences Flanking Mutated A and T Nucleotides1,2

Jo Spencer and Deborah K. Dunn-Walters3

Department of Immunobiology, King’s College London School of Medicine at Guy’s, King’s and St. Thomas’ Hospitals, Guy’s Campus, London, United Kingdom


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
Hypermutation is thought to be a two-phase process. The first phase is via the action of activation-induced cytidine deaminase (AID), which deaminates C nucleotides in WRC motifs. This results in the RGYW/WRCY hot spot motifs for mutation from G and C observed in vivo. The resemblance between the hot spot for C mutations and the reverse complement of that for G mutations implies a process acting equally on both strands of DNA. The second phase of hypermutation generates mutations from A and T and exhibits strand bias, with more mutations from A than T. Although this does not concur with the idea of one mechanism acting equally on both strands, it has been suggested that the AT mutator also has a reversible motif; WA/TW. We show here that the motifs surrounding the different substitutions from A vary significantly; there is no single targeting motif for all A mutations. Sequence preferences associated with mutations from A more likely reflect an influence of adjacent nucleotides over what the A mutates "to." This influence tends toward "like" replacements: Purines (A or G) in the 5' position bias toward replacement by another purine (G), whereas replacement with pyrimidines (C or T) is more likely if the preceding base is also a pyrimidine. There is no reverse complementarity in these observations, in that similar influences of nucleotides adjacent to T are not seen. Hence, WA and TW should not be considered as reverse complement hot spot motifs for A and T mutations.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Disclosures
 References
 
The generation of a diverse Ig repertoire is initiated at the IgH locus by recombination of V, D, and J gene segments. If recombination is unsuccessful on the first allele of IGH, rearrangement at the second allele is initiated. If this is successful, V and J segments rearrange at the Ig L chain loci on each allele in turn, until a successful rearrangement is achieved. As a consequence of this process, some B cells carry out-of-frame Ig gene rearrangements. A second wave of diversification of IG genes is generated by somatic hypermutation (SHM)4 in the germinal centres of B cell follicles. SHM is characterized by predominantly single base substitutions and results in a characteristic spectrum of mutations (1, 2, 3). Functional IG genes diversified by SHM are selected based on the affinity of the newly encoded Ig for Ag. Thus the mutations observed in the functional genes are a result of both SHM and selection. Any out-of-frame IG gene rearrangements within the same cell also undergo SHM but, because these genes are not expressed, the distribution of mutations is unaffected by the selection process. These genes are therefore of use in the study of the mechanism of hypermutation.

Analysis of the sequence context of mutations in out-of-frame Ig genes has proved a powerful tool enabling several accurate deductions concerning the mechanism of SHM. Differences in the characteristics of sequences flanking mutations from G and C nucleotides and those flanking A and T nucleotides implied separate mechanisms for G/C mutations and A/T mutations (4). Moreover, the remarkable resemblance between the flanking sequence surrounding mutations from G and the reverse complement of flanking sequence surrounding mutation from C lead us to suggest that either G or C nucleotides were likely to be mutated and not both (5). Both of these predictions have now been confirmed because considerable progress in the understanding of the SHM process has been made. The current, broadly accepted, hypothesis is that SHM is a two-step process (6). The initiating event is via the action of activation-induced cytidine deaminase (AID), which is both necessary and sufficient for SHM, class switching and gene conversion (7). AID can directly deaminate C nucleotides in DNA, targeting deamination events to C nucleotides in WRC motifs (8, 9). This results in the in vivo observations of the RGYW/WRCY hot spot motifs for mutations from G and C. The second step of SHM involves error prone repair enzymes and generates further mutations, most notably those from A and T.

Mismatched U-G base pairs caused by cytosine deamination can be repaired either by base excision repair (BER) or by mismatch repair (MMR). Both are excision repair processes that require resynthesis of excised nucleotides by polymerases—especially for long patch repair. Evidence for the involvement of BER and MMR is strong, both processes have been shown to affect the SHM spectrum if altered. In the case of BER, Uracil N-glycosylase (UNG) is the key first step in removing mispaired uracil. The absence of UNG (either in mice, in cultured B cells, or in hyper-IgM syndrome type 4 patients) causes a skewing in the pattern of SHM so that more transitions at G:C pairs are seen, but the pattern of A and T mutations appears normal (10, 11). The evidence for the involvement of MMR derives from observations of deficiencies in the mismatch repair process. Deletions of mismatch repair proteins MSH2 or MSH6 also causes skewing of the pattern of SHM—in this case to exclude mutations from A and T (3). Similarly a deficiency in exonuclease 1, another component of the MMR process, can result in a reduction in the number of mutations from A and T in Ig genes (12). Recent experiments combining deficiency of both UNG and MSH2 showed an ablation of all mutations except transitions at G:C pairs (13). The error prone polymerase that appears to be the most important for the secondary phase of SHM is DNA polymerase {eta} (Pol{eta}). Pol{eta} is absent in patients with XP-V, and these patients have a reduced (but not completely absent) number of mutations from A and T in their Ig genes (14, 15). Further in vitro analysis of the Pol{eta} error spectrum reports that it shares many features with the SHM spectrum found in vivo (16, 17, 18). However, other error prone polymerases such as Pol{zeta} (19, 20), Pol{iota} (21), and Polµ (22, 23) may also be involved.

Targeting of mutations to certain areas of the IGHV sequence is biologically important because mutations are advantageous predominantly when they modify the hypervariable regions. However, because the mechanisms that mutate G/C and A/T are not the same, the mechanisms that target mutations to the hypervariable regions are not likely to be the same either. Unlike the RGYW/WRCY motifs, which reflect target preferences of the AID complex (8, 9), the significance of the motifs that appear to focus mutations to A/T nucleotides is unknown. The issue of whether both processes act on one strand or two has still not been completely resolved. There is no strand bias in G vs C mutations in most studies. In contrast, the AT mutator consistently shows strand bias in that there are always more mutations from A than mutations from T. The lack of strand bias in GC mutations, coupled with the fact that the RGYW/WRCY motifs are reverse complements of each other, shows that the GC mutator likely involves one mechanism that acts on both strands of DNA (5, 24). Strand bias in AT mutations indicates a possible preference for the action of the mutator for one strand over the other, or the existence of separate mutators for A and T mutations. The hot spot for mutations from A is generally accepted as being WA (17). Evidence that mutation occurs by the same mechanism on both strands of DNA would be that mutations from T occur in the reverse complement hot spot TW. This has been found in some cases, and has been used as a predictor of mutations from T (25). However, we have previously shown that the hot spot motifs for mutations from A and T vary depending whether the mutations are transitions or transversions (4) and these are not necessarily reverse complement.

To analyze influences on AT mutations we have analyzed the hot spot motifs around each individual mutation (A-C, A-G, A-T, T-A, T-C, T-G). This analysis has been done in out of frame Ig sequences to exclude any effects of selection. We show that WA is not a target motif for all mutations from A and that adjacent nucleotides bias the nature of replacements from A. Furthermore there are qualitative, as well as quantitative, aspects to strand bias. These results have been confirmed in mouse JH intronic sequences.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Disclosures
 References
 
Two different sets of data were used in the primary analysis. Both were of Ig gene rearrangements that were nonproductive due to their V and J regions being in different reading frames. These genes had, however, been isolated from postgerminal centre cells and therefore these nonproductive rearrangements carried mutations. The advantage of using such data is that the mutations have accumulated without any possible confounding effects of selection. One set of data was of H chain VH-DH-JH rearrangements (4) and the other was of {lambda} L chain VL-JL rearrangements (24). The genes were arranged according to their IGV gene usage. Eight groups of H chain genes were collated, containing a total of 55 sequences with 732 mutations from the germline IGHV sequence. Six groups of L chain genes were collated, containing a total of 25 sequences with 548 mutations from the germline IGLV sequence (3). In addition, mutated sequences from four additional sources were analyzed: 750 mutations from a 580-bp region of the mouse JH intron (13), 296 mutations from a 320-bp region of the human JH intron in patients with XPV (26), 282 mutations from a 560-bp region of the Sµ switch region in a Pol{eta} –/– mouse (27), and 2324 mutations from the V{kappa}Ox1 transgene mutated in vivo (916 mutations) or in vitro (1408 mutations) (18).

The mutated sequences were aligned beneath the appropriate germline sequence and a raw text file of the alignment created. This file was imported into a Microsoft Excel spreadsheet and computations of the number of each type of nucleotide substitution (e.g., A to T, A to C, A to G, etc.) and the composition of the flanking sequences around these substitutions were performed using macros in Excel (Visual Basic). Calculations were extended to 6 bases either side of the mutated base.

Because the chances of seeing a particular base in each position are not always 25%, and there are differences in the germline genes of individual sequences, the composition of each germline gene used in the analysis was determined in terms of the percentage composition of bases at each position around each separate base (A, C, G, T). The individual compositions for each IGV gene were compiled into two sets of baseline data for H and L chain genes, the resulting compositions being the outcome from an analysis of 15,003 and 7,740 bases of sequence respectively. For example, the percentage composition at position –1 from an A in the H chain IGHV genes used in this analysis was 17% A, 34% C, 32% G, and 17% T as compared with the same composition in L chain IGLV genes of 14% A, 41% C, 27% G, and 18% T.

The percentage composition of each base at each position flanking a particular mutation was determined. The baseline percentage composition of the germline sequences was subtracted from this to show any differences particular to that mutation. {chi}2 analysis was used to determine whether any differences seen were significant. Computations of percentage differences and {chi}2 analysis were also performed using Excel.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Disclosures
 References
 
Different motifs favor individual mutations from A and T

1251 nucleotide substitutions in out of frame Ig rearrangements were analyzed, including 727 from IGVH, and 524 from IGVL. Consistent with all previous studies, significant strand bias in mutations from A and T was observed in IGVH and IGVL sequences (Fig. 1). Because the two different data sets revealed very similar mutation spectra the data were pooled for further analyses. We determined how the sequence flanking A and T nucleotides influenced the probability of their mutation by analysis of the bases favored (or not) in positions surrounding a mutated A or T, after correction for the natural bias present in the germline sequence. The strongest, and most consistent, influences on A and T mutations were from the bases in positions –1 and +1. This analysis is presented in graphs that show whether a particular base is over- or underrepresented (compared with the germline sequence) in these positions around a mutated A or T.



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  		FIGURE 1. Hypermutation spectra. The spectra of mutations, as percentage of total mutations, is shown for each of two different data sets. H chain Ig genes (a) and L chain Ig genes (b).

 
The motifs thus determined for all mutations from A or T appear to be the reverse complement of each other, as illustrated in Fig. 2. Having a T before a mutated A, or an A after a mutated T, are consistent positive influences on whether A and T are mutated. However, this reverse complementarity did not always hold true when individual substitutions from A and T were analyzed separately. Although the motifs around the different substitutions from T were very similar, those around mutations from the different substitutions from A showed significant differences (Fig. 3). Looking at the flanking bases with a positive influence on mutation from A, the motifs are: TAC for transversions from A to C, TAT for transversions from A to T, and AAT for transitions from A to G (where the mutated base is underlined). Looking at the flanking bases with a negative influence on a particular mutation, a G in position –1 from an A has a negative influence on the transversions (A-C and A-T), the influence being much stronger for the A-T mutations. A transitions (A-G) are negatively influenced by a C in position –1, as are the A-C transversions, but this is not apparent in the A-T transversions (Fig. 3).



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  		FIGURE 2. Reversibility of A-N and T-N hypermutation motifs. Base preferences at positions –1 (5' side) to +1 (3' side) around mutations from A and T (a and b). In each case, the motif for one mutation is shown above the reverse complement of the motif for the matching mutation, i.e., the T-N motif is shown in the opposite direction (3' to 5') with the complementary bases (A is read as T, C is read as G, etc.) as c underneath the A-N motif in a. Similarly, the reverse complement of the motif for A-N (d) is compared with the T-N motif (b). The bars represent the percentage difference between the base composition around the mutation compared with the normal germline base composition The levels of significance after {chi}2 test are indicated by the shading of the bars: {cjs2108}, p < 0.05; {cjs2113}, p < 0.005; and {blacksquare}, p < 0.0005. Where the percentage difference is significant this represents a positive or negative influence of that base in that position over the mutation in question. For example, T and A in position –1 both have a significant positive influence on an A-N mutation, while G and C both have a significant negative influence at this position. In position +1 there is no significant effect of A or C, but G has a negative influence and T has a positive influence. Overall this results in a WAT motif for the A-N mutation (where W is A or T and N is any nucleotide).

 


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  		FIGURE 3. Hypermutation motifs around individual mutations from A and T. Base preferences at positions –1 to + 1 around mutations from A and T. The bars represent the percentage difference between the base composition around the mutation compared with the normal germline base composition. The levels of significance after {chi}2 test are indicated by the shading of the bars: ({cjs2108}), p < 0.05, ({cjs2089}), p < 0.005, and ({blacksquare}), p < 0.0005.

 
Adjacent bases influence the spectrum of replacements from A

The data in Fig. 3 are inconsistent with the notion that the flanking sequences associated with mutations from A are ‘target’ motifs, because a targeting motif would result in some aspect being common to all three different motifs for mutations from A and this is not the case. We therefore considered the possibility that what is perceived to be a motif is in reality a consequence of the influence of adjacent bases on either the replacement spectra, or the probability of subsequent fixing of mutation or repair. The analysis used in generating Figs. 2 and 3, in common with other analyses of hypermutation motifs (4, 5, 28, 29) corrects for the germline composition of the Ig genes in question. To view the influence of adjacent bases on nucleotide replacements directly, we looked at the numbers of each substitution without correcting for germline composition. Fig. 4 shows the nucleotide replacement spectrum when A or T are flanked by different nucleotides in either the 5' or the 3' positions.



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  		FIGURE 4. Influence of neighboring bases on hypermutation. Base composition of the 5' and 3' positions for each of the three different types of mutation: Transition ({cjs2108}), complement ({blacksquare}), and transition complement ({square}). In the case of a and b, transition = A-G, complement = A-T, and transition complement = A-C. In the case of c and d, transition = T-C, complement = T-A, and transition complement = T-G. The germline distribution of bases adjacent to A for this data is also shown (e and f). Significant differences from the average distribution of all mutations in these data (50.2% transitions, 30.9% complements, and 18.9% transition complements) are indicated as follows: *, p < 0.05; **, p < 0.005; and ***, p < 0.0005.

 
There are significant differences in the proportions of transition (e.g., A-G or T-C), complement (e.g., A-T or T-A), or transition complement (e.g., A-C or T-G) mutations depending on the base in the 5' or 3' position from the mutations. Because the normal distribution of transition, complement and transition complement mutations in mutated Ig genes is not equal we used the average percentage distribution from all mutations (50.2, 30.9, and 18.9%, respectively) as the expected values for comparison. The significant changes from these expected values are indicated in Fig. 4.

Strikingly, the normal transition bias observed when all replacements are pooled is not seen when A is preceded by a T, and the number of transition complements is significantly increased. Hence, in this sequence context the replacement of A with C, G or T occurs with approximately equal frequency. The presence of a C in the 3' position has a similar effect. An A or a G in the 5' position predisposes the replacements toward transitional (A-G) mutations. The 5' G also prejudices against complement (A-T) mutations, while a C in the 5' position favors them. There are no such changes in the spectra of T mutations, the only point of change that is significantly different from the normal is that a T in the 5' position from a T prejudices against transition complement mutations (T-G).

Microsequence effects around mutations from A and T are not reverse complements of each other

Reverse complementarity of motifs around complementary mutations can indicate targeting of one base on both strands of DNA. The data presented in Fig. 4 above shows quite clearly that there are significant effects of the bases immediately flanking mutations from A which are not seen for those around T. If the effect were due to the same mechanism acting on both strands of DNA, then one would expect the effects seen at the 5' side of A mutations (Fig. 4a) to be mirrored at the 3' side of T mutations (Fig. 4d), this is not the case. Moreover, when the individual motifs for the different mutations from A are considered alongside the reverse complement motifs for their corresponding reverse complement mutation it can be seen that there are more points that differ than there are that match (Fig. 5).



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  		FIGURE 5. Nonreversibility of hypermutation motifs for A and T transitions. Base preferences at positions –1 to +1 around A-C, A-G, and A-T mutations compared with the reverse complement of the corresponding T-A, T-C, and T-A motifs, respectively. The bars represent the percentage difference between the base composition around each mutation, compared with the normal germline base composition. The levels of significance after {chi}2 test are indicated by the shading of the bars: {cjs2108}, p < 0.05; {cjs2113}, p < 0.005; and {blacksquare}, p < 0.0005.

 
Comparison with mutations from the mouse JH intronic sequence

Human out-of-frame IGV gene data has the advantage that it is made up of 14 different IGHV and IGLV genes so that the chances of bias arising from multiple copies of a single gene are less. However, because IG genes have been selected through evolution alongside the hypermutation mechanisms they have characteristics that may cause perceived biases compared with non-Ig gene sequences. Data are available from the mouse JH intronic region (13) and we have analyzed this with respect to the two key findings in this paper. First, with respect to the effect of the preceding base on the type of mutation that occurs, our results show that an A in the position immediately preceding the mutated A causes a bias toward transition mutations, whereas a T in this position causes a bias toward transversions (Fig. 4a). We found that this was also true in a database of 750 mutations measured in the JH intronic region of the mouse (of which 280 mutations were from A) and in 916 mutations measured in a VkOx1 transgene (of which 298 mutations were from A). In both cases the ratio of transitions to transversions was >1 in the motif AA and <1 in the motif TA (Table I). Second, with respect to the nonreversibility of complementary mutations, the reverse complements of motifs for mutations at T are not the same as the motifs for A (Fig. 5). The effect of 5' T on the types of mutation that occur from A is not mirrored by the effect of A in the 3' position from a T (Fig. 4a compared with Fig. 4d). This is also illustrated in Fig. 6a, showing the distribution of the different types of mutation from A in the TA motif compared with the reverse complement situation—the distribution of the different types of mutation from T in the TA motif. Mutations in the TA motifs of the mouse JH intronic sequences (Fig. 6b) have the same trend of nonreversibility for transition (A-G vs T-C) and complement (A-T vs T-A) mutations. However, this does not hold true for the transition complement (A-C and T-G) mutations. We investigated whether this may be due to a skewing in the germline composition of the two data sets. The microsequence that favored A-C mutations was TAC and the effect of a 3' C on the types of mutations from A is very striking (Fig. 4b). TAC occurs with a frequency of only 0.52% in the JH intronic sequence, compared with 2.1% in the human IGV gene sequences.


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  		Table I. Relative numbers of transitions and transversions from A occurring in motif AA as compared with motif TA

 


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  		FIGURE 6. Qualitative nonreversibility of the TA motif; the distribution of the three different types of mutation in motif TA from both A and T mutations. A-G transitions are shown in gray, A-T complement mutations are shown in black, and A-C transition complement mutations are shown in white. The corresponding mutations from T (T-C transitions, T-A complement, and T-G transition complement, respectively) are shown in the adjacent striped bars. The values are given as a percentage of the total numbers of mutations from A in TA (n = 116 for human IGV; n = 130 for mouse JH intron) or from T in TA (n = 72 for human IGV; n = 62 for mouse JH intron).

 
Comparisons with Pol{eta} activity

Mutations from A and T have been ascribed to the error prone polymerase activity of Pol{eta}. The sequence context of in vivo IGV mutations from A and T has been compared favorably with that shown by mutations caused by Pol{eta} when copying a lac Z gene, or a mouse transgene in vitro (16, 17, 18), and Pol{eta}-deficient mice and humans show a reduced level of mutation from A and T (14, 15, 26, 27). An analysis of the replacement spectrum of mutations from A caused by Pol{eta} in the AA and TA motifs shows a strong bias toward transition mutations when synthesizing the nontranscribed strand of an IGVK transgene, and a bias toward transversions when synthesizing the transcribed strand. There are differences between the mutations in the AA motif compared with those in the TA motif, the transition bias is very high for the AA motif (Table I). In contrast, the transition bias normally seen in the AA motif as compared with the TA motif is absent in the mutation spectrum of mice and humans deficient in Pol{eta} (Table I).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Disclosures
 References
 
We have analyzed the replacement spectra resulting from the SHM of A and T nucleotides in the context of local microsequence. We have observed that adjacent bases 5' and 3' consistently and significantly influence the replacement spectrum of mutations from A. Most notably we observed random replacement of A (i.e., C, G, or T occur with equal frequency) when A is flanked by a T in the 5' position, or a C in the 3' position. This is significantly different to the pattern of mutations from A seen in other sequence contexts, where the more usual bias toward A-G transitions occurs. Other studies of hypermutation hot spots, including our data in Fig. 1, involved the determination of the proportion of mutations occurring in a particular sequence context as compared with the frequency of that sequence context in the germline. Such analysis, using proportions to control for germline sequence biases, can mask more simple trends such as the random replacement spectrum from A in the context of TA described above and illustrated in Fig. 6. Other biases in substitution were apparent, and indicated an influence of the adjacent nucleotides over the incorporation of mis-paired nucleotides. This preference tended toward "like" nucleotides: if a purine (A or a G) preceded the target A, then the replacement base was more likely to be another purine (G). However, if a pyrimidine, T, preceded the target A, then the replacement base was more likely to be the pyrimidines C or T. Similarly, the presence of a pyrimidine, C, in the 3' position predisposes toward replacement by pyrimidines C or T. The most striking observation in this regard is that there is a bias in the A-G transitions from the second A of an AA motif, whereas the bias switches toward transversions (A-C and A-T) in the A of a TA motif. This observation is consistent between different data sets, including those from non-Ig sequence (Table I). The influence of adjacent bases on replacements from A was not mirrored in mutations from T. The only significant variability in the replacement spectrum from T occurred when there was a C or a T in the 5' position. The levels of significance were much smaller in this instance but it is still possible to see a trend toward replacement by pyrimidine C when preceded by pyrimidines C or T.

The fact that adjacent bases can influence the type of mutation is consistent with the involvement of error prone polymerases at this stage of SHM. Different polymerases have widely differing abilities to insert, and to extend from, a mispaired insertion and it has been shown that sequence context can influence the specificity of a polymerase (30). It is therefore likely that what has hitherto been perceived as motifs targeting mutation from A and T may actually be a consequence of the influence of adjacent bases on substitution preferences by the error prone polymerases. Pol{eta} is thought to be the main error-prone polymerase causing mutation of A and T nucleotides; the absence of Pol{eta} causes a reduced number of mutations at A and T (14, 15, 26, 27) and it has recently been shown to have physical and functional links with MSH2 (31). This polymerase tends to generate transitions as a consequence of misincorporation of dGMP opposite T (16, 32). Transitions from T predominate when the transcribed strand is synthesized (18), and are more likely to occur when the base pair preceding the error is T.A or A.T than when it is G.C or C.G (16). The sequence context-dependent variations in replacement spectrum observed in our study were not observed in the in vitro models of Pol{eta} activity. However, we did see that the transition bias of mutations from A as a result of the in vitro Pol{eta} activity was much higher in the AA than in the TA motif. This is in accord with the transition bias seen in vivo in the human IGV sequences as well as the data from the VkOx1 mouse transgene (18) and mouse JH intron (13). Also consistent with a role for Pol{eta} in AT mutation is the reduction in the transition bias of mutations from A in the AA motif in the human and mouse models of Pol{eta} deficiency (26, 27), although the numbers of mutations available in this analysis are rather low. However, removal of Pol{eta} does not completely abrogate mutations from A and T and on balance it is likely that Pol{eta} is not the only error prone polymerase involved in the generation of mutations at A and T in vivo. Other error-prone polymerases (Pol{zeta}, Pol{iota} and Polµ) have also been implicated (19, 20, 21, 22, 23).

Strand bias, generating more mutations from A than from T, is a consistent feature of the SHM process in vivo. The implication has been that this reflects differences in activity of the AT mutator on the transcribed and non-transcribed strands. The idea that the A and T mutators are equivalent, but operate unequally on both strands in vivo, was supported by the apparently reversible motifs WA and TW that are associated with hypermutation hot spots. A previous study by Cowell and Kepler (33) reported symmetry under complementation in support of this hypothesis. However, in this study we show that WA and TW are not truly reversible motifs for A and T mutations, but only appear so as a result of pooling transitions and transversions. There are some striking differences in motifs from A compared with the reverse complement of the complementary motifs, most notably in the transitions; A to G mutations occur preferentially in AAT, but T to C mutations occur preferentially in TTA (Fig. 5). This finding is in accord with the finding of Cowell and Kepler (33) that a nucleotide within a homodimer is more likely to undergo a transition mutation. However, these motifs are not reverse complements of each other so do not indicate strand symmetry under complementation. The actual numbers of mutations, without the proportional correction for germline sequence, clearly illustrate that the influences of adjacent nucleotides on the types of mutations from A are not mirrored in mutations from T (Fig. 4). This is also true for mutations in non-Ig sequence (Fig. 6). Thus there are two aspects to strand bias; a quantitative bias indicating that a mechanism operates unequally on both strands, and a qualitative difference—in the type of mutation that is created in a given context—indicating that the mechanism itself may be different on each strand.

Instances of TA and TAC sequence motifs where the A is in the second position of a codon are most commonly observed in the complementarity determining regions of the Ig genes. Hence, the mutation of A in these circumstances is likely to have functional consequences. For example, the TAC codon is often observed in complementarity determining regions where mutation of the A would result in replacement of tyrosine with phenylalanine, serine, or cysteine. This could potentially generate significant changes in the Ag binding sites.

In summary, we have shown that adjacent nucleotides affect the substitutions when A nucleotides are mutated. However, mutations from T are not influenced in the same way. Equivalent, complementary, sequence contexts for A and T mutations result in different replacement spectra. Therefore, not only is there a quantitative difference between mutations from A and T, but there is also a qualitative difference. This could be a consequence of differential mutation and/or repair activity on the two DNA strands.


   Acknowledgments
 
We are grateful to Laurent Boursier and Su Wen for producing Ig gene sequence data, and to Mark Dunn for help with the programming.


   Disclosures
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
References
 
The authors have no financial conflict of interest.


   Footnotes
 
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1 This work was supported by the Wellcome Trust (to J.S.) and the Medical Research Council (to D.K.D.-W.). Back

2 The sequence(s) presented in this article has been submitted to GenBank under accession number(s). DNA sequences are available in GenBank (<www.ncbi.nlm.nih.gov/Genbank/index.html>) under the following accession numbers: AJ493283-88, AJ493291, AJ508940-45, AJ508947-49, AJ535508-11, AJ535514, AJ535516, AJ576317-19, X87032, Y13167, Y13172, Y16646-49, Z738020-21, Z80389, Z80708, Z93132, Z93134, Z93138, Z93141, Z93153-54, Z93156, Z93158-59, Z73863, Z93213-14, Z93216, Y13167-68, Z73839, Z73858, Z73860, Z80570-71, Z80760, Z93198-99, Z93204, Z80673, X87013, X87064, X87075, X97784, Z80753, X87035, X87082, Z80396, Z803564, and Z803719. Back

3 Address correspondence and reprint requests to Dr. Deborah K. Dunn-Walters, Department of Immunobiology School of Medicine at Guy’s, King’s and St. Thomas’ Hospitals, 2nd Floor New Guy’s House, Guy’s Hospital, London SE1 9RT, U.K. E-mail address: deborah.dunn-walters{at}kcl.ac.uk Back

4 Abbreviations used in this paper: SHM, somatic hypermutation; AID, activation-induced cytidine deaminase; BER, base excision repair; MMR, mismatch repair; UNG, uracil N-glycosylase. Back

Received for publication April 14, 2005. Accepted for publication August 11, 2005.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Disclosures
 References
 

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