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MBE Advance Access originally published online on June 22, 2005
Molecular Biology and Evolution 2005 22(10):2063-2072; doi:10.1093/molbev/msi197
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© The Author 2005. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oupjournals.org

Research Article

Entropy and GC Content in the ß-esterase Gene Cluster of the Drosophila melanogaster Subgroup

Evgeniy S. Balakirev*,{dagger},{ddagger}, Vladimir R. Chechetkin§, Vasily V. Lobzin§ and Francisco J. Ayala*

* Department of Ecology and Evolutionary Biology, University of California, Irvine; {dagger} Academy of Ecology, Marine Biology, and Biotechnology, Far Eastern State University, Vladivostok, Russia; {ddagger} Institute of Marine Biology, Vladivostok, Russia; and § Troitsk Institute of Innovation and Thermonuclear Investigations (TRINITI), Theoretical Department of Division for Perspective Investigations, Moscow Region, Russia

E-mail: fjayala{at}uci.edu.


    Abstract
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
We perform spectral entropy and GC content analyses in the ß-esterase gene cluster, including the Est-6 gene and the {psi}Est-6 putative pseudogene, in seven species of the Drosophila melanogaster species subgroup. {psi}Est-6 combines features of functional and nonfunctional genes. The spectral entropies show distinctly lower structural ordering for {psi}Est-6 than for Est-6 in all species studied. Our observations agree with previous results for D. melanogaster and provide additional support to our hypothesis that after the duplication event Est-6 retained the esterase-coding function and its role during copulation, while {psi}Est-6 lost that function but now operates in conjunction with Est-6 as an intergene. Entropy accumulation is not a completely random process for either gene. Structural entropy is nucleotide dependent. The relative normalized deviations for structural entropy are higher for G than for C nucleotides. The entropy values are similar for Est-6 and {psi}Est-6 in the case of A and T but are lower for Est-6 in the case of G and C. The GC content in synonymous positions is uniformly higher in Est-6 than in {psi}Est-6, which agrees with the reduced GC content generally observed in pseudogenes and nonfunctional sequences. The observed differences in entropy and GC content reflect an evolutionary shift associated with the process of pseudogenization and subsequent functional divergence of {psi}Est-6 and Est-6 after the duplication event.

Key Words: Drosophila melanogaster subgroup • ß-esterase gene cluster • Est-6 • {psi}Est-6 • entropy • GC content


    Introduction
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
The ß-esterase gene cluster is on the left arm of chromosome 3 of Drosophila melanogaster, at 68F7-69A1 in the cytogenetic map. The cluster comprises two tandemly duplicated genes, first described as Est-6 and Est-P (Collet et al. 1990Go), with coding regions separated by only 193 bp. The coding regions are 1,686 and 1,691 bp long, respectively, and consist of two exons (1,387 and 248 bp) and a small (51 bp in Est-6 and 56 bp in Est-P) intron (Oakeshott et al. 1987Go). The Est-6 gene is well characterized (reviews in Richmond et al. 1990Go; Oakeshott et al. 1993Go, 1995Go). The gene encodes the major ß-carboxylesterase (EST-6) that is transferred by D. melanogaster males to females in the seminal fluid during copulation (Richmond et al. 1980Go) and affects the female's consequent behavior and mating proclivity (Gromko, Gilbert, and Richmond 1984Go). Less information is available for Est-P. Collet et al. (1990)Go concluded that Est-P is a functional gene based on several lines of evidence: transcriptional activity, intact splicing sites, no premature termination codons, and presence of initiation and termination codons. Balakirev and Ayala (1996)Go and Balakirev et al. (2003)Go found premature stop codons within the Est-P–coding region and some other indications suggesting that Est-P might be in fact a pseudogene, which they labeled {psi}Est-6. Dumancic et al. (1997)Go showed that some alleles of the Est-P produce a catalytically active esterase corresponding to the previously identified EST-7 isozyme (Healy, Dumancic, and Oakeshott 1991Go) and renamed the gene Est-7. The ß-esterase gene cluster in other Drosophila species also includes two (or three, in Drosophila pseudoobscura and related species) closely linked genes (Yenikolopov et al. 1989Go; Brady, Richmond, and Oakeshott 1990Go; East, Graham, and Whitington 1990Go; Oakeshott et al. 1993Go, 1995Go; King 1998Go).

We have detected in D. melanogaster different patterns of nucleotide variation in Est-6 and {psi}Est-6 (Balakirev and Ayala 2003aGo, 2003bGo, 2004Go; Balakirev et al. 2003Go). Total variation is 2.1 times higher in {psi}Est-6 than in Est-6. In {psi}Est-6 the rate of synonymous substitutions is higher than the rate of nonsynonymous substitutions and neutrality tests (Kelly 1997Go; Wall 1999Go) are significant; the ratio of replacement to synonymous polymorphic sites is 1.2 for {psi}Est-6 but 0.59 for Est-6. The number of amino acid replacements is 2.9 times higher in {psi}Est-6 than in Est-6 and some of them are drastic. In non-African populations the recombination rate is 2.6 times higher in Est-6 than in {psi}Est-6 so that linkage disequilibrium is more pronounced in {psi}Est-6; however, in the African population, the recombination rate is similar for both genes. We have detected much higher gene conversion within {psi}Est-6 than within Est-6. The intergenic gene conversion is limited. Within the {psi}Est-6–coding region we found 17 premature stop codons among 78 sequences. The structural entropy analysis reveals significantly lower structural regularity and higher structural divergence for {psi}Est-6 than for Est-6, as expected if {psi}Est-6 is a pseudogene or nonfunctional gene (Balakirev et al. 2003Go). However, as noted, the gene can be expressed (Collet et al. 1990Go) and some alleles of {psi}Est-6 produce a catalytically active esterase (Dumancic et al. 1997Go), although this is detected in late larvae and adults of both sexes, whereas the functional Est-6 gene transcripts are found in all life stages but predominantly in adult males (Collet et al. 1990Go; Dumancic et al. 1997Go), consistent with the significant role of EST-6 in male mating (Richmond et al. 1980Go; Gromko, Gilbert, and Richmond 1984Go).

We have recently suggested that pseudogenes may be an important part of the genome, representing a repertoire of sequences evolving toward the acquisition of new or changing functions (Balakirev and Ayala 2003bGo, 2003cGo, 2003dGo, 2004Go; Balakirev et al. 2003Go). A pseudogene may lose the initial specific coding function but retain or acquire others, which may not be simply recognizable. Pseudogenes along with their parental sequences may constitute indivisible functionally interacting entities ("intergenic complex" or "intergene") in which each single component cannot successfully accomplish the final functional role. The Est-6/{psi}Est-6 complex in D. melanogaster may represent such an intergenic complex (Balakirev and Ayala 2003bGo, 2003dGo, 2004Go) where the Est-6 gene plays the structural role (coding for the EST-6 enzyme) while {psi}Est-6 may enhance genetic variation in the Est-6 gene and contribute to regulate its expression.

Previously, we have investigated nucleotide variability of the Est-6 gene and {psi}Est-6 in a D. melanogaster sample from a natural population of California (Balakirev and Ayala 1996Go; Balakirev et al. 1999Go, 2003Go; Ayala, Balakirev, and Sáez 2002Go; E. S. Balakirev, E. I. Balakirev, and Ayala 2002Go) and also in three populations of East Africa (Zimbabwe), Europe (Spain), and South America (Venezuela) (Balakirev and Ayala 2003aGo, 2003bGo, 2004Go). Now we extend the analysis by comparing the nucleotide variability of Est-6 and {psi}Est-6 in seven species of the D. melanogaster subgroup. We analyze the entropy and GC content of the genes. Spectral entropies are significantly higher for {psi}Est-6 than for Est-6 in all species studied. The observations agree with our previous results for D. melanogaster. For the first time we show that the accumulation of structural entropy is not completely random but is nucleotide dependent and related to GC content of the genes.


    Materials and Methods
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
Drosophila Strains and Species
The D. melanogaster strains have been previously described (E. S. Balakirev, E. I. Balakirev, and Ayala 2002Go; Balakirev and Ayala 2003aGo). Drosophila sechellia, Drosophila mauritiana, Drosophila erecta, Drosophila teissieri, and Drosophila orena strains were obtained from the Drosophila Species Stock Center (Bowling Green, Ohio).

DNA Extraction, Amplification, and Sequencing
The procedures were described earlier (Balakirev et al. 1999Go, 2003Go; E. S. Balakirev, E. I. Balakirev, and Ayala 2002Go). For each line, the sequences of both strands were determined using 24 overlapping internal primers spaced, on average, 350 nt. At least two independent polymerase chain reaction (PCR) amplifications were sequenced in both directions to prevent possible PCR or sequencing errors. The new sequence data have been deposited in the GenBank under the following accession numbers: AY695919 (Drosophila simulans), AY695920 (D. sechellia), AY695921 (D. mauritiana), AY695922 (D. teissieri), AY695923 (D. erecta), and AY695924 (D. orena). The population data for D. melanogaster are from Balakirev and Ayala (2003aGo, 2003bGo, 2004Go); see GenBank accession numbers AF147095–147102, AF150809AF150815, AF217624AF217645, AF526538AF526559, AY247664AY247713, AY247987AY248036, AY368077AY368109, and AY369088AY369115.

DNA Sequence Analysis
The esterase sequences were assembled using the program SeqMan (Lasergene, DNASTAR, Inc., 1994–1997). Multiple alignment was carried out manually and using the program ClustalW (Thompson, Higgins, and Gibson 1994Go). GC content was computed using the DnaSP program, version 3.50 (J. Rozas and R. Rozas 1999Go) and PROSEQ, version 2.4 (Filatov and Charlesworth 1999Go). The Wilcoxon and Mann-Whitney tests were used to evaluate the significance of the pairwise differences in GC content.

Spectral Structural Entropy Analysis
Balakirev et al. (2003)Go have previously compared the characteristics of Est-6 and {psi}Est-6 in terms of spectral entropy (for a general review of methods and further references, see Lobzin and Chechetkin 2000Go). Spectral entropy characterizes the structural regularity of a nucleotide sequence. In our case it allows us conveniently to assess the comparative rates and positional distribution of mutations, as well as their influence on the regularity of the nucleotide sequences for Est-6 and {psi}Est-6, and to shed additional light on gene function. For the convenience of the reader, we reproduce here the main definitions in the Supplementary Material online.

Because the methods based on the spectral entropy are a bit novel, we will elucidate two questions: why Fourier transform and what is spectral entropy useful for? Tandem repeats and scattered DNA repeats play important roles in the structural organization of chromatin and regulatory mechanisms (Lewin 2000Go). Moreover, the underlying repeats in quasi-randomly modified form and quasi-periodically phased nucleotides also play important roles in protein-coding fragments attributed to a fraction of "unique DNA" in genomic sequences (Lobzin and Chechetkin 2000Go, and references therein). Such periodicities emerge because the coding concordant with B-DNA double helix pitch, quasi-repeated package of nucleosomes, cooperative binding with regulatory proteins etc., exhibit evolutionary preference with respect to nonphased synonymous or nearly synonymous (in the sense of proximity between physicochemical characteristics of encoded amino acids) counterparts. We illustrate these mechanisms with examples.

For instance, GGGCCC tracts in the presence of Mg++, or (A)n tracts with n = 3–8 phased with dsDNA helix pitch, cause DNA curvature and alleviate the package into nucleosomes (Harvey et al. 1995Go). Indeed, underlying periodicities both with periods P = 10.3–10.5 and 200 ± 30 bp can be detected in many sequences (Chechetkin and Lobzin 1998Go; Thåström et al. 1999Go). It is known that protein RecA participates in Escherichia coli recombination. These proteins bind cooperatively to single-stranded and double-stranded DNA and form helical structures with pitch 18.6 bp (Bar-Ziv and Libchaber 2001Go). The mode of binding is preferable to T-rich tracts. Periods P = 18.64 for T are observed for bacteriophage PHIX174 attacking E. coli (Chechetkin and Turygin 1995Go). Other highly reproducible features are related with periodicities P = 3 in the protein-coding regions (Tiwari et al. 1997Go; Lobzin and Chechetkin 2000Go, and references therein; see also figs. 2 and 3 below).



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FIG. 2.— Normalized structure factor spectra (see eqs. 1s–5s) for Est-6 in Drosophila orena.

 


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FIG. 3.— Normalized structure factor spectra (see eqs. 1s–5s) for {psi}Est-6 in Drosophila orena.

 
The underlying quasi-periodic features may effectively be displayed via the Fourier technique, while their integral contribution is assessed with the spectral entropies. Therefore, Fourier transform and spectral entropy provide rather simple and effective ways to place evolutionary modifications into structural context. In the case of neutral mutations the higher the rate of mutations, the higher the randomization in nucleotide sequence and the higher the spectral entropy. As Fourier transform (eq. 1s) can be reciprocated, the structure factors (2s) contain information not only about particular periodicities but also convey general information about nucleotide positions in a DNA sequence. Normalization of structure factors (5s) ensures the independence of the structural ordering criterion from nucleotide composition. Thus, the presence or absence of correlations between ordering and composition provides valuable biological information.


    Results
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
We present the entropy characteristics and GC content analysis of the ß-esterase gene cluster in seven sibling species belonging to the D. melanogaster species subgroup. These seven species belong to three complexes: (1) the melanogaster complex, represented by D. melanogaster, D. simulans, D. mauritiana, and D. sechellia; (2) the yakuba complex, represented by D. teissieri (Drosophila yakuba and Drosophila santomea are the two other species in this complex); and (3) a complex represented by D. erecta and D. orena (Lemeunier et al. 1986Go; Cariou 1987Go; Lachaise et al. 1988Go, 2000Go). The phylogenetic relationships of the Est-6 and {psi}Est-6 in the seven species are presented in figure 1. Alternative distance methods implemented in the MEGA 2.1 program (Kumar et al. 2001Go) yield identical topologies (data not shown). The tree in figure 1 is consistent with those derived from other genes (Kalantzi-Makri et al. 1999Go; Avedisov et al. 2001Go; Parsch et al. 2001Go; Ko, David, and Akashi 2003Go; Matsuo 2003Go).



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FIG. 1.— Neighbor-joining tree of the ß-esterase genes using Kimura 2-parameter distances. The tree is based on the coding (exon I + exon II) sequence for each gene. The numbers at the nodes are bootstrap percentage probabilities based on 10,000 replications.

 
Entropy Analysis
In order to calculate the relevant entropy characteristics for Est-6 and {psi}Est-6, the lengths of the nucleotide sequences were preliminarily equalized by removing insertions/deletions. Thus, the lengths of all sequences were equal to M = 1,614 bp. All Fourier spectra for the structure factors (eq. 2s) appear to be very similar to the counterpart spectra for D. melanogaster (Balakirev et al. 2003Go); examples for Est-6 and {psi}Est-6 in D. orena are illustrated in figures 2 and 3. The highest peaks with harmonics number n = 538 correspond to periodicity P = 3 typical for all protein-coding regions (Tiwari et al. 1997Go; Lobzin and Chechetkin 2000Go).

The results for the normalized deviations (eq. 9s) in spectral entropies are summarized in table 1. They show distinctly higher structural ordering for Est-6 than for {psi}Est-6 in all species. Using probability distribution (10s) for normalized deviations r, the statistical assessment of entropy variations within species for Est-6 and {psi}Est-6 in table 1 may be performed with corresponding rank order statistics (Johnson and Leone 1977Go). In particular, taking from statistical tables the mean value and standard deviation for sweep one finds for the group of n = 7 species the values 2.70 ± 0.83. Therefore, despite the seemingly large entropy variations, both groups of data for Est-6 and {psi}Est-6 can be considered as statistically homogeneous within each group.


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Table 1 Relative Normalized Deviations for Structural Entropy, r{alpha},rel and rrel

 
The partial spectral entropies (6s) or the corresponding normalized deviations (9s) may formally be considered as vectors in four-dimensional parameter space. The appropriate metrics (e.g., Euclidean or maximum of modulus difference between components) in this space can be applied to the construction of phylogenetic trees as well. Using the data in table 1, it is easy to show nearly complete correspondence with the tree in figure 1 for Est-6 and to a lesser extent for {psi}Est-6.

The entropy values for the nucleotides A and T are similar for Est-6 and {psi}Est-6, but for G and C (and for the "total," as a consequence) the entropy values are lower (or the structural ordering is higher) in Est-6 than in {psi}Est-6 (table 1). Thus, the present analysis shows that the Est-6 and {psi}Est-6 characteristics of structural entropy are nucleotide dependent. Partially, the bias in entropy for G may be attributed to the more pronounced periodicity P = 3 for Est-6 than for {psi}Est-6, which is the common structural marker of protein-coding regions (see figs. 2 and 3). For Est-6, the normalized deviations are significant for G in all species, while A and T show particularly strong regularity in D. orena and D. erecta. For {psi}Est-6, there is significant regularity for D. erecta only for G. This observation is in good agreement with previous results for D. melanogaster and supports previous inferences about the functional roles of Est-6 and {psi}Est-6 (Balakirev et al. 2003Go; see below).

To illustrate the higher rate of mutation accumulation in {psi}Est-6 with respect to Est-6, we performed a simulation by introducing random point mutations into a sequence for Est-6 and we analyzed the diminishing of the normalized deviation rrel for the total entropy Stotal. The corresponding dependence is illustrated in figure 4. The simulation results averaged over 20 realizations indicate that it is necessary to introduce about 20% of random point mutations into the sequence for Est-6 in D. orena to obtain the same structural ordering as for {psi}Est-6.



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FIG. 4.— Est-6 in Drosophila orena: dependence of normalized deviation for total entropy (see eqs. 9s and 11s) on the percentage of random point mutations introduced into the sequence without the preservation of initial nucleotide composition (solid curve) and without the preservation of initial nucleotide composition during mutation accumulation (dotted curve).

 
Polymorphism Analysis with Spectral Entropy
Spectral structural entropy may be used for analyzing intraspecific polymorphism in related genes. Positional variation is assessed by standard methods with sliding windows. A quantitative measure of polymorphism is given by the coefficient of variation,

(1)
where deviations of spectral entropy are calculated for fragment sequences extending from site m0 W to a site m0 + W and averaged over a set consisting of P sequences. The mean and standard deviations are

(2)
and

(3)
respectively.

The sliding window should be wide enough to ensure the robustness of the reference characteristics for comparable random sequences (Lobzin and Chechetkin 2000Go). We selected a sliding window of 2W + 1 = 201 sites with one-site increments. To avoid overestimation of polymorphic variation for small mean values of the peaks in the coefficients of variation were cut at the threshold |CV| = 3.

The coefficients of variation were applied to (1) polymorphic changes for Est-6 and {psi}Est-6 in 78 strains of D. melanogaster (P = 78) collected in Zimbabwe, Spain, California, and Venezuela (Balakirev and Ayala 2003aGo, 2004Go) and (2) corresponding evolutionary changes in the set of seven species (P = 7). The coefficients of variation CVintra (in case [1]) and CVinter (in case [2]) characterize intraspecific diversity and interspecific divergence, respectively. The sliding window plots for the coefficients of variation related to intraspecific variability in 78 strains of D. melanogaster as well as the corresponding plots characterizing interspecific divergence for the seven Drosophila show noticeably more preserved regions in Est-6 than in {psi}Est-6 (data not shown).

An important issue concerns the intraspecific and interspecific correlations in Est-6 versus {psi}Est-6, which may be assessed by the cross-correlation coefficients of intraspecific variability versus interspecific divergence within the sliding windows. For a window of width 2w + 1, these correlation coefficients are defined as

(4)
where the variation coefficients CV(m) are defined by equations (1–3) and

(5)

(6)

According to Fisher's theory (Johnson and Leone 1977Go), the mean characteristics for the random correlations are given by

(7)
while the normalized variable

(8)
has an approximately Gaussian distribution with a unit variance.

The relevant global cross-correlation coefficients (corresponding to 2w + 1 = M – 2W – 1 = 1413) for the total entropies Stotal (eq. 11s) for Est-6 are k = 0.11, r(k) = 4.08 and for {psi}Est-6 are k = 0.07, r(k) = 2.51. The probability of obtaining the observed correlations by chance is Pr {approx} 10–5 (for Est-6) and Pr {approx} 8 x 10–3 (for {psi}Est-6). Thus, the correlations between intraspecific variability and interspecific divergence are significant for both genes but turn out to be lower in {psi}Est-6 than in Est-6. In agreement with this observation, we have previously shown that the tests of neutrality of Kelly (1997)Go and Wall (1999)Go are significant for both Est-6 and {psi}Est-6 (Balakirev et al. 2003Go; Balakirev and Ayala 2004Go). Moreover, for {psi}Est-6 the tests are significant with lower level of recombination than for the Est-6 gene. Using maximum likelihood estimates of nonsynonymous/synonymous rate ratios ({omega} = dN/dS) (reviewed by Yang and Bielawski 2000Go) we also have shown (Balakirev, Anisimova, and Ayala 2005Go) that the proportion of sites evolving under negative selection is substantially higher in {psi}Est-6 ({omega} = 0.11; 83.7%) than in Est-6 ({omega} = 0.003; 48.1% of sites).

GC Content
Table 2 shows the distribution of GC content. The average GC:AT ratios for all positions and coding positions are not significantly different between Est-6 and {psi}Est-6 (P < 0.05, Fisher's exact test), but the ratio is significantly different for the third codon position (P = 0.0143, Fisher's exact test). Total GC content is significantly lower in {psi}Est-6 than in Est-6 (46.6% vs. 49.7%; Wilcoxon test P = 0.0156; Mann-Whitney test P = 0.006) mostly due to GC3, the third codon position (46.0% vs. 55.1%; Wilcoxon P = 0.0156; Mann-Whitney P = 0.006). For all coding positions the difference in GC content (GCc) between {psi}Est-6 and Est-6 is not significant (47.0% vs. 46.9%; Wilcoxon P = 0.6875; Mann-Whitney P = 0.9015). Thus, the most pronounced difference in base composition between Est-6 and {psi}Est-6 is GC content at the third codon position.


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Table 2 GC Content (%) and Overall GC to AT Ratio of the Est-6 and {psi}Est-6 Genes in Seven Species of the Drosophila melanogaster Subgroup

 
Exon I has significantly higher GC content than exon II for both genes (47.7% and 51.9% vs. 40.6% and 37.3%; Wilcoxon P = 0.0156; Mann-Whitney P = 0.006). The difference in GC content between exon I and exon II is more pronounced for Est-6 than for {psi}Est-6 (table 2). For Est-6 there is pronounced difference between GC3 (58.5%) and GCc (48.6%) in exon I (Wilcoxon P = 0.0156; Mann-Whitney P = 0.006); for {psi}Est-6 the difference is much less pronounced: 47.0% versus 48.1%, although marginally significant (Wilcoxon test P = 0.0469; Mann-Whitney P = 0.0379). For exon II there is no difference between GC3 and GCc for either Est-6 (Wilcoxon P = 0.2187; Mann-Whitney P = 0.1649) or {psi}Est-6 (Wilcoxon P = 0.8125; Mann-Whitney P = 0.9015). The introns of both genes have significantly lower GC content than the two exons (Wilcoxon P = 0.0156; Mann-Whitney P = 0.006). Intron GC content is significantly higher in {psi}Est-6 than in Est-6 (Wilcoxon P = 0.0312; Mann-Whitney P = 0.0070).

The dispersion of the GC values between regions (exon I, intron, and exon II) is lower for {psi}Est-6 than for Est-6. Est-6 GC content ranges from 22.9% in the intron to 58.5% at GC3 of exon I. GC content in {psi}Est-6 ranges from 30.4% in the intron to 48.1% in exon I. GC content varies narrowly in the {psi}Est-6 exons (40.2%–48.1%) but more broadly in Est-6 (36.1%–58.5%) (table 2).


    Discussion
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
Two different approaches, entropy and GC content analyses, reveal significantly different patterns of evolution in two genes, Est-6 and {psi}Est-6, in seven species of the D. melanogaster subgroup. Higher values of entropy for {psi}Est-6 than for Est-6 that were first encountered in D. melanogaster (Balakirev et al. 2003Go) are also observed in six other species. The significantly lower structural ordering (regularity) of {psi}Est-6 in comparison with Est-6 is compatible with the suggestion that {psi}Est-6 might be a pseudogene or nonfunctional gene. An interesting feature of the entropy in Est-6 and {psi}Est-6 is its being nucleotide dependent. The entropy values for nucleotides A and T are similar for Est-6 and {psi}Est-6, but for G and C the entropy values are lower for Est-6, which indicates that entropy increase is not a purely random process. In addition, there are significant correlations between intraspecific variability and interspecific divergence in entropy data for both genes. These observations are consistent with other {psi}Est-6 characteristics that combine features of functional and nonfunctional genes (Balakirev and Ayala 2003cGo, 2003dGo; Balakirev et al. 2003Go).

The entropy nucleotide-dependent characteristics of Est-6 and {psi}Est-6 are related to their base composition. In all seven species the main difference is in the GC content of third codon positions, which is significantly higher in Est-6 than in {psi}Est-6. There are few differences between Est-6 and {psi}Est-6 in AT overall content and in GC content at the first and second codon positions. Interestingly, for Est-6 there are noticeable differences in average values of the GC content between the third position (GC3) and the overall coding (GCc) positions, while these differences do not exist for {psi}Est-6 (table 2). Thus, there is a relationship between the nucleotide-dependent entropy and the differences in GC content.

The evolution of nucleotide composition has been extensively studied in different Drosophila lineages (for reviews see Moriyama and Hartl 1993Go; Akashi, Kliman, and Eyre-Walker 1998Go; Kliman and Eyre-Walker 1998Go; Rodrígues-Trelles, Tarrío, and Ayala 2000Go; Begun and Whitley 2002Go; Marais, Mouchiroud, and Duret 2003Go). Selection at the translational level, mutation bias, and recombination have been proposed as major factors determining base composition in Drosophila. All three factors seem to be involved in the evolution of the GC content of Est-6 and {psi}Est-6. Nucleotide variability and intragenic conversion events are significantly higher in {psi}Est-6 than in Est-6 (Balakirev and Ayala 2003aGo, 2004Go; Balakirev et al. 2003Go). GC content is significantly higher in exon I than in exon II for both genes, and this difference is more pronounced for Est-6 than for {psi}Est-6. Codon bias is uniformly higher for Est-6 than for {psi}Est-6, and codon bias is noticeably different between exon I and exon II (data not shown). Taking into account the fact that Est-6 and {psi}Est-6 are very closely linked genes (the intergenic sequence is only 193 bp long), these observations may indicate that translational selection is more pronounced in Est-6 than in {psi}Est-6; relaxed translational selection in {psi}Est-6 would lead to increased AT content.

A similar trend in GC content has been observed in comparative investigations of pseudogenes and their functional homologs of Drosophila (Shields et al. 1988Go; Starmer and Sullivan 1989Go; Moriyama and Gojobori 1992Go; Currie and Sullivan 1994Go; Sullivan et al. 1994Go; Ramos-Onsins and Aguadé 1998Go). A comprehensive survey of Caenorhabditis elegans, Saccharomyces, D. melanogaster, and human pseudogenes shows that the nucleotide composition of pseudogenes is invariably intermediate between genes and intergenic regions (Echols et al. 2002Go). Drosophila pseudogenes have nearly the same composition as intergenic DNA. In D. melanogaster, GC content is uniformly higher at silent sites in coding regions than in the putatively neutrally evolving introns (Kliman and Hey 1994Go).

In the amylase (Amy) gene family of Drosophila, decrease in GC3 content is coupled with gene and regulatory-element loss and decrease of selection intensity after duplication, suggesting that one of the two Drosophila types of Amy genes is undergoing functional decay (Zhang et al. 2002Go, 2003GoaGo, 2003bGo; Zhang and Kishino 2004Go). These authors suggest that one of the duplicated genes with low GC3 content (Amy3-type) is losing the ancient function. An unresolved question, however, is why the Amy3-type genes have not lost their function completely (Zhang et al. 2002Go). Inomata and Yamazaki (2000)Go have shown that the activity of amylase encoded by Amy1-type genes changes more in response to food quality and developmental stage than that encoded by Amy3-type genes, suggesting stronger regulation of the Amy1-type genes. The two genes have different expression and evolutionary patterns and may represent an intergene complex providing greater ability to respond to severe environments (see Balakirev and Ayala 2003cGo, 2003dGo, 2004Go).

There is evidence of a general positive correlation between GC3 content and functionality (Epstein, Lin, and Tan 2000Go; Lin et al. 2003Go). GC-rich genes tend to be of a greater transcriptional and mitogenic significance than AT-rich genes (Epstein, Lin, and Tan 2000Go). Moreover, third-base GC retention also identifies critical amino acids within individual proteins, as indicated by nonrandom patterns of codon variation between gene homologs (Epstein, Lin, and Tan 2000Go; Lin et al. 2003Go). Sequence analysis of human receptor tyrosine kinase genes confirms that functionally important transmembrane hydrophobic amino acids are specified by codons containing GC third bases significantly more often than transmembrane neutral amino acids. Amino acids encoded by GC third bases thus appear more tightly linked to cell function and survival than those encoded by AT third bases. The same pattern appears in tumor-associated genes undergoing either loss-of-function mutation or rearrangements. As in gene-pseudogene comparisons, genes undergoing loss-of-function mutation tend to be GC poor, whereas those involved in rearrangements tend to be GC rich. Moreover, actively transcribed genes use more often C and G at synonymous sites than low-expressed genes (Shields et al. 1988Go; Duret and Mouchiroud 1999Go).

The overall data on pseudogenes and nonfunctional sequences support the hypothesis that sites under low functional constraints tend to increase AT content (see however Duret and Hurst 2001Go). This AT bias has been observed for eukaryotic pseudogenes (Gojobori, Li, and Graur 1982Go; Li, Wu, and Luo 1984Go) and thoroughly investigated at the genomic level (Alvarez-Valin, Lamolle, and Bernardi 2002Go; Echols et al. 2002Go; Zhang and Gerstein 2003Go). There is evidence implying that in GC3-rich genes the majority of new mutations that are GC -> AT are eliminated by negative selection (Alvarez-Valin, Lamolle, and Bernardi 2002Go). SNP analysis of mammalian genomes evinces that GC-rich genes undergo an excess of GC -> AT mutations over AT -> GC mutations (Eyre-Walker 1999Go; Smith and Eyre-Walker 2001Go), but AT -> GC mutations have higher probability of fixation (Duret et al. 2002Go; Webster and Smith 2004Go). This fixation bias exhibits little variation across genome regions with different GC content (Lercher and Hurst 2002Go; Webster and Smith 2004Go) and could be explained by selection (Alvarez-Valin, Lamolle, and Bernardi 2002Go), biased gene conversion (Eyre-Walker 1993Go; Galtier et al. 2001Go; Birdsell 2002Go; Lercher and Hurst 2002Go; Marais 2003Go), or both (Smith and Eyre-Walker 2001Go; Lercher et al. 2002Go). Consequently, functional genes tend to be GC rich because negative selection eliminates the excess of GC -> AT mutations, whereas in pseudogene or nonfunctional sequences this elimination is not as efficient, leading to increased AT content. The contrasting characteristics of GC3 content and entropy values between Est-6 and {psi}Est-6 suggest that the major determinant of these differences may be a balance between the fixation-mutation bias (Alvarez-Valin, Lamolle, and Bernardi 2002Go; Webster and Smith 2004Go) and selection favoring increase in the GC3 content of Est-6 but not in {psi}Est-6. The observed differences in entropy and GC content may reflect an evolutionary shift associated with {psi}Est-6 pseudogenization and consequent functional divergence of {psi}Est-6 and Est-6.


    Supplementary Material
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
The main definitions are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/).


    Acknowledgements
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 
We are grateful to W. M. Fitch, B. Gaut, R. R. Hudson, and A. Long for detailed and valuable comments. We thank Elena Balakireva and Iria Blanco Barca for encouragement and help. This work has been supported by National Institutes of Health grant GM42397 to F.J.A.


    Footnotes
 
Takashi Gojobori, Associate Editor


    References
 TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Supplementary Material
 Acknowledgements
 References
 

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Accepted for publication June 14, 2005.


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