Proc. Natl. Acad. Sci. USA
Vol. 95, pp. 5094–5099, April 1998
Evolution
Toward a resolution of the introns early͞late debate: Only phase
zero introns are correlated with the structure of ancient proteins
(introns-early͞introns-late͞modules)
SANDRO J. DE SOUZA, MANYUAN LONG, ROBERT J. KLEIN, SCOTT ROY, SHIN LIN, AND WALTER GILBERT*
Department of Molecular and Cellular Biology, The Biological Laboratories, Harvard University, Cambridge, MA 02138
Contributed by Walter Gilbert, February 25, 1998
ABSTRACT We present evidence that a well defined
subset of intron positions shows a non-random distribution in
ancient genes. We analyze a database of ancient conserved
regions drawn from GenBank 101 to retest two predictions of
the theory that the first genes were constructed by exon
shuffling. These predictions are that there should be an excess
of symmetric exons (and sets of exons) flanked by introns of
the same phase (positions within the codon) and that intron
positions in ancient proteins should correlate with the boundaries
of compact protein modules. Both these predictions are
supported by the data, with considerable statistical force (P
values < 0.0001). Intron positions correlate to modules of
diameters around 21, 27, and 33 Å, and this correlation is due
to phase zero introns. We suggest that 30–40% of present day
intron positions in ancient genes correspond to phase zero
introns originally present in the progenote, while almost all of
the remaining intron positions correspond to introns added,
or moved, appearing equally in all three intron phases. This
proposal provides a resolution for many of the arguments of
the introns-early͞introns-late debate.
The rapid expansion of knowledge of DNA sequences, rising
a factor of 10 every 5 years, has now reached the point where
one can survey with great statistical power the intron spectrum
of genes. This has enabled us to create critical tests of
speculations about the role of introns and their history by
studying ancient conserved genes, whose protein products are
conserved between prokaryotes and eukaryotes. Such genes
have no introns in their prokaryotic forms but introns in their
eukaryotic homologs. Introns-late models must predict that all
introns in these genes were inserted into previously continuous
genes that correspond to ancestral forms that were similar to
the current prokaryotic genes (1, 2). Thus, such models predict
that these introns should not respect intron phase (the position
within a codon), should not show phase correlations, and
should not be related to the three-dimensional structure of the
protein products of these genes. Alternatively, introns-early
models, which hypothesize that introns were used in the
progenote to assemble the first genes (3–6), look upon some
or all of these introns as residues of that process and expect
these introns to have been associated with the process of exon
shuffling and, hence, to show restrictions on intron phase, to
show phase correlations, and to be related to the threedimensional
structure of the proteins.
Over the last several years, we have published two statistical
arguments that suggest that introns share properties of the type
predicted by an introns-early theory. One of these arguments
is that introns in genes for ancient conserved proteins are
correlated in phase (the position within the codon) so that
exons, or sets of exons, tend to begin and to end in the same
phase, to be multiples of three bases. This argument was shown
to hold at about the P ϭ 0.01 level (7). A second argument
showed that intron positions were correlated with an aspect of
the three-dimensional structure of ancient proteins, specifically
that intron positions were associated with compact modules
of diameters 21, 27, and 33 Å, with P values less than 0.01
(8). Both of these regularities are predictions of any theory that
holds that some or all of the introns were used in the progenote
to assemble the genes for these proteins by exon shuffling;
neither of these regularities is predicted by theories which hold
that the introns were inserted into DNA by processes that are
unrelated to the ultimate structure of the gene product.
However, in the last year two papers have appeared that
continue the argument that introns are late. One by Cho and
Doolittle (9) tries to study a possible coincidence of intron
positions in gene pairs that represent duplications that occurred
in the progenote, ancient paralogous genes to ask
whether the pattern of intron positions in those genes is more
suggestive of intron addition or intron loss. A second paper
studying the intron distribution in a large gene family argues
that the pattern observed is more one of addition or movement
than loss (10).
The continuing increase of DNA sequences in the public
databases, increasing by a factor of two every 18 months, has
led us to reinvestigate this problem using much more data. In
this paper, we shall show that the statistical regularities
mentioned above can now be analyzed in greater detail with
much higher statistical confidence. We reaffirm the basic
regularities that we saw before, but now, since there is more
data, we can go further in the analysis of the correlation of
introns with three-dimensional structural elements. This further
analysis shows that the strong correlation is carried by
introns that lie between codons (in phase zero), while the
introns that lie within the codons (phase one and phase two)
do not show strong correlations with three-dimensional structure.
This analysis suggests an explicit description of intron
positions in terms of both ancient introns and later additions
in a way that resolves the conflict between the two viewpoints.
We conclude that about 35% of the introns present in ancient
genes are ancient, lie primarily in phase zero between codons,
and are related to compact elements of protein structure,
modules, ranging in diameter between 21 and 33 Å. About 65%
of the introns have been added to pre-existing genes, equal
fractions in each of the other phases uncorrelated to structure.
This division explains why certain analyses see a large fraction
of introns as being added to previously existing genes, while the
theory that the original genes were constructed through introns
remains the simplest and strongest way of predicting the
observed regularities.
The publication costs of this article were defrayed in part by page charge
payment. This article must therefore be hereby marked ‘‘advertisement’’ in
accordance with 18 U.S.C. §1734 solely to indicate this fact.
© 1998 by The National Academy of Sciences 0027-8424͞98͞955094-6$2.00͞0
PNAS is available online at http:͞͞www.pnas.org.
Abbreviation: ACR, ancient conserved region.
*To whom reprint requests should be addressed at: Department of
Molecular and Cellular Biology, The Biological Laboratories, 16
Divinity Ave., Harvard University, Cambridge, MA 02138. e-mail:
gilbert@chromo.harvard.edu.
5094
PROCEDURES
Intron Database. We used GenBank release 101 to construct
a database containing all entries with an intron͞exon
organization. We then purged it down to a criterion of a 20%
match to the shorter sequence, keeping the sequence with
more introns each time, using a program, GBPURGE, written for
a DEC Alpha based on a FASTA comparison. The ancient
conserved region (ACR) database was constructed, and the
expected frequencies of intron phase combinations were calculated
as described before (7).
Dataset for Structural Analysis. Forty-four ancient proteins
(list below) with 988 intron positions were used in this study.
Intron positions were defined by searching the full intron
database with the Protein Data Bank reference sequence using
FASTA. One difference between the approach used here and
that in de Souza et al. (8) and Gilbert et al. (11) is that a specific
program creates two files, one containing the structure coordinates
and one containing the sequence of the reference
protein in FASTA format (used to search the intron database),
using the original Protein Data Bank file as a template. This
additional step made sure that the coordinate and FASTA
sequence files exactly correspond to each other. The source
code of this program will be available on our web site
(http://golgi.harvard.edu/gilbert.html).
List of 44 Ancient Proteins. The names inside parentheses
correspond to the Protein Data Bank accession codes; the 12
additional proteins are starred: aspartate aminotransferase
(1ama); acid amylase (2aaa); acyl-CoA dehydrogenase
(3mdd); adenosine deaminase* (1add); alcohol dehydrogenase
(1adb); adenylate kinase* (3adk); aldehyde dehydrogenase*
(1ad3); aldolase (1ald); alkaline phosphatase (1aja);
aldose reductase (1dla); amylase (1ppi); aspartate transcarbamoylase*
(1raa); aspartyl-trna synthetase* (1asy); catalase
(8cat); citrate synthase (1cts); cuϩϩ superoxide dismutase
(1sdy); cytochrome c (1ccr); dihydrofolate reductase (1dhf);
dihydrolipoamide dehydrogenase* (3lad); elongation factor tu
(1eft); enolase (1ebg); glucose 6-phosphate dehydrogenase
(1dpg); glyceraldehyde 3-phosphate dehydrogenase (3 gpd);
glutamate dehydrogenase* (1hrd); glycogen phosphorylase (1
gpa); glutathione reductase* (1 gra); glutathione S-transferase
(1gss); hemoglobin (2dhb); high pi amylase (1amy); heat shock
protein 70 (1atr); lactate dehydrogenase (2ldx); lysozyme
(1laa); malate dehydrogenase (4mdh); mnϩϩ superoxide
dismutase (1msd); nucleoside diphosphate kinase* (1ndl);
ornithine transcarbamoylase* (1ort); porphobilinogen deaminase*
(1pda); phosphofructokinase (3pfk); phosphoglycerate
kinase (3pgk); phosphoglycerate mutase (3pgm); pyruvate
kinase (from author); thioredoxin* (2trx); triosephosphate
isomerase (1tim); xylanase (1clx).
RESULTS
Intron Phase Correlations Revisited. We extracted a subdatabase
of genes with introns from GenBank 101 to obtain a
database with 25,666 entries. We purged this to eliminate
sequences that matched by more than 20% of the shorter
sequence, using a FASTA matching program, and saved the
versions that have more introns to produce a reduced database
of 5,772 members. A large fraction of the genomic genes now
come from the Caenorhabditis elegans sequencing project. The
intron͞exon structure of these genes is somewhat problematic
because it is predicted by computer. These genes account for
42% of our original database. We constructed purged databases
with or without the C. elegans material: 5,772 genes with
and 1,997 genes without. We identified ACRs as those regions
of eukaryotic sequence homologous and colinear to prokaryotic
genes using as a criteria a BLAST score greater than 75.
We thus obtained a database of introns that lie within the
ACRs which we could analyze for intron-phase correlations.
All of these introns must have been added to the pre-existing
gene on an introns-late model, since there can be no exon
shuffling in the history of these particular regions of the
eukaryotic genes. However, introns-early models predict that
some or all of these introns could be the result of exon shuffling
that created the ancestral form of these genes in the progenote.
As we previously observed (7), there is a bias in the intron
phase distribution for ACR introns: 54% lie in phase zero, 25%
lie in phase one, and 21% lie in phase two. Above this bias,
there are correlations in phase between introns on either side
of exons producing an excess of symmetric exons. Table 1
shows these excesses, as well as listing the behavior of symmetric
pairs, triples, quadruples, and quintuples of exons. For
each of these cases, the expected values are calculated based
on the observed frequencies for the components. The expectation
for symmetric exons is based on the frequency of introns
in each phase; the expectation for the symmetric pairs of exons
is calculated using the observed frequency for the component
exons, beginning and ending in all phases; and similarly for the
other sets. Table 1 shows that the excesses of symmetric exons
and exon sets above expectation are extremely significant.
Table 2 shows the same calculation for the ACR dataset
derived from the database that includes C. elegans; this larger
dataset shows an even greater statistical significance.
The approximately 10% excess of symmetric zero–zero
exons and 15% excess of one–one exons (and exon sets) is not
the expectation of any insertional model but is consistent with
an exon shuffling history. These excesses are above the biased
expectations based on the observed intron phase frequencies,
in which the greatest number of introns are in phase zero, and
the largest excess over that biased expectation is for the
one–one symmetric exons. We stress that the actual deviations
from randomness are very large. If the original expectation for
intron phases had been random, as it would be on the simplest
addition model, one-third in each phase, then there are almost
three times more zero–zero exons than expected, a 200%
excess.
Correlations between Intron Position and Module Boundaries.
We have reanalyzed the correlation between intron
positions and the three-dimensional structure of the protein
products of ancient conserved genes, using a larger set of genes
and a more extensive set of intron positions. We expanded the
group of 32 proteins (8) to a set of 44 ancient conserved
proteins and 988 intron positions from GenBank 101. Where
the three-dimensional structure was available, if we had not
already used those genes, we added new genes that had been
Table 1. Intron correlations within ancient conserved regions (C. elegans sequences excluded)
Length (0,0) (1,1) (2,2) Number ␹2 P
1 1046͞934 (12%) 237͞210 (13%) 165͞140 (18%) 3241 41.5 1 ϫ 10Ϫ6
2 879͞779 (12%) 172͞154 (19%) 115͞113 (11%) 2599 32.4 1 ϫ 10Ϫ4
3 739͞656 (13%) 143͞116 (23%) 84͞90 (Ϫ6%) 2105 39.8 5 ϫ 10Ϫ6
4 616͞556 (11%) 111͞88 (26%) 64͞69 (Ϫ7%) 1702 26.4 8 ϫ 10Ϫ4
5 486͞456 (7%) 82͞71 (15%) 57͞53 (8%) 1371 8.4 0.4
The data are given for each exon type as observed number͞expected number, with the percent excess of observed over
expectation in parentheses. The column labeled ‘‘Number’’ lists the total number of exons or of exon sets of the given length.
There are 910 ACR regions in this database, and the overall phase bias is 54, 25, and 21% for phases zero, one, and two.
Evolution: de Souza et al. Proc. Natl. Acad. Sci. USA 95 (1998) 5095
used in two recent papers that argued for a pattern of
later-moved introns.
We analyzed the three-dimensional structures with a program,
INTERMODULE (8). Briefly, we define a module as a
segment of the polypeptide chain such that all the distances
between the C-alpha carbons are bounded by some maximum
diameter. The program dissects each three-dimensional structure
into a minimally overlapping set of modules of the
specified diameter. The overlaps between the modules, which
we call boundary regions, provide a series of regions in which
we expect to find an excess of intron positions. These ‘‘boundary
regions’’ are such that if an intron were to be placed into
each of the boundary regions, the gene product would be
dissected into a set of modules all less than the specified
diameter. We accumulate a list of all intron positions in genes
homologous to the sequence of the known structure, counting
each different intron position in the nucleic acid sequence
once. We then calculate whether there is an excess of intron
positions in the boundary regions over the random expectation,
which is that the introns were added to the DNA in a
manner that did not respect protein structure. We test the
significance of the excess with a simple ␹2
calculation. Fig. 1
shows the output of this calculation for this set of 44 protein
and 988 intron positions and displays the ␹2
values for each
possible module diameter from 15 Å to 40 Å. Fig. 1 shows that
there is a statistically significant excess of intron positions in
boundary regions for a range of module sizes, with striking
peaks around diameters of 21, 28, and 33 Å [as we observed in
de Souza et al. (8)]. Minor peaks appear near 25 and 37 Å. The
major peaks reach ␹2
values of 11, 13, and 9 and probability
values around P ϭ 0.001. We interpret this curve as showing
that introns tend to mark the boundaries of modules of
different sizes in this set of proteins. The linear amino acid
sequences that correspond to these module diameters are
about 15 amino acids long for the smallest modules and range
up to an average length of 30 amino acids for the 33-Å modules.
Fig. 1 shows that intron positions are correlated with short
elements of polypeptide structure in these 44 ancient conserved
proteins. The phenomenon is robust; if one examines
the excess of intron positions in these regions, one sees a
moderately smooth curve that tracks with the ␹2
result.
Now that we have so much more data, we can examine the
separate components of the statistical signal. Slightly more
than half the intron positions correspond to phase-zero introns,
and so we break the data into a phase-zero portion and
a phase-one plus phase-two portion. Fig. 2 shows the ␹2
Table 2. Intron correlations within ancient conserved regions using the entire purged database
Internal
Exons (0,0) (1,1) (2,2)
No. of
exons ␹2 P
1 1506͞1388 (8%) 392͞321 (22%) 300͞272 (10%) 5133 51.7 3 ϫ 10Ϫ8
2 1181͞1059 (12%) 279͞234 (19%) 226͞203 (11%) 3857 46.7 5 ϫ 10Ϫ8
3 931͞828 (13%) 202͞171 (18%) 141͞149 (Ϫ5%) 2921 40.2 1 ϫ 10Ϫ6
4 731͞640 (14%) 153͞129 (19%) 108͞111 (Ϫ3%) 2231 29.9 2 ϫ 10Ϫ4
5 556͞507 (10%) 107͞100 (7%) 85͞78 (9%) 1711 16.7 3 ϫ 10Ϫ2
The data are given for each exon type as observed number͞expected number, with the percent excess of observed over
expectation in parentheses. The column labeled ‘‘Number’’ lists the total number of exons or of exon sets of the given length.
There are 1,916 ACR regions in this database, and the overall phase bias is 52, 25, and 23% for phases zero, one, and two.
FIG. 1. ␹2 values for the excess of intron positions inside the
boundary regions as a function of module diameter. The major peaks
are around 21, 27, and 33 Å. The 988 intron positions were drawn from
release 101 of GenBank.
FIG. 2. The ␹2 values for the excess of intron positions inside the
boundary regions as a function of module diameter for phase zero and
for phases one and two separately. The INTERMODULE calculation was
done for phase zero intron positions only (554 positions) (black) and
for a set of both phase one and phase two intron positions (434
positions) (gray).
5096 Evolution: de Souza et al. Proc. Natl. Acad. Sci. USA 95 (1998)
distribution for the excess of phase-zero intron positions in
boundary regions as compared with the phase-one and phasetwo
intron positions. The statistical effect is carried entirely by
the phase-zero introns. Phase one and phase two introns do not
show enough preference for the boundary regions to be
statistically notable. Furthermore, the statistical signal is stronger
for the phase-zero data alone, which means that we have
taken a random background out of the calculation. The
statistical signal now reaches a ␹2
value of 16.5, a P value
smaller than 0.0001 for the 21-Å diameter modules. In general,
the P values are 10-fold better for the phase zero introns.
Of the 988 introns, 56% are phase zero, 23% are phase one,
and 21% are phase two. We suggest that, since the simplest
model for intron addition is that equal numbers of introns are
added in all three phases, one should interpret the phase two
introns as a measure of the background rate of addition and
estimate that an equal number of introns were added in phase
zero and phase one (added or randomly moved). The excess
intron positions over this background, the 35 percentage points
of the intron positions in phase zero, are candidates for being
ancient introns. About two percentage points of the intron
positions that lie in phase one are candidates for being ancient.
To put this another way, we suggest that about 65% of all
introns are new, added equally in all three phases, and that
about 35% of all introns are candidates for being old, are
correlated with three-dimensional structure of ancient proteins,
and show the excess phase correlations. Of these, almost
all are phase zero; 60% of all phase zero intron positions
represent old positions, and about 10% of the phase one
positions represent old positions.
This analysis can be taken further by asking whether one can
see any variation in the different kingdoms in terms of this
distribution of phase zero introns. For the 44 proteins, 405
intron positions (224 in phase zero) arise in genes sequenced
from the vertebrates. There are 238 positions (150 in phase
zero) in genes from the plants, 287 positions (163 in phase
zero) in genes from the invertebrates, and 149 positions (72 in
phase zero) in the genes from the fungi. When we look at these
groups, we observe that vertebrate introns lack a correlation
with protein modules. Fig. 3 shows as a percentage the excess
of phase zero introns over the expectation for vertebrate and
nonvertebrate introns. Vertebrate introns do not show much of
an excess of phase zero introns, although there is a small excess
around 33 Å. Fig. 4 shows that the overall ␹2
values
improve for the set of nonvertebrate phase zero introns. The
curve identifies patterns of modules at diameters of 21, 28, and
33 Å with P values Ͻ 0.0001.
DISCUSSION
This finding that the correlation of intron positions with the
modular structure of ancient proteins is carried primarily by
the phase zero introns, along with the interpretation that about
65% of the present introns are added or moved, while about
35% of the introns are correlated with the three-dimensional
structure and are candidates for introns left over from exon
shuffling in the progenote, provides a resolution of many of the
arguments about introns early versus introns late. We identify
one fraction of the introns as candidates for introns-late and
another fraction as specific candidates for introns-early. This
compromise does not, however, satisfy an introns-late view
because it argues that a fraction of the introns are early, which
has the implication that exon shuffling was involved in the
construction of the first genes (5).
The lack of a general signal (there is a small excess of intron
positions around 33 Å) for correlation in the vertebrates is
interesting and puzzling. There is roughly the same excess of
phase zero introns in the subset of vertebrate intron positions
as there is in the other subsets. This would suggest that intron
positions are subject to different dynamics in accordance with
their phylogenetic distribution. The genes that we added to our
original set of 32 proteins tended to weaken the statistical
signal rather than strengthen it. The reason, we now understand,
lies in that the bulk of the intron positions in those genes
came from vertebrate sequences. We expect future work with
other organisms will only strengthen the statistical signal.
FIG. 4. ␹2 values for the excess of nonvertebrate phase zero intron
positions (389 positions) inside the boundary regions as a function of
module diameter.
FIG. 3. The percentage excess of intron positions above expectation
((0-E)/E) for the datasets of nonvertebrate (black) and vertebrate
(gray) phase zero intron positions.
Evolution: de Souza et al. Proc. Natl. Acad. Sci. USA 95 (1998) 5097
How can this emphasis on phase zero intron positions be
reconciled with the apparently greater excess of (1, 1)
symmetric exons than (0, 0) symmetric exons? As we pointed
out earlier, and as Tables 1 and 2 show, there is a much
greater absolute number of symmetric (0, 0) exons than (1,
1) exons. In Table 1, there are 1,046 (0, 0) exons, 237 (1, 1)
exons, and 165 (2, 2) exons. There are four times as many (0,
0) exons as (1, 1) exons and six times as many as (2, 2) exons,
which represents, on our model, the ‘‘background’’ assumption.
The greater background number of (1, 1) exons is part
of the reason that we think there were a few phase one
introns originally.
We have argued that about one-third of all introns are
candidates for being ancient and fall mostly in phase zero
(about 10% may be in phase one). The other two-thirds occur
roughly equal in all three phases and are candidates for introns
added in all three phases or moved randomly into all three
phases. We can further use our data to estimate how many
introns would have been lost during evolution. If the conjecture
that the first genes were constructed of exons, in the length
patterns that we infer, is correct (lengths ranging from roughly
15 to 30 amino acids), we might expect the 44 proteins, whose
aggregate length is 15,400 amino acids, to have about 670
introns originally in phase zero. Since we now see about 330
introns in phase zero correlated with three-dimensional structure,
we suggest that half of the original introns were lost. This
figure is also consistent with the argument that half the introns
were lost to generate the current exon spectrum from the
original shorter spectrum.
Considerations on Theory. How does one test a theory?
The general goodness of a theory lies in how well satisfied
and how varied are its predictions. Does a theory encompass
many aspects of the observed world or is it simply an ad hoc
restatement of an observation? The theory that the intron͞
exon structure of genes is a consequence of the first genes
being assembled by exon shuffling at the beginning of
evolution makes a variety of different predictions, some of
which have now been tested and shown to hold with high
statistical support. This theory predicts that introns should
tend to be in the same phase, that intron phases should be
correlated across groups of exons with a preference for
symmetric patterns, and that introns should be related to
three-dimensional structure of proteins. We showed here
that these three predictions are met for phase zero intron
positions in ACRs; the actual fraction of intron positions
involved we estimate to be about 30 to 40% of all intron
positions in the ACRs.
The theory of early exon shuffling also makes further
predictions which have not yet been tested. One of these
predictions is that the modules should show a pattern of reuse
across protein structures that would follow from their having
been used by exon shuffling as elements to assemble these
proteins. This prediction is that a small set of modules were
used over and over again. Still a further prediction is that a
pattern of introns will be found to repeat at the boundaries of
modules reused by shuffling. These two further predictions
have not yet been tested and are independent of the three tests
that have already been done.
Further Alternative Theories. Are there alternative theories
that could explain the observations? We discuss some theories
of intron addition below. These theories have an ad hoc
character and can often be shown not to hold by a consideration
of other properties.
The excess of introns in phase zero in the intron phase
distribution might be explained by the introns adding to
shadow sequences in previously continuous genes, sequences
like AGGT or AGG that have been hypothesized to serve as
targeting sites for the insertion of introns (12). Such a theory
can be tested by examining the conservation of exon sequences
at intron boundaries, to see how strong such ‘‘shadow sequences’’
actually are, and by examining the distribution of putative
target sequences to see if they match the phase distribution.
We have given a discussion (13) that shows that the current
distribution of such sequences does not mimic the intron phase
distribution.
A separate theory to explain intron phase correlations, that
exons are often multiples of three bases, is to postulate that the
splicing mechanism measures the size of an exon and tends to
measure that size in multiples of three. That such a mechanism
might possibly exist could be supported biochemically by such
arguments as those by Robberson et al. (14), that splicing
mechanisms can recognize both ends of the exon, and by the
observation in some RNA viruses (15) of a preferred packaging
of RNA by a physical process in multiples of six. In such
a model, one might hypothesize that the nucleosome restricts
exons to multiples of three (by an unknown mechanism).
Although such a model would predict an excess of symmetric
exons, it would not predict any further excesses of symmetric
exon pairs, triples, etc.
Consider the alternative theory that there was a set of target
sequences, present a billion years ago but which have mutated
since, that were correlated with amino acid sequences in such
a way that the inserted introns tend to lie between amino acids
and the corresponding amino acid sequences lie in the regions
between the modules, the boundary regions. Such a theory has
a superficial plausibility. However, it would be untestable by
the phase position, the symmetric exon, or the module data
because it is hypothesized to agree with these findings. However,
this example of an ad hoc theory does not predict the
excess of symmetric sets of exons nor does it predict any reuse
of modules in different proteins.
There are a variety of theories that attempt to correlate
positions of added introns to the boundaries of modules by
invoking some form of evolutionary selection pressure. One
class of such theories suggests that introns are effectively
mutagenic upon their addition to a previously existing gene
and, hence, would tend to survive in loops in the proteins or
in other regions of low conservation. However, the boundaries
of modules, as we have described them, lie frequently within
alpha helices or beta strands. Introns are often found in regions
of extremely high conservation, and, in general, introns lie in
regions of high conservation in proportion to the extent of such
regions.
Another hypothesis is that, as introns add to pre-existing
genes, if a pair of introns falls around a module, that module
might be shuffled out and used in another gene and, hence,
selected by evolution. Such models preserve the modules
created by intron addition because they are used by shuffling.
However, these models invoke a wrong view of evolution. The
selection procedure that fixes in the population the shuffled
module in the largest gene does not fix the original version of
the donor gene, since the donor gene, in general, is genetically
unlinked. The ancient conserved genes that we have studied
here have to be donor genes on these models.
Another evolutionary argument suggests that when introns
add to pre-existing genes, the increased homologous recombination
that the intron creates, between the parts of the
protein that lie outside its termini, is deleterious if the intron
lies inside a module because recombination breaks up coadapted
sites inside the module (M. Meselson, unpublished
manuscript). This model, however, does not explain why the
exon͞module correlation exists only for phase zero introns as
well as the excess of symmetric exons.
Although these particular ad hoc theories fail, there may still
be some alternative theory that accounts for all the data. The
nature of the alternative is yet unknown, the best tests of the
Exon Theory of Genes lie in its further predictions.
Overall, our final picture is that about 35% of today’s intron
positions in ancient proteins represent ancient introns, that
over the course of evolution about half of the original introns
5098 Evolution: de Souza et al. Proc. Natl. Acad. Sci. USA 95 (1998)
were lost, and that, again over evolutionary time, a number of
introns have been added in all three phases corresponding
roughly to 65% of the intron positions in today’s databases.
S.J.d.S. was supported by Fundacao de Amparo a Pesquisa do
Estado de Sao Paulo (Sao Paulo, Brasil) and the PEW-Latin American
Fellows Program.
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