Abstract
The nematode Caenorhabditis elegans is an important model for studies of germ cell biology, including the meiotic cell cycle, gamete specification as sperm or oocyte, and gamete development. Fundamental to those studies is a genome-level knowledge of the germline transcriptome. Here, we use RNA-Seq to identify genes expressed in isolated XX gonads, which are approximately 95% germline and 5% somatic gonadal tissue. We generate data from mutants making either sperm [fem-3(q96)] or oocytes [fog-2(q71)], both grown at 22°. Our dataset identifies a total of 10,754 mRNAs in the polyadenylated transcriptome of XX gonads, with 2748 enriched in spermatogenic gonads, 1732 enriched in oogenic gonads, and the remaining 6274 not enriched in either. These spermatogenic, oogenic, and gender-neutral gene datasets compare well with those of previous studies, but double the number of genes identified. A comparison of the additional genes found in our study with in situ hybridization patterns in the Kohara database suggests that most are expressed in the germline. We also query our RNA-Seq data for differential exon usage and find 351 mRNAs with sex-enriched isoforms. We suggest that this new dataset will prove useful for studies focusing on C. elegans germ cell biology.
Germ cell biology is central to reproduction and fertility. The nematode Caenorhabditis elegans is a well-established model for genetic and molecular analyses of germline sex determination (Ellis and Schedl 2007; Kimble and Crittenden 2007), progression through the meiotic cell cycle (Rog and Dernburg 2013), and gametogenesis (Greenstein 2005; L’Hernault 2006). Moreover, C. elegans was the first metazoan with a fully sequenced genome (C. elegans Sequencing Consortium 1998) and a central player in ModENCODE (Gerstein et al. 2010). Therefore, C. elegans is poised to serve as a model to analyze germ cell biology at a comprehensive systems level.
State-of-the-art transcriptome data lie at the foundation of virtually any modern study of biological regulation. To this end, Reinke et al. (2004) reported a pioneering analysis of spermatogenic and oogenic transcriptomes. This now classic study relied on mRNAs extracted from whole animals, custom-spotted microarrays, and a 2003 version of the C. elegans genome annotation. Other studies have also generated the following relevant transcriptomes: maternal RNAs, which can be used as a proxy for a subset of oogenic RNAs (Baugh et al. 2003); germline-specific RNAs obtained from gonads extracted from adult wild-type hermaphrodites and subjected to serial analysis of gene expression (SAGE) (Wang et al. 2009); and RNAs in isolated mature sperm (Ma et al. 2014). In addition, a study identified several hundred mRNAs whose expression depends on the sperm-specific transcription factor SPE-44 (Kulkarni et al. 2012); a proteomics study discovered proteins in isolated mature oocytes (Chik et al. 2011); and RNA immunoprecipitation studies identified RNAs associated with RNA-binding proteins in adult oogenic germlines [FBF-1 (Kershner and Kimble 2010); GLD-2 and RNP-8 (Kim et al. 2010); GLD-1 (Jungkamp et al. 2011); EFL-1 and DPL-1 (Kudron et al. 2013)]. However, the classic analysis of Reinke et al. (2004) remains the only dataset available focusing on spermatogenic vs. oogenic transcriptomes.
As background for the current work, C. elegans develops as either XX hermaphrodites or XO males; XX hermaphrodites make sperm as larvae and oocytes as adults, whereas XO males make sperm only and continuously. Because nematode XX hermaphroditism evolved recently, closely related species remain gonochoristic (XX females and XO males), and elimination of a single gene, fog-2 (feminization of germline), transforms C. elegans into a gonochoristic strain with XX females and XO males (Schedl and Kimble 1988). A single gonadal arm in adult C. elegans XX hermaphrodites possesses ∼1000 germ cells, with stem cells at one end and differentiating gametes at the other; each isolated gonad also possesses ∼25 somatic gonadal cells. Many existent sex determination mutants affect the germline, including nonconditional and temperature-sensitive alleles of varying strengths and tissue specificities. Of particular relevance to this work are temperature-sensitive fem-3(gf) and homozygous fog-2 mutants. XX fem-3(gf) mutants make no oocytes, but instead produce sperm continuously in a hermaphrodite/female soma (Barton et al. 1987); by contrast, fog-2 mutants make no sperm but make oocytes continuously in an equivalent soma (Schedl and Kimble 1988).
Our analysis of spermatogenic and oogenic transcriptomes begins with XX animals possessing germlines of the opposite sex but housed in somas of equivalent sex, RNAs extracted from isolated gonads, RNA-Seq data based on eight biological replicates, and the most recent version of the C. elegans reference genome annotations available in Ensembl (Flicek et al. 2014). Other details of our experimental design differ from those used previously, as outlined in Results. Where possible, we used the Kohara in situ hybridization database (NEXTDB: nematode.lab.nig.ac.jp/) to validate RNAs that previously had not been identified as expressed in the germline or previously had not been annotated as spermatogenic or oogenic. We compared our data to relevant datasets mentioned above and analyzed our data for alternative splicing. We suggest that this new dataset will prove useful in combination with other datasets for studies of germline regulation and gamete differentiation.
Materials and Methods
C. elegans strains
We used two homozygous mutant strains: fem-3(q96gf) IV, which is temperature-sensitive, and fog-2(q71) V. The fem-3(q96gf) stocks were maintained at 15° and experimental animals grown at 22°; fog-2 mutants were maintained at 22°. For an immunostaining control, we used wild-type Bristol strain N2, also grown at 22°.
Dissection of gonads for immunostaining
Synchronized young adults (0–2 hr past the L4 to adult molt) were cut just behind the pharynx in PBS-Tween (0.1% Tween20) with 0.25 mM Levamisole; dissected animals were fixed in 3% paraformaldehyde, 0.1 M K2HPO4 for 30 min and permeabilized in 100% methanol at −20° for 30 min. Samples were washed three times in PBST and blocked in PBST plus 0.5% BSA for 30 min at room temperature. Samples were incubated with primary antibodies at 4° overnight in PBST plus 0.5% BSA at the following dilution: mouse anti-SP56 (1:100) (gift from S. Strome) and rabbit anti-RME-2 (1:500) (gift from B. Grant). They were then incubated with Cye3 and FITC conjugated secondary antibodies (Jackson ImmunoResearch), both at a 1:1000 dilution in PBST plus 0.5% BSA, for 1 hr at room temperature. Finally, samples were mounted on slides in VectaShield containing DAPI to visualize DNA and imaged with a Zeiss Axioimager microscope.
Isolation of gonads for RNA extraction
Synchronized young adults (0-2 hr past the L4 to adult molt) were first cut behind the pharynx as described above. Gonadal arms were then cut at or near the spermathecae to isolate them from the carcass. Total RNA was extracted from the gonads using TRIzol (Invitrogen) and RNeasy Mini Kit (Qiagen) following the manufacturer’s instructions.
Replicates and sequencing
We generated eight independent samples for fog-2 and another eight for fem-3. Each sample contained approximately 30 gonadal arms and most (14/16) had a total RNA concentration of 20–34 ng/ml. The University of Wisconsin Biotechnology Center prepared libraries for each sample using the TruSeq Illumina sequencing protocol, which includes mRNA purification (poly-A selection) and fragmentation, cDNA synthesis, end repair, adapters ligation, and DNA fragment enrichment. Each library was bar-coded and sequenced in four different lanes to obtain single-end 101-bp reads using Illumina HiSeq2000. We obtained more than 36 million reads of high-quality score (>35 mean quality score) on average per sample. All sequencing data are available in the National Institutes of Health Gene Expression Omnibus database under accession number GSE57109.
Transcript analysis
We used TopHat2 v2.0.11 (with −g 1 option) (Trapnell et al. 2012) to align reads to the C. elegans reference genome (WBcel235.75.fa) and gene annotations (WBcel235.75.gtf) in WormBase WS240 (Ensembl) (Flicek et al. 2014). For compatibility to feature-counting software, we created sorted and indexed SAM versions of the BAM files (SAMtools) (Li et al. 2009). To create a read-count dataset, we processed SAM files with python scripts described elsewhere (Anders and Huber 2010). Our cutoff was two mapped reads per gene for each of eight replicates or a minimum of 16 total reads per gene, applied to each mutant independently. Genes with ambiguous annotations or fewer reads (<16 reads/gene) were removed. To identify differentially expressed transcripts, we used R/Bioconductor package DESeq, a common method to evaluate differential expression (Anders and Huber 2010; Rapaport et al. 2013). DESeq performs normalization by applying a scaling factor to each sample; this scaling factor is the median calculated from the ratios of read counts for each gene to the geometric mean of all samples (Anders and Huber 2010; Rapaport et al. 2013). We also determined abundance as rpkm using Cufflinks v2.1.1 (with −N, −u, and −b options) (Trapnell et al. 2012) (Supporting Information, Table S1). In total, we found 10,754 unambiguously expressed genes with at least 16 uniquely high-quality aligned reads. For data plotting, we used ggplot2 R/Bioconductor package (Wickham 2009).
Exon usage analysis
We used TopHat v2.0.11 (−m 2 −g 1 and −G options) to align reads to the C. elegans reference genome (WS235). We used Cufflinks v2.1.1 (with −N, −u, and −b options) (Trapnell et al. 2010; Trapnell et al. 2012) to assemble isoforms and measure isoform expression. For analysis of differential exon usage between spermatogenic and oogenic gonads, we used the DEXSeq package for R/Bioconductor (Anders et al. 2012). We obtained reads per exon from the alignment files using a script accompanying the DEXSeq package. For an exon to be scored significantly different, we set a false discovery rate of <1% and a minimum fold change requirement of two-fold. We also set a minimum expression threshold of two reads per exon. We used gene annotations in WS240 and a custom script to compare our differential exon results with annotated alternative exon usage. Custom scripts were also used to count the number of exon junction–spanning reads for the alignment files to determine whether alternative exon usage was in a coding or noncoding region and to discriminate types of alternative splicing observed. The UCSC Genome Browser ce10 (www.ucsc.genome.edu) was used to visualize alternative splicing of WIG files that were converted from BAM files using SAMtools mpileup (SAMtools) (Li et al. 2009) and a custom script.
Results and Discussion
Experimental design
Many mutants affecting gamete sex must be grown at 25°, thus reducing fertility even in wild-type animals (Hirsh et al. 1976). We avoided growth at 25° by using fog-2(q71) mutants, whose XX germline makes oocytes and only oocytes at all standard growth temperatures (Schedl and Kimble 1988), and the strong fem-3(q96gf) allele (Barton et al. 1987), which makes sperm and only sperm when raised at 22° even 3 days into adulthood (100%; n = 150). To ensure germline sex transformation of these two mutants, we stained for sex-specific germline markers, SP56 for spermatogenic germlines (Ward et al. 1986) and RME-2 for oogenic germlines (Grant and Hirsh 1999). For wild-type animals grown at 22°, staining was as expected with SP56-positive sperm and RME-2-positive oocytes (Figure 1A). More importantly, fem-3(q96) sperm-only adults raised at 22° possessed SP56 but not RME-2 (Figure 1B), and fog-2(q71) oocyte-only adults raised at 22° had RME-2 but not SP56 (Figure 1C). Yet these two XX mutants have morphologically indistinguishable somatic tissues, including the somatic gonad (Barton et al. 1987; Schedl and Kimble 1988). We note that use of mutants was essential for this analysis and caution that a mutant transcriptome may include changes not found in wild-type and that XX sperm are only a proxy for XO sperm.
Immunocytochemistry of sex-specific gamete markers in wild-type and mutants used in this work for RNA-Seq. (A–C) Extruded gonads from young adult XX worms (L4/A molt+2 hr), all raised at 22°; each image merges staining of the α-SP56 sperm-specific marker (red), α-RME-2 oocyte-specific marker (green), and DAPI DNA marker (blue). Asterisk marks distal end of gonad; red arrows mark SP56; green arrows mark RME-2. (A) Wild-type hermaphrodite gonad with both sperm-specific and oocyte-specific markers. (B) Sperm-only fem-3(q96gf) gonads stain only with sperm-specific marker (red). (C) Oocyte-only fog-2(q71) gonads stain only with oocyte-specific marker (green). Scale bars: 50 μm.
Two other features were specific to our analysis of spermatogenic vs. oogenic transcriptomes. First, we isolated gonads and discarded the main body and intestine; an isolated gonad contains approximately 1000 germ cells but many fewer somatic gonadal cells (1 DTC, 10 sheath, and some portion of the 26-celled spermatheca). Gonad isolation therefore removes most somatic RNAs (e.g., hypodermis, nerve, muscle, intestine) but still includes approximately 25 somatic gonadal cells. Second, we isolated gonads from young adults only 0–2 hr after the molt from L4 to adulthood. This stage harbors fully differentiated gametes but has not begun to accumulate unused gametes, which affect germline physiology (e.g., mitotic index) (Jaramillo-Lambert et al. 2007; Morgan et al. 2010).
Genes expressed in gonadal transcriptome
We prepared and sequenced polyadenylated RNAs from eight biological replicates of each mutant [fem-3(gf) and fog-2], with 30 isolated gonads per replicate. Using TopHat (Trapnell et al. 2012), >90% of sequence reads could be mapped uniquely to the most recent version of the C. elegans genome (see Materials and Methods). A gene was scored as expressed when 16 or more reads mapped to that gene. Expression abundance was measured in normalized total read counts per gene. Because transcript isoforms were ignored for this first analysis, we discuss the data in terms of “genes expressed” rather than “transcripts expressed.” For quality reference, 97% of the reads mapped to the annotated transcriptome; of those, 1.7% mapped partly to noncoding sequences and partly to coding sequences and 0.3% fell in ambiguous gene sequence annotations. In this way, we identified totals of 10,733 genes expressed in fem-3(gf) gonads, 10,631 in fog-2 gonads, and 10,610 shared (Figure 2A). Together, a total of 10,754 mRNAs comprise the polyadenylated transcriptome of these XX gonads.
Identification of genes expressed in spermatogenic and oogenic gonads. (A) Volcano plot of all genes expressed in fem-3(gf) spermatogenic and fog-2 oogenic gonads, showing fold changes in abundance on the X-axis and significance on the Y-axis. Colors indicate enriched expression in spermatogenic gonads (blue), oogenic gonads (red), or neither (gender-neutral) (gray). (B) Histogram of all genes expressed in fem-3(gf) spermatogenic and fog-2 oogenic gonads, showing fold changes in expression abundance with color coding as in (A).
We compared our dataset with a previously published dataset of 4699 mRNAs detected in isolated wild-type adult hermaphrodite gonads using SAGE (Table 1). Most SAGE-identified genes were also found in our work (92%; 4323/4699). We also compared our dataset with lists of germline transcripts deduced by comparing “soma plus germline” to “soma-only” transcriptomes. Reinke et al. (2004) found 3145 germline RNAs in this manner from microarray data, whereas Wang et al. (2009) found 1063 using SAGE. Again, most germline RNAs previously reported were also identified in this work (84%; 2637/3145 and 95%; 1017/1063). The design differences among these various studies (Table 1 and Table 2) were so extensive that the main conclusion is that our data include most genes previously reported as expressed in the gonad and doubles their number.
Gene expression enriched in spermatogenic vs. oogenic gonads:
We next identified genes whose expression was enriched in spermatogenic vs. oogenic gonads. To this end, we used DESeq to compare the 10,733 genes expressed in fem-3(gf) spermatogenic gonads with the 10,631 in fog-2 oogenic gonads. Using thresholds of a two-fold difference in abundance and a false discovery rate of 1%, we identified 2748 genes with expression enriched in spermatogenic gonads and 1732 enriched in oogenic gonads; the remaining 6274 were not enriched in either spermatogenic or oogenic gonads (Figure 2, Table 3, and Table S1). We refer to these as spermatogenic, oogenic, and gender-neutral genes, respectively. All spermatogenic, oogenic, and gender-neutral genes are labeled as such and listed in an Excel searchable format in Table S1, column H. Table 4 shows 12 representative genes previously determined experimentally to have gender-neutral or sex-biased germline expression.
A comparison of our datasets (spermatogenic, oogenic, and gender-neutral genes) with those of a similar but earlier study (Reinke et al. 2004) reveals considerable overlap between spermatogenic and gender-neutral genes, but less with oogenic genes (Table 3). Only 37% of oogenic genes were found in our oogenic gene list. Where were the missing 63%? The majority were in the gender-neutral gene list (99%). Why were so many “oogenic” genes in the study by Reinke et al. (2004) “gender-neutral” genes in our study? One possible explanation is that our work queried very young adult gonads with only a few mature oocytes, whereas Reinke et al. (2004) used older adults with many mature oocytes. Another explanation is that our study had greater sensitivity. Both explanations likely have some validity. We blindly surveyed expression of all the Reinke et al. (2004) study’s oogenic genes in the NEXTDB database and found 582 genes with unambiguous in situ hybridization data; of these, 42% (242/582) were enriched for germline expression in adult hermaphrodites compared with L4s, consistent with their oogenic classification (Table S1, column I), whereas 58% (243/582) were expressed at approximately the same level in both larval and adult germlines. The percentage of the Reinke et al. (2004) study’s oogenic genes validated as enriched during oogenesis according to NEXTDB (42%) is therefore similar to the percentage overlap between oogenic genes found here and that work (37%) (Table 3). We suggest that the datasets are comparable but not identical.
We also compared our data with recent studies of sex-biased gene expression and evolution (Thomas et al. 2012; Albritton et al. 2014). In agreement with those works, we found that the average fold change in expression of spermatogenic genes was greater than that of oogenic genes (Figure 3A). We also found that oogenic genes were significantly enriched compared with total gonadal genes on chromosome X (28% oogenic vs. 22% gonadal on X) but underenriched on autosomes (72% vs. 78% on autosomes); conversely, spermatogenic genes were significantly underenriched on chromosome X (7% spermatogenic vs. 12% gonadal on X) but enriched on autosomes (93% vs. 88% on autosomes) (Figure 3B, see legend for p-values), confirming previous results (Reinke et al. 2000, 2004). Finally, those previous studies found more spermatogenic genes than oogenic genes, in agreement with our results (Figure 2, Figure 3A, and Table S1). Therefore, recent studies using RNA-Seq from whole worms are consistent with this analysis of gonadal sex-biased gene expression.
Analyses of spermatogenic and oogenic-enriched mRNAs/genes. (A) Box plot of expression fold changes for spermatogenic-enriched (blue) and oogenic-enriched (red) mRNAs, with whiskers indicating outliers. (B) Bar graph showing percentage of genes encoding spermatogenic-enriched (blue) or oogenic-enriched (red) mRNA on autosomal (left) and X (right) chromosomes. Significance of enrichment or depletion was calculated using Hypergeometric distribution with comparisons between the number of genes with sex-enriched expression on autosomal or X chromosomes and the total number of gonad-expressed genes on autosomal (9476 genes) or X chromosomes (1274 genes). *p-value < 10−24; **p-value < 10−93.
We hypothesized that genes involved in common germline processes, such as meiosis, would be enriched in the gender-neutral expression category. To test this idea, we searched for genes involved in meiosis according to Gene Ontology classification and RNAi experiments reported in WormBase. Our gender-neutral list included 82% (231/281) of those genes with meiosis-related functions (Table S2). Thus, meiotic cell cycle genes are enriched in our gender-neutral dataset compared with sex-enriched datasets.
Gonadal genes identified specifically in this study:
Using the NEXTDB database, we explored the tissue expression of gonad-expressed mRNAs identified in this work but not in previous studies of isolated gonads (Wang et al. 2009) or germline expression (Reinke et al. 2004). NEXTDB archives in situ hybridization results for approximately half the annotated C. elegans genes and includes unambiguous staining patterns for 1522 of the 2567 genes found specifically in this study. Of these 1522 staining patterns, 92% of spermatogenic (178), 90% of oogenic (294), and 74% of gender-neutral (743) genes were expressed in the germline tissue according to NEXTDB (Table S1, column J). Moreover, a sampling of genes was scored for gender expression. Most genes classified as sperm-enriched were visibly more abundant in L4 spermatogenic than adult oogenic germlines (69%; n = 103); most classified as oocyte-enriched were visibly more abundant in adult than L4 germlines (75%, n = 216); and most classified as gender-neutral were found at both stages with no obvious visible difference in abundance (78%; n = 363). Therefore, our dataset provides a new source for genes expressed in the germline.
Other comparisons:
We also compared our spermatogenic, oogenic, and gender-neutral datasets with several others (Figure 4). First, we compared them to lists of target genes or target mRNAs of crucial gamete regulators. The SPE-44 transcription factor drives spermatogenesis with many predicted target genes (Kulkarni et al. 2012). Most spe-44 predicted targets were found in our list of spermatogenic genes (475/668) but not in our list of oogenic genes (55/668) (Figure 4A). GLD-2/RNP-8 and EFL-1/DPL-1 heterodimers drive the process of oogenesis (Kim et al. 2009; Kudron et al. 2013). Many GLD-2/RNP-8 (178/317) and EFL-1/DPL-1 (130/309) predicted targets were on our list of oogenic genes, and the majority in a combined list of oogenic plus gender-neutral genes [GLD-2/RNP-8 (313/317); EFL-1/DPL-1 (290/309)], whereas overlap with spermatogenic genes was low [GLD-2/RNP-8 (4/317); EFL-1/DPL-1 (19/309)] (Figure 4, B and C).
Dataset comparisons. (A–E) Pie charts with overlaps between other relevant datasets, as noted in figure, and this work’s spermatogenic (blue), oogenic (red), and gender-neutral (gray) datasets. See text for explanation and references.
Second, we compared our datasets with transcriptomes obtained from isolated mature sperm (Ma et al. 2014) or zygotes (Baugh et al. 2003). Both contained many of our gender-neutral expression gene set. However, the mature sperm transcriptome contained almost half of our spermatogenic gene dataset (1216/2748) and the zygote transcriptome contained 64% of our oogenic dataset (1117/1732), which represent 45% and 23% of the sperm and zygote transcriptomes (Figure 4, D and E). These comparisons therefore provide additional validation for our spermatogenic, oogenic, and gender-neutral datasets.
Datasets for differential exon usage in spermatogenic vs. oogenic gonads:
To further characterize spermatogenic and oogenic transcriptomes, we analyzed the original Seq data to look for transcript level differences. Out of 99,984 total exon–exon junctions identified by TopHat in both transcriptomes, 86,452 (86.5%) represented canonical junctions (consecutive exons) and 13,532 (13.5%) represented noncanonical junctions (nonconsecutive exons) (Table S3). Transcripts were assembled in each gonad transcriptome using Cufflinks. We detected 25,461 expressed transcripts in spermatogenic gonads and 24,333 expressed transcripts in oogenic gonads, including isoforms in both cases (Table S4).
To identify isoforms enriched in spermatogenic and oogenic gonads, we analyzed differential exon usage between the gonadal transcriptomes. We identified 577 differentially expressed exons (DEXSeq; FDR < 1%) affecting 351 genes (Table S5). Of the 351 genes, 326 genes (93%) have annotated gene models on WormBase that correspond to our exon usage analysis. We also found that 253 genes (73%) were affected in protein-coding exons. As an example, we visualized mapped reads to the fog-1 gene locus with the UCSC Genome Browser. In agreement with the exon usage analysis, we found both the long and short fog-1 isoforms with enrichment of the “long” isoform in spermatogenic gonads and enrichment of the “short” isoform in oogenic gonads (Figure 5A). This finding mirrors fog-1 isoforms found previously using Northern blots (Luitjens et al. 2000). We also identified, as another example, sex-specific enrichment for the first exon of the mRNA encoding Argonaute protein CSR-1 (Figure 5B), which is intriguing given the role of CSR-1 in spermatogenesis (Conine et al. 2013). Among the 351 genes with sex-enriched exons, 50% occurred in spermatogenic, 30% occurred in oogenic, and 17% occurred in gender-neutral genes (Table S5). To further characterize these 351 mRNAs, we performed Gene Ontology (GO) analysis. The following biological processes were over-represented compared with all gonad-expressed genes: cell cycle (P < 0.005); glucose metabolism (P < 0.007); and post-transcriptional gene regulation (P < 0.04). Molecular functions relating to ATP binding were also enriched (P < 0.003).
Sex-enriched exon usage in sperm-only vs. oocyte-only XX gonads. (A and B) Coverage plots of sequencing reads mapping to exons in spermatogenic gonads (above) and oogenic gonads (below). Depth of coverage is measured as average reads per nucleotide. Relevant isoform models are shown for reference at bottom. Smoothing windows: 5 pixels in (A) and 10 pixels in (B). (A) Differential exon usage at the fog-1 locus. (B) Differential exon usage at the csr-1 locus. (C) Locations within transcripts of differentially used exons. Exons are displayed according to log2 fold change of normalized counts in fem-3(q96gf) vs. fog-2(q71). Positive values show increased exon use in sperm-only gonads, whereas negative values show increased exon use in oocyte-only gonads.
We next located differentially expressed exons within their transcripts: 19.2% (111/577) were the first exon; 17.7% (102/577) were the last exon; and 63.1% (364/577) were in the middle (Figure 5C). These middle exons reveal exon-skipping events predicted to alter the proteomes of spermatogenic vs. oogenic gonads. Although splicing factors have dramatic effects on gamete specification (Puoti and Kimble 1999, 2000; Kerins et al. 2010), the affected RNAs are not yet known. This dataset of differently expressed exons in spermatogenic and oogenic gonads may be a useful resource for finding events relevant to germline development or more broadly for studies of alternative 5′ and 3′ end formation as well as alternative splicing.
Conclusions
This work provides new datasets for spermatogenic, oogenic, and gender-neutral genes expressed in the C. elegans gonad. The major advantages over earlier datasets are doubling the number of genes found expressed in the gonad, with most likely expressed in germline tissue, and identification of sex-enriched mRNA isoforms.
Acknowledgments
Antibodies were generous gifts from Barth Grant (RME-2) and Susan Strome (SP56). E.P.S. was supported by the Biotechnology Training Program (NIH T32 GM08349). This work was supported in part by NIH grant GM069454 (to J.K.). J.K. is an investigator at the Howard Hughes Medical Institute.
Footnotes
Supporting information is available online at http://www.g3journal.org/lookup/suppl/doi:10.1534/g3.114.012351/-/DC1
Communicating editor: M. Walhout
- Received May 27, 2014.
- Accepted July 14, 2014.
- Copyright © 2014 Ortiz et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
