Predicting Regional Mutability in Antibody V
Genes Based Solely on Di- and Trinucleotide
Sequence Composition
This information is current as
of June 18, 2017.
Gary S. Shapiro, Katja Aviszus, David Ikle and Lawrence J.
Wysocki
J Immunol 1999; 163:259-268; ;
http://www.jimmunol.org/content/163/1/259
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References
Predicting Regional Mutability in Antibody V Genes Based
Solely on Di- and Trinucleotide Sequence Composition1
Gary S. Shapiro,*‡ Katja Aviszus,* David Ikle,† and Lawrence J. Wysocki2*‡
D
uring T cell-dependent immune responses, Ab V genes
of activated B cells are modified by a somatic mutation
process that indirectly exerts a strong influence on recruitment of B cells into the memory compartment by producing
structural and functional alterations in V region domains of surface
receptor Abs. Despite the importance of somatic mutagenesis to
immune and autoimmune processes, its mechanism has proved to
be conceptually elusive. Somatic mutations occur within variable
region gene segments (1– 6), but are selectively absent from exons
encoding constant domains (7–9). Transcription seems to be necessary, but not sufficient, for targeting mutagenesis (10 –12). A link
to transcription is supported by the influence of promoter location
on the distribution of mutations along a segment of DNA (13).
However, mutagenesis is not strictly dependent on Ig-specific promoters or coding sequences, since replacing either does not dramatically alter mutation frequency (13–16). A correlation between
predicted RNA secondary structure and intrinsic mutability was
observed in one study of an artificial mutation substrate under the
control of Ig k regulatory elements (17). On the basis of these data,
Storb et al. (17) proposed a model in which a mutator travels with
the transcription machinery and stalls at points of nascent RNA
secondary structure, thereby leading to higher frequencies of mutagenesis in adjacent DNA. k intron and 39 enhancers play an
essential role in the mutation process as revealed in transgenic
studies (15, 18 –20), yet the analogous heavy chain gene enhancers
*Department of Pediatrics, Division of Basic Sciences, and †Division of Biostatistics,
National Jewish Medical and Research Center, Denver, CO 80206; and ‡Department
of Immunology, University of Colorado Health Sciences Center, Denver, CO 80262
Received for publication December 28, 1998. Accepted for publication April 9, 1999.
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
appear to be insufficient for full mutagenesis (21–24). These differences raise the possibility that different mutation mechanisms
may operate on heavy and light chain V region genes.
Somatic mutations are not distributed randomly throughout V
region genes. In part this is due to selection pressures that favor
alteration of the complementarity-determing region (CDR).3 However, an intrinsic target bias of the mutation mechanism has been
revealed by the nonrandom nature of mutations within sequences
that are not influenced by cellular selection processes (8, 25, 26).
Lebecque and Gearhart (27) observed that particular types of mutations occurred more frequently than others, leading them to deduce that the mechanism possesses a strand bias. Rogozin and
Kolchanov (28) observed a higher than average frequency of mutations in RGYW and TAA nucleotide sequences. Similarly, Betz
et al. (29) observed that AGY serine codons in a passenger transgene mutated at an inordinately high frequency. This led them to
propose that CDR are more intrinsically mutable than FR because
of differences in AGY vs TCN serine codon use by segments encoding the two types of regions (30). However, somatic mutations
often occur in nucleotide sequences that are not included in these
motifs, and this led us to examine the relative mutability of all diand trinucleotides. Our analysis was confined to mutations within
Ig intronic sequences that presumably are not subject to the indirect, but substantial, influences of selection (31). The results of this
work revealed a hierarchy of mutability among all di- and trinucleotide sequences. In addition, the results helped to refine previously proposed motifs, identifying AGC, for example, as the mutable component of the AGY motif. Defining intrinsic mutability
provides clues to the mechanism of mutation and is important to
interpretations concerning Ag-driven selection in immune and autoimmune processes that are often drawn on the basis of mutational distribution within V genes.
This work supported by National Institutes of Health Grant RO1AI39563.
2
Address correspondence and reprint requests to Dr. Lawrence J. Wysocki, Department of Pediatrics K902, National Jewish Medical and Research Center, 1400 Jackson Street, Denver, CO 80206. E-mail address: [email protected]
Copyright © 1999 by The American Association of Immunologists
3
Abbreviations used in this paper: CDR, complementarity-determining region; FR,
framework; obs/exp, observed/expected.
0022-1767/99/$02.00
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
Somatic mutations are not distributed randomly throughout Ab V region genes. A sequence-specific target bias is revealed by a
defined hierarchy of mutability among di- and trinucleotide sequences located within Ig intronic DNA. Here we report that the
di- and trinucleotide mutability preference pattern is shared by mouse intronic JH and Jk clusters and by human VH genes,
suggesting that a common mutation mechanism exists for all Ig V genes of both species. Using di- and trinucleotide target
preferences, we performed a comprehensive analysis of human and murine germline V genes to predict regional mutabilities.
Heavy chain genes of both species exhibit indistinguishable patterns in which complementarity-determining region 1 (CDR1),
CDR2, and framework region 3 (FR3) are predicted to be more mutable than FR1 and FR2. This prediction is borne out by
empirical mutation data from nonproductively rearranged human VH genes. Analysis of light chain genes in both species also
revealed a common, but unexpected, pattern in which FR2 is predicted to be highly mutable. While our analyses of nonfunctional
Ig genes accurately predicts regional mutation preferences in VH genes, observed relative mutability differences between regions
are more extreme than expected. This cannot be readily accounted for by nascent mRNA secondary structure or by a supplemental
gene conversion mechanism that might favor nucleotide replacements in CDR. Collectively, our data support the concept of a
common mutation mechanism for heavy and light chain genes of mice and humans with regional bias that is qualitatively, but not
quantitatively, accounted for by short nucleotide sequence composition. The Journal of Immunology, 1999, 163: 259 –268.
260
In this manuscript we compare relative intrinsic mutabilities of
di- and trinucleotides in heavy and light chains and V genes of
mice and humans in search of evidence for common or distinct
mutation mechanisms. In addition, we used di- and trinucleotide
mutability preferences in a comprehensive analysis of germline V
region gene sequences to predict intrinsic regional mutabilities of
CDR and FR. We compared these predictions with empirical mutation data from nonproductively rearranged human VH genes to
determine whether regional mutability indexes based upon di- and
trinucleotides composition alone could predict the pattern and relative extent of mutational accumulation in different segments of
Ab V genes. Finally, we examined the relationship between predicted RNA secondary structure and observed regional mutability.
Our results support the idea that all Ig genes in mice and humans
mutate by a common mechanism and that di- and trinucleotide
sequence composition alone can predict regional mutation patterns, but in a nonquantitative manner. The quantitative discrepancy is not obviously resolved by taking predicted nascent secondary RNA structure into consideration.
Sequence sources
For regional mutability predictions of human V genes, sequences were
extracted from the V BASE index (32) which contains all known human
germline heavy and light chain V genes. When sequence discrepancies due
to potential mistakes or polymorphisms occurred, the Tomlinson et al. (33)
sequence was used. Murine Ig V gene sequences were extracted from the
ABG germline directory of mouse Ig sequences, organized by the Ab
Group of Instituto de Biotecnologia, Universidad Nacional Autonoma de
Mexico (34). In those few cases where identical amino acid sequences were
specified by different nucleotide sequences, only one sequence was selected for analysis. Because complete sequence information was not available for all V genes of any strain, the known sequences from all strains
were combined in our analyses. Altogether, 47, 40, and 29 human heavy,
k, and l genes as well as 72 and 42 murine heavy and k genes were
included in the analyses.
Empirical mutation frequencies were determined using somatically mutated, but unselected, Ig sequences derived from several sources. Mutations
in murine intronic sequences for the JH and Jk clusters that flank assembled
V gene exons were analyzed using raw data (A/J 1 literature 1 autoimmune) obtained by Smith et al. (31). Mutations in human VH genes were
analyzed from sequences of nonproductively rearranged VH genes obtained
by Dorner et al. (35) and Dunn-Walters and Spencer (36). In all cases
insertions and deletions were not included in the analyses, and nonproductive rearrangements were defined by out-of-frame J segments or junctional
stop codons. We also analyzed somatic mutations in a k transgenic construct containing a 100-nt insertion with repeated EcoRV and PvuII restriction sites under the control of k regulatory elements (EPS insert) (17).
Forty-six such mutated transgene sequences (27,278 nt) containing 135
mutations were obtained from data reported by Storb et al. (17).
Sequence manipulation
All unmutated germline sequences were manipulated and analyzed with
MacVector version 5.0 software (Oxford Molecular Group, Beaverton,
OR). Sequences were divided into FR and CDR according to both the
Kabat (37) and Chothia (38 – 40) definitions; the former is based on sequence variability, and the latter is based on location of structural loop
regions. In each sequence file used in the dinucleotide analysis, one extra
nucleotide was included from adjacent sequence at each end of the region
under consideration. Similarly, sequence files for trinucleotide analyses
included two extra nucleotides at each end. Mutated nonproductive human
VH sequences were treated identically, except that 10 nt were deleted from
the 39 end of FR3 to insure that discrepancies with germline sequence were
due to somatic mutagenesis as opposed to junctional diversification during
V segment assembly (41, 42). The transgene of Storb et al. (17) was divided into segments of 100 nt in a manner that left the artificial EPS insertion intact in one file. Collectively, 6507 files containing regional sequence data for V genes were generated for analysis.
Oligonucleotide mutability indexes
Di- and trinucleotide observed/expected (obs/exp) mutability indexes were
calculated as previously described (31). Briefly, the number of times a
given oligonucleotide within a segment of DNA contained a mutation was
divided by the number of times the oligonucleotide was expected to be
mutated for a mechanism with no bias. Mutability indexes are normalized
for the di- and trinucleotide compositions of unmutated templates covering
the precise regions for which mutational data were analyzed.
Predicting regional mutability
Regional mutability based solely on DNA sequence was predicted using diand trinucleotide obs/exp mutability indexes (A/J and literature) defined by
Smith et al. (31). The mutability index of a di- or trinucleotide is a normalized measure of its tendency to mutate, where a value of 1 indicates the
average mutability for di- or trinucleotides. The predicted mutability index
for a region was calculated by determining the number of times each di- or
trinucleotide occurred within each region (file) of each gene (regardless of
frame of reference) and multiplying by its mutability index. The resulting
products for the 16 dinucleotides or 64 trinucleotides were summed and
then divided by the total number of di- or trinucleotides in the region (file)
under consideration. That is, di- and trinucleotide mutabilities were
summed in all frames of reference. The composite mutability index predicted for a type of region, for example nucleotide sequences encoding
human VH FR1, was determined by summing all di- or trinucleotide products (occurrences 3 mutability index) and dividing this number by the sum
of all di- or trinucleotide occurrences in the region for all such sequences
in the database. When predicting regional mutabilities for human VH genes
within the databases of nonproductively rearranged VH genes, calculations
were weighted proportionally to the number of times a mutated version of
a given gene appeared in the database. Microsoft Excel 98 and version 4.0
(Redmond, WA) were used for database management and calculations.
Observed mutability
The empirical relative mutabilities (observed mutability index) for each
region of the nonproductively rearranged human VH genes and the murine
k transgene were determined by dividing the number of mutations per
nucleotide for a region by the number of mutations per nucleotide for the
entire gene. In essence, this gives the obs/exp mutability ratio for a region,
where the expected frequency is the average frequency of mutations for the
whole gene. For a given subregion, such as nucleotide sequences encoding
VH FR1, the observed composite mutability index was calculated as the
number of mutations per nucleotide in all VH FR1 of the database divided
by the number of mutations per nucleotide for the entire length (FR1,
CDR1, FR2, CDR2, FR3) of all V regions within the database.
Relationship of mutation distribution to mRNA secondary
structure stability
Six-base intervals of the nonproductive human VH genes were defined by
aligning all the sequences while adjusting for CDR length variability. Predicted folding energy of nascent mRNA was used as a measure of secondary structure stability. Members of the mutated nonproductive human VH
gene databases from Dorner et al. and Dunn-Walters and Spencer (35, 36)
were divided into 51-nt intervals in steps of 6 nt. The mRNA folding
energy for each interval was calculated by the online version of Mfold (43)
and reported in kilocalories per mole, where stability increases as the number becomes more negative. For each 6-nt segment, we determined the
mRNA folding energy by averaging the folding energies of the 51-nt interval whose 39 end coincided with the 6-base segment under consideration
and the two immediately flanking 51-nt intervals. This analysis correlates
a 6-nt segment with upstream RNA secondary structure that has the potential to influence the polymerase complex. Calculations for some 6-nt
segments in FR1 could not be performed due to lack of leader sequence
information.
Statistics
Continuous data are summarized as the mean and SEM. Mean ratios were
compared between regions using one-way ANOVA. The percentages of
nucleotides with mutations were compared with the expected percentages
under the assumption of uniform mutation rates by x2 tests for comparing
observed to expected proportions. Pearson correlation coefficients were
used to evaluate associations between continuous variables. Simple linear
regression with confidence intervals and tests of hypotheses on the intercepts and slopes were used to evaluate linear relationships between continuous variables. All tests of hypotheses were considered significant at an
a level of 0.05, except that tests for significance of mutation indexes were
performed at the 0.01 level.
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Materials and Methods
REGIONAL MUTABILITY IN Ab V GENES
The Journal of Immunology
261
Shared positional mutation preferences
Results
Shared mutation preferences in heavy and light chain genes of
mice and humans
If a common mechanism generates somatic mutations within Ig
heavy and light chain V genes, then the two should reveal a common di- and trinucleotide target bias. To test this idea, we calcu-
To further investigate the consistency of sequence-specific mutability, we calculated the mutability index for each position of all
di- and trinucleotides in the murine JH and Jk and human VH
sequences. As shown in Table III, the JH and Jk as well as the
murine and human Ig sequences possessed a striking consistency
of mutational bias at the level of individual positions. Besides providing further support for a common mutation mechanism, these
Table I. Human and murine dinucleotide mutability indexes
Murine JH/Jk Intronica
Dinucleotide
GC
TA
AC
AA
AT
AG
CT
GT
TG
CA
CC
GA
GG
TT
TC
CG
Mutations
Nucleotides
Mut. Freq. (%)
No. of
mutations
Mutability
index
114
169
114
226
143
170
129
113
100
72
42
84
71
69
48
6
2.03*
1.84*
1.53*
1.47*
1.42*
1.17
1.06
1.01
0.74*
0.72*
0.71
0.65*
0.56*
0.49*
0.45*
0.40
Murine JH Intronica
No. of
mutations
60
64
50
78
66
70
70
41
49
34
28
46
44
34
27
1
835
92,228
0.91
A/J 1 autoimmune 1 literature sequences from Smith et al.(31).
Sequences from Dorner et al.(35) and Dunn-Walters and Spencer(36).
p, Statistically significant by x2 test at p 5 0.01.
a
b
Mutability
index
2.15*
1.87*
1.49*
1.55*
1.40*
1.22
1.08
0.89
0.73
0.71
0.81
0.82
0.64*
0.52*
0.48*
0.21
381
37,769
1.01
Murine Jk Intronica
No. of
mutations
Mutability
index
54
105
64
148
77
100
59
72
51
38
14
38
27
35
21
5
1.88*
1.87*
1.57*
1.48*
1.42*
1.16
1.00
1.11
0.74
0.72
0.54
0.53*
0.44*
0.47*
0.40*
0.50
454
54,459
0.83
Human VHb
No. of
mutations
Mutability
index
160
124
108
86
88
181
105
100
63
87
96
63
87
40
60
28
1.72*
2.03*
1.20
1.43*
1.36*
1.50*
0.89
1.13
0.56*
0.77
0.76*
0.60*
0.66*
1.01
0.61*
0.55*
738
14,811
4.98
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
FIGURE 1. Common hierarchy of mutability among di- and trinucleotides in JH and Jk intronic DNA. Mutability indexes (obs/exp) for all
dinucleotides (A) and trinucleotides (B) were compared.
lated normalized obs/exp mutability indexes for all di- and
trinucleotides within mutated JH and Jk intronic DNA from a panel
of murine hybridomas (31). The index is a measure of the tendency
to mutate, where a value of 1 is the average. As shown in Fig. 1A
and Table I, a comparison of dinucleotide mutability indexes in the
two regions revealed a close agreement. This is most clearly seen
in a simple regression analysis, which yielded a slope and y-intercept of 1 and 0, respectively, within a 95% confidence interval.
Similar results and statistical significance were obtained upon
comparative analyses of trinucleotide mutability indexes for the
two regions of DNA (Fig. 1B and Table II).
Using sequences obtained by Dorner et al. (35) and DunnWalters and Spencer (36), we similarly calculated dinucleotide
mutability indexes for 730 mutations located within 60 nonproductively rearranged human VH genes. Again, there was close
agreement between dinucleotide mutability indexes for human VH
genes and those of murine intronic JH and Jk DNA (Fig. 2A and
Table I). This was demonstrated by the slope of their linear regression equaling 1 and their y-intercept falling within a 95% confidence interval of 0. In all cases GC and TA were the preferred
targets. The trinucleotide mutability indexes were also in close
agreement as shown in Fig. 2B and Table II. This consistent hierarchy of di- and trinucleotide mutability in all analyzed Ig sequences supports the idea that a common mutation mechanism acts
on heavy and light chain genes of both species regardless of
whether DNA is located within an intron or an exon encoding a V
region domain.
262
REGIONAL MUTABILITY IN Ab V GENES
Table II. Human and murine trinucleotide mutability indexes
Murine JH/Jk Intronica
Trinucleotide
Mutations
Nucleotides
Mut. Freq. (%)
Mutability
index
80
50
80
75
55
62
65
63
38
77
43
95
69
82
78
41
109
55
48
40
66
20
29
38
43
43
66
23
40
26
40
50
50
54
31
19
34
23
21
37
24
4
36
37
9
4
4
33
40
35
30
28
23
34
35
26
18
4
11
11
1
0
0
0
2.80*
2.71*
2.41*
2.19*
1.81*
1.74*
1.69*
1.65*
1.57*
1.56*
1.56*
1.54*
1.50*
1.49*
1.49*
1.43
1.36*
1.36
1.26
1.17
1.11
1.09
1.05
1.01
0.98
0.95
0.94
0.91
0.91
0.90
0.90
0.89
0.88
0.87
0.86
0.77
0.75
0.74
0.74
0.69
0.68
0.64
0.61*
0.59*
0.59
0.58
0.57
0.56*
0.55*
0.55*
0.55*
0.53*
0.52*
0.50*
0.48*
0.43*
0.42*
0.39
0.38*
0.33*
0.17
0.00
0.00
0.00
No. of
mutations
34
19
16
36
18
26
24
29
26
37
19
27
38
34
27
20
30
24
18
12
30
17
19
19
29
20
27
8
13
18
23
30
13
19
17
8
15
16
11
24
12
1
22
23
8
1
2
13
24
16
17
17
13
26
18
19
8
0
7
6
0
0
0
0
835
92,228
0.91
A/J 1 autoimmune 1 literature sequences from Smith et al.(31).
Sequences from Dorner et al.(35) and Dunn-Walters and Spencer(36).
*, Statistically significant by x2 test at p 5 0.01.
a
b
Mutability
index
3.08*
2.85*
2.15*
2.43*
1.61
1.97*
1.57
1.70*
1.72*
1.75*
1.45
1.39
1.64*
1.54
1.82*
1.34
1.39
1.37
1.30
0.81
1.15
1.26
1.50
0.75
1.27
1.29
1.05
0.73
0.73
1.11
0.89
0.89
0.74
0.74
1.06
0.65
0.63
0.79
0.75
0.82
0.67
0.80
0.76
0.71
0.74
0.32
0.61
0.57
0.61
0.51*
0.59
0.67
0.46*
0.70
0.61
0.66
0.42
0.00
0.42
0.33*
0.00
0.00
0.00
0.00
381
37,769
1.01
Murine Jk Intronica
No. of
mutations
Mutability
index
46
31
64
39
37
36
41
34
12
40
24
68
31
48
51
21
79
31
30
28
36
3
10
19
14
23
39
15
27
8
17
20
37
35
14
11
19
7
10
13
12
3
14
14
1
3
2
20
16
19
13
11
10
8
17
7
10
4
4
5
1
0
0
0
2.68*
2.70*
2.62*
2.02*
1.97*
1.64*
1.80*
1.61*
1.22
1.43
1.66
1.67*
1.34
1.48*
1.41
1.50
1.42*
1.37
1.27
1.46
1.08
0.53
0.67
1.36
0.65
0.79
0.90
1.06
1.04
0.61
0.88
0.83
0.97
0.97
0.70
0.88
0.87
0.59
0.71
0.52
0.67
0.64
0.46*
0.45*
0.20
0.80
0.54
0.56*
0.47*
0.58
0.50
0.40*
0.57
0.25*
0.40*
0.22*
0.42*
0.46
0.32
0.32*
0.26
0.00
0.00
0.00
454
54,459
0.83
Human VHb
No. of
mutations
Mutability
index
148
78
68
101
32
32
39
43
11
18
38
59
39
21
9
46
10
36
40
30
42
37
58
30
15
27
21
56
43
20
35
65
58
36
34
34
17
41
24
42
48
24
82
26
15
24
14
51
24
11
6
35
20
39
4
55
17
15
33
9
3
6
15
5
2.50*
2.33*
2.62*
2.18*
1.67*
1.52
2.54*
1.62*
0.52
0.84
1.26
1.29
1.24
1.83*
2.22
1.53*
0.80
1.13
1.12
0.74
1.14
0.71
1.69*
0.91
0.85
1.81*
0.59
1.18
0.89
0.82
1.54*
0.73*
1.20
1.02
1.69*
0.79
0.37*
0.71
0.74
0.56*
0.88
1.46
1.21
0.68
0.37*
0.62
0.57
0.98
0.57*
0.28*
0.50
0.77
0.46*
0.64*
0.95
0.76
0.73
0.99
0.65*
0.24*
0.32
0.57
0.57
0.43
738
14,811
4.98
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AGC
TAC
GTA
GCT
ATA
AAC
TAG
CTA
TGC
ATG
GCA
AAG
ACT
AAT
TAA
TAT
AAA
GAT
CAA
ACA
GAA
GCC
ATC
GGT
CTT
GTT
AGA
ACC
GTG
CAT
ATT
CTG
AGT
TGT
TTA
CAC
CTC
CCT
GGC
TGG
CCA
ACG
CAG
AGG
CCC
CCG
CGG
GAG
TCT
TGA
TTG
TCA
GTC
GGG
TTT
GGA
TTC
CGT
TCC
GAC
TCG
CGA
CGC
GCG
No. of
mutations
Murine JH Intronica
The Journal of Immunology
263
data indicate that positions within di- and trinucleotides are targeted to differing degrees (29, 44).
Predicted regional mutations in heavy and light chain V genes
Table III. Human and murine di- and trinucleotide mutability indexes by position
Murine JH/Jk Intronica
Oligonucleotide
First
position
Second
position
Third
position
Murine Jk Intronica
Murine JH Intronica
First
position
Second
position
Third
position
First
position
Second
position
Third
position
Human VHb
First
position
Second
position
Third
position
Most mutable
GC
TA
AC
AA
AT
2.06*
1.18
1.53*
1.25
1.76*
1.99*
2.50*
1.53*
1.69*
1.07
1.87*
0.99
1.61
1.19
1.87*
2.44*
2.74*
1.37
1.91*
0.94
2.22*
1.32
1.47
1.32
1.66*
1.53
2.42*
1.67*
1.64*
1.18
1.95*
1.67*
1.31
0.93
1.70*
1.48*
2.40*
1.09
1.92*
1.02
Least mutable
GA
GG
TT
TC
CG
0.70
0.33*
0.59*
0.41*
0.40
0.61*
0.78
0.40*
0.49*
0.40
0.89
0.35*
0.62
0.36*
0.43
0.75
0.94
0.43*
0.61
0.00
0.56*
0.29*
0.56*
0.46*
0.40
0.50*
0.59
0.37*
0.34*
0.60
0.46*
0.48*
0.91
0.51*
0.47*
0.74
0.83
1.11
0.71
0.63
Most mutable
AGC
TAC
GTA
GCT
ATA
1.68
1.46
2.71*
2.97*
1.08
3.36*
3.74*
1.08
2.80*
2.07*
3.36*
2.93*
3.43*
0.79
2.27*
1.90
1.35
2.02
3.25*
0.81
2.72*
4.50*
0.40
3.45*
1.61
4.62*
2.70
4.04*
0.61
2.42
1.57
1.57
3.07*
2.79*
1.28
3.84*
3.40*
1.35
2.33*
2.39*
2.62*
3.14*
3.43*
0.93
2.23*
1.47
2.51*
2.89*
3.83*
0.47
3.44*
2.24*
1.27
2.01*
2.19*
2.58*
2.24*
3.70*
0.71
2.35*
Least mutable
GGA
TTC
CGT
TCC
GAC
0.40*
0.62
0.59
0.52
0.09*
0.50
0.28*
0.59
0.31
0.27
0.40*
0.35
0.00
0.31
0.63
0.52
0.62
0.00
0.53
0.17
0.83
0.16
0.00
0.53
0.33
0.62
0.47
0.00
0.18
0.50
0.28
0.63
0.69
0.47
0.00
0.19
0.38
0.69
0.00
0.19
0.19
0.25
0.00
0.47
0.76
0.58
1.16
0.99
0.41
0.16*
0.62
0.51
1.39
0.65
0.40
1.07
0.51
0.60
0.89
0.16*
A/J 1 autoimmune 1 literature sequences from Smith et al.(31).
Sequences from Dorner et al.(35) and Dunn-Walters and Spencer(36).
*, Statistically significant by x2 test at p 5 0.01.
a
b
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FIGURE 2. Common hierarchy of mutability among di- and trinucleotides in V genes of humans and mice. Mutability indexes (obs/exp) for all
dinucleotides (A) and trinucleotides (B) were compared. The upper limit of
the 95% confidence interval of the slope of the linear regression for
trinucleotides is slightly ,1 (0.96).
To address the importance of DNA sequence in directing somatic
mutation, we first comprehensively analyzed di- and trinucleotide
sequence compositions of murine and human germline V region
genes. Human and murine germline-encoded genes were divided
into regions encoding FR and CDR based on the definitions of
Kabat (37) and Chothia (38 – 40). For each region in every category, we calculated a composite obs/exp mutability index. Our
analysis includes all available unmutated human and murine Ig
sequences: 47, 40, and 29 human heavy, k, and l genes and 72 and
42 murine heavy and k Ig genes, respectively, organized into 4780
regional sequence files.
The composite regional mutability indexes predicted for murine
and human VH genes are shown in Fig. 3. There is an excellent
agreement between results obtained with VH genes of the two species. With obs/exp mutability indexes .1, CDR1 and CDR2 in
both species are predicted to mutate the most when normalized for
length. In contrast, FR1 and FR2 are predicted to mutate the least,
while FR3 is predicted to mutate at an intermediate level. The
regional patterns calculated using the Kabat and Chothia CDR and
FR definitions are similar. Although modest in extent, the predicted regional mutability differences are remarkably consistent
among individual VH genes (data not shown) and regardless of
whether they are calculated using di- or trinucleotide mutability
indexes. This finding together with the large number of regions
examined and consistency between species suggest that the predicted regional mutability differences are not due to chance alone.
Statistical analysis of the data support this interpretation (two-way
ANOVA for comparing means with p , 0.0001).
Analysis of di- and trinucleotide compositions in light chains
yielded an unexpected regional mutability prediction in which FR2
is comparable to CDR1 and CDR2 (Fig. 4). Nearly identical regional
264
REGIONAL MUTABILITY IN Ab V GENES
FIGURE 3. Predicted regional mutability in human and murine germline VH genes. VH genes were divided into Kabat (A) and Chothia (B)
regional definitions. Regional mutability was calculated on the basis of diand trinucleotide compositions and their mutability indexes. The data are
reported as the obs/exp mutation ratio 6 SEM for each region. Error bars
are obscured in most cases by symbols.
trends were seen for human Vk, human Vl, and murine Vk genes,
with a remarkable consistency among individual light chain genes
(data not shown). Murine Vl genes were excluded because their
numbers were insufficient to permit statistical analysis. As with
the heavy chain genes, there was good agreement between results
obtained using di- and trinucleotide mutability indexes according
to either the Kabat or Chothia regional definition. Predicted
regional differences were statistically tested as before and were
significant ( p , 0.0001).
Comparing predicted and observed regional mutabilities
Our predictions of regional mutabilities are based solely on di- and
trinucleotide composition. To assess the importance of these short
sequences in directing mutation into a longer segment of DNA, we
compared the regional predictions to empirical data from somatically mutated V genes. To exclude potential bias due to cellular
selection, only somatic mutations within nonproductively rearranged V genes were analyzed. Only two available sets of human
VH sequences satisfied this important criterion, and no comparable
data were available for light chain genes. Empirical regional mutability indexes were determined by dividing the actual number of
mutations in each region by the expected quantity, assuming a
nondiscriminatory mechanism would randomly distribute mutations throughout the VH genes. Observed regional mutabilities in
these VH genes were compared with predicted regional mutabilities for germline-encoded correlates, such that the germline database was weighted according to the frequency with which each
gene was found in the database of mutated genes. As shown in Fig.
5, the results of these comparisons revealed a generally good
agreement between predicted and observed mutability patterns.
This was true for results obtained using both di- and trinucleotide
mutability indexes and according to the Kabat and Chothia regional definitions. However, the observed differences in mutability
among regions were more extreme than predicted. For example,
among the VH genes divided by the Kabat definition, CDR1 mutated 2.8 times more frequently than FR1, while it was predicted to
mutate only 1.5 and 1.2 more frequently on the basis of di- and
trinucleotide compositions, respectively. Thus, our predictions
were qualitatively, but not quantitatively, accurate.
To explain the quantitative discrepancy, we considered the possibility that some somatic mutations might be derived by gene
conversions involving unrearranged donor VH genes. Such a
mechanism might increase the proportion of mutations in segments
of rearranged VH DNA encoding CDR because VH germline sequence diversity is greatest in CDR-encoded DNA. With this in
mind, we compared the observed mutational distribution within a
k transgene construct (10) to mutational distribution predicted on
the basis of di- and trinucleotide composition. The transgene includes a 100-nt segment of DNA that contains repeated EcoRV/
PvuII restriction sites and that is unrelated to V region gene DNA.
Work by Storb et al. (17) had indicated that this segment of DNA
mutated disproportionally to its trinucleotide composition. The results in Fig. 6 confirm this and reveal that, as with the human VH
genes, we were able to qualitatively predict regional mutability
preferences from di- and trinucleotide composition, but as before,
the observed differences were more extreme than predicted. These
quantitative differences between predicted and observed mutations
in an artificial sequence are therefore unlikely to be due to mutagenesis by gene conversion.
Downloaded from http://www.jimmunol.org/ by guest on June 18, 2017
FIGURE 4. Predicted regional mutability in human and murine germline VL genes. Germline VL genes were divided into Kabat (A) and Chothia
(B) regional definitions. The data are reported as described in Fig. 3.
The Journal of Immunology
265
Discussion
FIGURE 5. Comparison of predicted and observed regional mutability
in human VH genes. Somatically mutated, nonproductively rearranged, human VH genes described by Dorner et al. (35) and Dunn-Walters and Spencer (36) were separated into regions according to Kabat (A) and Chothia
(B) definitions. Observed mutability indexes were determined and compared with expected mutability indexes calculated for germline correlates,
as described in the text. Data are reported as described in Fig. 3.
Comparing mutation distribution with nascent mRNA secondary
structure
To address the possibility that mRNA secondary structure amplifies mutagenesis in CDR, we adopted an approach used by Storb
et al. (17) to predict the stability of mRNA secondary structure
within 51-nt-long regions at six-nt steps for germline correlates of
the mutated VH genes described above. Fig. 7A shows a comparison of average predicted mRNA secondary structure and mutation
distribution for 60 nonproductively rearranged human VH genes
encompassing four families. Segments encoding CDR1 and CDR2
were most mutable, and substantial mRNA secondary structure
occurred 59 of each. However, for CDR1, mRNA stability peaked
about 30 bases before the peak of mutation, whereas for CDR2,
peaks of mRNA stability and mutation nearly coincided. Furthermore, while FR3 was substantially mutated, a distinct decrease in
the predicted mRNA stability occurred within this region. Finally,
FR1 possessed considerable mRNA secondary structure yet contained few somatic mutations. A correlation coefficient of 0.09 and
a linear regression with a p value of 0.55 indicated no significant
linear correlation between observed mutability and the position of
predicted stability of mRNA secondary structure (data not shown).
To further investigate the relationship between mutational distribution and mRNA secondary structure, we analyzed two VH genes
for which the most mutational data were available (235 and 172
mutations in 18 and 12 sequences for 4 –34 and 5–51, respectively). As shown in Fig. 7, C and D, there was no obvious linear
correlation between predicted mRNA secondary structure and mutation frequency. However, it is intriguing that the pattern of
mRNA secondary structure stability was somewhat conserved
even among VH genes belonging to different families (Fig. 7B).
We report results of a comparative analysis of di- and trinucleotide
target preferences in human and mouse Ab V genes as well as an
extensive analysis of predicted and observed regional mutability
patterns in human VH genes. The shared hierarchy of di- and trinucleotide target mutabilities among H and L chain V genes in mice
and humans suggests that a common mutation mechanism acts on
all Ig genes of both species. This is supported by the excellent
agreement between actual regional mutability patterns in human
VH genes and mutability patterns in human VH genes predicted
using di- and trinucleotide mutability indexes derived from sequences of mouse Jk and JH intronic DNA. While not entirely
surprising, the consistency in the mutation bias is an important
result because distinct regulatory elements differentially control
developmental expression of H and L chain genes and because the
intron and 39 L chain enhancers are essential for full mutation,
while analogous H chain enhancers are not sufficient (15, 18 –24).
We cannot entirely exclude the possibility that distinct mutation
mechanisms operate on H and L chain genes and that the two only
share elements that generate sequence-specific bias. For example,
observed somatic mutations are ones that have been fixed and
propagated by B cells. Accordingly, sequence-specific mutation
bias could be due to a bias in nucleotide repair rather than to a bias
in the initial mutagenic event. Nevertheless, our interpretation is
the most straightforward given the nature and consistency of the
results.
Predicted and observed higher mutability of DNA encoding VH
CDR vs FR suggests that evolution has carved the VH sequence to
optimize beneficial effects of somatic mutation while minimizing
potential detrimental effects during Ag-driven somatic diversification. This view is consistent with the observations of Chang and
Casali (45) that codon use by CDR is such that random mutations
will produce amino acid changes at an inordinately high frequency
and with a similar finding by Kepler (46), who also took into
consideration intrinsic codon mutability. Kepler’s results show the
same general mutability trend as ours, except in FR2 of light
chains, where he found no differential localization of synonymous
codons that preferentially mutate to produce amino acid changes,
while we predicted this region to be highly mutable (46). These
previous studies have been limited to in-frame codon analysis
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FIGURE 6. Predicted and observed regional mutability in a k transgene.
The sequence data are from the report by Storb et al. (17) using a k transgene with an artificial insert containing repeated EcoRV/PvuII restriction
sites. Observed and predicted mutability indexes for the artificial insert
(608 –707) and murine k Ig sequences were determined as described in the
text. Data are reported as described in Fig. 3.
266
REGIONAL MUTABILITY IN Ab V GENES
without evidence that the mutation mechanism has a frame of reference. Our analysis is thus unique in that all di- and trinucleotides
were considered regardless of reading frame.
On the basis of di- and trinucleotide composition, the sequences
encoding light chain FR2 were predicted to mutate more frequently than those for CDR2. This was true for humans and mice
and for k and l light chain genes. At present, there are insufficient
sequence data from nonproductively rearranged light chain genes
to permit a test of this unexpected result. However, quantitative
differences between predicted and actual regional mutabilities in
VH genes suggest that other undefined factors may influence mutational accumulation. Thus, it will be interesting to determine
whether regional trends in light chain mutability follow predictions
based only on short sequence composition.
We considered several possible explanations for the quantitative
discrepancy between predicted and observed regional mutabilities.
The mutation mechanism might recognize oligonucleotide motifs
longer than trinucleotides. However, this is difficult to reconcile
with the consistent hierarchy of di- and trinucleotide mutation indexes observed for different types of V genes in both coding and
noncoding regions for two species as well as the consistent positional mutation preferences among the different sequence types.
We have conducted a more limited regional predictive analysis
using tetranucleotide sequences that have been proposed to be
most mutable by other investigators (28, 47), including RGYW, as
well as sequences composed of overlapping mutation-prone
trinucleotides (AGCT, GTAC, CTAC, GCTA, TAGC, GTAG).
The results of this analysis failed to resolve the quantitative discrepancy between predicted and observed regional mutabilities
(data not shown). Furthermore, using alignment algorithms on the
entire human database of germline V genes, we have been unable
to identify a new motif that is preferentially located in regions of
high or low mutability. Again without success, we tested the possibility that only some triplets were targets for mutagenesis by
performing the predictive analysis with selected trinucleotides of
highest mutability with or without regard to reading frame (data
not shown). Finally, the quantitative discrepancy between predicted and observed regional mutation in the k transgene containing the artificial insert argues against a supplemental mutagenesis
mechanism involving a recombinational process with unrearranged donor V genes.
Storb et al. (17) found a region of secondary structure stability
in RNA located 40 nt downstream of a highly mutable segment in
their k transgene. From this observation they proposed that mutations are directed into a region by pausing of the RNA polymerase
due to secondary structures within the nascent RNA, and the DNA
sequence is responsible for the fine specificity of the mutation
mechanism. However, our observations are not consistent with this
model, in that we found no linear correlation between areas of
observed high mutability in human VH genes and positions of predicted RNA secondary structure stability. Yet, we cannot rule out
the possibility that RNA secondary structure plays a more elusive
and complex role than we were able to detect. We note, for example, that there appears to be a somewhat recurrent pattern of
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FIGURE 7. Observed mutation distribution in human VH genes compared with predicted mRNA secondary structure: A, composite; B, composite mRNA
stability among human VH families; C, gene 4 –34; and D, gene 5–51. The predicted stability of mRNA secondary structure for 51-nt intervals at steps of
6 nt was determined using the online version of Mfold (line 6 SEM) (43). For each 6-nt segment, we determined the mRNA folding energy by averaging
the folding energies of the 51-nt interval whose 39 end coincided with the 6-base segment under consideration and the two immediately flanking intervals.
This analysis correlates a 6-nt segment with upstream RNA secondary structure that has the potential to influence the polymerase complex. Kabat and
Chothia CDR are indicated.
The Journal of Immunology
Acknowledgments
We thank Drs. Dorner and Spencer for supplying their databases, and
Prasanna Jena, Andy Liu, Chris Snyder, Amanda Guth, Diana Smith, Bristol Sorenson, and Xianghua Zhang for their insights and for critically reading the manuscript.
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predicted secondary structure in mRNA for VH genes, even among
members of different families (Fig. 7B). If very short or long segments of RNA secondary structure were influencing mutagenesis,
these would not necessarily be detected by our analysis, which was
predicated on stability within 51-base-long segments. Our analysis
does not take into consideration the possibility that secondary substructures within this length interval or superstructures formed by
spatially separated regions of RNA could be involved in mutagenesis. As suggested by other investigators, other components, such
as palindromes and repeats (28, 48, 49), could be acting together
with oligonucleotide motifs to direct mutations. Palindromes and
repeats are abundant in the most mutable region of the murine
artificial transgene, but are virtually absent from adjacent regions.
This distribution might account for the more extreme discrepancies
between observed and expected regional mutabilities found for the
artificial transgene compared with those found for human VH
genes.
Our findings are perhaps most consistent with the accumulation
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accurately predict the pattern, but not the number, of mutations
within a region. Despite quantitative issues, our results indicate
that short nucleotide sequences play an important role in distributing somatic mutations within V genes.
267
268
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