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Physiol. Genomics 24: 75-85, 2006. First published November 15, 2005; doi:10.1152/physiolgenomics.00215.2004
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Received 16 September 2004; accepted in final form 13 November 2005.
Physiological Genomics 24:75-85 (2006)
1094-8341/05 $8.00 © 2006 American Physiological Society

Expression profiling of purified male germ cells: stage-specific expression patterns related to meiosis and postmeiotic development

Alan L. Y. Pang1, Warren Johnson1, Neelakanta Ravindranath1, Martin Dym2, Owen M. Rennert1 and Wai-Yee Chan1,2,3

1 Section on Developmental Genomics, Laboratory of Clinical Genomics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland
2 Cell Biology
3 Pediatrics, Georgetown University, Washington, District of Columbia


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Gene expression profiling was performed using the National Institute on Aging 15,000-cDNA microarray to reveal the differential expression pattern of 160 genes between meiotic pachytene spermatocytes and postmeiotic round spermatids of the mouse. Our results indicate that more genes are expressed in spermatids than in spermatocytes. Genes participating in cell cycle regulation and chromatin structure and dynamics are preferentially expressed in spermatocytes, while genes for protein turnover, signal transduction, energy metabolism, and intracellular transport are prevalent in spermatids. This suggests that a switch of functional requirement occurs when meiotic germ cells differentiate into haploid spermatids. Concordant expression patterns were obtained when quantitative real-time polymerase chain reaction was performed to verify the microarray data. Interestingly, the majority of the differentially expressed genes were underrepresented in mitotic type A spermatogonia, and they were preferentially expressed in the testis. Our results suggest that an even higher proportion of the mouse genome is devoted to male gamete development from meiosis than was previously estimated. We also provide evidence that underscores the advantage of using purified germ cells over whole testes in profiling spermatogenic gene expression to identify transcripts that demonstrate stage-specific expression patterns.

gamete biology; testis; spermatogenesis; gametogenesis; developmental biology


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
SPERMATOGENESIS IS A COMPLICATED, yet highly orchestrated, developmental process of the male germline. Spermatogonial stem cells are capable of either undergoing mitotic divisions or differentiating into spermatocytes (8). Meiosis takes place in the spermatocytes. In these cells, two rounds of cell divisions, without intervening DNA replication, occur to reduce the chromosome number to haploid. The meiotic prophase can be further divided into five stages, in which pachynema persists for the longest interval (45). During meiosis, homologous chromosomes synapse and recombine. Elevated gene transcription and chromatin remodeling occur during this period. Eventually, haploid round spermatids form that gradually transform into spermatozoa (6, 15). The finely tuned nature of the spermatogenic process indicates the existence of a concerted global change in gene expression. Consequently, elucidation of the transcriptome at different stages of male germ cell development will allow us to understand the molecular mechanisms of spermatogenesis.

Recently, we reported on the differential gene expression patterns in isolated germ cells at distinct stages of spermatogenesis, namely, type A spermatogonia (Spga), pachytene spermatocytes (Spcy), and round spermatids (Sptd); these are representative of mitotic proliferation and meiotic and postmeiotic development, respectively (32). However, the small number of genes on the microarray (5,184 genes) limited the conclusions. Therefore, we pursued further experiments using the National Institute on Aging (NIA) mouse 15,000-cDNA microarray. Investigations have reported on the mouse testicular transcriptome (1, 39, 40). In two of these studies (39, 40), the same set of Affymetrix GeneChips was used to profile the testicular transcriptomes of mice at different ages. Germ cell-specific transcripts were identified by cluster analysis and in silico subtraction of whole testis profiling data with that obtained from testicular somatic cells. These data showed the temporal changes in gene expression patterns in testes as a function of the age of animals. However, no information can be derived directly from these data to illustrate stage-specific spermatogenic gene expression patterns unless secondary experiments such as in situ hybridization were performed (1, 39) to correlate the developmental gene expression changes from whole testes to specific cell types. The appearance of different stages of germ cells, in addition to the diverse types of somatic cells such as Sertoli cells, Leydig cells, peritubular myoid cells, and testicular macrophages in the developing testes, could mask the authentic gene expression pattern in a specific stage of germ cells. We believe the use of whole testes in gene expression profiling experiments cannot reliably predict stage-specific spermatogenic gene expression patterns. Therefore, isolated germ cells were used in our experiments. We focused on the changes between meiotic (Spcy) and postmeiotic (Sptd) male germ cells to identify genes that are preferentially expressed in either differentiation process. Hints on the genetic cause(s) of male infertility may be obtained, as genes involved in fertilization are expected to be active late in spermatogenesis. Quantitative real-time polymerase chain reaction (QPCR) was performed to validate the microarray data. Surprisingly, a high proportion of these genes were underrepresented before meiosis, and they were preferentially expressed in testis compared with other tissues. The differentially expressed genes would represent potential participants of the meiotic/postmeiotic development of male germ cells. Our results also suggest that an even higher proportion of the mouse genome is involved in spermatogenesis than was estimated (39). Out of our expectation, a comparison of our microarray data with that of Schultz et al. (39) showed only a low degree of concordance. In contrast, the comparison of our expression profiles with the serial analysis of gene expression (SAGE) data generated from the same stages of purified germ cells (50) showed a better agreement of results. Our data suggest that such a discrepancy could be attributed to the dynamic change in cellular composition in the developing testis. We concluded that the use of purified germ cells would be more advantageous to whole testes in studying stage-specific spermatogenic gene expression patterns.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Animal, cell, and RNA preparation.
Protocols for the use of mice were approved by the Georgetown University Animal Care and Use Committee. The use of animals in this study, isolation of germ cells at different stages, extraction and purification of total RNA from germ cells, and quality control were performed as described before (32). Briefly, Spcy and Sptd were isolated from 60-day-old BALB/c mice by STAPUT technique (9). Purity of either cell type was at least 90% in multiple preparations. For Spga, 6-day-old animals were used, and the purity of cells was >95%. Sertoli cells were also purified from 6-day-old animals by a similar method standardized for rats with minor modifications (34), and the purity of cells was at least 96%. Total RNA was extracted and cleaned up from the cells using Trizol reagent (Invitrogen, Gaithersburg, MD) and RNeasy Mini column (Qiagen, Valencia, CA). RNA integrity was monitored by denaturing agarose gel electrophoresis. RNA content and purity were measured by absorbance at 260 and 280 nm. Only total RNA samples showing an OD260/OD280 ratio higher than 1.8 were used for microarray hybridization and subsequent experiments.

Microarray experiment.
Glass slide microarrays fabricated with the NIA 15,000-mouse cDNA clone set (43) were used in this study. Fifty micrograms of total RNA from each type of germ cells were used for each microarray hybridization experiment. First-strand cDNA was synthesized from Spcy and Sptd total RNA in the presence of Cy3-dUTP or Cy5-dUTP, respectively, using MicroMax Direct Labeling Kit (Perkin Elmer Life Sciences, Boston, MA). Labeled cDNA samples were then processed according to the manufacturer's suggestion with a minor modification: the target samples were heated at 65°C for 5 min before hybridizing to the microarrays. Hybridization was carried out at 65°C for 14 h. Each microarray was then subjected to posthybridization washes at room temperature with gentle agitation in 45 ml of each of the following solutions: 1x SSC with 0.2% SDS for 5 min, 0.5x SSC with 0.01% SDS for 15 min, 0.06x SSC with 0.01% SDS for 15 min, and 0.06x SSC for 15 min. The washed microarrays were spun at 1,000 rpm for 4 min to remove residual liquid and then scanned at 5-µm resolution using the ScanArray 5000XL microarray analysis system (Packard Bioscience, Billerica, MA). Microarray hybridization was carried out in duplicate with total RNA samples derived from a pool of four separate preparations of Spcy and a pool of three separate preparations of Sptd. An additional dye-swapping hybridization (Cy3-dUTP for Sptd and Cy5-dUTP for Spcy) was carried out using the same pools of total RNA. Signals generated from Cy3 and Cy5 channels on each microarray were background subtracted and normalized to the total signals of all spots generated from the Cy5 channel and were analyzed by the QuantArray microarray analysis software version 3.0 (Packard Bioscience). Data were exported to a Microsoft Excel program for further sorting and categorization. The normalized and background-subtracted ratio of fluorescence intensity represented the gene expression ratio. Subsequent analysis indicated that the use of fold change was compatible with statistical methods in data presentation. In this report, we considered an at least twofold change in gene expression level to be biologically significant. Genes were considered to be truly differentially expressed if they both displayed the same trend of change in expression pattern in all experiments and an at least twofold difference in fluorescence signal ratio between Spcy and Sptd. The microarray data were deposited to the Gene Expression Omnibus (GEO) database of the National Center for Biotechnology Information (NCBI) with the accession number GSE1768.

QPCR.
An independent preparation of purified Spcy and Sptd was used for total RNA isolation. Synthesis of first-strand cDNA and QPCR analysis were carried out as described previously (32) with minor modifications. Total RNA samples from different stages of germ cells were first treated with DNase I (Invitrogen) to eliminate genomic DNA. RNA integrity and concentration were monitored by the Bioanalyzer 2100 (Agilent Technologies, Germantown, MD). First-strand cDNA was then synthesized using SuperScript II and random hexamers (Invitrogen) according to the manufacturer's instructions. Equal amounts of total RNA from each cell type were used, and they were processed simultaneously to avoid experimental variation. Primers specific for each gene were designed using Primer Express version 2.0 (Applied Biosystems) (Table 1), and their specificities were confirmed by a basic local alignment search tool (BLAST)N search against the nonredundant and expressed sequence tag (EST) mouse sequence sets from NCBI. Primers for QPCR were ordered from Invitrogen. QPCR was performed in triplicate using the 7900 HTS Sequence Detection System (Applied Biosystems), in the presence of 1x SYBR Green PCR Master Mix (Applied Biosystems, Warrington, UK), 200 or 900 nM primer mix, and 1 µl of germ cell first-strand cDNA sample at different concentrations, in a final volume of 25 µl. QPCR samples were first incubated at 50°C for 2 min, followed by an activation step at 95°C for 10 min. Amplification was carried out for 40 cycles at 95°C for 15 s and 60°C for 60 s. The QPCR samples were then subjected to a slow temperature-ramping dissociation stage at 95°C for 15 s, 60°C for 15 s, and 95°C for 15 s to monitor the specificity of amplification. Relative standard curve method was used to quantify gene expression levels (2a, 32). For quantification of 18S rRNA content of germ cell cDNA samples, QPCR was carried out in the presence of 1x Taqman Universal PCR Master Mix (Applied Biosystems, Branchburg, NJ) and Taqman ribosomal RNA control reagents (Applied Biosystems, Warrington, UK), which included 50 nM forward and reverse primers as well as 200 nM rRNA probe (VIC probe) specific to 18S rRNA. Gene expression data were reported after normalization to that of 18S rRNA content.


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  		Table 1. List of primers used in QPCR

 
Multiple tissue expression screening by RT-PCR.
Total RNA from different mouse tissues was obtained from Ambion (Austin, TX) and subjected to DNase I treatment and first-strand cDNA synthesis as described in QPCR. 18S rRNA contents were assayed as described above for normalization of gene expression level among tissue samples. Primer mix for ß-actin (QuantumRNA ß-actin internal standards kit) was purchased from Ambion (Austin, TX). Primers for mouse Transferrin gene were designed as in the QPCR experiment and ordered from Qiagen (Germantown, MD). PCR was performed in the presence of 1 µl of the fivefold diluted first-strand cDNA product, 1x PCR buffer, 2.5 mM MgCl2, 0.5 mM dNTP mix, 200 or 500 nM forward and reverse primers (Table 1), and 0.5 units of Platinum Taq DNA polymerase in a final volume of 20 µl. All reagents were purchased from Invitrogen except dNTP mix (Roche Diagnostics, Mannheim, Germany). PCR samples were first incubated at 94°C for 5 min. Amplification was carried out according to the following temperature cycles: 94°C for 30 s, 60°C for 35 s, and 72°C for 30 s, for 30 or 35 cycles. The reaction mixes were then subjected to a further 7-min extension at 72°C. PCR products were analyzed on 4% Tris-acetate-EDTA (TAE) agarose gel prestained with ethidium bromide (EmbiTec, San Diego, CA).

Bioinformatics.
DNA sequences for primer design, gene mapping data, gene expression in testis, and gene ontology data were retrieved and finalized from NCBI Mouse Unigene Cluster Build no. 134 (6 January 2004) and LocusLink (http://www.ncbi.nih.gov/LocusLink), Mouse Genome Informatics from the Jackson Laboratory (http://www.informatics.jax.org/), GeneCards from the Weizmann Institute of Science (http://bioinformatics.weizmann.ac.il/cards/), and literature search. Chromosomal locations of transcripts without Unigene IDs were mapped in silico using the Mouse Genome Resources from NCBI (http://www.ncbi.nlm.nih.gov/genome/seq/MmBlast.html). For data comparison, probe identities of the transcripts represented on the Affymetrix mouse U74v2 GeneChips were verified by querying the NetAffx database (http://www.affymetrix.com) with the gene accession ID, Unigene cluster ID, or Gene Index ID of the cDNA sequences represented in the NIA mouse 15,000-cDNA clone set. SAGE profiles of purified germ cells were generated as described (50).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Microarray experiments.
Analysis of 15,264 genes in triplicate microarray experiments documented the differential expression of 160 unique genes between Spcy and Sptd (Supplemental Table S1; available at the Physiological Genomics web site).1 Fifty-one and one hundred nine genes were preferentially expressed in Spcy and Sptd, respectively, indicating a larger repertoire of expressed genes in postmeiotic germ cells. Among the genes preferentially expressed in Spcy, 30 had known biological functions and 21 were uncharacterized transcripts or ESTs. For Sptd, the number of known genes and uncharacterized transcripts/ESTs was 50 and 59, respectively. Among the 160 genes identified, 14 were not known to be expressed in mouse testis according to mouse Unigene information nor did they have a Unigene cluster assignment at the time of analysis.

With the use of gene ontology information, the 160 differentially expressed genes were categorized according to the known gene subset (Fig. 1 and Supplemental Table S1). Genes responsible for cell cycle regulation (e.g., Rnf2, Hspb1, and Cks2) and chromatin structure and dynamics (H3f3b, Myst2, Smc4l1, and Fancg) were found upregulated in Spcy. On the other hand, genes participating in protein turnover (e.g., Ube2n, Psma6, and Psmd10), signal transduction (most belonging to protein kinases and phosphatases such as Prkcd, Pctk1, Ppm1a, and Ptp4a1), energy metabolism (e.g., Glul, Facl2, Gpi1, Sqrdl, Atp1b3), and intracellular transport (e.g., Ap3s1, Sypl, Kif2c, Scamp1, Stard10) were preferentially expressed in Sptd.



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  		Fig. 1. Functional categorization of the 160 differentially expressed genes identified between pachytene spermatocytes (Spcy) and round spermatids (Sptd). Gene ontology information was retrieved from databases as indicated in MATERIALS AND METHODS. A: pie chart showing the general functions of the 160 genes. B: bar graph showing the distribution of genes involved in specific biological functions in Spcy and Sptd.

 
Among the 160 differentially expressed genes, we identified genes previously shown to be preferentially expressed during the meiotic or postmeiotic stage, e.g., H3f3b (4), Siah2 (7), Stmn1 (25), Calm2 (41), Cks2 (42), Hspb1 (49), Txndc2 (17), Akap1 (23), Ccnd3 (35), and Stard10 (51). We also identified genes (Bag1, Ccnd3, Cks2, Fancg, Hspb1, H3f3b, Prkcd, Ube2n) whose functionally related homologs (Bax, Ccnd2, Cdk4, Fanca/Fancc/Fancg, Hsp70-2, H3f3a, Prkaca, Ube2b, respectively), when disrupted, cause spermatogenic defects (28). In addition, we identified genes that displayed expression patterns correlating with their specific roles during spermatogenesis. From our data, Fancg and Cks2 were found to be preferentially expressed in Spcy. A null mutation of Fancg, one of the affected genes in Fanconi anemia (a hereditary chromosomal instability disorder in humans), results in reduced fertility in mice; the Fancg–/– cells show an elevated level of spontaneous chromosomal breakage (22). Analogous to the latter observation is the initiation of meiotic recombination of homologous chromosomes by DNA double-strand breaks, which supports the involvement of Fancg in maintaining chromosomal integrity during meiosis. Mice lacking Cks2 are sterile due to a failure of germ cells to progress through the first meiotic metaphase (42). Antibodies directed against Sperm-specific antigen-1 (Ssfa-1) completely block sperm-zona pellucida interaction in mice (54). From our data, Ssfa-1 was preferentially expressed in Sptd, which agrees with the temporal requirement of the gene product. These observations strongly suggest that the gene expression profiles of germ cells are not altered by the cell isolation and purification procedures.

QPCR.
To validate the microarray data, we randomly selected 16 genes (with definitive Unigene information) known to be expressed in testis or displaying stage-specific expression in spermatogenesis and 12 uncharacterized transcripts/ESTs that may not show testis expression for QPCR experiment (Fig. 2). Care was taken to eliminate genomic DNA contamination from the total RNA samples prepared for QPCR and RT-PCR (see below). For instance, the total RNA samples were DNase I treated and subject to PCR analysis with primers targeting to housekeeping transcripts such as Gapdh and ß-actin. The absence of PCR products confirmed the success of DNase I treatment. Also, minus RT reactions were included during first-strand cDNA synthesis to further verify the absence of genomic DNA contamination (data not shown). As shown in Fig. 2, the QPCR data were perfectly concordant with the microarray data; all of the selected genes displayed the same trend of change in expression between Spcy and Sptd. In addition, we determined the expression level of these 28 genes/transcripts in purified Spga to examine their developmental expression profiles. Surprisingly, we observed a tremendous underrepresentation of these genes in Spga; only five of them (18%) displayed a comparable or higher expression level in Spga with respect to Spcy or Sptd. In contrast, the remaining 23 genes (82%) were preferentially expressed either in meiotic or postmeiotic male germ cells.



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  		Fig. 2. Verification of differential gene expression patterns between pachytene spermatocytes (Spcy) and round spermatids (Sptd) by quantitative real-time PCR (QPCR). Expression of the selected genes in purified type A spermatogonia (Spga) was also tested. A: gene expression patterns for selected known genes. B: gene expression patterns for selected uncharacterized transcripts/expressed sequence tags (ESTs).

 
Tissue distribution by RT-PCR.
An RT-PCR experiment was performed to identify the expression patterns of the same 12 uncharacterized transcripts studied by QPCR across different mouse tissues (Fig. 3A). With the exception of AW556756, all transcripts displayed a preferential expression in the testis. For AW547981, the expression level was so low that we were unable to produce a publishable quality image. However, a PCR product of the expected size was observed in testis and kidney with similar intensities. The expression of some transcripts was restricted to certain tissues. For instance, EST AU040146 was detected only in testis and ovary, whereas EST BG068805 was expressed predominantly in testis and ovary but weakly in brain and lung. In addition, EST BG069933 was present exclusively in the mouse testis. We also examined the expression of these transcripts in Sertoli cells (Fig. 3B), and the results indicated a variable expression level. Notably, ESTs BG082966 and BG068805 were barely detectable. The absence of expression for AW547981 may be due to its low abundance. In contrast, a clear absence of BG069933 transcripts in Sertoli cells was observed. These results identified testis-enriched and potentially germ cell-specific transcripts that were differentially expressed during spermatogenesis.



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  		Fig. 3. Tissue specificity of expression of the uncharacterized transcripts/ESTs selected for QPCR verification. A: expression of selected transcripts in different mouse tissues. M, GeneRuler 100-bp Ladder Plus (Fermentas, Hanover, MD), with the molecular size increases successively upward from 100 bp in each panel; L, liver; B, brain; H, heart; Ln, lung; S, spleen; T, testis; O, ovary; K, kidney; E, embryo at embryonic days 10–12; –, no template control. The amplification of ß-actin gene is indicated as a 294-bp fragment. Size of the PCR product for each transcript is listed in Table 1. AW556756, AU040146, BG071158, BG070835, BG068805, and AW47981 were not reported to be expressed in mouse testis before. B: expression of the selected uncharacterized transcripts/ESTs in purified mouse Sertoli cells. Numbering of samples is in accordance with those assigned in parentheses in A. Trf, PCR product for the mouse Transferrin gene that serves as a Sertoli cell positive control (2). Stard10 was included as a known gene control.

 
In silico data comparison.
We compared our microarray data with the mouse testicular transcriptome data reported by Schultz et al. (39). In the latter study, testicular gene expression profiles using Affymetrix GeneChips were generated from whole testes of mice of different ages, corresponding to the first appearance of a particular stage of germ cells in the seminiferous tubules. In this regard, day 4, 14, and 21 GeneChip profiles are equivalent to gene expression derived from Spga, Spcy, and Sptd, respectively (10). Germ cell-enriched gene expression profiles were generated by excluding from the whole testis profiles genes that were detected in Sertoli cells and interstitial cells. Data comparison was first performed between the QPCR-verified 28 genes and the corresponding GeneChip data obtained from day 4, 14, and 21 mouse testes. In the second comparison, the expression patterns of the 160 differentially expressed genes identified in our study were compared with the day 14 and 21 GeneChip profiles. On the GeneChip microarray, multiple probe sets may be present for the detection of some transcripts. Because both the cDNA and GeneChip microarrays used a nucleic acid probe hybridization-based strategy, we expected similar magnitudes of change in gene expression levels between the two data sets. Five of the uncharacterized transcripts were not represented in the GeneChips and therefore excluded from comparison. Among the remaining 23 genes, 10 of them (43%) showed a similar expression pattern between the two data sets for Spcy and Sptd in the first comparison (Table 2). However, 6 of these 10 genes (namely Siah2, Sparc, Ddx20, Stard10, Clu, and BG071080) showed a <1.5-fold difference in expression level. The other 13 genes (57%) showed discordant results. If Spga (day 4) expression was considered, only 6 of 23 genes (26%) from the GeneChip experiment displayed a similar expression pattern as in our QPCR results; the overall expression patterns of the other 17 genes (74%) were different from what we found. Most of the genes displayed elevated expression levels in the day 4 GeneChip profile, in contrast to the underrepresentation we observed in Spga, and in this GeneChip profile positive signals were detected in Sertoli cells and/or Leydig cells. In the second comparison, 14 genes were not represented in the GeneChips and thus excluded from comparison. Among the remaining 146 genes, only 41 (28%) showed concordant results. Seventy-six of the genes (52%) showed discordant results in the GeneChip data, and 14 genes (10%) were undetected. The other 15 genes (10%) showed expression in both day 14 and day 21 profiles by virtue of the multiple probe sets represented on the GeneChips (Supplemental Table S2). Although the signals detected, and thus the change in gene expression level, may be statistically significant, many of the concordant genes showed a less than twofold difference in fluorescence signals between the day 14 and day 21 GeneChip profiles.


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  		Table 2. Comparison of expression patterns (Schultz et al.)

 
As a control, we performed a similar comparison of our microarray data with the SAGE data obtained from comparable stages of purified germ cells (50). Among the 12 uncharacterized transcripts of the 28 differentially expressed genes, two of them represented the 5'-end of their corresponding full-length transcripts, one did not possess a polyadenylation signal, and three did not have tag records in the NCBI SAGEmap. Hence, these six transcripts were excluded from comparison. In the first comparison between Spcy and Sptd, 20 of the 22 genes (91%) showed SAGE tag levels that matched with the microarray data. If Spga expression was considered, 18 genes (82%) showed concordant expression patterns between the microarray and SAGE data (Table 3). Unexpectedly, we could not identify the Fancg SAGE tag(s), and the SAGE result for Lcn2 was discordant. The SAGE protocol measures transcript levels based on a short sequence upstream of the poly(A) tail and downstream of a specific restriction enzyme recognition site (47). The appearance of multiple tags for some transcripts is thus attributable to the use of alternate polyadenylation signals, which is common in spermatogenic cells (10, 21). The same situation might occur as that which generated the corresponding tag sequences, but they were not annotated yet by SAGEmap to the two genes. When we expanded the analysis, i.e., the second comparison, 117 of the 160 genes (73%) had SAGE tags showing expression patterns similar to the microarray results (Supplemental Table S2).


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  		Table 3. Comparison of expression patterns (Wu et al.)

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
By using cDNA microarray to study the stage-specific gene expression patterns in Spcy and Sptd, we identified 160 genes that may be crucial to meiotic and postmeiotic male germ cell development. To ensure the quality of the microarray data, the hybridization experiments were repeated, and an extra dye-swapping experiment was included to eliminate potential variation in dye incorporation and probe hybridization efficiency (19). The identification of genes that are known to display stage-specific expression patterns and phenotypic changes that correspond to their stage-specific functions, as well as the perfect concordance between our microarray and QPCR results, unambiguously validated the microarray data.

By functional categorization, we could identify genes with specific biological functions that were predominant in either type of germ cell. The gene ontology data predicted for uncharacterized transcripts also generated a similar representation of biological functions as from the known genes (data not shown). Our results thus illustrate an overview of the biological activities that are essential to meiotic and postmeiotic male germ cells, respectively.

During meiotic prophase, homologous chromosomes synapse and recombine for the exchange of genetic materials before haploid formation. To facilitate these processes, the chromatins undergo remodeling that contrarily makes them susceptible to damage. The induction of activities to maintain genomic integrity would be essential to the completion of meiosis. Because DNA recombination and the associated processes are specific to meiotic germ cells, we would not expect any of these genes to be actively expressed during spermiogenesis. The preferential expression of genes related to chromatin structure and dynamics in Spcy therefore reflects such functional requirements during meiosis. Male germ cells are committed to differentiation beyond the spermatogonial proliferation stage. In this respect, spermatids are conceivably "terminally differentiated" cells, and cellular proliferation or division activities should be minimal. On the other hand, spermatocytes undergo transition from G2 (the meiotic prophase) to MI (the first meiotic division) phase of the cell cycle. Hence, the expression of genes participating in cell cycle regulation (e.g., Stmn1, Rnf2, Hspb1, Calm2, and Cks2) should be more prominent in Spcy. The upregulated expression of CyclinD3 in Sptd is discordant with this notion. However, similar elevations of Cyclin gene expression in nondividing testicular cells have been observed, which raised the possibility that the gene products may have unique functions in haploid germ cells distinct from those known in mitotic cells (35).

A gradual cessation of gene transcription occurs during spermiogenesis as the haploid genome condenses. The higher percentage of differential gene expression in Sptd is consistent with the burst of gene transcription in these cells before differentiation into elongating spermatids (20), to ensure the availability of transcripts for protein expression in late spermiogenesis. From our data, biological activities such as protein turnover, signal transduction, energy metabolism, and intracellular transport are more prevalent in Sptd. The disruption of mHR6B (a mouse homolog of the yeast ubiquitin-conjugating enzyme RAD6) has been shown to impair chromatin condensation in spermatids (37). Also, an elevated ubiquitinated histone H2A level was observed in mouse elongating spermatids preceding histone replacement (3). Ubiquitination activity is thus essential to the completion of spermiogenesis, which explains the preferential upregulation of genes mediating ubiquitin-conjugating (Ube2n, Hip2, Psma6, Psmd10) and ubiquitin-ligating (Siah2) activities in Sptd.

Meanwhile, the preferential expression of genes responsible for various metabolic processes indicates a higher energy demand in Sptd, presumably required for the structural and chromatin remodeling activities during spermiogenesis. Upregulation of genes encoding protein kinases and phosphatases was also observed in this stage. Taken together, Sptd seems to be biochemically more active than Spcy. Interestingly, an analogous phenomenon was reported in Caenorhabditis elegans (36); a preferential upregulation of genes encoding protein kinases, phosphatases, and enzymes for energy production was found in mutant worms that produce only sperms compared with their oocyte-only counterparts. Together with the relationship between mitochondrial fusion and spermatogenesis in Drosophila (13), our data favor the postulation that increased energy requirement and signaling activities are intrinsic to the later stages of germ cell development, and these functional requirements are conserved throughout evolution.

Despite morphological and cytoskeletal changes, germ cells also undergo drastic nuclear changes and redistribution of membrane domains and formation of organelles specific to sperm development (e.g., the acrosomes) during spermiogenesis. The involvement of motor proteins and other transport proteins in such processes has been documented (5, 23, 53). Therefore, the upregulation of genes in Sptd related to vesicle and nutrient transport (Sypl, Scamp1, and Stard10; Ref. 51), regulation of membrane organelle transport (Kifap3; Ref. 52), and intracellular trafficking (Akap1; Ref. 23) is consistent with the elevation of cellular remodeling activities in preparation of sperm formation.

From our QPCR data, the majority (82%) of the genes verified were found to be underrepresented in Spga, which is also evident in our SAGE analysis of the same cell type (Table 3). Our results agree with the observation by Schultz et al. (39) that most of the testis-specific (or predominant) transcripts are first expressed during or after meiosis. An earlier study on measuring poly(A) levels in rats provided evidence for mRNA overexpression in Spcy and Sptd with respect to other testicular cells (29). Also, numerous stage-specific (e.g., PACH1 and CREM-tau; Refs. 12, 24, 30) and general (11) transcription factors and components of transcription machinery (e.g., TBP, TFIIB, and RNA Pol II; Refs. 26, 33, 38) are expressed specifically or at an unusually high level in both meiotic and early postmeiotic germ cells, suggesting an overall activation of the transcriptional machinery in these cells. Overexpression of genes during meiosis has been proposed to be consequential to the open chromatin structure in facilitating chromosome pairing and recombination (21). Nevertheless, no definite data are available to explain the molecular basis of such "biased" gene expression patterns during spermatogenesis.

From a literature search, most of the known genes identified in our study are predominantly expressed in the testis, e.g., H3f3b (4), Pknox2 (14), Sparc (16), Clusterin (18), Tes3 (27), Ddx20 (31), Fancg (46), Fem1b (48), Stard10 (51), Ssfa-1 (54), and SMC4l1 (A. L. Y. Pang, unpublished data). A similar phenomenon was also observed from the uncharacterized transcripts. Meanwhile, these genes/transcripts were not necessarily germ cell specific. On the basis of only germ cell-specific transcripts, Schultz et al. (39) estimated that ~4% of the mouse genome is specific to the meiotic and postmeiotic male germ cells. Our current results therefore further extend their estimation that an even larger proportion of the mouse genome is devoted to male gamete development starting from meiosis.

The advantage of using purified germ cells in studying stage-specific spermatogenic gene expression patterns was illustrated in the comparison of our microarray and the GeneChip data. The expression data generating from whole testes at a specific age represent only the accumulated gene expression level appearing in all types of cells present. Because the proportion of different stages of germ cells is dynamic in the developing testes, indiscriminative data interpretation may occur from the use of whole testes. The presence of the different testicular somatic cells is another source of interference that would mask the true spermatogenic gene expression patterns, particularly during the premeiotic stage in which the ratio of somatic cells to germ cells is higher. This is exemplified by the general increase in transcript level detected in the day 4 GeneChip profile (Table 2). On the contrary, the ability to reproduce documented gene expression patterns and the higher degree of concordance between our microarray and SAGE data strongly support the use of purified germ cells for such experiments. Despite the incomplete coverage of the mouse transcriptome, we believe our data provide a more accurate view on the gene expression patterns between meiotic and postmeiotic male germ cells than the use of whole testes. The distinct expression patterns of genes should provide leads to the elucidation of the mechanisms of male germ cell development.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Child Health and Human Development, and in part by NIH Grants HD-33728 and HD-36483 to M. Dym.


   ACKNOWLEDGMENTS
 
We are grateful to Dr. Yan A. Su of the Department of Pathology, Loyola University Medical Center (Maywood, IL), for fabricating the 15,000 mouse cDNA microarrays and Dr. Yali Chen of the Department of Cell Biology, Georgetown University (Washington, D.C.), for performing the STAPUT isolation of male germ cells. Special thanks go to Vanessa Bexandale and Dr. Tin-lap Lee for the preparation of germ cell SAGE data and advice on data analysis, respectively.


   FOOTNOTES
 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: A. L. Y. Pang, Section on Developmental Genomics, Laboratory of Clinical Genomics, National Institute of Child Health and Human Development, National Institutes of Health, 49 Convent Dr., Rm. 2C08, MSC 4429, Bethesda, MD 20892-4429 (e-mail: panga{at}mail.nih.gov)

10.1152/physiolgenomics.00215.2004.

1 The Supplemental Material (Supplemental Tables S1 and S2) for this article is available online at http://physiolgenomics.physiology.org/cgi/content/full/00215.2004/DC1. Back


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 ABSTRACT
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 MATERIALS AND METHODS
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 DISCUSSION
 GRANTS
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