Somatic hypermutation introduces mutations into IgV genes during affinity maturation of the B cell response. Mutations are introduced nonrandomly, and are generally targeted to the complementarity determining regions (CDRs). Subsequent selection against mutations that result in lower affinity or nonfunctional Ig increases the relative number of mutations in the CDRs. Investigation of somatic hypermutation is hampered by the effects of selection. We have avoided this by studying out-of-frame human IgVH4.21 and 251 genes, which, being unused alleles, are unselected. By comparison of the frequency of A, C, G, and T nucleotides at positions −3 to +3 around mutated or unmutated A, C, and G nucleotides, we have identified flanking sequences that most commonly surround mutated bases. Distinct trends in flanking sequences that were unique for each base were observed. Statistically significant trends that were common to both IgVH4.21 and 251 were used to deduce motifs that bias somatic hypermutation. The motifs deduced from this data, with targeted bases in regular type, are AANB, WDCH, and DGHD (where W = A/T, B = C/G/T, D = A/G/T, H = A/C/T, and N = any base). Mutations from C and G in two further groups of out-of-frame human IgVH genes, not used in the deduction of the motifs, occurred significantly within the motifs for C and G. The proposed target sequence for G is within the reverse complement of the target sequence for C, suggesting that the hypermutation mechanism may target only G or C. The mutation in the complementary base would appear on the other strand following replication.

Affinity maturation of the B cell response involves diversification of the B cell repertoire by somatic hypermutation of the IgV genes, followed by selection of B cells according to affinity of the encoded Ig for Ag (1). Somatic hypermutation targets bases nonrandomly; mutations tend to accumulate in the complementarity determining regions (CDRs)4 that encode the Ag binding loops (2), while the framework (Fw) regions, which are required for the structural integrity of Ig gene, remain largely intact. Hotspots for mutation can occur throughout the Ig gene (3).

A significant problem in analyzing targets for hypermutation is eliminating the effects of selection. This increases the tendency for mutations to accumulate in the CDRs, since mutations that result in impairment of Ab function (mostly in the Fw regions), or in lowering affinity, often result in apoptosis of the cell carrying the mutation (4, 5). Restricting analysis to silent mutations introduces significant biases, since this limits the study to a large proportion of bases in the third position of the codon, and eliminates most of the rest of the sequence (6). A consensus sequence RGYW (A/G G C/T A/T) as a preferred target for hypermutation was deduced from analysis of selected human IgVH sequences (7). Preferred dinucleotide (GC and TA) and trinucleotide (AGC, TAC, GCT, and GTA) targets for hypermutation have been identified by analysis of mutated, noncoding, sequences of murine IgV genes (8). Consistent with these proposed targets, it has been observed that AGY serine codons are concentrated in the CDRs, whereas TCN serine codons are concentrated in the Fw regions (9). Not only are AGY codons more frequently mutated than TCN codons in unselected passenger transgenes (4), mutations in AGY are more likely to result in amino acid replacement than mutations in TCN, where all third base changes are silent.

In this study we have avoided the effects of selection in analysis of targets for hypermutation by using out-of-frame alleles of human IgVH genes 4.21 and 251. Since out-of-frame alleles are subjected to the hypermutation process but are not expressed or subjected to selective pressure, the distribution of mutations will reflect the mechanism that generated them (10, 11). Only deletions or insertions (which are rare events) in the D region subsequent to selection could result in the inclusion of selected alleles in the population studied. Since hypermutation is thought to be template dependent (12), we only considered trends that were observed in both IgVH 4.21 and 251 and that were significant at p = 0.05 in χ2 analysis of the combined data.

Highly mutated human IgVH gene sequences from DNA microdissected from human intestinal lamina propria plasma cells and marginal zone B cells were analyzed. Bases flanking mutated and unmutated A, G, and C nucleotides were studied independently. Sequences that commonly surrounded mutated bases were deduced, and were considered as motifs that identify likely targets for somatic hypermutation. The effectiveness of these motifs in highlighting mutated bases was then tested using different groups of mutated out-of-frame human IgVH genes.

Thirteen out-of-frame VH4.21 genes (codons 25–94) with 197 mutations and eight out-of-frame VH251 genes (codons 24–94) with 156 mutations were available for the analysis of flanking sequences (13, 14, 15). Two groups of bases were used in the analysis; bases that were unmutated and bases that were mutated in two or more sequences. Of the available mutations, 230 were used in the analysis. Germline VH4.21 and VH251 sequences and the positions of the CDRs were taken from Tomlinson et al. (16).

In addition, four out-of-frame VH32 genes from our laboratory with a total of 76 mutations, and a group of five genes retrieved from EMBL Data Library (10) (one sequence from each of DP71, DP65, DP47, DP42, and DP53) with 112 mutations, were used to test the motifs deduced from analysis of flanking sequences around mutated and unmutated bases in VH4.21 and VH251.

A, C, and G nucleotides were studied separately and the flanking sequences surrounding mutated or unmutated bases in each were considered independently. The frequency with which A, C, G, or T occurred in each flanking position, from −3 to +3, around mutated and unmutated A’s, C’s, or G’s, was expressed as a percentage of the total bases at that position. The figures for VH4.21 and VH251 were calculated independently. Although biases may exist in the germline sequences flanking a particular base, this was controlled for by strict comparison of flanking sequence around mutated and unmutated bases. Since there are fewer T’s in germline, and also because T’s are infrequently mutated, we were not able to generate reliable data to assess the flanking sequence around mutated T’s. Therefore, analysis of flanking sequences around mutated and unmutated T nucleotides is not included in this study.

Two criteria were used in the deduction of motifs. Firstly, trends had to be common to both VH4.21 and VH251. Where a base occurred over 15% more frequently in a particular position flanking a mutated compared with an unmutated base, in both VH4.21 and VH251, this was considered to be a possible element of a targeting sequence. Where the frequency of a base was 15% lower at a particular position in the flanking sequence around a mutated compared with an unmutated base, this was taken to reflect the absence of that base in that position in the motif. The figure of 15% is an arbitrary cut off point. Secondly, trends had to be statistically significant. The number of times a flanking base occurred at positions −3 to +3 around each mutated base was compared with the number of occurrences around unmutated bases, allowing for the total numbers available, by χ2 analysis of the combined data for VH4.21 and VH251.

Where motifs involve degenerate bases, the following standard code is used: A/G = R, A/T = W, C/T = Y, A/G/T = D, A/C/T = H, C/G/T = B.

Two groups of sequences, which were not used in the deduction of the motifs, were used to test their effectiveness. For each sequence to be tested, the number of bases that were highlighted by the motif and those that were not were determined. χ2 analysis was then used to determine whether mutations from each base occurred most frequently within their motifs.

The frequencies of A, C, G, and T nucleotides that flank mutated and unmutated A’s, C’s, and G’s at positions −3 to +3 in IgVH4.21 and IgVH251 are illustrated in Figures 1 to 3. It was possible to identify some common features of the flanking sequences in IgVH4.21 and IgVH251 using these graphs. Positions around each mutated and unmutated base were compared using χ2 analysis of the combined data for IgVH4.21 and IgVH251 (Table I). The graphs in Figures 1 to 31–3, and the values in Table I were studied together in deducing sequences that identify individual A’s, C’s, and G’s as targets for hypermutation. Only trends observed in both IgVH4.21 and IgVH251 that were also statistically significant were considered to contribute to the motifs. Where data in Figures 1 to 31–3 and the statistical analysis in Table I indicate both the dominance of a nucleotide and lack of a nucleotide in the same position, the lack of a nucleotide in that position is used in the motif, as this can include the dominance of another base at that position. In all of the proposed motifs below, the targeted base is illustrated in bold type.

FIGURE 1.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding A nucleotides (which are positioned at 0 on the horizontal axes). The frequency of each base around mutated A’s is represented by triangles and around unmutated A’s by squares. Where the frequency of a base around a mutated A exceeds the frequency of a base around an unmutated A by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target sequence for hypermutation. Where the frequency of a base around a mutated A is less than the frequency of a base around an unmutated A by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation.

FIGURE 1.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding A nucleotides (which are positioned at 0 on the horizontal axes). The frequency of each base around mutated A’s is represented by triangles and around unmutated A’s by squares. Where the frequency of a base around a mutated A exceeds the frequency of a base around an unmutated A by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target sequence for hypermutation. Where the frequency of a base around a mutated A is less than the frequency of a base around an unmutated A by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation.

Close modal
Table I.

Probability values obtained by χ2 analysis, comparing flanking sequences of mutated and unmutated bases from out-of-frame human IgVH4.21 and 251 genesa

Targeted BaseFlanking Base−3−2−1+1+2+3
0.98 0.65 0.03 0.90 0.04 0.46 
 0.93 0.37 0.27 0.80 0.61 0.86 
 0.62 0.79 0.21 0.79 0.25 0.94 
 0.55 0.32 0.27 0.94 0.74 0.53 
0.39 0.0003 0.65 0.67 0.82 0.78 
 0.74 0.04 0.04 0.35 0.64 0.80 
 0.74 0.02 0.07 0.04 0.87 0.61 
 0.22 0.47 0.02 0.54 0.40 
0.41 0.54 0.02 0.13 0.70 0.81 
 0.69 0.93 0.02 0.44 0.05 0.90 
 0.94 0.21 0.59 0.05 0.26 0.59 
 0.47 0.32 0.53 0.02 0.002 0.79 
Targeted BaseFlanking Base−3−2−1+1+2+3
0.98 0.65 0.03 0.90 0.04 0.46 
 0.93 0.37 0.27 0.80 0.61 0.86 
 0.62 0.79 0.21 0.79 0.25 0.94 
 0.55 0.32 0.27 0.94 0.74 0.53 
0.39 0.0003 0.65 0.67 0.82 0.78 
 0.74 0.04 0.04 0.35 0.64 0.80 
 0.74 0.02 0.07 0.04 0.87 0.61 
 0.22 0.47 0.02 0.54 0.40 
0.41 0.54 0.02 0.13 0.70 0.81 
 0.69 0.93 0.02 0.44 0.05 0.90 
 0.94 0.21 0.59 0.05 0.26 0.59 
 0.47 0.32 0.53 0.02 0.002 0.79 
a

Values that are significant at p = 0.05 are in bold. ▦▦ ▦ ▦ ▦ ▦▦ ▦ ▦

FIGURE 2.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding C nucleotides (that are positioned at 0 on the horizontal axes). The frequency of each base around mutated C’s is represented by triangles and around unmutated C’s by squares. Where the frequency of a base around a mutated C exceeds the frequency of a base around an unmutated C by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target for hypermutation. Where the frequency of a base around a mutated C is less than the frequency of a base around an unmutated C by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation.

FIGURE 2.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding C nucleotides (that are positioned at 0 on the horizontal axes). The frequency of each base around mutated C’s is represented by triangles and around unmutated C’s by squares. Where the frequency of a base around a mutated C exceeds the frequency of a base around an unmutated C by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target for hypermutation. Where the frequency of a base around a mutated C is less than the frequency of a base around an unmutated C by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation.

Close modal
FIGURE 3.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding G nucleotides (which are positioned at 0 on the horizontal axes). The frequency of each base around mutated G’s is represented by triangles and around unmutated G’s by squares. Where the frequency of a base around a mutated G exceeds the frequency of a base around an unmutated G by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target for hypermutation. Where the frequency of a base around a mutated G is less than the frequency of a base around an unmutated G by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation. The frequency with which G occurs at +2 flanking G may be important in the light of the data as a whole. This has been indicated using a question mark.

FIGURE 3.

Graphs of percentage frequency (vertical axes) of A, C, G, or T nucleotides at flanking positions −3 to +3 surrounding G nucleotides (which are positioned at 0 on the horizontal axes). The frequency of each base around mutated G’s is represented by triangles and around unmutated G’s by squares. Where the frequency of a base around a mutated G exceeds the frequency of a base around an unmutated G by 15% or more, in both VH4.21 and VH251, the peak (marked with an arrow), is considered as a possible element of a target for hypermutation. Where the frequency of a base around a mutated G is less than the frequency of a base around an unmutated G by 15% or more, in both VH4.21 and VH251, the point (marked with an arrowhead), is also considered as a possible element of a target sequence for hypermutation. The frequency with which G occurs at +2 flanking G may be important in the light of the data as a whole. This has been indicated using a question mark.

Close modal

From analysis of individual bases flanking mutated and unmutated A’s, it is apparent that there is a strong tendency toward A at position −1 and against an A at position +2 around mutated A’s (Fig. 1, Table I). This suggests a motif of AANB.

The data in Figure 2, and the results of statistical analysis in Table I illustrate the dominance of A and lack of G or C at position −2 from a mutated C. The lack of C at position −1 is also significant. In addition, there is a marked dominance of T at +1 after a mutated C, which is accompanied by very strong bias against G at this position. These data suggest a motif of (A, not G or C)(not C)C(T,not G) (Fig. 4). The motif tested below is therefore WDCH.

FIGURE 4.

Flanking sequences around mutated C and mutated G nucleotides, which are significantly different from the flanking sequence around unmutated bases in χ2 analysis and which are common to both IgVH4.21 and IgVH251. The targeted bases are boxed. The reverse complement of the flanking sequence for C has all elements of the flanking sequence for G.

FIGURE 4.

Flanking sequences around mutated C and mutated G nucleotides, which are significantly different from the flanking sequence around unmutated bases in χ2 analysis and which are common to both IgVH4.21 and IgVH251. The targeted bases are boxed. The reverse complement of the flanking sequence for C has all elements of the flanking sequence for G.

Close modal

At position −1, there is a strong tendency for an A, and a strong bias against C (Fig. 3 and Table I). At position +1 there is a marked bias against G and a tendency toward T (Table I). However, it is clear in Figure 3 that this dominance of T is only apparent in VH4.21. This was not included in the motif since it was clearly not a trait common to both genes. At position +2 there is a strong predominance of T and a bias against C. These data are consistent with (A, not C)G(not G) (T, not C) as a motif (Fig. 4). The motif that we tested therefore is DGHD.

The motifs AANB, WDCH, and DGHD were tested for their ability to highlight bases that had been mutated in two groups of out-of-frame IgVH genes, using χ2 analysis (Table II). Mutations from C and G were significantly concentrated within the motifs for these bases. Mutations from A were not significantly targeted by AANB.

Table II.

Comparison of the numbers of mutations occurring in bases within motifs, and the numbers occurring in bases outside motifs, for two groups of out-of-frame human IgVH genes

MotifGeneBases in MotifsMutations in MotifsBases Not in MotifsMutations Not in Motifsχ2p value
AANB       
 VH32 46 13 NS 
 VH3+4 genesa 27 275 34 NS 
WDCH       
 VH32 31 19 47 0.0016 
 VH3+4 genesa 106 17 250 10 0.0004 
DGHD       
 VH32 27 22 35 0.0020 
 VH3+4 genesa 164 22 218 0.0006 
MotifGeneBases in MotifsMutations in MotifsBases Not in MotifsMutations Not in Motifsχ2p value
AANB       
 VH32 46 13 NS 
 VH3+4 genesa 27 275 34 NS 
WDCH       
 VH32 31 19 47 0.0016 
 VH3+4 genesa 106 17 250 10 0.0004 
DGHD       
 VH32 27 22 35 0.0020 
 VH3+4 genesa 164 22 218 0.0006 
a

From Ref. 10.

This is a unique study in a number of ways. It is the first to consider out-of-frame alleles of human IgVH genes, which are mutated but unselected, in the study of somatic hypermutation. It is the first analysis of somatic hypermutation based on comparison of flanking sequences around mutated and unmutated bases in human IgVH genes, and it is the first study to consider the flanking sequence around each nucleotide separately. The data presented here support the hypothesis that somatic hypermutation is template dependent and that specific motifs are involved in the generation of mutational hotspots (3, 4, 12). We have observed trends in the flanking sequences around mutated A, C, and G nucleotides that are consistent between VH4.21 and VH25. These flanking sequences cannot be reconciled into a single targeting sequence, implying a separate motif for each base. The motifs we tested are AANB, WDCH, and DGHD.

Although the motifs are highly degenerate, in some cases identifying over 40% of the sequence, the WDCH and DGHD motifs were highly effective in identifying bases that were likely targets for somatic hypermutation when tested using additional sets of mutated out-of-frame IgVH genes. In general, we know that a large proportion of the IgVH sequence can be mutated. It is also likely that the mechanism that mutates bases nonrandomly is not likely to be highly stringent, or the consequences of its action would be obvious to us. The motifs proposed are therefore likely to be a reflection of a mechanism that biases toward a certain group of nucleotides and against another. The motif deduced for A was ineffective when used to identify likely targets for hypermutation. It is clearly not significant as written and future studies may resolve this.

The motif deduced for targeted C’s, when read in the reverse complement, is very close to the motif for targeted G’s (Fig. 4). The only point of difference between the motif for C and the reverse complement of the motif for G is marked with a question mark in Figure 3. It is possible that only either the G’s, or the C’s, are mutated, if it is assumed that mutation acts on both strands (not necessarily equally), and occurs in one direction only (e.g., 5′ to 3′). As an example, a targeted mutation from G on the coding strand, following replication, would appear as a mutation from C on the complementary strand, with an identical flanking sequence.

There are a number of similarities between the motifs that we propose and the RGYW motif (7). The RGYW sequence incorporates elements of our target sequences for C and G, and seems more effective at identifying areas of mutation when these elements are used (R = A, Y = C) than when they are not (R = G, Y = T). However, it was clear, from the mutated sequences analyzed, that our targets are not simply a reflection of the effectiveness of RGYW in predicting mutations, since RGYW only coincided with a proportion of the mutated bases used to deduce the motifs proposed here. We compared the ability of our three motifs and RGYW to identify mutated A, C, and G nucleotides in two groups of sequences that had been mutated in the absence of selection; out-of-frame mutated alleles of the human VH32 genes and a β-globin transgene (Refs. 12–15, and N. Klix and M. S. Neuberger, Personal communication). When a χ2 test was used to compare the numbers of mutations occurring in motifs with the number occurring outside motifs, correcting for the frequency of occurrence of the motif, both RGYW (p = 2.1 × 10−4) and the combination of AANB, WDCH, and DGHD (p = 3.56 × 10−12) were significantly effective in identifying potential target bases. The effectiveness of RGYW was due almost exclusively to the efficiency of RGYW in identifying mutated G’s. The high level of significance using AANB, WDCH, and DGHD was achieved despite having no significant contribution from AANB. Our proposed motifs are in general agreement with the preferred di- and trinucleotide targets proposed by others (8), since the most preferred di- and trinucleotides either could comprise, or do comprise, part of our proposed target sequences. Infrequently mutated di- and trinucleotides often contain inhibitory elements of the proposed motifs.

A number of studies have observed that A is more commonly mutated than T, suggesting strand discrimination (12, 17, 18). Preferential targeting of mutations to one strand of DNA is consistent with the theory of transcriptional regulation of hypermutation (19). However, the existence of strand bias does not eliminate the possibility that both strands are mutated. There are conflicting reports in the literature on the relative frequency of mutations from G and C; some suggest strand bias, others do not (3, 12, 17, 18). The proposed motifs are asymmetrical and unique for each base. The differences in the tendencies for G and C to mutate in different sequences may be due to the relative representation of nucleotides targeted by the motifs within the different germline sequences studied.

The mechanism responsible for somatic hypermutation can generate few or multiple mutations within an Ig VH or VL gene depending on dose and time of antigenic exposure (18, 20). Although some bases are hotspots for mutation and others are rigorously conserved, most form a spectrum between these points, varying in their susceptibility as targets for the hypermutation mechanism. The data presented here, which identify significant differences in the sequences flanking mutated A, C, and G nucleotides, suggest that there is no single motif that targets all nucleotides, but that motifs target individual nucleotides. The focusing of the hypermutation mechanism by the clustering of motifs for individual nucleotides is likely to be a significant factor in targeting codons and the generation of hotspots, though it is likely to be one element of a more complex story.

1

This work was supported by The Special Trustees of St. Thomas’ Hospital.

2

Sequences from our laboratory analyzed in this paper are available from the GenBank/EMBL databases under the following accession numbers: Z93132, Z93134, Z93138, Z93153, Z93156, Z93158, Z93159, Z73820, Z73821, Z73839, Z73858, Z73864, Z73860, Z93198, Z93199, Z93204, Z93213, Z93214, Z93216, and Y13167 to Y13172. Sequences accessed from GenBank/EMBL used in this study were X87019, X87075, X87080, X87064, and X87082.

4

Abbreviations used in this paper: CDR, complementarity determining regions of Ig heavy chain variable region genes; Fw, framework regions of Ig heavy chain variable region genes.

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