The Evolutionary Value of Recombination
Is Constrained by Genome Modularity
Darren P. Martin1*, Eric van der Walt2, David Posada3, Edward P. Rybicki2
1 Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa, 2 Department of Molecular and Cell Biology, University of Cape
Town, Cape Town, South Africa, 3 Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain
Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered
recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV), we experimentally demonstrate
that fragments of genetic material only function optimally if they reside within genomes similar to those in which they
evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic
interaction networks within which genome fragments must function. There is a striking correlation between our
experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory
maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this
virus and probably for genomes in general.
Citation: Martin DP, van der Walt E, Posada D, Rybicki EP (2005) The evolutionary value of recombination is constrained by genome modularity. PLoS Genet 1(4): e51.
Genetic recombination may predate the evolution of
cellular life  and is the basis of ubiquitous biological
processes such as DNA repair and sexual reproduction. The
combinatorial nature of recombination can provide organ-
isms with vastly more evolutionary options than are available
through mutation alone [2–4]. However, kingdom-wide
analyses of bacterial recombination  and DNA-shuffling
studies [6,7] have indicated that the evolutionary value of
recombination can vary depending on both the genes and the
sub-gene modules transferred. In bacteria, the complexity
hypothesis has been proposed to explain an imbalance in
detectable informational and operational gene transfers
between species . Similarly, the schema hypothesis has
been proposed to explain patterns of sequence mosaics
observed in DNA-shuffling experiments . Although the
complexity hypothesis concerns genes within the context of
genomes, the schema hypothesis concerns amino acids within
the context of proteins. Both hypotheses are conceptually
related and propose that the functionality of sequence
fragments in foreign genetic backgrounds is inversely
correlated with the complexity of interaction networks within
which they must function.
Here we provide experimental support for these hypoth-
eses using the small single stranded plant DNA virus, Maize
streak virus (MSV; Geminiviridae, Mastrevirus) as a model
organism to investigate the effect of genomic recombination
on viral fitness.
The MSV genome is approximately 2,690 nucleotides long
and contains only three genes and two intergenic regions. We
constructed 18 paired reciprocal recombinants (36 genomes
in total) from four pairs of MSV isolates sharing genome-wide
nucleotide sequence identities of 98%, 95%, 89%, and 78%
. Recombinant viruses were constructed in which the three
genes and two intergenic regions of MSV were reciprocally
exchanged between the four pairs of viruses (Figure 1).
As a correlate of viral fitness, we determined the induced
chlorotic leaf areas (ICLA) of parental and recombinant
viruses in infected maize plants . The relationship between
symptom severity and fitness is complex for most pathogens.
However, MSV populates mesophyll cells within precisely
defined chlorotic lesions of infected maize leaves  and the
chlorotic surface area of an infected leaf is positively
correlated with the total amount of viral DNA within the
leaf [10,11]. The correlation between MSV pathogenicity and
fitness is also evident in the greater geographical distribution
and incidence of more pathogenic MSV genotypes relative to
less pathogenic genotypes .
For each pair of reciprocal recombinants, we defined the
recombination tolerance index (Ti) as the average ICLA of
the recombinant pair divided by the average ICLA of their
parental viruses. If reciprocally exchanged sequence frag-
ments continue to function as well within recombinant
genomes as they did in their original genomic backgrounds,
we expect that the average ICLA of reciprocal pairs should be
identical to that of their parental pairs—i.e., we would expect
a Ti ¼ 1.0. Conversely a drop in Ti below 1.0 would indicate
that reciprocally exchanged sequences might not function as
well in their new genomic backgrounds as they did in their
In 17 out of 18 recombination experiments, the average
Received August 16, 2005; Accepted September 22, 2005; Published October 21,
Copyright: ? 2005 Martin et al. This is an open-access article distributed under the
terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author
and source are credited.
Abbreviations: ICLA, induced chlorotic leaf area; LIR, long interegenic region; MSV,
Maize streak virus; RID, recombination-induced diversification; SIR, short intergenic
region; Ti, tolerance index
Editor: Greg Gibson, North Carolina State University, United States of America
* To whom correspondence should be addressed. E-mail: email@example.com
A previous version of this article appeared as an Early Online Release on
September 22, 2005 (DOI: 10.1371/journal.pgen.0010051.eor).
PLoS Genetics | www.plosgenetics.orgOctober 2005 | Volume 1 | Issue 4 | e51 0475
ICLA of reciprocal recombinant pairs was lower than that of
their parental viruses (i.e., Ti , 1). Values of Ti generally
decreased with increasing divergence of exchanged sequen-
ces, with a distinct rate of decrease for each genome region
exchanged (Figure 2). Given equal degrees of divergence, it
seems that the short intergenic region (SIR) and movement
protein gene (MP) function better in foreign genetic back-
grounds than do the replication-associated protein gene
(Rep), the coat protein gene (CP), or the long intergenic region
(LIR). In other words, the SIR and MP appear more modular
than the other regions of the genome.
To better understand these differences in modularity, we
examined the network of known direct protein–protein and
protein–DNA interactions that occur during an MSV
infection of maize (Figure 3) [13–22]. Whereas every other
genome component or its expression product participates in
multiple specific protein–DNA and/or protein–protein inter-
actions with other virus components, the SIR apparently
interacts only with host transcription and DNA replication
factors . The only known specific interaction of the MP
with another virus component is a protein–protein inter-
action with the CP gene .
To determine whether the known network of interactions
occurring during an MSV infection is anticipated by our Ti
data, it was necessary to first extract a relative modularity
score for each of the MSV genome regions from the Ti plots.
To do this we fitted quadratic equations to the plots (see
Figure 2) to estimate similarly tolerable degrees of recombi-
nation-induced diversification (RID) in the five genomic
regions. Our aim in fitting a line to the Ti plots was to
objectively estimate degrees of RID tolerated in the different
genome regions at particular Ti values. For example, fitting
quadratics to the plots and picking a Ti value of 0.9
(reciprocal recombinants have an average ICLA 90% that of
their parents) the corresponding estimates of tolerable
recombination induced diversification in the SIR, MP, CP,
LIR, and Rep are 15.3%, 8.3%, 2.7%, 3.3%, and 3.8%
respectively. To avoid any biases due to ‘‘cherry picking’’
the Ti values we used to compare the different genome
regions, we examined estimated recombination tolerances
over the range of Ti values between 0.99 and 0.7. There is
good correlation between the number of known MSV
intergenome component protein–protein and protein–DNA
interactions for different genome regions (SIR¼1, MP¼2, CP
¼ 5, LIR ¼ 4, and Rep ¼ 4) and recombination tolerance
estimated for these same regions over the entire Ti range
between 0.94 and 0.7 (Pearson’s R2. 0.87, p , 0.05,
Spearman’s rho corrected for ties ¼?0.975, p ¼ 0.051).
Analysis of Natural Recombinants
To investigate whether experimentally determined Ti
values provide any insights into real processes that influence
the survival of recombinants in nature, we examined all
available Mastrevirus sequences in GenBank for evidence of
recombination. In each of the five genomic regions (LIR, MP,
CP, SIR, and Rep), we identified evidence for unique
recombination events involving MSV isolates or the closely
Figure 1. Laboratory Constructed MSV Recombinants and Their Relative
Fitness (as Measured by ICLAs) in Maize
Five genome regions corresponding to the three MSV genes (MP, CP, and
Rep) and two intergenic regions (LIR and SIR) were reciprocally
exchanged between four pairs of MSV isolates (MSV-Mat/MSV-Kom,
MSV-Mat/MSV-R2, MSV-Mat/MSV-VW, and MSV-Kom/MSV-Set). Genome-
wide sequence identities are indicated. SD, standard deviation.
PLoS Genetics | www.plosgenetics.orgOctober 2005 | Volume 1 | Issue 4 | e510476
Genome Modularity and Recombination
Genetic exchange between organisms, called recombination, occurs
in all biological kingdoms and is also common in viruses in which it
may threaten the long-term control of important human pathogens
such as HIV and influenza. Although recombination can produce
advantageous gene combinations, bioinformatic analyses of bacte-
rial genomes have suggested that recombination is not well
tolerated when it involves exchanges of genes that interact with a
lot of other genes. Using laboratory-constructed recombinants of a
small plant virus called MSV, Martin and co-workers provide the first
direct experimental evidence that the evolutionary value of
exchanging a genome fragment is constrained by the number of
ways in which the fragment interacts with the rest of the genome.
They note that fitness losses suffered by artificial MSV recombinants
increase with decreasing parental relatedness. Furthermore, these
losses accurately anticipate the patterns of genetic exchange
detectable in natural MSV recombinants, suggesting that they
accurately reflect the impact of deleterious selection on natural
isolates of the virus.
related African streak viruses. We only retained evidence of
recombination events detectable in genomes with proven
viability (as determined by the existence of infectious clones
of these genomes). For each recombination event involving
two identifiable parental sequences and comprising two easily
identifiable breakpoints both unambiguously within one of
the five defined genomic regions, we used the identified
parental sequences to infer the number of nucleotide
differences between the transferred sequence and the
sequence it replaced (Table 1). The greatest number of
nucleotide changes observed in a single recombination event
in each of the five genomic regions provides a gross estimate
of the maximum parental divergence tolerated in nature. The
set of values thus determined (SIR¼15.0%, MP¼7.7%, CP¼
3.2%, LIR ¼ 5.4%, and Rep ¼ 3.9%) was significantly
correlated with equivalent sets of values derived from the
quadratic regressions shown in Figure 2 (Figure 4; Pearson’s
R2. 0.96, p , 0.01, Spearman’s rho ¼ 0.9, p ¼ 0.037 over the
Ti range 0.95–0.7).
By demonstrating a negative correlation between the
relative modularity of defined genomic regions and the
complexity of interactions in which they are involved we have
provided experimental support for the complexity hypothesis
. This hypothesis was proposed to explain the disparity in
informational (those involved in transcription, translation,
and related processes) and operational (those involved in
housekeeping) gene transfer rates in bacteria. It states that
because informational genes are generally involved in more
complex interactions than operational genes, they are less
likely to continue functioning well after horizontal transfer.
The progressive decrease in tolerance of recombination
with increasing divergence of exchanged sequences observed
in Figure 2 has strong parallels with parental sequence
imbalances observed in ‘‘family shuffling’’ variants of DNA-
shuffling experiments . The functional genes produced by
shuffling three or more distinct sequences (i.e., 60%–85%
identical) are usually derived predominantly from either one
sequence or combinations of the most similar sequences
[2,6,23,24]. The schema hypothesis proposes that these
imbalances are due to the probability of recombinant
protein-fold disruption increasing with increasing divergence
of parental sequences [6,7]. We shuffled entire intergenic
regions and genes, and therefore the effect we observed
cannot be explained directly in terms of the schema
hypothesis. We have, however, provided empirical evidence
for a whole-genome analogue of this hypothesis: The
probability of the normal network of intragenome inter-
actions being disrupted by recombination increases with
increasing divergence of the exchanged fragments.
The successful inheritance of genomic fragments through
recombination is expected to depend on the maintenance of
important intragenome interactions. After all, the exchange
of a genome fragment could be seen as a simultaneous
introduction of multiple mutations. Negative or purifying
selection should remove those recombinants that break the
epistatic interactions that define the architecture of a
particular genome, whereas genetic drift might permit the
survival and spread of ‘‘neutral’’ recombinants. Alternatively,
positive selection should favour the spread of rare recombi-
nants with improved genomic interactions. The genomic
interactions in the (natural) parental viruses used in these
experiments have most likely been optimised through
selection over long evolutionary periods. None of the
recombinants generated from these viruses was more fit than
the fitter of its parents, which is expected if negative selection
Figure 3. The Network of Known Protein–Protein and Protein–DNA
Interactions during a MSV Infection of Maize
Rep/RepA indicates the two alternative expression products of the
replication-associated protein gene. Solid lines represent specific
protein–protein interactions [14,16–18,21,22], dotted lines represent
specific protein–DNA interactions [14,16,19–21], and dashed lines
indicate CP-DNA interactions of unknown specificity [18–20,22]. For
protein–DNA interactions, arrows point from the protein component to
the DNA component of the interactions. Rep interacts with the LIR at
three distinct sites . CP and Rep form oligomers (solid circular arrows)
[14,22]. Although CP must interact with the rest of the genome
(including its own gene) during encapsidation, the sequence specificity
of these interactions is unknown.
Figure 2. Tolerance of Recombination in MSV Differs According to the
Genome Region Involved and the Degree of Divergence between
Each plotted point represents a Ti value calculated as the average fitness
of a pair of recombinant viruses with reciprocally exchanged MP genes
(cyan circles), CP genes (orange diamonds), Rep genes (blue inverted
triangles), SIR (red triangles), or LIR (green squares) divided by the
average fitness of their parental viruses. Error bars represent the standard
deviations of Ti values. Curved lines represent quadratic regressions of Ti
values against parental SIR, MP, LIR, CP, and Rep nucleotide sequences.
PLoS Genetics | www.plosgenetics.orgOctober 2005 | Volume 1 | Issue 4 | e51 0477
Genome Modularity and Recombination
is the dominant force that now maintains the integrity of
The relative degree of modularity that we demonstrated
experimentally for each genome component appears to be
reflected in the recombination events detected within the
same regions in natural viruses represented in GenBank. This
correlation is surprising because the natural recombinants—
unlike the recombinants we constructed in the laboratory—
involve exchanges of fragments of genes or intergenic
regions. Such exchanges may disrupt intraprotein or intra-
intergenic region interactions as well as interaction networks
amongst whole genes and intergenic regions. Survival of the
natural viruses with detectable recombination events in
coding regions presumably depended on their inheritance
of sequences that did not overly disrupt either intraprotein
or intergene/intergenic region interaction networks; survival
of natural intergenic region recombinants and those we
generated in the laboratory would have been subject only to
the latter constraint. The correlation between our exper-
imental results and the inferred natural recombinants may
indicate that maintenance of intergenome component
interactions is the principal determinant of recombination
tolerance (at least for MSV and closely related viruses).
Alternatively, a requirement for the preservation of both
intergenome component, and intragene, interaction net-
works has a net effect that is difficult to distinguish from
either constraint operating alone.
We have provided experimental support for the complexity
hypothesis by demonstrating a relationship between the
relative modularity of defined genomic regions and the
complexity of interactions in which they are involved. The
striking correlation between our experimental results and the
types of recombination observed in nature lends credence to
the notion that these detectable modularity differences are
evolutionarily relevant. Our results also suggest that the
degree of similarity between an inherited sequence and the
sequence it replaces is an important additional determinant
of recombinant fitness. Whereas recombination can substan-
tially increase the evolutionary options of an organism, the
Table 1. Evidence of Recombination within Five Defined Regions of Publicly Available African Streak Virus Genome Sequences
3.30 3 10?03
9.83 3 10?07
1.72 3 10?05
5.76 3 10?03
1.90 3 10?03
7.50 3 10?03
1.98 3 10?17
4.52 3 10?05
3.94 3 10?03
1.07 3 10?05
1.40 3 10?03
7.88 3 10?03
3.36 3 10?03
7.30 3 10?03
1.84 3 10?03
1.96 3 10?02
3.28 3 10?02
1.36 3 10?02
2.95 3 10?05
2.60 3 10?04
4.37 3 10?03
aCo-ordinates are relative to the origin of virion strand replication.
RIP, recombination-induced polymorphism.
Figure 4. The Experimentally Determined Relative Recombination
Tolerance of Five MSV Genomic Regions Is Highly Correlated with
Values Inferred from Nature
We used the quadratic regressions presented in Figure 2 to derive
experimental estimates of similarly tolerable degrees of RID in the five
genomic regions over a range of Ti values between 0.99 and 0.70 (290
values at 0.01 intervals). Using a range of Ti values avoids any biases that
might occur due to inadvertently choosing particularly poor/favourable
Ti values for estimating similarly tolerable degrees of RID from the
experimental data. For example, the set of similarly tolerable degrees of
RID calculated when Ti¼0.9 is 15.3%, 8.3%, 2.7%, 3.3%, and 3.8% for the
SIR, MP gene, CP gene, LIR, and Rep gene, respectively. Each of the 290
sets of values thus determined was linearly regressed against the set of
values for the maximum tolerable RID inferred for the same five regions
from an examination of natural recombinants (15.0%, 7.7%, 3.2%, 5.4%,
and 3.9%, for SIR, MP, CP, LIR, and Rep, respectively). R2values
determined for these 290 regressions are plotted against their
corresponding Ti values (solid line). The correlation is significant (broken
line¼R2value corresponding to a p-value , 0.01) over the Ti range 0.95–
0.7 (Pearson’s R2. 0.96, p , 0.01; Spearman’s rho ¼ 0.9, p ¼ 0.037).
PLoS Genetics | www.plosgenetics.org October 2005 | Volume 1 | Issue 4 | e510478
Genome Modularity and Recombination
obligatory maintenance of co-evolved interaction networks
may severely restrict its evolutionary value.
Materials and Methods
Recombinant construction. We have previously described the
construction and symptom analysis of 15 reciprocal recombinant
pairs for the MSV isolates MSV-Mat, MSV-Kom, MSV-R2, and MSV-
VW . PCR mutagenesis was used to introduce NcoI restriction sites
immediately upstream of the CP gene start codons of the MSV
isolates MSV-Set and MSV-Kom to obtain SNco and KNco,
respectively. Reciprocal MP gene recombinants were obtained by
exchanging BamHI-NcoI restriction fragments containing the entire
MP between MSV-SNco and MSV-KNco. Reciprocal CP recombinants
were obtained by exchanging NcoI-NcoI restriction fragments
containing the entire CP between MSV-SNco and MSV-KNco.
Agroinfectious partially dimeric clones of recombinant viruses were
constructed as previously described .
Fitness testing. The fitness of recombinant and parental viruses as
indicatedby ICLA was determined in maize by agroinoculation of 3-d-
old cv. Jubilee seedlings with image analysis quantification of ensuing
disease symptoms . An ICLA score for each virus was determined by
averaging the percentage chlorotic areas determined on leaves two
through six for between three and 14 symptomatic plants in each of
three to seven replicated agroinoculation experiments.
Recombination detection. All available Mastrevirus sequences were
gap extension penalties of 12 and 6, respectively. Identification of
potential recombinant and parental sequences, and localisation of
possible recombination breakpoints was carried out using the RDP
, and SisterScan  methods as implemented in RDP2 . The
a Bonferroni corrected p-value cutoff of 0.05, and a requirement that
any potential event be detectable by two or more methods.
The GenBank (http://www.ncbi.nlm.nih.gov/Genbank) accession num-
bers for the genome sequences are CSMV (NC001466), DSV
(NC001478), MiSV (NC003379), MSV-Ama (AF329878), MSV-Gat
(AF329879), MSV-Jam (AF329887), MSV-K (X01089), MSV-KA
(AF329885), MSV-Km (AF395891), MSV-Kom (AF003952), MSV-MakD
(AF329884), MSV-Nig (X01633), MSV-Pat (AF329888), MSV-Raw
(AF329889), MSV-Reu (X94330), MSV-SA (NC001346), MSV-Sag
(AF329880), MSV-Set (AF007881), MSV-Tas (AF239962), MSV-VM
(AF239961), MSV-VW (AF239960), PanSV-Kar (NC001647), PanSV-
Ken (X60168), SSEV-Ben (AF039529), SSRV (NC004755), and SSV-N
We would like to thank the South African National Research
Foundation and National Bioinformatics Network for funding this
work. DP is supported by the Ramo ´n y Cajal Programme of the
Spanish Government, and funded by grants R01-GM55276 from the
United States National Institutes of Health, and BFU2004–02700
from the Spanish Education and Science Ministry (MEC).
Competing interests. The authors have declared that no competing
Author contributions. DPM, EVDW, and EPR conceived and
designed the experiments. DPM, EVDW, and EPR performed the
experiments. DPM, EVDW, DP, and EPR analyzed the data. DPM
contributed reagents/materials/analysis tools. DPM, EVDW, DP, and
EPR wrote the paper.
1.Lehman NA (2003) A case for the extreme antiquity of recombination. J
Mol Evol 56: 770–777.
2.Crameri A, Raillard SA, Bermudez E, Stemmer WP (1998) DNA shuffling of
a family of genes from diverse species accelerates directed evolution.
Nature 391: 288–291.
3. Drummond DA, Silberg JJ, Meyer MM, Wilke CO, Arnold FH (2005) On the
conservative nature of intragenic recombination. Proc Natl Acad Sci U S A
4. Stemmer WPC (1994) Rapid evolution of a protein in vitro by DNA
shuffling. Nature 370: 389–391.
5.Jain R, Rivera MC, Lake JA (1999) Horizontal gene transfer among
genomes: The complexity hypothesis. Proc Natl Acad Sci U S A 96: 3801–
6.Meyer MM, Silberg JJ, Voigt CA, Endelman JB, Mayo SL, et al. (2003)
Library analysis of SCHEMA-guided protein recombination. Prot Sci 12:
7.Voigt CA, Martinez C, Wang ZG, Mayo SL, Arnold FH (2002) Protein
building blocks preserved by recombination. Nat Struct Biol 9: 553–558.
8.Martin DP, Rybicki EP (2002) Investigation of Maize streak virus
pathogenicity determinants using chimaeric genomes. Virology 300: 180–
9.Lucy AP, Boulton MI, Davies JW, Maule AJ (1996) Tissue specificity of Zea
mays infection by maize streak virus. Mol Plant Microbe Interact 9: 22–31.
10. Schnippenkoetter WH, Martin DP, Willment JA, Rybicki EP (2001) Forced
recombination between distinct strains of Maize streak virus. J Gen Virol
11. Shepherd DN, Martin DP, McGivern DR, Boulton MI, Thomson JA, et al.
(2005) A three-nucleotide mutation altering the Maize streak virus Rep
pRBR-interaction motif reduces symptom severity in maize and partially
reverts at high frequency without restoring pRBR-Rep binding. J Gen Virol
12. Martin DP, Willment JA, Billharz R, Velders R, Odhiambo B, et al. (2001)
Sequence diversity and virulence in Zea mays of Maize streak virus isolates.
Virology 288: 247–255.
13. Boulton MI (2002) Functions and interactions of mastrevirus gene
products. Phys Mol Plant Path 5: 243–255.
14. Castellano MM, Sanz-Burgos AP, Gutierrez C (1999) Initiation of DNA
replication in a eukaryotic rolling-circle replicon: Identification of multi-
ple DNA-protein complexes at the geminivirus origin. J Mol Biol 290: 639–
15. Dickinson VJ, Halder J, Woolston CJ (1996) The product of maize streak
virus ORF V1 is associated with secondary plasmodesmata and is first
detected with the onset of viral lesions. Virology 220: 51–59.
16. Donson J, Morris-Krsinich BA, Mullineaux PM, Boulton MI, Davies JW
(1984) A putative primer for second-strand DNA synthesis of maize streak
virus is virion-associated. EMBO J 3: 3069–3073.
17. Horvath GV, Pettko-Szandtner A, Nikovics K, Bilgin M, Boulton M, et al.
(1998) Prediction of functional regions of the maize streak virus
replication-associated proteins by protein-protein interaction analysis.
Plant Mol Biol 38: 699–712.
18. Liu H, Boulton MI, Oparka KJ, Davies JW (2001) Interaction of the
movement and coat proteins of Maize streak virus: Implications for the
transport of viral DNA. J Gen Virol 82: 35–44.
19. Liu H, Boulton MI, Thomas CL, Prior DA, Oparka KJ, et al. (1999) Maize
streak virus coat protein is karyophyllic and facilitates nuclear transport of
viral DNA. Mol Plant Microbe Interact 12: 894–900.
20. Liu H, Boulton MI, Davies JW (1997) Maize streak virus coat protein binds
single- and double-stranded DNA in vitro. J Gen Virol 78: 1265–1270.
21. Nikovics K, Simidjieva J, Peres A, Ayaydin F, Pasternak T, et al. (2001) Cell-
cycle, phase-specific activation of Maize streak virus promoters. Mol Plant
Microbe Interact 14: 609–617.
22. Zhang W, Olson NH, Baker TS, Faulkner L, Agbandje-McKenna M, et al.
(2001) Structure of the Maize streak virus geminate particle. Virology 279:
23. Aharoni A, Gaidukov L, Yagur S, Toker L, Silman I, et al. (2004) Directed
evolution of mammalian paraoxonases PON1 and PON3 for bacterial
expression and catalytic specialization. Proc Natl Acad Sci U S A 101: 482–
24. Joern JM, Meinhold P, Arnold FH (2002) Analysis of shuffled gene libraries.
J Mol Biol 316: 643–656.
25. Lee C, Grasso C, Sharlow MF (2002) Multiple sequence alignment using
partial order graphs. Bioinformatics. 18: 452–464.
26. Martin D, Rybicki E (2000) RDP: Detection of recombination amongst
aligned sequences. Bioinformatics 16: 562–563.
27. Padidam M, Sawyer S, Fauquet CM (1999) Possible emergence of new
geminiviruses by frequent recombination. Virology 265: 218–225.
28. Martin DP, Posada D, Crandall KA, Williamson CA (2005) A modified
bootscan algorithm for automated identification of recombinant sequences
and recombination breakpoints. AIDS Hum Retro 21: 98–102.
29. Smith JM (1992) Analyzing the mosaic structure of genes. J Mol Evol 34:
30. Martin DP, Williamson C, Posada D (2005) RDP2: Recombination detection
and analysis from sequence alignments. Bioinformatics 21: 260–262.
31. Gibbs MJ, Armstrong JS, Gibbs AJ (2000) Sister-scanning: a Monte Carlo
procedure for assessing signals in recombinant sequences. Bioinformatics
PLoS Genetics | www.plosgenetics.orgOctober 2005 | Volume 1 | Issue 4 | e51 0479
Genome Modularity and Recombination