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Genetics, Vol. 174, 1469-1480, November 2006, Copyright © 2006
doi:10.1534/genetics.106.062018
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Heinrich Heine Universität Düsseldorf, Institut für Genetik, 40225 Düsseldorf, Germany
1 Corresponding author: Institut für Genetik, Universitätsstrasse 1, 40225 Düsseldorf, Germany.
E-mail: martin.hasselmann{at}uni-duesseldorf.de
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ABSTRACT |
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 TOP ABSTRACT MATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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) reveals a sevenfold increase of polymorphism within the sex determination gene complementary sex determiner (csd) that rapidly declines within 45 kb to levels of genomewide estimates. Although no recombination was observed within SDL, which contains csd, analyses of heterogeneity, shared polymorphic sites, and linkage disequilibrium (LD) show that recombination has contributed to the evolution of the 5' part of some csd sequences. Gene conversion, however, has not obviously contributed to the evolution of csd sequences. The local control of recombination appears to be related to SDL function and mode of selection. The homogenizing force of recombination is reduced within SDL, which preserves allelic differences and specificity, while the increase of recombination activity around SDL relaxes conflict between SDL and linked genes.
The sex determination locus (SDL) of the honeybee is an informative example for exploring the combined forces of recombination, linkage, and selection and their effects on the evolution of DNA sequences. Balancing selection operates strongly among sex-determining alleles. Homozygotes at SDL develop into diploid males that do not reproduce while heterozygotes at SDL differentiate into fertile females. As in all hymenopteran insects, males arise from hemizygous, unfertilized eggs. The great advantage of heterozygotes results in strong balancing selection at this locus. Rare alleles benefit from their increased representation in viable heterozygotes, while more common alleles have a selective disadvantage as they are present more often in nonviable homozygotes (KIMURA and CROW 1964; YOKOYAMA and NEI 1979). The sex determination function within SDL is encoded by the complementary sex determiner (csd) gene (see Figure 1A for exon structure) (BEYE et al. 2003; HASSELMANN and BEYE 2004).
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The complete isolation of SDL and its linked genomic sequences provides us with the power to determine the local recombination activity and the levels of polymorphism within SDL and its linked genomic regions. Recombination activity that increases with decreasing distance from SDL may be taken as evidence that recombination reduces the potential conflict between SDL and linked sites. Levels of polymorphism that decline with increasing distances from SDL may be a result of the combined forces of balancing selection at SDL, linkage, and recombination. Polymorphism differences among csd alleles could provide evidence of whether recombination has influenced sequence evolution within SDL (BEYE et al. 2003), which is under strong balancing selection (CHARLESWORTH 2004; HASSELMANN and BEYE 2004). Heterogeneity of nucleotide differences across csd sequences or a decay of linkage disequilibrium (LD) with physical distance may be taken as evidence of recombination, while shared clusters of polymorphic sites may indicate the occurrence of gene conversion resulting from recombination.
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MATERIALS AND METHODS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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Sequence and statistical analysis:
Fragments of loci DF37, DF33, HF63, KF, and KF22 that show linkage to SDL and loci of high (loci RR 21, RR11, RR17, RR28, RR7, and RR14) and low (loci RR 22, RR25, RR8, RR9, RR23, and RR19) recombining regions that show no linkage to SDL were amplified using standard protocols (HASSELMANN et al. 2001) from a population sample of 10 chromosomes (haploid drones) collected in Davis, California. Estimates of local recombination rates were derived from genetic mapping and sequence data (BEYE et al. 2006). Mean nucleotide differences () (NEI 1987) and standard deviations were calculated using the DnaSP 3.5.3 program (ROZAS and ROZAS 1999). Sequences were initially aligned using the ClustalX (THOMPSON et al. 1997) program and then manually edited by eye using the BioEdit program (HALL 1999). Gaps were excluded from the analysis. Sequence information from a chromosomal walk (BEYE et al. 2003) was used to design oligonucleotides that amplify fragments of linked loci: DF37, 5'-TACGATTGGCAGACACGAAGG-3' and 5'-CTGTGAAAGCAACACAAGTCC-3'; DF33, 5'-AGAATTGAATCTGTCACATCTGG-3' and 5'-TTACCAATCGCCATTG AAATTC-3; HF63, 5'-CGTGTTCGTCAAATAATCGC-3' and 5'-GCATACATGTTGAG AATCGAT-3; KF, 5'-TATTCGAAATAGAGAATCTTCACCG-3 and 5'-GATCGAATGTC CAAACTCGACG-3'; and KF22, 5'-TTGACACGTGCCTGAAGAAACAT-3' and 5'-CGATGGTTGCTTGTCGACTGACA-3'. Sequence information from the honeybee genome was used to design oligonucleotides that amplify loci of high and low recombining regions (available from the authors upon request).
Distances between loci 3' of csd rely on complete sequence information (for KF and KF22) and the restriction map (BEYE et al. 2003). Specific PCR reaction conditions are 94° for 160 sec, followed by 35 cycles of 94° for 30 sec, 52° for 30 sec for primer combination DF33, or 55° for primers HF63 or 60° for primers DF37, KF, and KF22, followed by a final step of 72° for 30 sec. Amplified fragments were resolved on 1.3% agarose gels (HASSELMANN et al. 2001), eluted, and cloned into the pGEM-T vector (Promega, Madison, WI). Sequencing was performed by MWG Biotech AG (Ebersberg, Germany).
Sequence characteristics, such as simple repeats, low-complexity DNA, and guanine–cytosine (GC) content of high and low recombining regions, were analyzed using the program Repeatmasker version 3.0.8 (http://repeatmasker.genome.washington.edu). Sequences were derived from contigs NW 629957.1; NW 627483.1, and NW 623616.1 of the honeybee genome.
Analyses of allelic csd sequences were performed only on the cDNA sequences of the type I class (HASSELMANN and BEYE 2004), as they show signatures of balancing selection. Heterogeneity across exon 2–3, exon 4–5, and exon 6–9 sequences (BEYE et al. 2003; HASSELMANN and BEYE 2004) was calculated separately for the number of nonsynonymous (dn) and synonymous (ds) differences per site (KIMURA 1980). Genetic distances were measured using Kimura's two-parameter model and used to construct a neighbor-joining tree implemented by the MEGA 2.1 program (KUMAR et al. 2001). Bootstrap resampling of 1000 replications was applied. LD, R2, and D' were estimated using the R2 program (http://www.daimi.au.dk/
compbio/r2). To test whether R2 or D' correlate with distance, levels of significance were determined from 5000 permutations that include either all polymorphic sites or only synonymous sites that have a frequency >10% (R2 program; http://www.daimi.au.dk/compbio/r2). The Stephens test (STEPHENS 1985), Sawyer's test (SAWYER 1989) (which is implemented in the GENECONV 1.81 program; http://www.math.wustl.edu/sawyer), and a maximum-composite-likelihood method (implemented in the MAXHAP program) were applied to identify the impact of short clusters of shared polymorphism among alleles on the overall variation. The Stephens test examines whether a collection of shared polymorphisms is consistent with a model of building two groups of sequences. Levels of significance were evaluated under the null hypothesis of a random distribution of sites. Sawyer's test identifies shared clusters of sites in pairwise alignments and evaluates their significance in the overall alignment by 10,000 random permutations of all polymorphic sites. Mismatches within the cluster of shared polymorphic sites were allowed and scaled by setting g at 2. The maximum-composite-likelihood method (HUDSON 2001) estimates a gene conversion rate parameter (f), which is the ratio of gene conversion to crossing-over rate. The gene conversion model assumes different tract lengths (denoted as L in base pairs) while sites with more than two alleles are ignored. Analysis were performed by setting f = 0 (no gene conversion) and f > 0 (crossing over with gene conversion). Under the gene conversion model, values are obtained that maximize the composite likelihood over the set of f-values (fmin = 0.1 to fmax = 10).
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RESULTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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2 = 4.03, P = 0.04). When a correction of small sample size of recombined genotypes is taken into account, the differences are marginally significant (Yates-corrected 2 = 3.1, P = 0.08). In contrast to the finding of an elevated recombination activity in flanking regions, no recombination event was observed within a genomic region of 36 kb that encompasses SDL. This result is not expected under the genomewide recombination rate (2 = 6.02, P = 0.01; Yates-corrected 2 = 4.18, P = 0.04) or under the recombination rate of the flanking regions (28.3 cM/Mb; 2 = 8.03, P = 0.005; Yates-corrected 2 = 6.2, P = 0.01), suggesting that recombination is reduced, or even suppressed, within SDL. An alternative explanation of this finding is that recombination within SDL results in nonfunctional sex-determining alleles that ensure male development (BEYE et al. 2003). Eggs that develop into diploid males are not included in the analysis as they are eaten by worker bees shortly after they hatch (MACKENSEN 1955). This is an unlikely scenario, however, as the gene that initiates female development by heterozygous allelic composition, csd, is confined to only a part of the whole SDL region (9 of 36 kb), while recombination events are expected to occur, on average, every 3 kb, given the local recombination rate. We were not able to detect any sequence characteristics (simple repeats, low-complexity DNA, increased GC content) specifically associated with the high recombination rate in closest proximity to SDL (0–10 kb) when compared to regions of more distant sequences (50–150 kb) using sequence analysis software (data not shown). We detected two putative chi-like motifs (CGACCACC) (CHENG and SMITH 1984), which are not present in the more distant sequences of 50–150 kb, as potential crossover instigators in the region of high recombination rate. This finding does not favor a simple, direct mechanistic interpretation that the local increase of recombination rate is solely based on distinct sequence differences. Even if differences in sequence composition or number of instigator motifs are mechanistically responsible for a higher recombination activity, the heterogeneity of potential facilitators across this sequence demands an explanation. Moreover, the finding that recombination rate steadily and independently increases on both sites of SDL in combination with recombination activity being reduced or even suppressed within SDL suggests a local control of recombination activity that is related to SDL function and to being a target of balancing selection.
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) was estimated at 5 linked and 12 unlinked loci that were compared to exon data of csd (Table 1). Linked loci are located at distances of 1.5, 2, 12, 28, and 45 kb downstream of csd, the gene under balancing selection. The unlinked loci were chosen to include regions of both high and low recombination. The loci themselves are assumed to not be direct targets of selection (i.e., neutral markers), as homology searches indicated no similarity to genes or regulatory elements (data not shown). Although several primer combinations were tested, not all chromosomes were amplified. The most plausible explanation is mismatches of primers to the designated binding sites in some haplotypes, but not in others, which is consistent with the finding that the number of nonisolated fragments increases with the number of nucleotide differences (see Table 1). When loci downstream of csd are compared, nucleotide diversity () sharply declines from 0.09 at exon 6/7 within the first 5 kb of distance (Figure 1D), but flattens within the subsequent 30 kb. KF22, a locus just 1.5 kb from the 3'-end of the csd gene, is 14 times higher when compared to DF37, a locus 43.5 kb downstream [ = 0.0233 vs. = 0.00169 (Table 1); Z-test, Z = 2.9; two-tailed: P < 0.01)] that is 4 times higher than our genomewide average estimate [ = 0.0233 vs. = 0.0055 (Table 1); Z-test, Z = 2.1; two-tailed: P < 0.05], suggesting that linkage to csd has a strong influence on sequence evolution. The severalfold increase of nucleotide diversity at linked downstream sites cannot be explained by the higher local recombination rate as diversity in regions of high recombination rates (51–72 cM/Mb) is still several magnitudes lower (Table 1). Although balancing selection substantially increases diversity at closely linked sites (<20 kb), this does not extend to larger distances. Within 45 kb, levels of polymorphism decline to the genomewide average estimate.
The analysis of at synonymous sites within csd (Figure 1A) shows a similar but weaker decline with distance (Figure 1D). The highest diversity is found in exon 6/7, which is 4 times higher than that of KF22 [ = 0.0918 vs. = 0.0233 (Table 1); Z-test, Z = 3.1; two-tailed: P < 0.01)], 7 times higher than that of exon 4/5 [ = 0.0918 vs. = 0.0135 (Table 1); Z-test, Z = 3.4; two tailed: P < 0.01], and 17 times higher than our estimate of the genomewide average [ = 0.0918 vs. = 0.0055 (Table 1); Z-test, Z = 4.0; two tailed: P < 0.01]. The striking differences suggest that exon 6/7 is a strong target of balancing selection within the csd gene.
Signatures of intragenic recombination among csd sequences:
No recombination was observed within the region of SDL containing the sex determination gene csd (Figure 1B). To explore whether recombination has contributed to the evolution of sex-determining alleles in the past, we searched for signatures of recombination in the coding sequences of csd.
Signatures of recombination in long segments of the sequence:
Tests of heterogeneity were performed on the combined exons, exon 2+3, exon 4+5, and exons 6–9. These combined sequences represent the specific clustering of exons in the genome (Figure 1A). The rationale of combining these exon sequences is that they are separated by large introns, which enhances the potential to detect signatures of recombination. Heterogeneity of nucleotide differences across exons was explored using the neighbor-joining method (Figure 2). Differences in the lengths of terminal branches illustrate that some alleles are more similar when differences in exon 2+3 and 4+5 sequences are compared (Figure 2, A and B; indicated by a shaded bar), but are more diverged when exon 6–9 sequences are examined (Figure 2C).
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30% of comparisons demonstrate heterogeneity, which again do not depend on whether synonymous or nonsynonymous sites are analyzed (e.g., B2-25 and D2-38; example 15 in Table 2), indicating a miscellaneous relation of these sequences. Heterogeneity is less frequent in exon 4+5 when compared to exon 2+3 comparisons (Table 2, lines 4 and 7). Other exon 4+5 sequences, however, are very similar to exon 2+3 sequences (see the shaded bars in Figure 2B and representative examples in Table 2, lines 1 and 6). Taken together, these analyses suggest that a considerable fraction of alleles share a more recent ancestral exon 2+3 sequence, an occurrence that is less frequently detected among exon 4+5 sequences. This finding is consistent with sporadic recombination, the likelihood of which increases with larger distances from exons 6–9, where balancing selection operates most strongly. LD of polymorphic sites among csd alleles was evaluated using R2 and D' estimates. The more distant two segregating sites are, the greater the probability that recombination has occurred. Under this model, we would expect to find a decay of LD with increasing distance between sites. The analysis (Table 3) was conducted on variants with a frequency of >10%, for all sites, and on synonymous and silent sites separately. When all sites are included, LD slightly decreases with physical distance for R2 (r = –0.13, P < 0.001), which is only marginally significant for D' (r = –0.08, P < 0.08). If the analysis is restricted to only synonymous sites, a correlation is supported only for D' (r = –0.4, P < 0.01). A previous study (INNAN and NORDBORG 2002) argued that heterogeneity across a sequence can mimic a decline of LD with distance. Thus, we analyzed exons 2–5 and exons 6–9 separately, as heterogeneity has been identified in these sequences (HASSELMANN and BEYE 2004). LD strongly decays with physical distance in exon 2–5 sequences when all differences are included (r = –0.5 for R2 and D', P < 0.001). The four synonymous sites follow the strong negative trend, but are too few to support the finding. There is support for a weak decline of R2 with distance in exon 6–9 sequences when all sites are included (r = –0.18, P < 0.001), although this is not supported by D' (r = –0.09, P < 0.1). LD decreases even more strongly in exons 6–9 when only synonymous sites are analyzed (r = –0.37, P < 0.05 for R2 and r = –0.56, P < 0.01 for D'); however, this estimate is based on only seven sites. Combined with the former results of the heterogeneity test, the LD analysis supports the operation of recombination among exon 2–5 sequences.
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2 = 0.14, P = 0.7). Given that the clusters are not the result of recurrent mutations, but rather of a single event of gene conversion, random association of these clusters is a further sign that recombination has operated among alleles. The minor, if any, contribution of gene conversion is further supported by the maximum-composite-likelihood analysis (HUDSON 2001). The maximum composite likelihood of exons 2–5 with the model of no gene conversion (f = 0) and the most likely gene conversion model (10% gene conversion: f = 0.1), were nearly identical (
= –722; Table 6). The distribution of sites can be explained either by recombination alone or by recombination plus a small contribution of gene conversion, irrespective of the various trace lengths of the gene conversion model (L = 50, 100, and 500 bp). Similar results were obtained for exons 6–9, although the contribution of recombination was far less dominant ( = –2955.35). Taken together, these analyses suggest that gene conversion has not played an important role in the sequence evolution of csd alleles.
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DISCUSSION |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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We have estimated local recombination activity within and around SDL on the basis of a large mapping population and defined physical fragments. The recombination rate increases from 2.5–5 times higher on both sides of SDL within a distance of 50–215 kb. This local increase is even more dramatic when the unobserved recombination within SDL and the high genomewide rates of recombination (HUNT and PAGE 1995; SOLIGNAC et al. 2004) are taken into account. These defined and pronounced differences suggest a position-specific control of recombination and demand an explanation related to SDL function and balancing mode of selection. Mechanistic explanations such as repair (BERNSTEIN et al. 1981) or the stabilization of chromosome segregation (BAKER et al. 1976; HAWLEY and THEURKAUF 1993) cannot explain these distinct differences within several kilobases. No obvious sequence characteristics associated with the severalfold recombination differences have been detected, which would support a direct mechanistic interpretation of recombination activity. The strength of selection at SDL (YOKOYAMA and NEI 1979) combined with the finding that rates of recombination can change in response to selection (MICHOD and LEVIN 1988; OTTO and BARTON 2001) suggests instead an evolutionary explanation. Recombination could be selectively favored to reduce interference between SDL and linked sites or genes. On average, linked genes likely experience selective pressures other than balancing selection. Recombination reduces conflicts by relaxing linkage between SDL and flanking genes, which in turn may improve the response to selection.
The conflict of selection could be rather strong at csd as genetic drift, which generates more frequent and more rare sex-determining alleles, is a dominant evolutionary force in honeybees. Rates of genetic drift are dependent on the effective size of a population. Honeybees have small local breeding populations (the queen is the only reproductive female) when compared to nonsocial insects (CROZIER 1979; PAMILO and CROZIER 1997). Several identified genes in close linkage (data not shown), upstream and downstream of csd, could be a source of selective conflicts.
In agreement with the evolutionary interpretation of an increase of recombination activity to decrease the selective interference among loci that have different selection regimes, several hot spots of recombination have been identified in the human MHC class II gene cluster (CULLEN et al. 2002). Recombination activity increases up to 100 times the genomewide average in several regions of this gene complex. In contrast to SDL, the increase of activity is found in different parts of the MHC gene cluster and is confined to small genomic regions of only several kilobases (JEFFREYS et al. 2001). The evolutionary interpretation of the MHC study is obviously more complex, as several genes of the MHC are under balancing selection while others are not (the MHC class II complex comprises >15 genes) (GARRIGAN and EDWARDS 1999; BECK and TROWSDALE 2000) and the strength of balancing selection differs among genes (MEYER and THOMSON 2001).
No recombination activity was detected within SDL, suggesting that recombination is reduced or even suppressed. This finding contradicts a previous hypothesis (BEYE et al. 1999) that an increase of recombination activity among SDL alleles could improve the effectiveness of removing deleterious mutations (KONDRASHOV 1984; RICE 2002). A reduction or even a suppression of recombination will preserve allelic differences, specificity, and function as recombination is a homogenizing force that will generate more similar sex-determining alleles over time. An unanswered question is, Why is the suppression of recombination not precisely restricted to the 9-kb genomic region of csd, the initial signal of complementary sex determination that is under balancing selection, but is also found in an additional 27 kb of genomic sequence?
Signatures of intragenic recombination in csd sequences:
Although we have no direct evidence of recombination activity within SDL, we have detected signatures of recombination among some 14 csd sequences. Tests of heterogeneity identified eight alleles most similar in exon 2+3 that extend in similarity to exon 4+5 for some allelic combinations. This is consistent with sporadic recombination that is more frequently detected with larger distances between exons. Concerted evolution and recurrent mutation could also lead to heterogeneity across haplotypes, although they are unlikely forces on the basis of the number of differences that were analyzed. In addition, weaker diversifying selection and stronger selective constraint on exon 2–5 sequences are unlikely alternative explanations as (i) silent sites show the same pattern; (ii) heterogeneity is absent in several alleles (e.g., Table 2, lines 16–18), arguing against a ubiquitous selective force but favoring a random process such as recombination; and (iii) the decline of LD with physical distance strengthens a model of recombination, but is not a plausible explanation under various models of selection. GC content or codon bias could homogenize sequences (HUGHES et al. 1993), but should effect all alleles similarly. In contrast to exon 2+3 and exon 4+5 sequences, there is only weak support for recombination within exon 6–9 sequences; all exon 6–9 sequences are highly diverged. There is, however, support for a decay of LD with distance in some tests, which indicates a potential weak role of recombination within exons 6–9.
The Sawyer's test, the Stephens test, and the maximum-composite-likelihood analysis provide little evidence that gene conversion has substantially contributed to the evolution of csd alleles. The contribution is rather small, if any, comprising <10% of nucleotide differences as shown in the Stephens test analysis. In contrast to SDL, gene conversion has contributed substantially to the evolution of MHC (HUGHES et al. 1993; OHTA 1997; TAKAHATA and SATTA 1998a; HOGSTRAND and BOHME 1999) and self-incompatibility alleles (S-alleles) (KUSABA et al. 1997; WANG et al. 2001). For example, almost all variation of HLA-DPB1 haplotypes in humans (MOONSAMY et al. 1992; ZANGENBERG et al. 1995) is confined to short clusters that are possibly the result of gene conversion. Statistical analysis of mouse MHC class I genes using the Sawyer's and the Stephens test identified 25 clusters that could be the products of gene conversion (KUHNER et al. 1990). Even though signatures of gene conversion in these sequences are quite common, the question of whether gene conversion has adaptive significance in the rise of new, functional allelic MHC variants, or is instead the consequence of the basic genetic process of recombination, is not yet settled (MARTINSOHN et al. 1999).
In summary, the analyses of heterogeneity, LD, and shared sites suggest that recombination has contributed to the evolution of exon 2–5, but not exon 6–9 sequences. The finding that not all alleles are affected supports a suppression of recombination within SDL so that recombination operates only sporadically. Hence, recombination is not a dominant evolutionary force in the short term, but has contributed to the sequence evolution of some csd alleles in the long term. This interpretation is in agreement with functional considerations that higher levels of recombination are a strong homogenizing force that makes alleles more similar and thus less functional, or even nonfunctional. Exons 6–9 show no signatures of recombination that would favor the idea that this region encodes the allelic specificity, while the exon 2–5 sequences are less constrained. Although very few signatures of gene conversion have been detected, these clusters are randomly associated across alleles (Table 5 shows the associations and the different amino acids that the clusters encode) and could be a potential source of allelic differentiation. Further molecular studies could test whether these clusters contribute to the specificity and functioning of sex- determining alleles.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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FOOTNOTES |
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LITERATURE CITED |
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TOPABSTRACTMATERIALS AND METHODSRESULTSDISCUSSIONACKNOWLEDGEMENTSLITERATURE CITED |
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