To evaluate the performance of the new microarray platform, we analyzed the expression of genes for which we had a priori expectations of sex-biased expression. First, we examined components of the somatic sex determination pathway and its known downstream targets 2627. As expected, the female-specific genes transformer and yolk proteins 1, 2, and 3, each represented by a single probe on our arrays, showed significantly female-biased expression in our experiments (Table 2). Female-biased expression was also observed for hermaphrodite and transformer 2 (tra2), which are expressed in both sexes. tra2 was represented by four hybridizing probes that targeted different regions of a nearly identical set of transcripts; all of these probes showed similar ratios of expression in males and females (Table 2). doublesex (dsx) is spliced in a sexually dimorphic manner, producing a male-specific and a female-specific transcript 28. In our design, dsx was represented by four probes: one targeting a male-specific exon, one targeting a female-specific exon, and two targeting an exon common to male and female transcripts. We found that the male-specific probe indeed showed male-biased expression, the female-specific probe showed female-biased expression, and the common probes showed expression levels intermediate between the two sex-specific probes (Table 2). These results indicate that, as intended, the new microarray platform can distinguish among different exons and thereby reliably indicate alternative transcript production.

Next, we retrieved from FlyBase a list of genes known to be involved in the development or function of reproductive organs. We subdivided this list into three non-overlapping sets: genes known to function only in the female reproductive system (565 microarray probes, representing 326 genes), those known to function only in the male reproductive system (60 probes/42 genes), and genes implicated in both male and female reproductive systems (120 probes/86 genes). Most of these genes, however, are not exclusive to the reproductive system and are expressed in a wide range of non-reproductive organs as well. Since our experiments utilized whole-body RNA samples, we may not always be able to detect sex-biased expression in the reproductive organs. We found that among the female reproductive system genes, 86% were female-biased, with 72.5% being significant for sex and/or sex-by-probe interaction effect (Additional file 1). Conversely, among the male reproductive system genes, 64.3% were male-biased, with 55.5% showing significant sex effect (Additional file 1). We also analyzed a set of genes that are thought to be expressed only in males. These genes included a number of secreted accessory gland proteins 293031, putative odorant-binding proteins expressed in male-specific chemosensory organs 25, and sperm-specific structural proteins 32. We found that 100% of these genes (11 out of 11) showed male-biased expression in our experiments (Additional file 1). Finally, we examined a set of male-specific transcripts identified earlier by differential cDNA hybridization 3334, and found that all genes detected in our experiments (ten out of ten) showed male-biased expression (Additional file 1). Finally, we examined the expression of six Y-linked genes represented on our arrays. Only two of them were expressed at detectable levels in enough samples to be considered informative. As expected, neither was present in any female samples, but both were detected in the majority of male samples. Together, these analyses confirm that the new microarray platform is effective for detecting sex-biased gene expression. For genes that produce multiple transcripts due to alternative splicing, or due to the presence of multiple transcription initiation or termination sites, we tested whether the relative proportions of alternative transcripts differed between sexes or lines. We used the ANOVA model for multiple transcripts (see Materials and methods) to examine the genes for which at least two probes targeting distinct sets of transcripts produced detectable hybridization. For these genes, we tested whether the relative amounts of signal from the different probes differed between sexes or lines. Such differences (called sex-by-probe or line-by-probe interactions) imply that the same gene produces alternative transcripts in different amounts in males versus females, or in different genotypes, respectively.

Sex-specific production of alternative transcripts has previously been reported for only a handful of genes, so we lack an extensive set of positive controls against which to compare our results. The best-known example in Drosophila is the dsx gene 28. Indeed, as shown above, probes targeting the male- and female-specific exons of dsx show different expression levels in different sexes (Table 2). When analyzed using the ANOVA model for multiple transcripts, the dsx gene shows a significant sex-by-probe interaction (P < 0.0001; Table 2). Sex-lethal (Sxl), which also produces male- and female-specific alternative transcripts 35, was represented in our experiments by five probes targeting different subsets of transcripts, and also showed significant sex-by-probe interaction (Table 2). These results suggest that our platform has the power to detect quantitative differences in the relative amount of alternative transcripts in different sexes.

We examined 828 genes for which 2 or more probes representing distinct sets of transcripts showed detectable hybridization. Of these, 182 (22%) showed significant sex-by-probe or line-by-probe interactions at the FDR of 0.05, indicating that the relative amounts of alternative transcripts were different in males and females, or in different lines (Table 3). For the vast majority of these genes (177 out of 182 genes), the differences were attributable to sex. These genes had a variety of molecular functions, including transcription factors, cell signaling components, cytoskeletal proteins, and others (Additional data files 2 to 4). Of the 828 multi-transcript genes, 55 had 2 or more probes targeting different subsets of transcripts, but no probes targeting the entire set of transcripts produced by the locus (that is, 'local' probes only; see Materials and methods). Among such genes, 19 (35%) showed evidence of sex-specific or line-specific bias in the production of alternative transcripts (Table 3). Interestingly, no obvious relationship was observed between the number of probes targeting a given gene and the likelihood of finding evidence for sex-specific transcript representation.

To examine sex-specific expression of alternative transcripts more closely, we analyzed the set of 177 genes that showed significant sex-by-probe interactions on a probe-by-probe basis (Additional file 5). In general, we found that probes targeting the same exon, or different constitutively spliced exons, tended to have similar male/female expression ratios (Figure 1). Conversely, probes targeting different exons tended to have expression ratios that were different from each other and from constitutively spliced exons (Figure 1).

We did observe some exceptions where different probes targeting the same set of annotated transcripts showed different male/female expression ratios (Additional file 5). Such exceptions could be due either to intrinsic biases in probe hybridization, or to mistakes in the current FlyBase annotation (that is, exons indicated as constitutive might in fact be subject to alternative splicing or transcription). To estimate the extent to which our results may be affected by these factors, we used the ANOVA model for multiple transcripts to compare probes that, according to the current annotation, targeted different regions of the same set of transcripts. This control allows us to assess the maximum proportion of significant sex-by-probe or line-by-probe interactions expected in the absence of differential transcript production (see Materials and methods). Of the 1,321 control probe sets, 129 (9.77%) showed significant interactions - a proportion that is well short of the 22% found for probes targeting distinct sets of transcripts. This suggests that although intrinsic probe biases and/or mistakes in the annotation may have an effect, this effect is not sufficient to explain the observed variation in relative transcript abundance. We conclude that a large proportion of multi-transcript genes in the Drosophila genome produce alternative transcripts in a sexually dimorphic manner.

Several genes that showed significant sex-by-probe interactions were further tested using quantitative rt-PCR (qPCR) with primers that flanked exon junctions. First we evaluated the ability of qPCR to detect sex-biased transcript abundance. The genes CG7441, Sxl, fru, and Nep4, which showed evidence of sex-specific expression in the microarray data, were used as positive controls, while Lsp1beta, which was not sex-biased on the array, was used as a negative control. In all cases, qPCR results were consistent with array results (Additional file 6). We then designed two to three primer pairs for each of nine genes that are known to be alternatively spliced and that showed evidence of sex-specific splicing in microarray experiments: unc-13, mud, Jupiter, r, aret, CG4662, CG10899, garz, and Akap200. These primer pairs were designed to amplify either constitutive exon junctions, or alternative splice junctions that were present in non-overlapping sets of transcripts. We measured the cycle thresholds of amplification (CT) for each primer pair in males and females of the Oregon-R line, and tested whether these values showed significant sex-transcript interaction. Such interaction would indicate that different exons were produced in different amounts in males versus females, confirming the microarray results. We observed statistically significant differences in transcript ratios in males versus females for eight out of nine genes (Additional data file 6; Figure 2). For the ninth gene, Akap200, transcript ratios also differed in the predicted directions, but the ANOVA interaction term was not statistically significant.

We tested whether the genes that showed evidence of differences in gene expression were more likely to be located on the X chromosome than on the autosomes using a χ² test. For single-transcript genes, 57% (840) of the X-linked genes showed a significant difference in gene expression among sexes or lines, compared to 54% (4,630) for the autosomal genes. This difference, while slight, is greater than expected by chance (P = 0.0260). In other words, X-linked genes are significantly more likely to show differences in gene expression than autosomal genes. We then tested whether male- and female-biased genes were distributed in the same proportions between the X chromosome and the autosomes. We identified 559 female-biased genes on the X chromosome and 2,466 on the autosomes, compared to 281 X-linked and 2,164 autosomal male-biased genes. Thus, 18.5% of all female-biased genes are located on the X chromosome, while for male-biased genes the corresponding number is only 11.5%. This difference is highly significant (P < 0.0001), demonstrating that the X chromosome is enriched for female-biased single transcript genes.

The same comparisons were performed for multi-transcript genes. There were 116 X-chromosomal and 616 autosomal genes that showed a significant difference in gene expression in either sex or line; these showed no statistical evidence for chromosomal bias (P = 0.9479). However, among genes that showed sex-biased transcript abundance, 78 X-linked and 304 autosomal genes were female-biased, compared to 38 X-linked and 312 autosomal genes that were male-biased. The proportions of female- and male-biased genes located on the X chromosome (20.4% and 10.9%, respectively) were significantly different (P = 0.0004), demonstrating that the X chromosome is enriched for female-biased multi-transcript genes.

We also tested whether sex-specific production of alternative transcripts (significant sex-by-probe interaction in the ANOVA model for multiple transcripts) was more likely to be observed for X-linked than for autosomal genes. There were 28 X-linked and 177 autosomal genes that showed significant sex-specific transcription; this proportion was not significantly different from that expected given the relative abundance of genes on the X chromosome and the autosomes (P = 0.3221). The male/female bias in alternative transcript representation was also independent of chromosomal location (P = 0.3479).

To perform a quantitative analysis of alternative transcript expression, we have designed transcript-specific probes based solely on sequence clustering (see Materials and methods). Definitions based on biological constructs such as exon junctions impose design restrictions that may result in probes that cross-hybridize to multiple genes, or do not have optimal hybridization properties with their intended targets. In contrast, our approach allows us to select probe sequences that will hybridize only to single transcripts. Our analysis shows that such probes perform in a uniform and highly reproducible fashion (Table 4). Moreover, a design based on the exon/intron structure of genes would require frequent revision to reflect changes in the genome annotation, whereas definitions based on sequence similarity are likely to change less frequently. A limitation to this design is that a gene nested in the intron of another gene can be difficult to distinguish from an alternative exon in the absence of junction information. We have based our microarray design on FlyBase v3.1 annotation 36. To keep pace with annotation updates, we have developed software that tracks the latest FlyBase annotation of the probes comprising our microarrays (or any other oligonucleotides). This insures that, as the understanding of the genome evolves, the classification of probes can be updated as well. The result is a flexible platform that will enable researchers to perform simultaneous analysis of transcription and alternative transcript production on a genome-wide basis.

A very large fraction of the genome appears to be differentially expressed between males and females. In our experiments, 53% of all expressed genes (5,832 out of 10,933, including 291 unannotated genes) showed sex-biased expression. Other studies utilizing different microarray platforms produced very similar estimates 19373839404142. It is worth observing that all these studies, like ours, were performed in sexually mature, intact adults, and it is not surprising that gene expression profiles at this stage are dominated by the reproductive differences between males and females. It is clear, however, that most of the sexual dimorphism in gene expression is due to the germline. Comparisons of gonadectomized adults, or adults in which germ cells have been genetically ablated, produce much lower estimates of sexual dimorphism, on the order of 1.5% to 3% 141. Sexually dimorphic gene expression is much more prevalent in the germline than in the soma not only in Drosophila, but also in Caenorhabditis elegans 434445 and in the mouse 46. This pattern is observed despite the differences in the mechanisms of sex determination in these taxa: in flies, the sex of each individual somatic cell is determined autonomously 47, whereas in mammals somatic sexual differentiation is controlled by a global hormonal mechanism 48.

We find that more genes show female-biased than male-biased expression (55% versus 45%). This result is in agreement with some of the previous reports 39, although other studies suggest that male-biased expression is more common than female-biased expression 41. The reasons for this contradiction are not clear, and could in principle include different lines, different microarray platforms, and/or different statistical approaches. However, many of the genes that showed significant differences in expression between males and females in our experiments were also found to be sexually dimorphic in other studies 1937383940. Interestingly, we found that female-biased genes were much more likely to be located on the X chromosome than male-biased genes (18.5% versus 11.5% for single-transcript genes and 20.4% versus 10.9% for alternatively spliced genes; P < 0.0001). Similar 'feminization' of the X chromosome has previously been observed in Drosophila 4041 and C. elegans 4445.

We found that only two genes, modulo and CG33092, show significant sex differences that change depending on the line examined (that is, have genetic variation for sex dimorphism). In contrast, some earlier reports suggested that as much as 10% of the genome may show such sex-genotype interactions 3738. This is despite the fact that the lines used in this study included the two parental lines used in one of these studies 38, as well as recombinant inbred lines derived from these two parents. The most likely reason for this is that significance thresholds used in our analysis were much more stringent than in previous reports. In fact, if we use the nominal significance threshold of 0.01, as in those reports, we find approximately the same proportions of genes showing sex-by-line interactions (not shown). We have chosen to report FDR-corrected thresholds since this approach incorporates an appropriate correction for multiple testing. It is also important to note that this study examines a limited number of lines, the two parents OregonR and 2b and six recombinant offspring from these two parents. The extent of alternative transcript production among lines will only be clear as more lines are sampled.

A large proportion of multi-exon genes in animal genomes are alternatively spliced, with estimates ranging from 30% to over 90% 2021222324. Alternative splicing is thought to make a significant contribution to phenotypic complexity by allowing a single locus to produce multiple, and possibly functionally distinct, proteins 49505152. Supporting this view, many of the alternatively spliced genes in the human genome are spliced in a tissue-specific manner 25. In Drosophila, alternative splicing plays a prominent role in development, most notably by controlling sex determination 535455. In at least some Drosophila genes, alternative splicing is regulated in a sex-, tissue-, and/or stage-specific manner, so that different subsets of proteins encoded by the locus are produced in different developmental contexts 53565758596061. Alternatively spliced protein isoforms can, at least sometimes, have distinct functional specificities. For example, alternative isoforms of the lola transcription factor have different functional domains, and mutations affecting the different isoforms have distinct phenotypes 57. Similarly, one of the alternatively spliced transcripts of the Drosophila tyrosine hydroxylase (pale) is required for cuticle development, while a different transcript functions primarily in neurotransmission 62. One dramatic example of alternative splicing is the cell adhesion receptor Dscam, which may produce up to 38,016 splicing variants 6364. Recent evidence indicates that specific isoforms function in distinct axon guidance pathways 65. However, evidence of the functional impact of alternative splicing remains largely anecdotal, and for the vast majority of genes functional comparisons between alternatively spliced variants are yet to be performed. At present, the extent to which alternative splicing contributes to functional protein diversity remains a matter of speculation. Exon-specific RNA interference 66 may finally allow this question to be addressed in a systematic manner.

We used the new microarray platform to estimate the extent of sex-specific production of alternative transcripts in the Drosophila genome. Approximately 22% of multi-transcript genes showed significant evidence that alternative transcripts were present in different ratios in males versus females. Some of these results might be experimental artifacts due to technical differences between probes, or mistakes in the current gene annotation. To address this concern, we used identified multiple probes that were predicted to hybridize to the same target transcripts as controls. Significant interactions between sex and probe will provide an estimate of the maximum proportion of significant tests that might be due to differences among probes, or problems with annotation. We found this proportion to be less than 10%, suggesting that at least 12% of all genes that produce alternative transcripts do so in a sex-specific manner. qPCR with primer pairs flanking alternative exon junctions confirmed sex-biased splicing for eight out of nine tested genes, indicating that exon-specific microarray probes provide a reliable means of detecting variation in the relative abundance of alternative transcripts. As in the case of sex-biased transcription, we suspect that much of the sex-specific splicing may be accounted for by reproductive tissues, and that most differences between males and females are likely to be quantitative rather than qualitative. Despite these qualifications, the prevalence of sexual differences in the production of alternative transcripts may have important functional consequences, and needs to be investigated in greater detail.

The Drosophila genome contains a number of RNA-binding proteins that function as splicing regulators in vivo 67. Importantly, some of these proteins appear to be required for alternative splicing. In particular, several of them are essential components of protein complexes that carry out sex-specific splicing of dsx and Sxl 68697071, while RNAi-induced knock-down of the pasilla and mub genes disrupts the splicing of specific exons in the para and Dscam transcripts 67. Thus, it is easy to envision a mechanism for sex-, tissue-, and stage-specific regulation of alternative splicing through differential expression of RNA-binding proteins. Indeed, we found that 95% (35 out of 37) of splicing regulators previously characterized 67 are expressed at significantly different levels in males and females at a FDR of 0.05 (Table 5). This proportion is much greater than the overall frequency of sex-biased gene expression in the Drosophila genome (approximately 53% in this study). We hypothesize that sex-specific expression of splicing regulators contributes to the prevalence of sex-specific production of alternative transcripts observed in our experiments. One attractive use of the new microarray platform would be to jointly monitor the expression of splicing regulators and the alternative transcripts of their target loci in different developmental contexts (tissues, sexes, and stages) and in different lines.

Our goal was to design microarray probes capable of distinguishing alternative transcripts, as well as members of multi-gene families. In order to maximize probe specificity, we first examined sequence similarity among all known and predicted transcripts of D. melanogaster. Sequences of 18,187 transcripts, including 16,064 transcripts annotated in FlyBase 36 and 2,123 predicted transcripts 72, were obtained in the fall of 2004, and 440 additional transcripts in the Spring of 2005 (FlyBase version 3.1). Gene and transcript identity was tracked through all following analyses using their CG numbers - unique identifiers assigned by the FlyBase 36. We identified and removed 160 duplicate transcripts. The remaining 18,027 transcripts were compared among themselves using BLAT v29 73 to identify regions of sequence similarity. This clustering resulted in a division of the transcriptome into two groups - 'singletons' and 'clusters'. The former group consisted of 13,069 transcripts that did not show sequence similarity to any other transcript, while the latter consisted of 4,958 transcripts that showed sequence similarity to at least one other transcript. We deliberately did not exclude paralogous genes from this clustering, as we wished to design probes targeting the most diverged regions of such genes. Each transcript cluster was aligned using ClustalW v1.8 74. Sequences that were shared by two or more transcripts were designated as 'common' regions, while regions that showed no similarity to other transcripts were designated as 'unique'. There were many possible scenarios for the alignment of transcripts within a cluster, some of which are illustrated in Figure 3. Some clusters displayed more complex relationships, including cases where the transcripts had no single region that was common to all of them, but did have several regions that were each shared by a different subset of transcripts. In these and other difficult cases, sequence alignments were performed manually. No a priori information about the exon/intron structure of the genes was used during cluster alignment. The overall set of 4,958 clustered transcripts contained 2,720 common and 2,545 unique regions. For most transcript clusters, common and unique regions identified by sequence alignment correspond to constitutively and alternatively spliced exons, respectively. Some examples of this correspondence are shown in Figure 1.

For each singleton transcript, and each unique and common region of clustered transcripts, we designed at least one 60-mer oligonucleotide probe. For 1,929 common regions of sufficient length to support non-overlapping probes that fit our design criteria, we designed two probes per region. To select the probes, we examined all possible 60-mers for each of the target regions, and scored each candidate based on several criteria, including GC content, OligoArray 2.1 score 75, homopolymer length, dimer formation, and self-complementarity. Probes that satisfied all optimality criteria could be designed for all but 312 target regions. For those regions, multiple non-optimal probes were selected. All probes were examined to verify that they matched only the expected regions in the current version of Drosophila genome annotation, and subjected to a final BLAT verification. In particular, probes that were designed for singletons or unique regions were checked to make sure they did not match any other transcripts, whereas probes that were designed to represent common regions were confirmed to match only the expected set of transcripts.

The resulting microarray design included 12,994 probes that targeted singleton transcripts (Table 6). If the current FlyBase annotation is correct, these transcripts represent genes that are not subject to alternative splicing. Most of these transcripts (12,912) were each represented by a single probe, while 37 were represented by multiple probes (for a total of 82 probes). Clustered transcripts were subdivided into two further categories. The smaller category consisted of 177 clusters where at least one probe matched more than one CG number in the latest FlyBase annotation. Each of these clusters was assumed to represent a paralogous 'gene family', and probes targeting common and unique sequences were designed for each such cluster for a total of 566 probes. In the larger category, 2,768 clusters represented by 7,207 probes each consisted of multiple transcripts designated by the same CG number in FlyBase, and thus corresponded to the same gene (Table 6). We refer to such genes as 'alternative transcripts', as in some cases the production of multiple transcripts is due not to differential splicing, but rather to utilization of different transcription initiation or termination sites. The alternative transcripts were targeted by probes belonging to two distinct types. Again, 'common' probes represent sequences found in more than one transcript, while 'unique' probes represent sequences found in only one transcript. Probes common to all transcripts in a cluster were designated as 'global', while those representing only a subset of transcripts, or a single transcript, were designated as 'local'.

We used the human genome to design 20 negative control probes according to the same criteria as the Drosophila probes. These probes were compared to the Drosophila genome sequence to verify that they had no sequence similarity to any D. melanogaster genes. Five of these negative controls were randomly chosen for printing, and each was placed o