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2006-The human cumulus--oocyte complex gene-expression profile

Human Reproduction Vol.21, No.7 pp. 1705–1719, 2006 Advance Access publication March 29, 2006.


The human cumulus–oocyte complex gene-expression

Said Assou1,2,3, Tal Anahory4, Véronique Pantesco2, Tanguy Le Carrour1, Franck Pellestor4,5, Bernard Klein1,2,3, Lionel Reyftmann6, Hervé Dechaud6, John De Vos1,2,3,7 and Samir Hamamah1,2,3,4,8
CHU Montpellier, Institut de Recherche en Biothérapie, H?pital Saint-Eloi, Montpellier, France; 2INSERM, U 475, 3Université Montpellier1, UFR de médecine, Montpellier, France; 4CHU Montpellier, Service de Biologie de la Reproduction B, H?pital Arnaud de Villeneuve, Montpellier, France; 5Institut de Génétique Humaine, CNRS UPR1142, Montpellier, France; and 6CHU Montpellier, Service de Gynécologie-Obstétrique B, H?pital Arnaud de Villeneuve, Montpellier, France
7 1

To whom correspondence should be addressed at: Research Institute for Biotherapy, H?pital Saint-Eloi, 80 rue Augustin Fliche, 34295 Montpellier Cedex 5, France. E-mail: devos@montp.inserm.fr
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To whom correspondence should be addressed at: CHU Montpellier, Service de Biologie de la Reproduction B, H?pital Arnaud de Villeneuve, 371, av. du Doyen Gaston Giraud, 34295 Montpellier Cedex 5. E-mail: s-hamamah@chu-montpellier.fr

BACKGROUND: The understanding of the mechanisms regulating human oocyte maturation is still rudimentary. We have identified transcripts differentially expressed between immature and mature oocytes and cumulus cells. METHODS: Using oligonucleotide microarrays, genome-wide gene expression was studied in pooled immature and mature oocytes or cumulus cells from patients who underwent IVF. RESULTS: In addition to known genes, such as DAZL, BMP15 or GDF9, oocytes up-regulated 1514 genes. We show that PTTG3 and AURKC are respectively the securin and the Aurora kinase preferentially expressed during oocyte meiosis. Strikingly, oocytes overexpressed previously unreported growth factors such as TNFSF13/APRIL, FGF9, FGF14 and IL4 and transcription factors including OTX2, SOX15 and SOX30. Conversely, cumulus cells, in addition to known genes such as LHCGR or BMPR2, overexpressed cell-to-cell signalling genes including TNFSF11/RANKL, numerous complement components, semaphorins (SEMA3A, SEMA6A and SEMA6D) and CD genes such as CD200. We also identified 52 genes progressively increasing during oocyte maturation, including CDC25A and SOCS7. CONCLUSION: The identification of genes that were up- and down-regulated during oocyte maturation greatly improves our understanding of oocyte biology and will provide new markers that signal viable and competent oocytes. Furthermore, genes found expressed in cumulus cells are potential markers of granulosa cell tumours.
Key words: cumulus/germinal cells/microarray/oocytes

Introduction The quality of oocytes obtained following controlled ovarian stimulation (COS) for assisted reproductive technology (ART) varies considerably. Although most oocytes are amenable to fertilization, only half of those fertilized complete preimplantation development and even fewer implant. During follicle growth, the oocyte obtains the complement of cytoplasmic organelles and accumulates mRNAs and proteins that will enable it to be fertilized and to progress through the first cleavage divisions until embryonic genes start to be expressed. Transcriptional activity decreases as the oocyte reaches maximal size (Fair et al., 1995), and later on, the oocyte depends on stored RNAs for normal function during maturation, fertilization and early embryonic development (Moor et al., 1998). After oocyte retrieval, the mature oocyte [metaphase II

(MII)] and even some immature oocytes [germinal vesicle (GV) and metaphase I (MI)] are surrounded by the cumulus oophorus. Several layers of cumulus cells surround the oocyte in the antral follicle and play an important support and regulation role in oocyte maturation (Dekel and Beers, 1980; Larsen et al., 1986). Analysis of oocyte maturation using microarray analysis techniques could detail the genes involved in this process and the specific checkpoints regulating acquisition of full competence for ovulation and fertilization. The understanding of the molecular processes involved in the development of a competent oocyte under COS conditions could guide the choice of ovarian stimulation protocols and lead to improvements in oocyte quality, oocyte culture and manipulation. Some studies demonstrate that changes in gene expression during COS, such as GDF9 or bone 1705

? The Author 2006. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

S.Assou et al.

morphogenic protein 15 (BMP15) in oocytes, or pentraxin 3 (PTX3) in cumulus cells, can be monitored for selecting appropriate oocytes for fertilization and embryos for replacement (Elvin et al., 1999; Yan et al., 2001; Zhang et al., 2005). Therefore, transcriptome studies in human oocytes and cumulus cells could contribute to not only elucidate the mechanisms of oocyte maturation but could also provide valuable molecular markers of abnormal gene expression in oocytes with reduced competence. The aims of the present study were to establish (i) whole-genome transcriptome of human immature and mature oocytes and cumulus cells, (ii) specific gene-expression signatures of immature and mature oocytes and cumulus cells and (iii) genes whose expression progressively increase during oocyte maturation. Materials and methods
Oocytes and cumulus cells Oocytes and cumulus cells were collected from patients consulting in our centre for conventional IVF (cIVF) or for ICSI (male infertility). This study has received institutional review board’s approval. Patients were stimulated with a combination of GnRH agonist (Decapeptyl PL 3; Ipsen, Paris, France) and recombinant FSH (Puregon, Organon, Saint Denis, France and Gonal F, Serono, Randolph, MA, USA) or Menopur (Ferring). Ovarian response was evaluated by serum estradiol level and daily ultrasound examination to observe follicle development. Retrieval of oocytes occurred 36 h after HCG administration and was performed under ultrasound guidance. Cumulus cells were removed from a mature oocyte (MII) 21 h after insemination. Immature oocytes (GV and MI) and unfertilized MII oocytes were collected 21 or 44 h after insemination or after microinjection by ICSI. Cumulus cells and oocytes were frozen at –80°C in RLT buffer (RNeasy kit, Qiagen, Valencia, CA, USA) before RNA extraction. Pools of 20 GV (seven patients, age 30 years ± 4.6), 20 MI (six patients, age 30.1 years ± 6.7) and 16 MII oocytes (six patients, age 34 years ±4.5) were analysed by DNA microarrays. All these oocytes were from couples referred to our centre for cIVF (tubal infertility) or for ICSI. Complementary RNA preparation and microarray hybridization RNA was extracted using the micro RNeasy Kit (Qiagen), and the RNA integrity was assessed by using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA, USA). RNA quantity was also assessed for some samples using the Nanodrop ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). Complementary RNA (cRNA) was prepared according to the manufacturer’s protocol ‘small sample protocol II’, starting from total RNA (ranging from ?4 ng pooled oocytes to 100 ng cumulus cells) and hybridized to HGU133 plus 2.0 GeneChip pan-genomic oligonucleotide arrays (Affymetrix, Santa Clara, CA, USA). HG-U133 plus 2.0 arrays contain 54 675 sets of oligonucleotide probes (probeset) which correspond to ≈39 000 unique human genes or predicted genes. The GeneChip system is a robust microarray system with more than 3000 publications using this technology (http://www.affymetrix.com/community/publications/index. affx), little lab-to-lab variability and a good accuracy and precision (Irizarry et al., 2005). Primary image analysis of the arrays was performed by using GeneChip Operating Software 1.2 (GCOS) (Affymetrix), resulting in a single value for each probeset (signal). Data from each different array experiment were scaled to a target value of 100 by GCOS using the ‘global scaling’ method. The dataset was floored to 2, that is, each signal value under 2 was given the value 2.

Statistical analysis Samples were analysed using a pairwise comparison using the GCOS 1.2 software. Interestingly, this algorithm provides the information of whether a gene is expressed with a defined confidence level or not (detection call). This ‘call’ can be either ‘present’ when the perfect match probes are significantly more hybridized than the mismatch probes, ‘absent’ when both perfect match and mismatch probes display a similar fluorescent signal or ‘marginal’ when the probeset complies neither to the ‘present’ nor to the ‘absent’ call criteria. A gene was denoted as exclusively expressed in one category when this gene displayed a detection call ‘present’ in this given category and ‘absent’ or ‘marginal’ in all the other three categories. A gene was considered as over- or underexpressed in a category when all the three possible pairwise comparisons showed a significant change in P-value (P ≤ 0.01) according to the GCOS 1.2 software and a ratio ≥ 3 or ≤ 0.333 for the genes increased or decreased, respectively. We also determined a list of genes whose expression progressively increased during oocyte maturation by selecting the probesets with a significant increase according to the GCOS 1.2 algorithm and matching the following ratio constraints: cumulus < GV (with GV/cumulus ≥ 3), GV < MI (MI/GV ≥ 1.73) and MI < MII (MII/MI ≥ 1.73), where cumulus, GV, MI and MII stand for signal values in these samples. Note that 1.73 × 1.73 = 3. Gene annotation was based on Unigene Build 176. For hierarchical clustering, data were filtered [15 000 genes with a significant expression (‘present’ detection call) in at least one sample and with the highest variation coefficient], log transformed, median centred and processed with the CLUSTER and TREEVIEW software packages with the average linkage method and an uncentred correlation (Eisen et al., 1998). Gene ontology (GO) annotations (http://www. geneontology.org/) were obtained and analysed via the Fatigo website tool (http://www.fatigo.org/) using level-three annotations. In some cases, we used the GO annotations downloaded from the Affymetrix NetAffx database. Genes with a role in cell-to-cell communication function were obtained by filtering the genes based on the following criteria: cellular component comprising the terms ‘membrane’ or ‘extracellular’. Bibliographical search was carried out in Pubmed using boolean logic. For each gene G present in Tables I and II, using its Hugo-approved abbreviation or any of its aliases, we looked for publication matching the query ‘gene G AND (gamete or ‘germ cell’ or ‘germ cells’ or egg or eggs or oocytes or oocyte or meiosis)’ for genes found preferentially expressed in oocytes, and the query ‘gene G AND (gamete or ‘germ cell’ or ‘germ cells’ or egg or eggs or oocytes or oocyte or cumulus or granulosa)’ for genes overexpressed in cumulus cells. The expression, including signal values, of all genes cited in Tables I and II can be examined on our website (http://amazonia.montp. inserm.fr/the_human_oocyte_transcriptome.html) as online supplemental data. The expression of these genes in various normal tissue transcriptome datasets, including ovarian and testis samples, is provided through the Amazonia! database Web page (unpublished data).

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Results Identification of genes expressed in human oocytes and cumulus cells Total cRNA was synthesized from pools of GV-, MI- or MIIstage oocytes, or cumulus cells, then labelled and hybridized to pan-genomic oligonucleotide microarrays. We analysed the detection call (GCOS 1.2 software) of all 54 675 probes in oocyte and cumulus samples. Oocytes express in average 8728 genes. The lowest number of genes expressed was found in MII oocytes (n = 5633) and highest in GV oocytes (n = 10 869)


Gene-expression profiling of oocytes

Table I. Genes significantly overexpressed in oocytes Gene symbol Gamete markers DAZL DDX4/VASA DPPA3/STELLA Gene title Fold ratio Probeset Chromosomal location chr3p24.3 chr5p15.2p13.1 chr12p13.31 Species References

Deleted in azoospermia like DEAD (Asp-Glu-Ala-Asp) box polypeptide 4 Developmental pluripotency-associated 3

976.3 1181.5 10389.1

206588_at 221630_s_at 231385_at

Homo sapiens Homo sapiens Homo sapiens

Nishi et al. (1999), Cauffman et al. (2005) Castrillon et al. (2000) Saitou et al. (2002)

Maturation-promoting factor and related factors CCNB1 Cyclin B1 CCNB2 Cyclin B2 CDC2 Cell division cycle 2, G1 to S and G2 to M CDC25A Cell division cycle 25A CDC25B Cell division cycle 25B CDC25C Cell division cycle 25C Spindle checkpoint BUB1 BUB1B / BUBR1 CENPA CENPE CENPH MAD2L1/MAD2 BUB1 budding uninhibited by benzimidazoles 1 homologue BUB1 budding uninhibited by benzimidazoles 1 homologue beta Centromere protein A Centromere protein E Centromere protein H MAD2 mitotic arrest deficient-like 1

157.0 308.8 18.4 90.8 9.7 75.2 20.6 117.8 88.1 113.9 14.3 53.5

228729_at 202705_at 210559_s_at 1555772_a_at 201853_s_at 205167_s_at 209642_at 203755_at 204962_s_at 205046_at 231772_x_at 203362_s_at

chr5q12 chr15q22.2 chr10q21.1 chr3p21 chr20p13 chr5q31 chr2q14 chr15q15 chr2p24-p21 chr4q24-q25 chr5p15.2 chr4q27

Homo sapiens Bos taurus (cow) Mus musculus (mouse) Mus musculus (mouse) Mus musculus (mouse) Capra hircus (goat) Homo sapiens Xenopus laevis (frog) Mus musculus (mouse) Mus musculus (mouse) NR Mus musculus (mouse)

Heikinheimo et al. (1995) Wu et al. (1997) Kalous et al. (2005) Wickramasinghe et al. (1995) Lincoln et al. (2002) Gall et al. (2002) Steuerwald et al. (2001)

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Abrieu et al. (2000) Schatten et al. (1988) Duesbery et al. (1997) Wassmann et al. (2003)

APC/C complex, securins and cohesions ANAPC1/APC1 Anaphase-promoting complex subunit 1 ANAPC10/APC10 Anaphase-promoting complex subunit 10 CDC20 cell division CDC20 cycle 20 PTTG1 Pituitary tumourtransforming 1 PTTG3 Pituitary tumourtransforming 3 STAG3 Stromal antigen 3 Epigenetic remodelling DNMT1 DNA (cytosine-5-)methyltransferase 1 DNMT3B DNA (cytosine-5-)methyltransferase 3 beta HDAC9 Histone deacetylase 9 H1FOO H1 histone family, member O, oocyte specific HCAP-G Chromosome condensation protein G Meiosis, miscellaneous AKAP1 A kinase (PRKA) anchor protein 1 MCM3 MCM3 minichromosome maintenance deficient 3 MOS v-mos Moloney murine sarcoma viral oncogene homologue SPAG16 Sperm-associated antigen 16 TUBB4Q Tubulin, beta polypeptide 4, member Q FBXO5/EMI1 F-box protein 5 AURKC Aurora kinase C

6.8 7.0 273.9 58.2 50.4 76.9 49.8 24.2 342.6 414.5 260.1

218575_at 207845_s_at 202870_s_at 203554_x_at 208511_at 219753_at 201697_s_at 220668_s_at 1552760_at 1553064_at 218663_at

chr2q12.1 chr4q31 chr1p34.1 chr5q35.1 chr8q13.1 Hs.323634 chr19p13.2 chr20q11.2 chr7p21.1 chr3q21.3 chr4p15.33

NR NR Mus musculus (mouse) Mus musculus (mouse) NR Homo sapiens Homo sapiens Homo sapiens Mus musculus (mouse) Homo sapiens NR Prieto et al. (2004) Huntriss et al. (2004) Huntriss et al. (2004) De La Fuente et al. (2004) Tanaka et al. (2003) Chang et al. (2004) Yao et al. (2003)

72.1 21.2 72.5 393.4 866.5 414.2 49.1

210625_s_at 201555_at 221367_at 240898_at 211915_s_at 234863_x_at 211107_s_at 221332_at 206176_at

Hs.78921 chr6p12 chr8q11 chr2q34 chr4q35 chr6q25-q26 chr19q13.43 chrxp11.2 chr6p24-p23

Rattus norvegicus (rat) Xenopus laevis (frog) Homo sapiens NR NR Mus musculus (mouse) NR Homo sapiens Mus musculus (mouse)

Carr et al. (1999) Kubota et al. (1995) Pal et al. (1994)

Paronetto et al. (2004)

Extracellular matrix, growth factors, cell surface, signalling BMP15 Bone morphogenetic 31.0 protein 15 BMP6 Bone morphogenetic 38.3 protein 6

Aaltonen et al. (1999) Lyons et al. (1989)


S.Assou et al. Table 1. Continued Gene symbol GDF9 FGFR2 FGF9 FGF14 KIT IL4 TNFSF13 / APRIL ERBB4 FZD3 GPR37 GPR39 GPR51 GPR126 GPR143 GPR160 ZP1 ZP2 ZP3 ZP4 SLC5A11 SOCS7 Transcription factors SOX15 SOX30 OTX2 FOXR1 Imprinted gene MEST Apoptosis BNIP1 BIRC5 BCL2L10 Gene title Growth differentiation factor 9 Fibroblast growth factor receptor 2 Fibroblast growth factor 9 (glia-activating factor) Fibroblast growth factor 14 v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homologue Interleukin 4 Tumour necrosis factor superfamily, member 13 v-erb-a erythroblastic leukemia viral oncogene homologue 4 Frizzled homologue 3 G protein-coupled receptor 37 (endothelin receptor type B like) G protein-coupled receptor 39 G protein-coupled receptor 51 G protein-coupled receptor 126 G protein-coupled receptor 143 G protein-coupled receptor 160 Zona pellucida glycoprotein 1 (sperm receptor) Zona pellucida glycoprotein 2 (sperm receptor) Zona pellucida glycoprotein 3 (sperm receptor) Zona pellucida glycoprotein 4 Solute carrier family 5 (sodium/glucose cotransporter), member 11 Suppressor of cytokine signalling 7 SRY (sex-determining region Y)-box 15 SRY (sex determining region Y)-box 30 Orthodenticle homologue 2 (Drosophila) Forkhead box R1 Mesoderm-specific transcript homologue BCL2/adenovirus E1B 19kDa interacting protein 1 Baculoviral IAP repeatcontaining 5 (survivin) BCL2-like 10 (apoptosis facilitator) Fold ratio 83.0 8.4 43.8 28.1 Probeset 221314_at 208228_s_at 206404_at 221310_at 205051_s_at 207538_at 210314_x_at 206794_at 219683_at 209631_s_at 229105_at 209990_s_at 213094_at 206696_at 223423_at 237335_at 207933_at 204148_s_at 231756_at 237254_at 2265772_at Chromosomal location chr5q31.1 chr10q26 chr13q11-q12 chr13q34 chr4q11-q12 chr5q31.1 chr17p13.1 chr2q33.3-q34 chr8p21 chr7q31 chr2q21-q22 chr9q22.1 chr6q24.1 chrxp22.3 chr3q26.2 11q12.2 chr16p12 chr7q11.23 chr1q43 chr16p-p11 chr17q12 Species Homo sapiens Mus musculus (mouse) NR NR Homo sapiens NR NR NR NR NR Liu (2006) References Aaltonen et al. (1999) Haffner-Krausz et al. (1999)

52.5 131.6 32.3 17.9 64.4 1234.0 5.7 11.7 94.1 11.3 86.6 1558.8 87.6 52.2 144.7 26.3

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NR NR NR NR NR Homo sapiens Homo sapiens Homo sapiens Homo sapiens NR NR Lefievre et al. (2004) Hinsch et al. (1998) Grootenhuis et al. (1996) Eberspaecher et al. (2001)

127.2 618.5 5022.8 344.1 39.2

206122_at 207678_s_at 242128_at 237613_at 202016_at

chr17p13 chr5q33 chr14q21-q22 chr11q23.3 chr7q32

NR NR NR NR Homo sapiens Salpekar et al. (2001)

20.8 23.2 623.3

207829_s_at 202094_at 236491_at

chr5q33-q34 chr17q25 chr15q21

NR NR Mus musculus (mouse) Burns et al. (2003)

NR, not reported. A Pubmed search using each synonym for this gene (as listed by LocusLink) and one of the following keywords, oocyte, germ cell, gamete, egg, meiosis, did not retrieve any significant result. Expression values of all the genes described in this table can be accessed on our website (see Materials and methods) or can be downloaded as supplemental data.


Gene-expression profiling of oocytes

Table II. Genes significantly overexpressed in cumulus oophorus cells Gene symbol Gene title Fold ratio Probeset Chromosomal location Species References

Hormone and hormone receptors LHCGR Luteinizing hormone/ choriogonadotrophin receptor PGRMC1 Progesterone receptor membrane component 1 PGRMC2 Progesterone receptor membrane component 2 STAR Steroidogenic acute regulator GNRH1 Gonadotrophin-releasing hormone 1 (luteinizing-releasing hormone) Prostaglandins biosynthesis PTGS1 Prostaglandin–endoperoxide synthase 1 PTGS2/COX-2 Prostaglandin–endoperoxide synthase 2 PTGIS PTGER2 Prostaglandin I2 (prostacyclin) synthase Prostaglandin E receptor 2

47.4 13.4 7.4 33.0 26.7

207240_s_at Chr2p21 201121_s_at chrxq22-q24 213227_at Chr4q26

NR Rattus norvegicus (rat) Park and Mayo (1991) Homo sapiens Homo sapiens Homo sapiens Tokuyama et al. (2001) Devoto et al. (2001) Leung et al. (2003)

204548_at Chr8p11.2 207987_s_at 8p21-p11.2

5.0 18.7 10.8 5.4 9.3 10.6 19.4 7.2 5.2 34.8

215813_s_at Chr9q32-q33.3 NR 204748_at Chr1q25.2-q25.3 Rattus norvegicus (rat) Sirois et al. (1993), Davis et al. (1999) 208131_s_at Chr20q13.11–13 NR 206631_at Chr14q22 Homo sapiens Narko et al. (2001) 203304_at 202701_at 235275_at 225144_at Chr10p12.3–11.2 NR

BMP and BMPR superfamily BAMBI BMP and activin membrane-bound inhibitor homologue BMP1 Bone morphogenetic protein 1 BMP8B Bone morphogenetic protein 8b BMPR2 Bone morphogenetic protein receptor, type II INHA Inhibin, alpha INHBA Inhibin, beta A activin A, activin AB alpha polypeptide TNF and TNFR superfamily TNFSF11/OPGL/ Tumour necrosis factor (ligand) RANKL superfamily, member 11 TNFRSF1A/TNF-R Tumour necrosis factor receptor superfamily, member 1A TNFRSF10B/DR5 Tumour necrosis factor receptor superfamily, member 10b TNFRSF12A Tumour necrosis factor receptor superfamily, member 12A Complement CFHL1 C7 IF CFH C1S C1R CLU Secreted (other) CXCL1 IL1B IL8 TIMP1 TIMP3 PAPPA PTX3 CD molecules CD24 CD44 CD47 CD58 Complement factor H-related 1 Complement component 7 I factor (complement) Complement factor H Complement component 1, s subcomponent Complement component 1, r subcomponent Clusterin (complement lysis inhibitor) Chemokine (C-X-C motif) ligand 1 Interleukin 1, beta Interleukin 8 Tissue inhibitor of metalloproteinase 1 (erythroid-potentiating activity, collagenase inhibitor) Tissue inhibitor of metalloproteinase 3 (Sorsby fundus dystrophy, pseudoinflammatory) Pregnancy-associated plasma protein A, pappalysin 1 Pentaxin-related gene, rapidly induced by IL-1 beta CD24 antigen CD44 antigen CD47 antigen CD58 antigen/LFA3

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Chr8p21 Chr1p35-p32 Chr2q33-q34

NR NR Rattus norvegicus (rat) Vitt et al. (2002) Homo sapiens Homo sapiens Jaatinen et al. (1994) Rabinovici et al. (1992)

210141_s_at Chr2q33-q36 210511_s_at Chr7p15-p13

79.9 14.9 5.9 4.6




207643_s_at chr12p13.2 209295_at chr8p22-p21

218368_s_at chr16p13.3

105.8 135.8 34.7 40.0 28.0 9.1 140.9 8.0 11.7 12.9 25.3 19.9 54.3 25.4

215388_s_at 202992_at 203854_at 213800_at 208747_s_at

chr1q32 chr5p13 chr4q25 chr1q32 chr12p13

NR NR NR NR NR NR Rattus norvegicus (rat) Hurwitz et al. (1996) Homo sapiens Homo sapiens Homo sapiens Homo sapiens NR Homo sapiens Homo sapiens Stanger et al. (1985) Zhang et al. (2005) Karstrom-Encrantz et al. (1998) de los Santos et al. (1998) Runesson et al. (2000) O’Sullivan et al. (1997)

212067_s_at chr12p13 208791_at 204470_at chr8p21-p12 chr4q21

39402_at chr2q14 202859_x_a chr4q13-q21 t 201666_at chrxp11.3–23 201150_s_at chr22q12.3 224942_at 206157_at chr9q33.2 chr3q25

126.9 17.0 4.6 18.6

208650_s_at 212063_at 213857_s_at 216942_s_at

chr6q21 chr11p13 chr3q13.1 chr1p13

Homo sapiens NR NR Homo sapiens

Hourvitz et al. (2000) Hattori et al. (1998)


S.Assou et al. Table II. Continued Gene symbol CD59 CD63 CD74 CD81 CDW92 CD99 CD151 CD200 Gene title CD59 antigen p18–20 CD63 antigen CD74 antigen CD81 antigen CDW92 antigen CD99 antigen CD151 antigen CD200 antigen Fold ratio Probeset 16.4 7.7 5.9 6.1 4.7 4.1 8.4 22.9 58.2 5.5 43.2 9.8 38.5 83.8 13.2 5.4 7.5

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Chromosomal location chr11p13 chr12q12-q13 chr5q32 chr11p15.5 chr9q31.2 chrxp22.32 chr11p15.5 chr3q12-q13 chr21q21.2 chr5q14.3 chr7p12.1 chr5q23.1 chr15q21.1 chr3q21-q25 chrxq22 chr15q24.3 chrxp11.4 Species References

228748_at 200663_at 209619_at 200675_at 224596_at 201029_s_at 204306_s_at 209583_s_at 222162_s_at 211571_s_at 206805_at 225660_at 226492_at 215034_s_at 209108_at 200973_s_at 209656_s_at

NR Rattus norvegicus (rat) Espey and Richards (2002) NR NR NR Homo sapiens Gordon et al. (1998) NR NR Mus musculus (mouse) Russell et al. (2003) Mus musculus (mouse) Russell et al. (2003) NR NR NR NR

Membrane bound (other) ADAMTS1 A disintegrin-like and metalloprotease (reprolysin type) with thrombospondin type 1 motif, 1 CSPG2 Chondroitin sulfate proteoglycan 2 (versican) SEMA3A Semaphorin 3A SEMA6A Semaphorin 6A SEMA6D Semaphorin 6D TM4SF1 Transmembrane 4 superfamily member 1 TM4SF6 Transmembrane 4 superfamily member 6 TM4SF8 Transmembrane 4 superfamily member 8 TM4SF10 Transmembrane 4 superfamily member 10 Transcription factors CEBPB CCAAT/enhancer binding protein (C/EBP), beta GATA6 GATA-binding protein 6 Other PRDX2 PRDX4 PRDX5 PRDX6 CDKN1A CDKN1B CTSK Peroxiredoxin 2 Peroxiredoxin 4 Peroxiredoxin 5 Peroxiredoxin 6 Cyclin-dependent kinase inhibitor 1A (p21, Cip1) Cyclin-dependent kinase inhibitor 1B (p27, Kip1) Cathepsin K (pycnodysostosis)

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7.4 56.8 6.2 31.2 5.3 23.2 17.0 17.0 11.8

212501_at 210002_at 39729_at 201923_at 1560587_s_at 200844_s_at 202284_s_at 209112_at 202450_s_at


Sus scrofa (pig)

Gillio-Meina et al. (2005) Suzuki et al. (1996) Leyens et al. (2004) Leyens et al. (2004) Leyens et al. (2004) Leyens et al. (2004) Jirawatnotai et al. (2003)

chr18q11.1–11.2 Homo sapiens chr19p13.2 chrxp22.11 chr11q13 chr1q25.1 chr6p21.2 chr12p13.1-p12 chr1q21 Bos taurus (cow) Bos taurus (cow) Bos taurus (cow) Bos taurus (cow) Mus musculus (mouse)

Mus musculus (mouse) Robker and Richards (1998) Rattus norvegicus (rat) Oksjoki et al. (2001)

NR, not reported. A Pubmed search using each synonym for this gene (as listed by LocusLink) and one of the following keywords, oocyte, germ cell, gamete, egg, cumulus, granulosa, did not retrieve any significant result. Expression values of all the genes described in this table can be accessed on our website (see Materials and methods) or can be downloaded as supplemental data.

Table III. Genes expressed in oocytes and cumulus cells Germinal vesicle Expressed genesa Exclusive genesb Genes overexpressedc Genes underexpressedd

Metaphase I 9682 326 4 5

Metaphase II 5633 234 444 803

Cumulus 10 610 1829 2600 1514

10 869 739 104 6

Genes (based on Unigene Build 176) that had at least one probe with a detection call ‘present’. b Genes (based on Unigene Build 176) that had a detection call ‘present’ only in one sample category. c Genes significantly overexpressed in one sample compared with all other samples, with a fold ratio of at least 3. d Genes significantly underexpressed in one sample compared with all other samples, with a fold ratio of at least 0.333.

and the oocyte samples as illustrated by dispersed scatter plots and low correlation coefficients (0.39–0.50) (Figure 1A). We visualized the respective gene expressions across all samples using hierarchical clustering. Average linkage hierarchical clustering on 15 000 genes showed that oocytes cluster together, demonstrating a common gene expression, but are only distantly related to cumulus cells (Figure 1B). These results highlight that feminine germ cells and their nourishing neighbour cumulus cells display very different expression profiles, in agreement with a very different but complementary biological function and with cell lineage disparity. Specific transcription program in each sample type We next examined which genes were specific to each sample category, using two different approaches. First, we determined the genes that were only detected in one sample and not in the three other samples. These genes were called ‘exclusively expressed’ (Table III). As expected, cumulus cells have the largest number of exclusively expressed genes (n = 1829), likely

(Table III). We found that expression variations between MI, MII and GV samples were low as illustrated by tight scatter plots and high correlation coefficients (0.63–0.92), as opposed to a marked difference of expression between the cumulus sample 1710

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Figure 1. Global gene-expression variation. (A) Scatter plots. Each sample was plotted against all other samples to visualize the expression variation. Only the 26 662 probes with at least one sample with a ‘present’ detection call were included. All signal values were floored to 2. Red circles, probes overexpressed in the sample specified on the left side; green circles, probes overexpressed in the sample specified at the bottom of each plot; grey circles, probes whose expression does not vary significantly between the two samples. For each couple of sample, the Pearson’s correlation coefficient was computed (r), based on the signal of probes with at least one sample with a ‘present’ detection call. GV, germinal vesicle; MI, metaphase I; MII, metaphase II. (B) Hierarchical clustering. The expression signatures of oocytes and cumulus cells were visualized by hierarchical clustering on the 15 000 probesets with the highest variation coefficient. The colours indicate the relative expression levels of each gene, with red indicating an expression above median, green indicating expression under median and black representing median expression. Cluster (a) was a group of genes overexpressed in oocyte (GV–MI–MII), including genes such as DAZL, GDF9, BMP15, ZP1,2,3,4. Cluster (b) was group of genes overexpressed in cumulus cells, including genes such as CD24, Activin A, PAPPA, TNTSF11, LHCGR and INHA.


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because they display a very different transcriptome as compared with oocytes (n = 234–739). Second, we considered the probes that were over- or underexpressed in one sample compared with all three other samples, with a fold ratio of at least 3. Again, cumulus cells show the largest lists of genes, overexpressing 2600 and underexpressing 1514 genes as compared with oocytes. Using this rather stringent criteria (fold change of at least 3 between a given sample and the three other samples), we found very few genes over- or underexpressed in GV and MI oocytes. This shows that very few genes modify their expression between GV and MI oocytes, as opposed to MII oocytes that overexpress more than 400 genes and underexpress more than 800. We compared functional GO annotations of overexpressed genes versus underexpressed genes in oocytes and cumulus cells. We observed that certain functional annotations were more represented in either oocytes or cumulus cells (Figure 2). There were significantly more genes involved in ‘response to stimulus’, ‘secretion’ and ‘extracellular matrix’ in cumulus cells, suggesting that cumulus cells are more active in cell-tocell communication processes. Conversely, genes annotated ‘reproduction’, ‘ubiquitin ligase complex’, ‘microtubule-associated complex’, ‘microtubule motor activity’, ‘nucleic acid binding’ and ‘ligase activity’ were significantly more frequently associated with genes overexpressed in oocytes, in agreement with the major processes involved in meiosis and implying microtubules’ attachment to chromosomes and the ubiquitin ligase complex APC/C regulation.

Whole-genome transcriptome of oocytes We observed that 1514 genes were expressed with at least a threefold increase in oocytes, that is, underexpressed in cumulus cells when compared with oocytes. Selected genes are highlighted in Table I, which is also available as Web supplemental data, including the expression histogram for each gene (http:// amazonia.montp.inserm.fr/the_human_oocyte_transcriptome. html). This list includes genes already recognized as specifically expressed in male and female germinal cells in mammals, such as DAZL, the RNA helicase DDX4/VASA or DPPA3/STELLA (full names are listed in Table I). Numerous well-recognized actors of meiosis were highly expressed in oocytes: the components of the maturation-promoting factor (MPF) (CDC2/CDK1, CCNB1 and CCNB2), CDC25 phosphatases (CDC25A, CDC25B and CDC25C), components of the spindle checkpoint (BUB1, BUBR1, MAD2L1/MAD2, CENP-A and CENP-E), CDC20, which is a component of the anaphase-promoting complex (APC/ C) and a downstream target, the meiosis-specific sister chromatid arm cohesin STAG3 (Figure 3A). As expected, we observed the overexpression of genes known to be specific to oocytes such as the Zona Pellucida genes (ZP1, ZP2, ZP3 and ZP4), members of the transforming growth factor (TGF)-β superfamily such as growth differentiation factor 9 (GDF9), bone morphogenetic protein 6 and 15 (BMP6 and BMP15), FGFR2, the chromatin remodelling molecules histone deacetylase HDAC9 and the oocyte-specific H1 histone H1FOO (Figure 3B). Thus, the data are in complete agreement with the published studies.

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Figure 2. Differential gene ontology (GO) annotations between oocytes and cumulus cells. We compared the frequency of level-three GO annotations of genes overexpressed in oocytes to those of genes overexpressed in cumulus cells. The statistical analysis was made using the Fatigo website (http://www.fatigo.org/) using Unigene cluster ID. Histograms show the percentage of genes with the specified GO annotation in the group of genes overexpressed in oocytes (purple) or in cumulus (green).


Gene-expression profiling of oocytes

Interestingly, we show here that many genes, previously found expressed in oocytes in various animal models, are indeed highly expressed in human oocytes. Hence, our microarray data are of sufficient scope and accuracy to pave the way to a systematic gene-expression exploration of oocyte and cumulus transcriptome. We observed that several genes previously reported to be expressed in male germ cells are also highly expressed in human oocytes, in all maturation stages, such as aurora kinase C (AURKC), SOX30 or sperm associated antigen 16 (SPAG16/ PF20). Still, the majority of the genes we found overexpressed in oocytes were not yet reported to be associated with gamete biology. Some of these previously unrecognized ‘oocyte genes’ are listed in Table I and comprise several functional categories. After fertilization, the spindle checkpoint inhibition is released and the APC/C complex degrades the securins, resulting in an entry into anaphase. We found that genes of the centromere protein CENPH that interacts with the spindle checkpoint, and the anaphase-promoting complex subunits ANAPC1 and ANPC10 are highly expressed in oocytes. Moreover, the securing genes PTTG1 and PTTG3 are 58 and 50 times more expressed in oocytes than in cumulus cells, respectively. We found several growth factors and growth factor receptors significantly overexpressed in oocytes (IL-4, FGF9, FGF14 and TNFSF13/APRIL), transcription factors (SOX15, OTX2 and FOXR1), three anti-apoptosis molecules (BCL2L10, BNIP1 and BIRC5/Survivin) and the glucose transporter (SLC5A11). Whole-genome transcriptome of cumulus cells Conversely, we observed that 2600 genes are overexpressed in cumulus cells compared with all three oocyte samples. The cumulus sample we studied was obtained from an MII oocyte during ovulation. First, we observed a marked expression of the LH receptor LHCGR in cumulus cells, which primes these cells to respond to the LH surge. Second, we observed that genes overexpressed in MII cumulus cells comprise the main genes that are induced by the LH surge during ovulation (Table II). We observed a very high expression of the progesterone receptors PGRMC1 and PGRMC2, and the steroidogenic acute regulator (STAR) that are induced by LH. Similarly, we found that eicosanoids biosynthesis enzymes, such as the two prostaglandin endoperoxide synthetase (PTGS1) and PTGS2/COX2 and the prostaglandin I2 (prostacyclin) synthase (PTGIS), the prostaglandin receptor (PTGER2) and two downstream effectors of this signalling pathway, interleukin IL1beta and pentaxin-related 3 (PTX3), are also overexpressed in cumulus cells. These genes were mostly described in animal models, and we show here for the first time that the RNA expression of these genes is also highly induced in human cumulus cells obtained after ovulation. Two chemokines are highly produced by cumulus cells, CXCL1/ GRO-alpha and IL8, in agreement with the invasion of the granulosa by leucocytes during ovulation. Interestingly, the metalloprotease ADAMTS1, as well as its target versican whose cleavage has been shown to contribute to the proteolytic disintegration of the cumulus matrix, was also highly induced. The transcription factor CEBPB, induced after the gonadotrophin surge and after mediating the up-regulation of inhibin alpha (INHA), is found overexpressed in our post-stimulation cumulus 1713

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Figure 3. Schematic representation of selected genes involved in meiosis and cumulus–oocyte complex (A) Meiosis. Actors of meiosis in oocytes: components of the maturation-promoting factor (MPF), components of the spindle checkpoint, components of the anaphase-promoting complex (APC/C), the downstream targets such as the securin PTTG3 and regulators. Genes in pink are up-regulated in oocytes. Genes that are specific to meiosis are highlighted by an orange hexagon. Genes in white did not display a significant modification in gene expression between oocytes and somatic cells (cumulus cells). See Table I for full name and references. (B) Cumulus–oocyte complex. Genes overexpressed in oocytes (pink) or overexpressed in cumulus (green) that are involved in the cumulus–oocyte complex interactions. Oocyte genes included members of the TGF-β superfamily such as growth differentiation factor 9 (GDF9), fibroblast growth factor 9 and 15 (FGF9, 15), bone morphogenetic protein 6 and 15 (BMP6, 15). Conversely, in cumulus cells, the genes overexpressed included hormonal receptors such as luteinizing hormone/choriogonadotrophin receptor (LHCGR), progesterone receptor membrane component 1 and 2 (PGRMC1, 2), interleukin IL1beta, chemokines (IL8) and CD24 antigen, inhibin alpha (INHA), activin A (INHBA). Genes in red are up-regulated in the oocytes compared with cumulus cells. Genes in green are up-regulated in the cumulus cells compared with oocytes. Genes shown in blue are expressed in oocytes and cumulus cells such as gap junction protein alpha (GJA1). See Table II for complete list of full names and references.

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cells. Accordingly, INHA and INHBA/activin A are 5 and 34 times more expressed in cumulus cells than in oocytes, respectively. Another transcription factor characteristic of granulosa cells, GATA6, is also highly overexpressed in comparison with oocytes. We observed the up-regulation of peroxiredoxins (PRDX2, PRDX4, PRDX5 and PRDX6), which are part of a family of peroxidases involved in antioxidant protection and cell signalling and recently reported in bovine ovaries (Leyens et al., 2004), as well as a lysosomal cysteine proteinase, cathepsin K (CTSK). Gene codings for protein found in follicular fluid such as PAPPA are also found overexpressed in cumulus cells. Thus, genes found overexpressed in cumulus cells by our whole-genome transcriptome analysis recapitulate previous expression studies on post-LH surge granulosa cells carried out in various species. Considering that cell-to-cell communication genes are a functional category that plays an essential role in the maturation of the cumulus–oocyte complex, we focused on genes filtered on the GO cellular localization annotations ‘membrane’ or ‘extracellular’ (see Materials and methods); 615 genes passed this filter. The most noticeable genes from this list were ligands (BMP1 and BMP8B) or receptors (BAMBI and BMPR2) from the TGF-β superfamily, ligands (TNFSF11/OPGL/RANKL) or receptors from the tumour necrosis factor receptor (TNFR) superfamily (TNFRSF1A/TNF-R, TNFRSF10B/DR5 and TNFRSF12A), components of the complement (CFHL1, C7, IF, CFH, C1S and C1R) and one inhibitor of the complement system (CLU), semaphorins (SEMA3A, SEMA6A and SEMA6D), tetraspanins (TM4SF1, TM4SF6, TM4SF8 and TM4SF10) and various CD members (CD24, CD44, CD47, CD58, CD59, CD63, CD74, CD81, CDW92, CD99, CD151 and CD200). Table II lists these genes, and references key publications relevant to female reproductive biology. Furthermore, components, such as connexin 43, of the cumulus–oocyte complex signalling pathways were retrieved. We found that this connexin was expressed at a high signal in both cumulus cells and in all oocyte categories, in line with its extracellular domains that provide strong and specific homophilic adhesion properties. Most interestingly, many of these genes were never before highlighted as expressed in granulosa cells. Differences in gene expression variation during oocyte maturation An important feature of our work is that we established a transcriptome for each of the three stages of oocyte maturation: GV, MI and MII. We were thus able to identify genes whose expression gradually increased during oocyte maturation (see Materials and methods). Fifty-two probesets were retrieved, including the phosphatase CDC25A, PCNA and SOCS7. However, most of the resulting genes are poorly characterized or only predicted coding sequences. All these genes are candidate markers for oocyte cytoplasmic and/or nuclear maturation (Figure 4). Discussion We undertook to establish the molecular transcriptome phenotype of the human oocyte and its surrounding cumulus cells by using oligonucleotide microarrays covering most of the genes 1714

identified in humans. Relying on a recently developed technique of double in vitro transcription, which amplifies more than 100 000 times the initial RNA input, we were able to establish the expression profile of pooled oocytes from distinct maturation stages and from cumulus cells of MII oocytes. Thus, for the first time, we report in human samples the variation of gene expression during oocyte nuclear maturation, and that of its neighbouring cumulus cells, at whole-genome scale. A global analysis of the number of genes detected in each sample category showed a progressive decrease of the number of genes expressed during oocyte nuclear maturation, with the lowest number of genes expressed found in MII oocytes compared with GV or MI oocytes. This is in agreement with the significant decrease, both in quantity and in diversity, of maternal RNAs observed in mouse oocytes (Bachvarova et al., 1982; Wang et al., 2004). Indeed, GV and MI oocytes over- or underexpressed few genes compared with the other samples (Table III), reflecting a very similar expression profile. By contrast, MII oocytes differed markedly, underexpressing specifically many genes (n = 803), which may be explained by the RNA content decrease. In addition, MII oocytes overexpress 444 genes, which may be because of a specific expression pattern related to the near completion of meiosis or to the longer in vitro incubation time secondary to the IVF procedure (21 or 44 h after insemination). Hierarchical clustering demonstrated that oocyte expression profiles were markedly different from those of cumulus cells (Figure 1). We compared the oocyte samples with the cumulus cells and we found that 1514 genes were up-regulated in oocytes, whereas 2600 genes were up-regulated in cumulus cells. Analysing these lists of genes, we observed that oocytes markedly overexpressed genes involved in meiosis process such as MPF, APC/C and spindle checkpoint complexes. Full completion of meiosis is only accomplished after fecundation because metaphase exit is prevented by the activity of cytostatic factor (CSF) that will only be relieved by gamete fusion. As expected, EMI1, which was recently found to be part of CSF, is highly expressed in all oocyte samples, as well as MOS. We also found that the two major cyclin-dependent kinase inhibitors CDKN1A/p21 and CDKN1B/p27, acting at the G1-S transition, were found markedly down-regulated in oocytes as compared with cumulus cells (Table II). The separation of sister chromatids at the metaphase-to-anaphase transition is activated by proteases called separases, which are activated by the destruction of the inhibitory chaperone securins. Interestingly, we found two securins highly expressed in all oocyte pools: PTTG1 and PTTG3. These securins are expressed at least 15 times more in oocytes than in cumulus cells, CD34+ sorted bone marrow cells, B lymphocytes or mesenchymal stem cells (data not shown). PTTG1 expression was reported in mice oocytes, but not human oocytes, whereas PTTG3-marked expression in oocytes was not previously noted. Considering that post-ovulation oocytes are germinal cells that have just escaped the very long meiosis I arrest and are due to the second meiosis arrest, securins, that are crucial to these processes, must be expressed at a high level. We propose that PTTG1 and PTTG3 play this role in oocytes (Figure 3). The metaphase-to-anaphase transition is associated with a rapid

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Figure 4. Expression histograms of selected genes in oocytes and cumulus cells. Histograms show signal values of 20 genes that are differentially expressed between oocyte (purple) and cumulus cells (green). Gene expression is measured by pan-genomic HG-U133 Plus 2.0 Affymetrix oligonucleotides microarrays, and the signal intensity for each gene is shown on the y-axis as arbitrary units determined by the GCOS 1.2 software (Affymetrix). GV, germinal vesicle; MI, metaphase I; MII, metaphase II; C, cumulus.

drop of securin protein level mediated by the proteases of the separase family. Degradation of securins leads to the destruction of cohesins, a ring structure formed by a multisubunit complex that holds sister chromatids together. We confirm the specific up-regulation of the meiosis-specific cohesin subunit STAG3 in human oocytes, whereas the mitotic cohesin STAG2 is markedly down-regulated in oocytes compared with cumulus cells or other somatic cells (data not shown). Thus, as for the securins, two homologues of an essential component of the cell division machinery are differentially expressed between human oocytes and somatic cells, implying that one homologue (the cohesin STAG2) is operating during mitosis, whereas the other homologue (the cohesin STAG3) is replacing the first one during the very specialized cell division process of meiosis. The high conservation of many of the molecular determinants of gametogenesis in the animal kingdom, sometimes from yeast to mammals, suggests that genes found in mammals’ oocytes should be expressed in human oocytes. We provide here the unambiguous demonstration for many genes that they are indeed strongly overexpressed in the three pools of oocytes (Table I). These genes include CENPA, CENPE, PTTG1, FBXO5/EMI1 and BMP6. These results underscore the consistency of our approach. Furthermore, the inventory of human genes essential for nuclear and cytoplasmic oocyte maturation is an important step towards the comprehensive understanding of oocyte biology.

Although female and male gametes differ in many aspects, they share a common meiosis machinery. Indeed, we see here that genes reported to be expressed specifically in spermatozoa are also highly overexpressed in oocytes in comparison with somatic cumulus cells. This is the case for aurora kinase C (AURKC), sperm associated antigen 16 (SPAG16/ PF20) and SOX30 (Osaki et al., 1999; Horowitz et al., 2005; Yan et al., 2005). Three aurora kinases have been identified (AURA/STK6, AURKB and AURKC) that share a conserved catalytic domain and play a role in centrosome separation and maturation, spindle assembly and segregation, and cytokinesis (Giet et al., 2005). Whereas AURA and AURKB are involved in mitosis in somatic cells, AURKC was only found highly expressed in testis, suggesting a tissue-specific role in meiosis. It is therefore of special interest to observe that AURKC is also 49 times more expressed in pure oocyte samples than in somatic cells. Because AURKB and AURKC have a similar cellular localization and a similar biological activity such as SURVIVIN/BIRC5 binding, we propose that AURKC is replacing AURKB during meiosis in both male and female gametes. In line with this proposition, our data show that in oocyte samples, AURKB expression is close to background, whereas SURVIVIN/BIRC5, a known partner of the AURKC complex (Yan et al., 2005), is also strongly overexpressed. We found the specific up-regulation in oocytes of two methyltransferase enzymes (DNMT1 and DNMT3B), one histone 1715

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deacetylase (HDAC9) and an oocyte-specific histone (H1FOO). Interestingly, the chromosome condensation protein G (HCAP-G), which is a component of the condensin complex that mediates genome-wide chromosome condensation at the onset of mitosis and directly interacts with DNMT3B (Geiman et al., 2004), is also found preferentially expressed in oocytes, suggesting that this condensin is essential to the nuclear maturation of oocytes. Keeping in line with epigenetic modifications of the genome, we screened our list of oocyte genes for imprinted genes. Of note, one paternally imprinted gene, MEST, was highly overexpressed in all three oocyte samples as compared with cumulus cells, whereas other paternally imprinted genes such as IGF2 and NNAT were not. We noted the overexpression of two pro-apoptotic genes in oocytes (BNIP1 and BCL2L10). These findings strongly argue in favour of a model where the survival of oocytes is mediated by external signals provided by surrounding cumulus cells rather than by intrinsic cues such as overexpression of antiapoptotic factors. Accordingly, we found many receptors for growth factors overexpressed on oocytes, including a BMP receptor (BMPR2), the receptor for the stem cell factor (KIT), a member of the EGF receptor family (ERBB4), and a frizzled receptor (FZD3) member of the WNT pathway. In addition, we observed 6 poorly characterized G protein-coupled receptors in oocytes (GPR37, GPR39, GPR51, GPR126, GPR143 and GPR160). The fact that oocytes overexpress these growth factor receptors strongly suggests that the ligands of these receptors are involved in conveying surviving and maturation cues from the oophorus cumulus to the oocytes. Conversely, oocytes express many growth factors. Among the genes, we noted the remarkable overexpression of a ligand from the TNF superfamily, TNFSF13/APRIL, which we found to be expressed 131 times more in oocytes than in cumulus cells. We did not see a significant expression of the two TNF receptors for APRIL, TNFRSF13B/TACI and TNFRSF17/BCMA (data not shown). But it was recently described that APRIL’s binding to proteoglycan was necessary for the survival signal conveyed by this cytokine to targets cells (Ingold et al., 2005). Because cumulus cells overexpress several proteoglycans such as CSPG2/versican (Table II) and SYNDECAN4 (data not shown), APRIL could mediate a comparable trophic signal from the oocyte to the surrounding cumulus cells. We also focused our analysis on genes for which the expression increased progressively during oocyte meiosis. We postulate that they could be interesting candidate genes for oocyte maturation. Indeed, if these genes fail to be up-regulated in MII-stage oocytes, it is likely that the maturation process was defective. Genes increasing progressively during oocyte maturation include SOCS7. This gene is part of a family of proteins negatively regulating intracellular signal transduction cascades (Krebs and Hilton, 2000). Its overexpression in MII-stage oocytes may indicate the shutting down of specific cytokine signalling. For this category, it must also be noted that many genes are still not characterized and remain without any hint about their function (20 of 48 genes, i.e. 42%). It is not a surprise if so many genes from this list have escaped bioinformatics or biological functional investigations to date, because (i) MIIstage oocytes are a very rare cell type, (ii) it is a very specialized 1716

cell type expressing numerous genes that may not be found in any other tissue type, including genes devoid of any molecular motif found in other tissues and (iii) we used pan-genomic microarray to study for the first time gene expression of this cell type without any selection bias. It will be essential to describe in detail the function of these genes to obtain further insights into oocyte biology. In order to decipher the tight relationship weaved between the oocyte and its surrounding follicle cells, we also analysed the transcriptome profile of cumulus cells. Indeed, 24% of the 2600 genes overexpressed in cumulus cells are annotated either ‘membrane’ or ‘extracellular’, demonstrating a strong bias towards genes involved in cell-to-cell communication processes. The signalling pathways involved comprise progesterone and its receptors, eicosanoids and several enzymes involved in their biosynthesis and chemokines. We showed in this study that cumulus cells up-regulated hormonal receptors and hormones such as LHCGR, Inhibin alpha, Inhibin beta A, GNRH1 and progesterone receptor membrane component 1 and 2. Interestingly, cumulus cells overexpress BMPR2, which is the receptor for GDF9 that is overexpressed by oocytes, demonstrating a typical intercellular communication process (Figure 4). In addition to the inhibins INHA and INHBA, we also observed the overexpression of BMP1 and BMP8B, as well as the pseudoreceptor BAMBI, lacking an intracellular serine/threonine kinase domain and thus negatively regulating TGF-β signalling. Another important growth factor superfamily found to be overexpressed in cumulus cells is the TNF superfamily. The marked overexpression of TNFSF11/OPGL/RANKL (80 times more expressed in cumulus cells than in oocytes) is intriguing and awaits further investigations. Magier et al. (1990) suggested a positive effect of cumulus cells on fertilization, and a protective effect and a possible beneficial effect on further embryo development. In addition, Platteau et al. (2004) suggested that the exogenous luteinizing hormone activity may influence treatment outcome in IVF but not in ICSI. We provide here molecular evidence for cumulus cell expression of hormones and growth factors that could mediate these functions. Another puzzling observation is the increased expression of seven complement factors or closely related genes. Whether this overexpression is involved in the cellular destruction process taking place in the antrum during ovulation needs to be considered. Finally, cumulus cells express several other cellsurface gene families such as semaphorins, first identified for their role in neuron guidance, tetraspanins, with one member, CD9, directly involved in fertilization (Le Naour et al., 2000), and many other CD molecules with various functions (Table II). Very interestingly, some genes overexpressed in granulosa cells are also found expressed in ovarian tumours. We found, for example, a high expression in cumulus cells of CD24 and CD99, which are expressed in ovarian tumours and have been proposed as either diagnostic tools (Choi et al., 2000) or as prognostic tools (Kristiansen et al., 2002). These findings suggest that many of the genes overexpressed in cumulus samples, including the cell-surface markers of cumulus cells listed in Table II, could provide ovarian cancer markers. We pooled oocytes according to their maturation stage for this first, exploratory, whole-genome transcriptome analysis.

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Gene-expression profiling of oocytes

This strategy levelled down differences that would be associated with different IVF settings such as maternal age, sperm exposure or in vitro incubation time. In order to describe the expression modifications that may be related to specific conditions, we are currently analysing the transcriptome of oocytes pooled according to the hormonal profile at day 3, maternal age or ovarian stimulation protocol. Nevertheless, to appreciate variations in gene expression according to each patient idiosyncrasies, we will need to achieve reliable transcriptome analysis from single oocytes. In conclusion, DNA microarray provided us with the opportunity to analyse human oocytes and cumulus cellexpression profiles on a genome scale and permitted significant progress in the understanding of the molecular events involved in the processes governing oocyte maturation. Many of the genes described here may well provide markers to monitor health, viability and competence of oocytes. In addition, underpinning oocyte growth factor receptors should help to design optimal in vitro culture conditions for oocyte and early embryo development. Acknowledgements
We are grateful to Stephan Gasca, Irène Fries, Benoit Richard, Benoit Latucca and Beno?t Crassou for helpful discussions. We thank all members of our ART team for their assistance during this study. This study was supported by grants from Ferring and Organon Pharmaceuticals, France.

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