Genome-Wide Patterns of Expression in Drosophila Pure Species and Hybrid Males

Pawel Michalak and Mohamed A. F. Noor

Department of Biological Sciences, Louisiana State University

Correspondence: E-mail: mnoor{at}lsu.edu.


    Abstract
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
One of the most fundamental questions for understanding the origin of species is why genes that function to cause fertility in a pure-species genetic background fail to produce fertility in a hybrid genetic background. A related question is why the sex that is most often sterile or inviable in hybrids is the heterogametic (usually male) sex. In this survey, we have examined the extent and nature of differences in gene expression between fertile adult males of two Drosophila species and sterile hybrid males produced from crosses between these species. Using oligonucleotide microarrays and real-time quantitative polymerase chain reaction, we have identified and confirmed that differences in gene expression exist between pure species and hybrid males, and many of these differences are quantitative rather than qualitative. Furthermore, genes that are expressed primarily or exclusively in males, including several involved in spermatogenesis, are disproportionately misexpressed in hybrids, suggesting a possible genetic cause for their sterility.

Key Words: gene expression • hybrid sterility • reproductive isolation • DNA microarrays


    Introduction
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
The formation of new species is often associated with reduced fertility or viability of hybrid progeny (Coyne and Orr 1989, 1997; Sasa, Chippindale, and Johnson 1998; Presgraves 2002; Price and Bouvier 2002). Dobzhansky (1936) proposed that hybrid sterility and inviability may arise as pleiotropic by-products of evolution in geographically separate lineages: alleles that increase fitness in pure-species genetic backgrounds may fail to interact properly when brought together in hybrid backgrounds. A distinctive feature of hybrid sterility and inviability is that they require epistasis: nonadditive interactions between alleles at different loci (Dobzhansky 1937; Muller 1940; Johnson and Porter 2000; Turelli and Orr 2000). Several types of gene interactions may create hybrid dysfunctions:

  1. Amino acid differences accumulated in divergent populations may render proteins incapable of interacting properly, thereby producing unfit phenotypes (e.g., Rawson and Burton 2002).
  2. Post-transcriptional processes such as mRNA splicing or mRNA stability may be disrupted (e.g., Braidotti and Barlow 1997).
  3. 3. Genes may be inappropriately overtranscribed or undertranscribed (misregulated) in hybrids relative to pure species (see below).

Both theoretical and empirical studies suggest that failures in the regulation of gene expression may contribute to hybrid dysfunctions (see review in Orr and Presgraves 2000). For example, Johnson and Porter (2000; see also Porter and Johnson [2002]) modeled the evolution of regulatory genetic pathways and found that binding strength of proteins to promoter regions can provide biologically plausible hybrid sterility. An empirical example is provided by the overexpression of Xmrk-2 oncogene (Xiphophorus melanoma receptor kinase) that is associated with tumor formation and hybrid lethality in crosses between swordtails (Xiphophorus helleri) and platyfish (X. maculatus) (Schartl 1995; Schartl et al. 1999). To evaluate the role of gene expression in hybrid sterility, technological advances can now enable researchers to examine expression patterns of hundreds or thousands of genes in hybrids relative to nonhybrids simultaneously.

Genome-wide expression profiling can rapidly identify whether qualitative failures in gene expression are associated with hybrid male sterility, and if so, what genes or genetic pathways are responsible. Two hypotheses may predict the identity and the location of genes that are misexpressed in hybrids, and hence possibly associated with sterility. First, genes expressed predominantly in males and the male germ line, and thus often subject to accelerated microevolutionary divergence (see review in Singh and Kulathinal 2000), may be most likely to be deregulated in hybrids. In Drosophila, it has been shown that male reproductive proteins, such as accessory gland proteins (Acps), can be twice as divergent between species as nonreproductive proteins (e.g., Civetta and Singh 1995). The coding regions of their corresponding genes exhibit a significant excess of nonsynonymous over synonymous substitutions, suggesting that positive Darwinian selection accelerated their divergence (e.g., Swanson et al. 2001). Second, X-chromosomal genes may be misexpressed in hybrids more than autosomal genes, corresponding with suggestions of a disproportionate X-effect in hybrid sterility (Charlesworth, Coyne, and Barton 1987; Coyne and Orr 1989; True et al. 1996).

To evaluate the potential for gene misexpression to cause sterility in hybrids, we must first ascertain whether and how much gene misexpression is detectable in hybrids and the nature of the misexpressed transcripts. In a previous study, Reiland and Noor (2002) documented a handful of transcripts misexpressed in hybrids of Drosophila pseudoobscura and D. persimilis relative to pure species, but their differential display technique had very low resolution for detecting quantitative differences in gene expression. Here, we apply much higher resolution techniques, microarrays and real-time fluorescent quantitative PCR, to examine differences in gene expression between two Drosophila species (D. simulans and D. mauritiana) and their sterile F1 hybrids. Infertility in male hybrids between these species is associated with spermiogenic, or postmeiotic, failure at the cytological level (Wu et al. 1992). We evaluate whether genes with male-specific patterns of expression, or those located on the X chromosome, are disproportionately disrupted in hybrids, testing the hypotheses laid out above, and we discuss the implications of our findings with regard to Haldane's rule (Haldane 1922).


    Methods
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
Flies
Stocks were reared in uncrowded cultures at 24°C with a 12-h light-dark cycle on standard sugar-yeast-agar medium. Drosophila simulans flies were taken from the Florida City (FC) line, an isofemale line collected in 1985 in Florida City. Drosophila mauritiana were taken from the SYN stock, a wild-type line synthesized by combining six isofemale lines collected on Mauritius in 1981. All F1 hybrids were produced by crossing D. simulans females with D. mauritiana males.

Oligonucleotide Microarray Assays
For each replicate, 5 µg of total RNA were obtained from 23 seven-day post-eclosion adult Drosophila simulans, D. mauritiana, and F1 hybrid males with the QIAGEN RNeasy kit. A total of 14 Affymetrix GeneChip Drosophila Genome array chips were used: 5 x D. simulans, 4 x D. mauritiana, 5 x F1 hybrids. The GeneChip Sample Cleanup Module (QIAGEN) was used according to the Affymetrix standard hybridization protocol. Double-stranded cDNA was synthesized with a T7-(dT)24 primer; cRNA was synthesized and biotin-labeled in an in vitro transcription reaction using the ENZO BioArray HighYield RNA Transcript Labeling Kit. The final concentration of cRNA in the fragmentation mixture was 0.5 µg/µL. The target cRNA was hybridized to arrays that allow one to monitor the relative abundance of more than 14,000 mRNA transcripts. Patterns of hybridization were detected in an Affymetrix scanner, and the results were analyzed using Affymetrix Microarray Suite (MAS) 5.0 software. The software Detection algorithm calculates the Discrimination Score from each probe pair (Perfect Match vs. Mismatch), assesses probe saturation, calculates a Detection P value from the one-sided Wilcoxon Signed Rank test, and assigns a Present, Marginal, or Absent Call in relation to a threshold value Tau = 0.015. All transcripts were scaled to a target intensity value of 10,000.

Expression differences obtained from this assay may be confounded by sequence differences between these species and D. melanogaster. Hence, we focus on those transcripts that show little difference in hybridization between the two pure species assayed but a large difference between the pure species and the F1 hybrid males. As the F1 hybrids were produced from the same strains as the pure species evaluated, they would possess no sequence difference from them, and differences in hybridization between these pure species and these F1 hybrids must reflect differences in transcript abundance.

Real-Time Polymerase Chain Reaction
For the real-time polymerase chain reaction (RT-PCR), 250 ng of total RNA prepared as described above were reverse transcribed in a reaction bearing 5 mM MgCl2, 50 mM KCl, 10 mM Tris–HCl, 1 mM dNTPs, 20 U RNasin, 20 U reverse transcriptase (SuperScript II), 2.5 µM of the target primer, and 50 nM of 18SrRNA reverse primer (Applied Biosystems [ABI]). All real-time PCR primers and fluorescent probes were designed using Primer Express 2.0 software (ABI), and their sequences are available by request. All target probes were FAM-labeled (Biosearch Technologies), and the normalizer probe (18S rRNA) was VIC-labeled (ABI). Pre-developed ABI TaqMan Assay Reagents and ABI standard protocols were used to prepare the RT-PCR reaction mixture. The probes contain a reporter dye at the 5' end of the probe and a quencher dye at the 3' end of the probe. During the reaction, the reporter dye and quencher dye are separated, resulting in increased fluorescence of the reporter. All PCRs consisted of an initial 2 min at 50°C and 10 min at 95°C, 40 cycles of 95°C for 15 s and at 60°C for 1 min. Applied Biosystems Prism 7000 SDS software was used for visualization and quantification of the amplification products.

Statistical Analysis
Standard one-way analyses of variance (ANOVAs) were used for detecting differences in expression between each pure species individually and the F1 hybrids. In addition, we used Bayesian regularized t-tests (Baldi and Long 2001; Long et al. 2001) to compare microarray expression signals between pure species and F1 hybrids. In this analysis, a prior estimate of variance within groups is estimated by the weighted average of a prior estimate of the variance for that gene (obtained from the local weighted average of the variance of other genes) and the experimental estimate of the variance for that gene. This leads to the desirable property of the Bayesian approach converging toward the t-test as the number of replicates increases and prior variance tends to zero. The mean difference in threshold cycle number (CT) was tested with a post hoc Duncan test after the 2-way repeated measures ANOVA analysis, in which genotype (D. simulans, D. mauritiana, and hybrids) effect was significant (P < 0.05). There were two levels of replications: two independent reverse transcriptase reactions and two PCR replicates of each sample within the RT reaction. All results were repeatable when different cycle thresholds were tested and were largely independent of whether or not normalization for 18SrRNA was applied.


    Results
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
Microarray Analysis
The mean expression of 435 genes in this assay differed significantly between F1 hybrids and either D. simulans or D. mauritiana (P < 0.05, ANOVA; fig. 1). The number decreased to 37 underexpressed and 14 overexpressed genes when the analysis was confined to those transcripts which differed significantly in F1 hybrids from both D. simulans and D. mauritiana analyzed separately (ANOVA, P < 0.05, see table 1 in the online Supplementary Material; all raw microarray data can be found at http://www.biology.lsu.edu/webfac/mnoor/alldata.xls). None of these genes were significantly misexpressed if a conservative Bonferroni correction was applied, but we were nonetheless able to confirm many of them via real-time PCR (see below). To estimate the extent of misexpression after eliminating genes not detectably expressed in pure-species males and those which fail to hybridize to the D. melanogaster array, we limited the analysis in two manners: (1) those transcripts which were detectably present based on Present Call in Affymetrix MAS 5.0 software in all 9 pure-species chips and (2) those transcripts for which the standard deviation of the expression level (calculated as Signal Call) within pure-species replicates was less than 25% of the mean assayed expression level (following Leemans et al. 2000). Limiting the data set according to (1) resulted in 10 underexpressed candidate gene and 1 overexpressed (CG11266, splicing factor) candidate gene from a total of 692 genes assayed. According to grouping (2), we identified 8 underexpressed candidate genes and 1 overexpressed candidate gene (CG11266) from a total of 394 genes. Transcripts designated as underexpressed in both groupings included several that previously had been shown to be expressed exclusively in testes and thus presumably are responsible for spermatogenesis: CG2206, Mst84Da, Mst84Db, Mst84Dc, Mst84Dd (Andrews et al. 2000; Jin et al. 2001; Swanson et al. 2001; Parisi et al. 2003), the RNA binding CG14718, cytosol aminopeptidase (CG13340), and complex homolog subunit 6 (CH6). Although statistically significant overexpression or underexpression of transcripts was observed, most differed in expression by a factor of two or less in hybrids relative to pure species. This observation may reflect truly quantitative differences or tissue-specificity of the disruptions in gene expression. No qualitative differences (e.g., tenfold or greater) in expression were noted between pure species and hybrids. Only one underexpressed gene, Mst84Dc, exhibited higher than fourfold underexpression in hybrids relative to both pure species, and this was the only gene with significant misexpression detected when a Bayesian regularized t-test was applied to the full data set (posterior P < 0.05) (Baldi and Long 2001; Long et al. 2001). For all subsequent analyses on the microarray data, we performed statistical tests on (1) all genes assayed on the chips and (2) only those genes which were detectably present based on Present Call in Affymetrix MAS 5.0 software in all 9 pure-species chips.



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FIG. 1. Volcano plots of gene expression difference (A) between pure D. simulans and F1 hybrids, and (B) between D. mauritiana and F1 hybrids. Each point represents a transcript from the microarray assay. The log10 fold change (ratio of mean expression values of pure species and F1 hybrids) is shown on the x-axis and the -log10 P values from ANOVA significance tests are shown on the y-axis

 

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Table 1 Repeated Measures ANOVA of Gene Expression, as Measured with Real-Time PCR, for Mst84Dc, Mst98Cb, CG5762, and CG4792 Genes.

 
Male-Specificity of Misexpression
We assigned transcripts from our microarray analysis to two sets: male-specific transcripts (according to combined lists from Andrews et al. 2000; Jin et al. 2001; Swanson et al. 2001; Parisi et al. 2003; from Jin et al. 2001 and Parisi et al. 2003, we took only those transcripts that differed between sexes by more than 100%) and all other genes. We then divided each set into two complementary subsets: one consisting of genes differing significantly in expression between both pure species and hybrids (ANOVA, P < 0.05 for both D. simulans and D. mauritiana, 51 genes in total; see Supplementary Material online) and the rest with no significant difference. We found that statistically significant misexpression tends to occur much more frequently in the male-specific group for both grouping criteria used (fig. 2). Indeed, based on grouping criterion (2), 11 genes exhibited statistically significant differences in expression between pure species and hybrids, and 6 of the 11 were male-specific. In contrast, only 34 of the 665 genes not exhibiting significant differences in expression between pure species and hybrids were expressed primarily in males.



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FIG. 2. Frequency (numbers in bars) of statistically significant misexpression (black), as detected by ANOVA (P < 0.05) of the microarrays, among male-specific genes (open) and all other genes (dotted) in F1 hybrids relative to both D. simulans and D. mauritiana. Genes were defined as male-specific according to the criteria of Andrews et al. 2000, Jin et al. 2001, Swanson et al. 2001, and Parisi et al. 2003. Overexpressed genes were included in the analysis, but only one of those occurred among male-specific genes. (A) All transcripts: chi-square = 51.55, df = 1, P < 0.0001. (B) When the comparison is limited to transcripts detectably present ("P" in Affymetrix MAS 5.0 software) in all 9 pure-species chips, misexpression in hybrids is ~19 times more frequent among male-specific genes (chi-square = 47.50, df = 1, P < 0.0001)

 
We also compared the mean expression level in hybrids relative to pure species between male-specific genes and all other genes (fig. 3). The difference was highly significant for both species and for both grouping criteria used: (1) D. simulans, Student t-test, t = 15.751, df = 13964, P < 0.0001; D. mauritiana, Student t-test, t = 3.371, df = 13964, P = 0.0008; (2) D. simulans, t = 10.444, df = 674, P < 0.0001; D. mauritiana, t = 4.175, df = 674, P < 0.0001). A similar result was obtained when fold change values were replaced with -log10 of P values from respective ANOVA contrasts (Mann-Whitney U test, P < 0.05).



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FIG. 3. Mean fold change (±SE) between F1 hybrids and pure species in male-specific gene expression (open) relative to all other genes (dotted) in microarrays. Genes were defined as male-specific according to the criteria of Andrews et al. 2000, Jin et al. 2001, Swanson et al. 2001, and Parisi et al. 2003. (A) D. simulans. (B) D. mauritiana. Left two bars: all transcripts; right bars: transcripts detectably present

 
The Analysis of X Chromosome Misexpression Linkage
We compared frequencies of significant misexpression (according to ANOVA, P < 0.05) within the group of the X chromosome–associated transcripts against the autosome-associated transcripts group. We did not observe a significant association of gene misexpression with chromosome X for any comparison (2 x 2 chi-square test, P > 0.05, see also table 2 in the online Supplementary Material).

Real-Time PCR Analysis
We validated the putative underexpression of Mst84Dc with quantitative fluorescent real-time PCR (RT-PCR, TaqMan Applied Biosystems). In this assay, we used a repeated measures ANOVA in which 12 bulk-RNA samples from males (4 each from D. simulans, D. mauritiana, and F1 hybrids) were analyzed, and each sample was replicated in two reverse-transcription reactions followed by independent RT-PCR assays. The cDNA from all F1 samples consistently amplified exponentially after ~4 more PCR cycles than pure species samples, indicated as higher threshold cycle (CT) values for hybrid samples than for nonhybrid samples (fig. 4a). This delayed amplification suggests a lower concentration of the transcript in hybrids than in pure species (table 1).



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FIG. 4. RT-PCR amplification plots for three genes: (A) Mst84Dc, (B) Mst98Cb, and (C) CG5762. Each curve represents a single sample; pure species in blue, F1 hybrids in red. PCR cycle numbers are shown on the x-axis and normalized fluorescence intensity (Rn) reflecting cDNA level is shown on the y-axis. (A) D. simulans was significantly different from F1 (P = 0.002, Duncan test) but not from D. mauritiana (P = 0.312). D. mauritiana differed from F1 (P = 0.015). (B) D. simulans was significantly different from F1 (P = 0.0002) but not from D. mauritiana (P = 0.068). D. mauritiana was different from F1 (P = 0.006). (C) D. simulans differed from F1 (P = 0.0009) but not from D. mauritiana (P = 0.070), and D. mauritiana was different from F1 (P = 0.041)

 
We extended the RT-PCR analysis and the ANOVA design to three additional genes: Mst98Cb, CG5762, both known to be among genes expressed predominantly in the male germ line (Andrews et al. 2000; Jin et al. 2001; Swanson et al. 2001; Parisi et al. 2003), and CG4792, which was a randomly chosen negative candidate from our microarray analysis and does not have a sex-specific expression pattern (table 1). Both Mst98Cb and CG5762 consistently exhibited mean CT values in F1 hybrids significantly higher by ~1.5 cycles than in nonhybrids, and there was no significant difference between D. simulans and D. mauritiana (fig. 4b and c). The expression level of our negative control, CG4792, which encodes an RNA helicase-like enzyme, did not differ significantly between hybrids and nonhybrids.


    Discussion
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
For more than 60 years, it has been recognized that hybrid sterility and other hybrid dysfunctions are caused by failures in epistatic interactions between alleles at loci derived from one species with alleles at different loci derived from the other species (Dobzhansky 1937; Muller 1942; see review in Johnson 2000). Here, we have established that dozens, perhaps hundreds, of genes are subject to quantitative transcriptional deregulation in male hybrids of Drosophila simulans and D. mauritiana. Hybrids are likely to suffer more from downregulation of genes than from upregulation of genes, as the former is several times more abundant than the latter in our data set. The transcripts downregulated in hybrids seem to be associated in large part with male reproduction, although they are randomly distributed between the X chromosome and autosomes.

One of the transcripts identified, Mst98Cb, has been described in some detail previously (Schäfer et al. 1993, White-Cooper et al. 1998). Schäfer et al. (1993) hypothesized it to function as a structural protein of the sperm tail. Mst98Cb is transcribed prior to spermiogenesis but not translated until after meiosis. As the spermatogenetic failure of these hybrids is postmeiotic, but transcription of Mst98Cb and the other genes identified is premeiotic (as is most transcription involved in Drosophila spermatogenesis; see Fuller [1998]), the misexpression in hybrids may contribute to sterility rather than being a mere by-product of possessing incompletely developed sperm.

Although we confirmed quantitative misexpression of Mst98Cb and CG5762 in hybrids, this misexpression was not statistically significant from the microarray analysis alone. Hence, the RT-PCR assay succeeded in detecting underexpression suggested by microarray analysis but not confirmed with our statistical tests, suggesting that the latter (especially the Bayesian approach) might increase type II statistical error. This exemplifies the need for an independent validation of microarray-based studies with more sensitive techniques such as RT-PCR (Rajeevan et al. 2001) and northern blots (Taniguchi et al. 2001).

Implications for Haldane's Rule
If one sex of interspecies hybrids is sterile or inviable, it is typically the heterogametic sex; a pattern referred to as Haldane's rule (see review in Orr 1997). In the past decade, three theories have emerged that may partially or completely explain Haldane's rule in a wide variety of taxa. First, if alleles conferring deleterious interactions in hybrids are typically recessive, heterogametic hybrids, which bear only a single X chromosome, will exhibit sterility earlier in evolutionary divergence than homogametic hybrids (Muller 1942; Turelli and Orr 1995). This theory has been supported by several recent observations (see review in Orr 1997), although it does not appear to completely explain hybrid sterility in Drosophila and mammals (see Wu, Johnson, and Palopoli 1996). A second, but not mutually exclusive, theory suggests that hybrid male sterility in particular may evolve rapidly, through either sexual selection or unique physiological properties of spermatogenesis (sometimes called "faster male": Wu and Davis 1993; Wu, Johnson, and Palopoli. 1996). This theory is supported by the higher number of factors conferring male sterility over female sterility in genetic mapping studies of D. simulans and D. mauritiana (e.g., True, Weir, and Laurie 1996) and the observation of greater male sterility in mosquito species lacking a degenerate Y chromosome (Presgraves and Orr 1998). However, it predicts that Haldane's rule should be weaker in Lepidoptera, where males are homogametic, than in Drosophila, and this prediction is not supported (Presgraves 2002). The final theory that may contribute to Haldane's rule is that the relative rate of evolution of sex-chromosomal genes may exceed that of autosomal genes if new advantageous mutations are typically recessive (sometimes called "faster X": Charlesworth, Coyne, and Barton 1987). This theory predicts an excess of hybrid sterility factors on the sex chromosomes, which is observed weakly (True et al. 1996), and generally higher rates of evolution of sex-chromosomal genes, something which is not detected in Drosophila (Betancourt, Presgraves, and Swanson 2002).

In our analyses, transcripts known to be predominantly male-specific in their expression were significantly overrepresented among underexpressed genes in hybrids. The male-specificity of misexpression is consistent with the faster-male theory and the repeated observations of rapid evolution of male reproductive proteins. The results demonstrate that genes with male-specific patterns of expression are more prone to disruption in hybrids of these species than genes without sex-specific expression. Indeed, our results may be conservative because male-specific genes are often among the most rapidly evolving (e.g., Singh and Kulathinal 2000; Swanson et al. 2001), so some of the most divergent male-specific genes may not have been surveyed here because of sequence divergence from D. melanogaster.

The lack of a disproportionate number of X-chromosome genes being misexpressed in hybrids may incorrectly appear to militate against the faster-X theory. The transcripts misexpressed in hybrids are likely to be downstream genetic targets of the changes that cause hybrid dysfunctions. Although genes involved in spermatogenesis are likely to regulate other genes involved in spermatogenesis or male secondary sexual traits, most X-linked genes probably do not regulate exclusively other X-linked genes (but see Boutanaev et al. 2002). As such, our results do not refute the faster-X theory.

Prospective
Our study is one of very few that have attempted to determine why genes might fail to interact properly in hybrids, resulting in sterility (e.g., Reiland and Noor 2002). Although this study has not directly shown that the observed quantitative disruptions in gene expression in hybrids cause sterility, we have shown that many genes do have disruptions in their expression in hybrids, including several that contribute to spermatogenesis. This study has further illustrated the utility of microarrays and other technologies for the global analysis of gene expression, to evolutionary studies. In addition, it has established a panel of genes on which to focus further investigations of the genetics of hybrid sterility. This panel constitutes a dramatic advance given that the past 70 years of study has identified one only gene (Ting et al. 1998). Given that we have now documented that gene misexpression does occur in sterile species hybrids, clear next steps will include (1) documenting transcriptional variation among various life cycle stages and tissues and (2) comparing gene expression in sterile and fertile males among multigenerational backcross lines to determine whether the disruptions in gene expression are directly associated with sterility.


    Acknowledgements
 TOP
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
 Literature Cited
 
This research was supported by National Science Foundation grants 9980797, 0100816, 0211007; Louisiana Board of Regents Governor's Biotechnology Initiative grant 005; and a Lalor Foundation fellowship to P.M. We thank Jill R. Schurr from LSU Health Sciences in New Orleans for assistance with the microarray assays; B. Counterman, S. Dixon, D. Ortiz, and R. Staten for helpful comments on the manuscript; K. Brown and R. Staten for technical assistance; and M. Batzer for use of real-time PCR machines.


    Footnotes
 
Diethard Tautz, Associate Editor Back


    Literature Cited
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 Abstract
 Introduction
 Methods
 Results
 Discussion
 Acknowledgements
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Accepted for publication March 10, 2003.