Genome Res. 13:1897-1903, 2003
©2003 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/03 $5.00
Letter
Effects of Recombination Rate and Gene Density on Transposable Element Distributions in Arabidopsis thaliana
Stephen I. Wright1,3,
Newton Agrawal2 and
Thomas E. Bureau2
1 Institute of Cell, Animal and Population Biology, University of Edinburgh,
Ashworth Laboratories, Edinburgh, Scotland EH9 3JT, UK
2 Department of Biology, McGill University, Penfield, Montreal, Quebec,
Canada H3A 1B1
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ABSTRACT
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Transposable elements (TEs) comprise a major component of eukaryotic
genomes, and exhibit striking deviations from random distribution across the
genomes studied, including humans, flies, nematodes, and plants. Although
considerable progress has been made in documenting these patterns, the causes
are subject to debate. Here, we use the genome sequence of Arabidopsis
thaliana to test for the importance of competing models of natural
selection against TE insertions. We show that, despite TE accumulation near
the centromeres, recombination does not generally correlate with TE abundance,
suggesting that selection against ectopic recombination does not influence TE
distribution in A. thaliana. In contrast, a consistent negative
correlation between gene density and TE abundance, and a strong
under-representation of TE insertions in introns suggest that selection
against TE disruption of gene expression is playing a more important role in
A. thaliana. High rates of self-fertilization may reduce the
importance of recombination rate in genome structuring in inbreeding organisms
such as A. thaliana and Caenorhabditis elegans.
Transposable elements (TEs) in many organisms have been shown to accumulate
differentially among chromosomal regions, including regions of contrasting
recombination rates (Charlesworth and
Langley 1989 ; Duret et al.
2000; Boissinot et al.
2001; Bartolome et al.
2002), gene density (Medstrand
et al. 2002), and base composition
(Lander et al. 2001). One
possible explanation for these patterns is that TEs have insertion preferences
for particular regions. Evidence for insertion bias is strong for some TEs
(Jakubczak et al. 1991),
although for the majority there is little evidence to support insertion
preference as an explanation for TE distribution
(Nuzhdin et al. 1997). An
alternative is the effects of differential selective constraints on TEs in
different regions of the genome
(Charlesworth and Langley
1989). First, TE's are almost exclusively found outside of coding
regions (Duret et al. 2000;
Nekrutenko and Li 2001;
Bartolome et al. 2002;
Pavlicek et al. 2002),
suggesting that the majority of insertions into exons are strongly deleterious
and rapidly eliminated by selection. Additionally, evidence from patterns of
TE insertion polymorphism in natural populations of some species indicate that
insertions segregating in noncoding genomic regions are almost always at low
frequencies, consistent with the hypothesis that TE abundance is controlled by
the action of purifying selection
(Charlesworth and Langley 1989;
Wright et al. 2001). If TE
abundance in noncoding DNA is determined by a balance between the forces of
transposition and natural selection, regional genome effects on the strength
or efficacy of natural selection will play a significant role in controlling
TE distribution.
Several models of selection against TEs in noncoding DNA have been
proposed. First, abundance may be controlled by weak selection against the
direct effects of insertions into noncoding regions
(Charlesworth and Langley 1989;
Biemont et al. 1997). In
particular, insertions into introns and regulatory regions may have, on
average, slightly deleterious consequences on fitness
(Long et al. 2000;
Lander et al. 2001) by causing
disruptions in gene expression. Similarly, element transposition may impose a
significant cost on the host due to expression of TE gene products, leading to
selection against TE activity (Nuzhdin et
al. 1996). Alternatively, the action of natural selection may be
only indirectly associated with TE mobility, by the deleterious effects of
ectopic recombination between elements located at distinct sites in the
genome, which can cause major chromosomal rearrangements and gene deletions
(Langley et al. 1988).
Under the ectopic exchange model, lower rates of ectopic exchange are
expected in regions of reduced recombination
(Virgin and Bailey 1998),
allowing TEs to accumulate in these chromosomal locations
(Langley et al. 1988).
However, under the insertion model, the action of positive and negative
selection at linked sites may also weaken the efficacy of selection against
deleterious insertions in regions of reduced recombination
(Duret et al. 2000;
Eickbush and Furano 2002), a
process known as the Hill-Robertson effect
(Hill and Robertson 1966).
Although further modelling is required to assess the action of Hill-Robertson
interference on TEs, the effects of linked selection may thus also allow
elements to accumulate in regions of reduced recombination. Unlike the ectopic
exchange model, however, the insertion model predicts that TE insertions
should accumulate in regions of low gene density; even within noncoding DNA,
TE insertions are less likely to interfere with gene expression in regions
with a low proportion of coding DNA.
Results showing higher copy numbers of TEs in regions of reduced
recombination in several species (Boissinot
et al. 2001; Bartolome et al.
2002) are consistent with this expectation of both models.
Although most of these studies have examined the effects of large-scale
heterogeneity in recombination, a recent genetic analysis in maize also
provided evidence for a strong reduction in the rate of recombination in
TE-rich regions at a very local level (Fu
et al. 2002). Furthermore, a recent study of TE frequencies in
populations of Drosophila melanogaster has found evidence for an
effect of TE size on the action of selection, which provides additional
support for the model of ectopic exchange exchange
(Petrov et al. 2003). In
contrast with these results, however, a recent study showed a positive
correlation between recombination rate and DNA transposon abundance in C.
elegans, and no effect of recombination on retrotransposon abundance
(Duret et al. 2000),
suggesting that the predictions of all selection models do not hold. Although
the explanation for the differences among species is unclear, C.
elegans is highly inbreeding in natural populations
(Graustein et al. 2002). In
highly inbred species, low effective rates of recombination across the genome
may remove effects of recombination rate heterogeneity on genome structure
(Charlesworth and Wright 2001;
Morgan 2001). First, unless
population size or physical recombination rates are very high, the action of
Hill-Robertson interference is expected to be present genome-wide
(McVean and Charlesworth
2000), and any recombination-based heterogeneity associated with
the efficacy of selection may be weak or absent. In addition, high
homozygosity in self-fertilizing populations is expected to lead to infrequent
ectopic recombination events, due to fewer chances for ectopic pairing, which
appears to be promoted by heterozygosity
(Charlesworth and Charlesworth
1995; Morgan 2001;
Wright et al. 2001). Patterns
of heterogeneity in TE distributions observed in the genomes of highly inbred
species should thus reflect other effects of natural selection, or the effects
of transposition preferences, and variation in recombination rate is less
likely to play a role.
To further evaluate this hypothesis, we investigate the effects of
recombination rate and gene density on TE distributions in the
self-fertilizing plant Arabidopsis thaliana. A. thaliana shows a high
diversity of TEs, most of which are widely dispersed across the genome
(Surzycki and Belknap 1999;
Le et al. 2000). This
diversity includes all major superfamilies of retrotransposons (Class I
elements), DNA transposons (Class II elements), as well as a recently
identified third class of TEs (Class III;
Le et al. 2000;
Kapitonov and Jurka 2001),
with similarities to bacterial rolling-circle transposons
(Kapitonov and Jurka 2001).
Genome analysis has provided preliminary evidence for an accumulation of many
TE families in pericentromeric regions
(Copenhaver et al. 1999;
Kumekawa et al. 2000), but the
relative importance of various characteristics of genome structure in driving
this pattern has not been investigated.
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RESULTS
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TE Accumulation in Low-Recombining Regions Surrounding the
Centromere
Central regions of reduced recombination, including the centromeres,
pericentromeric regions, and heterochromatic knobs, have been shown to have a
strong reduction in rates of recombination
(Copenhaver et al. 1999;
Haupt et al. 2001), and we
first compare TE abundance in these regions with the chromosome arms. All
classes of TEs show evidence for accumulation in these regions of reduced
recombination surrounding the centromere
(Arabidopsis Genome Initiative
2000; Table 1). In
total, TE-derived DNA represents -27% of the central regions of reduced
recombination, compared with only 3% of DNA in the rest of the genome. Two
superfamilies of elements, gypsy- like and CACTA, show a particularly
striking accumulation in the centromeric regions, and are almost exclusively
found in these regions, and we therefore consider these elements separately.
These TEs, particularly the gypsy-like element Athila, have
many centromeric copies arranged in tandem, often as truncated or fragmented
elements, located near the centromeric core
(Pelissier et al. 1995;
Kumekawa et al. 2000). Such
elements have been hypothesized to be associated with centromere function
(Malik and Henikoff 2002), and
they may have acquired new mutational mechanisms for their spread in the
centromere. However, all other elements, which are not found as tandem arrays,
also show significant accumulation in pericentromeric regions of reduced
recombination.
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Table 1. TE Copy Number (Per MB) and Genome Characteristics in Regions of Reduced
Recombination Compared With the Chromosome Arms
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In addition to low levels of crossing-over, A. thaliana
pericentromeric regions also have low exon density, and the fraction of DNA
that is coding is much lower compared with the rest of the genome
(Table 1; for review, see
Arabidopsis Genome Initiative
2000). Similar to recent studies in D. melanogaster
(Comeron and Kreitman 2000),
average intron length is significantly larger in the regions of reduced
recombination, even when the contribution of TE insertions to intron size is
factored out (Table 1). Overall
differences in base composition are also significant, but the difference in
mean base composition between regions is very weak. Surprisingly, GC content
is slightly higher in the pericentromeric regions compared with the chromosome
arms (Table 1). This contrasts
with the pattern at the local level, where base composition surrounding TE
insertions has been found to show an elevated frequency of AT
(Le et al. 2000).
Because gene density is higher in regions of normal recombination, one
simple explanation for the differential accumulation of TEs in low-recombining
regions is that it reflects the action of strong purifying selection against
insertions into exons. We find an almost complete absence of insertions into
exons (Table 2), suggestive of
very strong selection. Note that we exclude from this category (1) annotated
genes matching solely to TE-derived gene products, (2) fusion proteins
encoding predicted genes which fuse coding sequence from TE insertions and
adjacent genes, and (3) acquired genes that are host genes internal to TE
insertions (Yu et al. 2000).
Although both fusion proteins and acquired genes may be expressed and
functional, they do not represent the insertion of TEs into pre-existing host
coding regions. TE insertions are also strongly under-represented in introns
in A. thaliana (Table
2); in both the centromere and the chromosome arms, there is a
strong reduction in the frequency of TE insertions in introns. Because most
insertions into introns and exons appear to be under strong purifying
selection, this might be the sole explanation for their low abundance in the
chromosome arms, where the density of coding regions is higher. When the
abundance of TEs within intergenic DNA is compared, however, TEs are still
significantly in excess in regions of low recombination
(Table 2), suggesting that the
difference in the abundance of coding DNA alone cannot explain their
differential accumulation.
Recombination Rate Does Not Explain TE Distribution in Intergenic
Regions of A. thaliana
The high number of TEs in pericentromeric regions is consistent with either
model of selection, as these regions are both gene-poor and
recombination-poor. Furthermore, the dense methylation and difference in
chromatin structure in heterochromatic regions may make these insertions more
effectively silenced (Singer et al.
2001), preventing the potentially deleterious expression of
TE-derived gene products in these regions. It is therefore important to
examine whether, in addition to this comparison between genomic regions, there
are general correlations between TE abundance and recombination rate. Given
the underrepresentation of TEs in coding regions, we consider only the TE
content in intergenic regions for this analysis. Excluding the
centromere-specific TEs (gypsy and CACTA), no correlation is observed
between the rate of recombination and TE abundance in intergenic DNA
(Table 3). Note that this
whole-genome correlation with recombination is not significant, despite
accumulation of elements near the centromere; because the pericentromeric
regions represent a low proportion of total DNA, even this effect is not
detected in a genome-wide correlation. Only gypsy and CACTA, which
are almost exclusively present in the central regions of reduced
recombination, show a significant negative correlation. If we consider only
the chromosome arms, no negative correlation is observed for any class of TE,
and all three major classes of element, in fact, show a positive relationship
with TE frequency. This positive relationship can be explained at least in
part by a negative correlation between coding density and recombination rate
along the chromosome arms (Table
3). Using a partial correlation correcting for the effect of
coding density, there is no significant effect of recombination rate on Class
II or III elements, and we observe a weaker positive relationship between
recombination rate and TE abundance for Class I TEs
(Table 3). Provided that the
rate of ectopic recombination correlates with the rate of crossing over, these
results suggest that selection against ectopic exchange does not drive TE
distribution in A. thaliana.
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Table 3. Spearman Rank Correlation Coefficients Between Element Frequency,
Fraction of Coding DNA and Recombination
Ratea
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Effect of Gene Density on TE Abundance in Intergenic DNA
Our initial analysis suggested that selection against insertions into exons
and introns is playing an important role in TE distribution in the A.
thaliana genome, given their strong underrepresentation compared with
intergenic DNA. We also wish to test whether regions of high gene density show
an underrepresentation of insertions in intergenic regions, due to a higher
density of untranslated and cis-regulatory regions. Alternatively,
silencing of TE insertions by DNA methylation and associated changes in
chromatin structure might interfere with the expression of nearby genes
(Gendrel et al. 2002). In a
given sample of DNA along the chromosome, increases in TE-derived DNA could
force the amount of coding sequence to be smaller, violating the standard
assumptions of correlation analysis. To avoid this effect, we excluded the
contribution of TEs to sequence length when sampling bins of constant size
(100 kb) across the genome to look at effects of coding density on TE
frequency. In contrast to recombination rate, all element families show a
significant negative correlation between the fraction of coding DNA and TE
frequency in intergenic regions (Table
3). If we consider only the chromosome arms, the negative
correlation remains significant for Class I and II elements, but not Class III
(Table 3). Furthermore, a
partial correlation analysis, factoring out the effects of recombination rate,
still reveals a residual negative correlation between coding density and TE
abundance for both the whole genome and the chromosome arms
(Table 3).
Whereas the above analysis suggests that selection against insertions near
coding regions is influencing TE distribution, the corresponding correlation
coefficients are low, and it is unclear how strong the action of purifying
selection would be to explain the data. To assess the insertion model more
directly, we use a maximum likelihood framework to test whether a simple model
that includes an effect of coding density on the amount of selective
constraint in intergenic regions provides a significant improvement to the
likelihood of the data compared with a model that assumes elements are
randomly distributed in intergenic regions (see Methods). Because the high
fraction of TE-derived DNA and the high frequency of nested insertions in the
centromere will violate the assumptions of independence among insertions, we
consider only the chromosome arms for this analysis, and once again exclude TE
contributions to sequence length.
For all three TE classes, a model that includes increases in selective
constraint in intergenic regions with an increasing amount of coding DNA
provides a significant improvement to the likelihood compared with a model of
random distribution in intergenic regions, consistent with the action of
purifying selection against insertions near genes
(Table 4). We can use this
model to estimate  , a measure of the amount to which increases in
coding DNA increase the selective constraint in intergenic regions. Estimates
of range from 0.27 for Class II elements to 0.64 for Class I.
Additional factors, such as variation across individual element families and
genomic regions in , the presence of nested insertions, and the
influence of historical selection pressures predating the evolution of
self-fertilization may all play a role in causing residual departures from
expectation. Nevertheless, we can use our analysis to roughly estimate the
total fraction of intergenic DNA that is under purifying selection against TE
insertions along the chromosome arms (see Methods). Using the total amounts of
intergenic and coding DNA in our sample from the chromosome arms, our
estimates of would imply that between 18% and 44% of intergenic DNA is
under selective constraint against TE insertions. Similarly, given an
estimated average of 1308 bp of coding DNA per gene along the chromosome arms,
this implies that each gene has on average 235–837 bp of intergenic DNA
that are under selective constraint against TE insertions. Given the short
distance between genes in the compact A. thaliana genome (average
length of intergenic DNA, 2013 bp), this conclusion appears reasonable.
Computer simulations of insertion into unconstrained regions using the
observed values of the abundance of coding and intergenic DNA and the maximum
likelihood estimates of parameters confirm that the observed correlation
coefficients between TE frequency and coding density are expected with this
level of selective constraint (Table
4). This illustrates that even fairly strong selection against
insertions in intergenic DNA will generate similar correlations between coding
density and TE frequency along the chromosome arms to those observed.
Multivariate Analysis of TE Distribution
It is important to assess whether our analyses on the basis of pairwise
correlations and the three major TE Class categories are robust to a more
global, multivariate analysis. To investigate this, we used principal
components analysis to summarize multivariate patterns of TE abundance in
intergenic DNA for all individual TE element families, excluding CACTA and
gypsy-like elements. The first axis in this data reduction, which
explains 23% of the variance, shows a general increase with TE abundance; all
TE families increase in abundance with an increasing value for factor 1 (see
Supplemental Data, available online at
www.genome.org).
We performed a multiple linear regression, using factor 1 as the dependent
variable, with coding density, recombination rate, and GC content as
independent variables. The model, which explains 20% of the overall variance
in global TE abundance, provides confirmation of our primary conclusions. As
expected, this analysis shows no significant effect of recombination rate on
this multivariate measure of TE abundance (P >> 0.05), whereas
there is a highly significant negative effect of coding density (regression
coefficient = -0.42, P << 0.05). The model also shows a significant
positive effect of base composition (regression coefficient = 0.40, P
<< 0.05), presumably as a result of the increased GC content close to the
centromeres (Table 1).
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DISCUSSION
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In the genome of the self-fertilizing A. thaliana, there are
strong effects of chromosome position on TE abundance, with a large
accumulation of TEs close to the centromere. However, although there is a
global difference between regions of contrasting recombination, our results
suggest that recombination rate is relatively unimportant in causing this
pattern, and the effects of selection against TE disruption of gene expression
may be the primary mode of selection affecting TE distribution in this
self-fertilizing species. Our results suggesting a low rate of ectopic
recombination in A. thaliana are in accordance with a recent analysis
of long terminal repeat (LTR) retrotransposons in this species
(Devos et al. 2002), which
indicated that small deletions within elements occurred at a much higher rate
than ectopic recombination events between LTRs.
Along the chromosome arms, most TE families show slight positive
correlations with recombination rate. This is similar to observations for DNA
transposons in the holocentric genome of the self-fertilizing nematode C.
elegans, in which a general positive correlation between recombination
rate and TE abundance is observed (Duret
et al. 2000), whereas no effect of recombination is seen for
retrotransposons. This correlation may result from the effects of biased
transposition (Duret et al.
2000). However, a negative correlation between recombination and
gene density in the euchromatic portions of A. thaliana, and a
generally higher gene density in regions of low recombination in C.
elegans (Barnes et al.
1995; Wilson 1999)
suggest that these effects may at least in part also be driven by selection
against insertions near genes.
Under the deleterious insertion model, higher gene density is expected to
reduce the abundance of TEs in intergenic regions, due to a higher fraction of
regulatory regions. However, our results
(Table 2) and those in C.
elegans (Duret et al.
2000) suggest that there is also an increase in TE abundance in
introns in regions of low gene density. Nevertheless, genome analysis in both
A. thaliana and C. elegans has provided evidence for a
higher proportion of pseudogenes in regions of low gene density
(Copenhaver et al. 1999;
Harrison et al. 2001) and a
lower proportion of annotated genes in these regions are known to be expressed
(C. elegans Sequencing Consortium
1998; Copenhaver et al.
1999), suggesting that this accumulation may also reflect a
relaxation of natural selection against the disruption of gene function.
Together, the results from both species are consistent with the hypothesis
that the mating system plays an important role in the evolution of genome
structure.
It is important to consider whether the results could be consistent with
alternative selection models to the deleterious effects of gene disruption.
First, the results might also be interpreted as consistent with a model of
selection against the deleterious expression of TE-derived gene products. In
particular, TE insertions in regions of high gene density may show higher
levels of TE-derived gene expression due to differences in chromatin
structure, and may consequently impose stronger deleterious effects on host
fitness. However, a large fraction of TEs in the Arabidopsis genome
lack coding capacity, and many appear capable of non-autonomous transposition
(Le et al. 2000;
Yu et al. 2000). Given that a
low proportion of TE insertions with coding capacity are contributing to
distribution patterns, the action of selection against TE-derived gene
products seems unlikely to provide a primary explanation for our results.
Secondly, an important assumption of our analyses is that current estimates
of recombination rates in A. thaliana are reflective of those in
which TE accumulation occurred. If recombination rates have changed
substantially recently, our ability to detect an effect of recombination on
genome evolution may be compromised. Although this possibility cannot be
completely excluded, recent comparative mapping in the outcrossing
Arabidopsis lyrata (O. Savolainen, pers. comm.), which diverged from
A. thaliana -5 Mya (Koch et al.
2000), suggests that map distances are very similar in these two
species, indicating that recombination rates have remained relatively stable
over this time period.
Thirdly, studies of recombination hotspots in yeast and plants have
provided some evidence that recombination preferentially initiates near genes
(for review, see Lichten and Goldman
1995; Schnable et al.
1998). If ectopic exchange events are thus more likely to occur
close to coding regions, TEs may show a pattern of underrepresentation in
regions of high gene density under the ectopic recombination model. Because
our recombination rate estimates are estimated over a large scale, we might
not observe this local effect of recombination on TE abundance in our
analysis. Furthermore, ectopic exchange events between elements in regions of
high gene density may be more deleterious to the organism, allowing greater
accumulation in regions with fewer genes. Although more understanding of both
the fitness effects of ectopic exchange and the relationship between ectopic
exchange and recombination initiation are obviously needed, the lack of a
negative correlation between recombination rate and TE abundance once gene
density is factored out (from partial correlation analysis) makes these
interpretations unlikely.
Testing whether ectopic exchange is of general importance, however, will
require comparisons of these results with TE distribution patterns in related
outcrossing species (Wright et al.
2001), in which ectopic exchange events are potentially more
frequent. Recent evidence for local suppression of recombination in TE-rich
intergenic regions in maize (Fu et al.
2002) is consistent with models of ectopic exchange, and it might
suggest that low levels of ectopic exchange in the intergenic DNA have allowed
for the rapid accumulation of retrotransposons
(SanMiguel et al. 1998) in
this species. Alternatively, however, this local reduction in recombination
might imply that TE silencing by DNA methylation and changes in chromatin
structure may themselves be a cause of recombination suppression
(Gendrel et al. 2002). If so,
ectopic recombination may be generally unimportant in driving TE distributions
in organisms that suppress TE activity by methylation, as recombination is
effectively suppressed within TE-rich regions. Variation among such organisms
in the proportion of neutral insertion sites could then be more important than
recombination in driving striking differences in the abundance of transposable
elements. For example, recent polyploid evolution or high rates of gene
duplication could create a large number of functionally redundant targets for
TE insertion, leading to relaxed selection against insertions near duplicate
genes (Matzke et al. 1999).
However, it is unclear whether the action of selection against deleterious
insertions can by itself lead to a stable equilibrium in element abundance
(Charlesworth and Langley
1989), and other forces may also be important in controlling TE
copy number. Possible additional factors include the presence of
self-regulated transposition, or stochastic loss of active elements, both of
which may be more frequent in highly inbred and asexual populations
(Charlesworth and Langley 1986;
Wright and Schoen 1999;
Morgan 2001;
Wright and Finnegan 2001).
Nevertheless, the data indicate that selection against the deleterious effects
of the disruption of gene expression may be a general force driving patterns
of TE distribution, and they suggest the importance of analyses to uncouple
recombination rate and gene density effects in other eukaryotic genomes.
Finally, although our results suggest that TE insertions near genes are
generally under purifying selection, this does not rule out an important role
of some TE insertions in the evolution of gene expression (e.g.,
Daborn et al. 2002), and
unusual TE insertions in promoter and coding regions represent potential
candidates for adaptive evolution.
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METHODS
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Genome Analysis
The genome sequence and positions of predicted genes for all five
chromosomes of A. thaliana were extracted from The Arabidopsis
Information Resource
(TAIR—www.arabidopsis.org).
The genome sequence is in the form of pseudomolecules, the concatenated
sequence of overlapping sequenced clones for each chromosome. These
pseudomolecules comprise the entire genome sequence, with the exception of
telomeres, the rDNA islands on chromosomes 2 and 4, and several small gaps
denoted as N's (Arabidopsis Genome
Initiative 2000). Sequences were divided into 100-kb fragments
across each chromosome, and information on base composition and annotated
(predicted) gene position was collected, excluding a small number of fragments
with estimated gaps or terminal sequence leading to a bin size of <50 kb.
Each pseudomolecule was submitted to a BLAST search (NCBI standalone BLAST
released for Unix on April 3,2001) against our Arabidopsis TE database
(www.tebureau.mcgill.ca/),
to determine the positions of each TE superfamily along the entire set of
chromosomes. TE positions were then verified manually, to eliminate all
redundancies and record the presence of nested insertions. For analysis of
gene density and the fraction of coding DNA, all annotated coding regions that
showed matches solely to TE-encoded gene products were removed. All putative
insertions into annotated exons and introns were verified by individual BLAST
searches of annotated coding regions. Matches to small internal fragments of
TEs, annotated proteins that represent fusions between TE mobility genes and
adjacent genes, and matches to host sequences internal to TE insertions were
eliminated.
Recombination Rate Estimation
The physical positions were also recorded for those genetic markers that
have both been mapped to the Recombinant Inbred (RI) recombination map (see
http://nasc.nott.ac.uk/new_ri_map.html),
and have been precisely physically mapped on the basis of flanking sequence,
using the marker position information from TAIR. To estimate rates of crossing
over, the relationship between genetic and physical distance was examined for
each chromosome. Because marker density was relatively low close to the
centromere, each chromosome was divided into two fragments, with the boundary
representing the centromere. Each fragment had an average of 40 markers, with
a total of 400 markers used genome wide. Third-order polynomials were fitted
to the relationship between genetic and physical distance (in cM/Mb) in each
region, similar to the approach of Kliman and Hey
(1993; see Supplemental Data).
Rates of crossing over could then be estimated by taking the first derivative
of this polynomial at any given physical position. With two exceptions, the
polynomial fits explained >97% of the variance in genetic distance; the
right arm of chromosome 5 had an R2 of 0.96, whereas the left arm
of chromosome 2, represented by 19 markers, had an R2 of 0.87.
Boundary regions with low marker density between the central regions of low
recombination and the chromosome arms were excluded from correlations with
recombination rate.
Central regions of reduced recombination, which include the centromeres and
heterochromatic knobs, were also delimited using the genetic marker data in
order to compare these regions with the rest of the genome, hereafter called
the chromosome arms. The central regions have been shown to have a strong
reduction in rates of recombination, by recombination rate estimation that is
independent of the genome project data used here
(Copenhaver et al. 1999;
Haupt et al. 2001). Because of
low-marker density, comparisons were restricted to central regions of clearly
reduced recombination versus the chromosome arms, with boundary regions of
low-marker density excluded from the analysis. In the case of chromosome 1,
fine-scale estimates of recombination rates in the centromeric region by Haupt
et al (2001) allowed the
recombination boundary on the short arm to be precisely delimited to BAC clone
T22A15. Estimates of average recombination rate along the arms (4.9 cM/MB)
using the polynomial fits were very similar to estimates of the average genome
recombination rate, 5.0 cM/MB (Haupt et
al. 2001). In the central regions of reduced recombination,
average recombination rate using polynomial fits was estimated to be 1.5
cM/MB, although this includes regions with much greater recombination rate
reduction, up to perhaps complete suppression in the centromere core
(Haupt et al. 2001).
Testing Effects of Coding Density on Purifying Selection Against
Insertions
We used a maximum likelihood method to test for the presence of selective
constraint in intergenic regions. If TE insertions are inserted randomly
within intergenic DNA along the chromosome arms, they should follow a Poisson
distribution. Specifically, the likelihood of observing n insertions
is the product of the likelihoods in each bin i:
Assuming no selective constraint in intergenic regions, the parametric mean
µi = (vIi), in
which Ii is the number of base pairs of
intergenic DNA in bin i estimated directly from the data, and
v is the per base pair probability of an insertion. This model
assumes complete independence among bins, that is, no local insertion
preference, and by constraining v across bins, we assume that TE
distribution is random across intergenic DNA. We can calculate the maximum
likelihood estimate of v, using the observed values of n and
I for each bin. As an alternative model, we allow
ui to vary as a function of the observed amount
of coding DNA (Ci) in bin i:
ui = v(Ii -
Ci), where
Ci < Ii.
Here,
is a measure of the proportion of intergenic DNA in bin i that is
under selection against TE insertion, and the total proportion of intergenic
DNA under selective constraint against TE insertions can be estimated by
summing across all bins. We assume that a given insertion site in intergenic
DNA is either unconditionally deleterious, with probability
or neutral, with probability
By calculating the joint maximum likelihood of v and , and
comparing it with a model in which = 0, we can test for an effect of
coding density on TE distributions. Significant improvement to the likelihood
is assessed using the statistic
in which L0 assumes = 0, and L1 allows
> 0. This statistic is asymptotically  2 distributed with 1
degree of freedom. To examine the expected correlation between coding density
and TE frequency under a model with these parameter estimates, we also run
10,000 computer simulations of random TE insertion into unconstrained
intergenic DNA using the observed sizes of intergenic and coding DNA in each
bin. In these simulations, we simply assume a Poisson distributed number of
insertions into each bin, with the parametric mean ui in bin i
given by the selection equation above. These simulations assume that the only
factor influencing TE distribution is random insertion into unconstrained
sites.
|
Acknowledgements
|
|---|
We thank T. Johnson, P. Andolfatto, D. Bachtrog, B. Charlesworth, D.
Charlesworth, and D. Schoen for discussion and comments on an earlier version
of the manuscript. We also thank three anonymous reviewers for their comments
on the manuscript. This work was supported by a National Science and
Engineering Research Council (NSERC) of Canada operating and Genomics Project
grants to T.E.B., and by a Commonwealth fellowship and an NSERC postgraduate
scholarship to S.I.W.
The publication costs of this article were defrayed in part by payment of
page charges. This article must therefore be hereby marked
"advertisement" in accordance with 18 USC section 1734 solely to
indicate this fact.
|
Footnotes
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|---|
Article and publication are at
http://www.genome.org/cgi/doi/10.1101/gr.1281503.
3 Corresponding author. E-MAIL
stephen.wright{at}ed.ac.uk;
FAX 131-6506564. 
[Supplemental material is available online at www.genome.org.]
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ABSTRACT
RESULTS
