Effect of luteal-phase support on endometrial microRNA expression following controlled ovarian stimulation

  • Yulian Zhao1Email author,

    Affiliated with

    • Howard Zacur1,

      Affiliated with

      • Chris Cheadle2,

        Affiliated with

        • Ning Ning3,

          Affiliated with

          • Jinshui Fan2 and

            Affiliated with

            • Nikos F Vlahos4

              Affiliated with

              Reproductive Biology and Endocrinology201210:72

              DOI: 10.1186/1477-7827-10-72

              Received: 4 June 2012

              Accepted: 31 August 2012

              Published: 6 September 2012

              Abstract

              Background

              Studies suggested that microRNAs influence cellular activities in the uterus including cell differentiation and embryo implantation. In assisted reproduction cycles, luteal phase support, given to improve endometrial characteristics and to facilitate the implantation process, has been a standard practice. The effect of different types of luteal phase support using steroid hormones in relation to endometrial miRNA profiles during the peri-implantation period has not seen described. This study was designed to evaluate the expression of miRNAs during the luteal phase following controlled ovarian stimulation for IVF and the influence of different luteal phase support protocols on miRNA profiles.

              Methods

              The study was approved by the Johns Hopkins Hospital Institutional Review Board. Endometrial biopsies were obtained on the day of oocyte retrieval from 9 oocyte donors (group I). An additional endometrial biopsy was obtained 3–5 days later (Group II) after the donors were randomized into three groups. Group IIa had no luteal-phase support, group IIb had luteal support with micronized progesterone (P), and Group IIc had luteal support with progesterone plus 17-beta-estradiol (P + E). Total RNA was isolated and microarray analysis was performed using an Illumina miRNA expression panel.

              Results

              A total of 526 miRNAs were identified. Out of those, 216 miRNAs were differentially regulated (p < 0.05) between the comparison groups. As compared to the day of retrieval, 19, 11 and 6 miRNAs were differentially regulated more than 2 fold in the groups of no support, in the P support only, and in the P + E support respectively, 3–5 days after retrieval. During the peri-implantation period (3–5 days after retrieval) the expression of 33 and 6 miRNAs increased, while the expression of 3 and 0 miRNAs decreased, in the P alone and in the P + E group respectively as compared to the no steroid supplementation group.

              Conclusion

              Luteal support following COS has a profound influence on miRNA profiles. Up or down regulation of miRNAs after P or P + E support suggest a role(s) of luteal support in the peri-implantation uterus in IVF cycles through the regulation of associated target genes.

              Keywords

              MicroRNA Ovarian stimulation Luteal phase support Microarray

              Background

              MicroRNAs (miRNAs) are a class of single-stranded, non-coding small RNAs that regulate gene expression at the translational level and play fundamental roles in several biological processes, including cell differentiation, proliferation, development and apoptosis [13]. It is believed that mammalian miRNAs are responsible for the regulation of over 60% of all human genes [4]. Either by controlling mRNA degradation or by translational repression, miRNAs have emerged as key regulators of gene expression [5, 6]. Each miRNA is predicated to have a broad range of target mRNAs and each mRNA may be regulated by multiple miRNAs [7, 8].

              The role of miRNAs in the female reproductive system and particularly in the endometrium has been the focus of several studies in recent years [9, 10]. So far it has been established that miRNAs are indeed expressed in the human endometrium and they are also subjected to hormonal regulation [10, 11]. Hawkins et al. were able to identify a number of miRNAs that were differentially regulated in endometriotic tissues as compared to normal endometrium [12]. The overall regulatory role of miRNAs in the pathophysiology of endometriosis has been reviewed extensively by Ohlsson Teaque et al.[13].

              Ovarian stimulation protocols with gonadotropins have been invariably associated with luteal phase deficiency and poor implantation rates [14, 15]. While the exact reasons for this phenomenon are still unclear, luteal phase support, given to improve endometrial characteristics and to facilitate the implantation process, has been a standard practice. Progesterone is a universally accepted agent for luteal phase support and can be administered orally, intramuscularly, or vaginally [16, 17]. Estrogens in the form of 17β- estradiol or estradiol valerate have also been used for luteal phase support [18], although studies aimed to evaluate the concept of estrogen addition during the luteal phase have lead to inconclusive results [14, 19] . It has been suggested that during ovarian stimulation for IVF, the endometrial receptivity starts to occur in mid luteal phase after oocyte retrieval [20]. Prior to, and during the implantation process, the expression of multiple endometrial genes and gene products is highly regulated [2123]. The role of miRNAs in regulating cellular processes during the endometrial transition has recently attracted a great deal of attention [10, 2428]. For example, Kuokkanen et al. reported distinct miRNA gene expression signatures in the late proliferative and mid-secretory phase endometrial epithelium [24]. However, the effect of different types of luteal support in relation to endometrial miRNA profiles during the period of peri-implantation has not been described. In this study, we have investigated the impact of two commonly used luteal phase support protocols, progesterone alone and progesterone plus estrogen, on the expression profiles of 526 miRNAs in the human endometrium following ovarian stimulation with a gonadotropin/ GnRH antagonist protocol.

              Methods

              Oocyte donors and ovarian stimulation

              The study was approved by the Johns Hopkins Hospital Institutional Review Board. Nine oocyte donors who enrolled in the Johns Hopkins oocyte donation program participated in the study. All donors were 21 to 31 years of age and underwent a standard screening protocol for oocyte donation, in accordance with the recommendations of the American Society for Reproductive Medicine [29]. The risks of the procedure were discussed in detail, with particular emphasis on the risks associated with the endometrial biopsy and the use of steroids during luteal phase, and written informed consents were obtained.

              Study subjects underwent ovarian stimulation according to a gonadotropin / GnRH antagonist protocol as described previously [30]. Briefly, ovarian stimulation was initiated with gonadotropins on the second day of vaginal bleeding following discontinuation of oral contraceptive pills. On the 6th day of stimulation, a daily subcutaneous evening dose of 0.25 mg ganirelix acetate (Schering-Plough Corp, West Orange, NJ, USA) was added. When at least three follicles reached a mean diameter of 18 mm, ovulation was triggered with a single dose of hCG (Profasi, 10,000 IU; Serono Inc. Rockland, MA, USA). Sonographically guided transvaginal oocyte retrieval was performed 34–36 hours after the hCG administration. The retrieved oocytes were used for IVF procedures and the resulting embryos were either transferred to matched recipients or cryopreserved for future use.

              Luteal-phase support and tissue collection

              Endometrial biopsies on oocyte donors were performed using a Pipelle catheter (Unimar, Wilton, CT) on the day of oocyte retrieval and served as baseline (group I). At that time, the donors were randomized into three groups, with three subjects in each group. Group IIa received no luteal phase support after retrieval. Group IIb had luteal phase support with micronized progesterone (P) in the form of vaginal suppositories (200 mg every 6 h starting from the day after retrieval). Group IIc received a daily oral dose of 2 mg 17β-estradiol in addition to the micronized progesterone (P + E). Endometrial biopsies were obtained again 3–5 days (each of treatment groups contains 2 samples from day 3 and 1 sample from day 5) after retrieval. All specimens were stored in liquid nitrogen at −196°C immediately after the biopsy.

              RNA preparation and miRNA analysis

              Total RNA was isolated and extracted from individual endometrial samples using the Trizol Reagent method (Invitrogen, Carlsbad, California 92008, cat. no. 15596–026). The quality of the RNA samples was assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). The integrity of miRNA was assessed by a miRNA specific RT-PCR using an ABI (Applied Biosystems; Foster City, CA) Taqman assay for U6 snRNA (AB Assay ID 001973). The results indicated an average Ct of 20.1 (SD 0.84) for all samples with a minimum Ct of 18.3 and maximum Ct of 22.

              Illumina miRNA expression profiling (Catalog # MI-501-1001) was carried out according to manufacturer’s recommended protocols. Briefly 200ngs of total RNA for each sample was polyadenylated and converted to cDNA using a biotinylated oligo-dT primer with a universal PCR sequence at its 5’-end. Biotinylated cDNA was annealed to query oligos. Each query oligo consisted of a universal PCR priming site at the 5’end, an address sequence that complements a corresponding capture sequence on the array, and a microRNA-specific sequence at the 3’end. This mixture was bound to streptavidin-conjugated paramagnetic particles to select the cDNA/oligo complexes; second strand cDNA synthesis was completed by primer extension. All cDNA templates were amplified with a pair of common PCR primers. The primer on the strand complementary to the array was fluorescently labeled for subsequent hybridization to the arrays.

              Validation of the selected miRNAs, shown to be regulated by Illumina miRNA microarray, was performed by RT-PCR. QRT-PCR was performed using the RT2 ProfilerTM Human miFinder miRNA PCR Array (MAH-001A) from SuperArray (SABiosciences, Gaithersburg, MD). RT2 Profiler™ PCR Arrays are designed for relative quantitative QRT-PCR based on SYBR Green detection and performed on a one sample/one plate 96-well format, using primers for a preset list of 88 most abundantly expressed and best characterized micro RNA sequences. In brief, miRNA was converted to cDNA via a universal tailing and reverse transcription reaction. CDNA volumes were adjusted to ~2.5 ml with SuperArray RT2 Real-Time SYBR Green/ROX PCR 2X Master Mix (PA-012) and 25 μl of cDNA mix was added to all wells. The PCR plate was sealed and spun at 1500 rpm X 4 min. Real time PCR was performed on an Applied Biosystem (Foster City, CA) 7300 Real Time PCR System. ABI instrument settings included setting reporter dye as “SYBR”, passive reference is “ROX”; Delete UNG Activation, and add Dissociation Stage.

              To correlate differentially expressed miRNAs and their regulated genes, we used differentially regulated and selected miRNAs against an established miRNA database for predicted target genes (Sanger miRBase, v9.1, February 2007 release). MicroRNA data was also analyzed through the use of Ingenuity Pathway Analysis (IPA, Ingenuity® Systems, http://​www.​ingenuity.​com). Pathway enrichments were calculated using the NIAID DAVID functional enrichment tool [31, 32].

              Statistical analysis

              Preliminary analysis of the scanned data was performed using Illumina BeadStudio software which returns single intensity data values/miRNA following the computation of a trimmed mean average for each probe type represented by a variable number of bead probes/gene on the array. Data was globally normalized by scaling each array to a common median value, and significant changes in gene expression between class pairs were calculated using the Student t-test. Significant gene lists were calculated by selecting genes which satisfied a significance threshold criteria of t-test p-values less than or equal to 0.05 and a fold change ± 2 or greater.

              Relative miRNA expression derived from QRT-PCR was calculated by using the 2-Ct method, in which Ct indicates cycle threshold, the fractional cycle number where the fluorescent signal reaches detection threshold [33]. The normalized ΔCt value of each sample is calculated using an endogenous control small molecular weight RNA (U6 snRNA). Fold change values are presented as average fold change = 2-(average Ct) for genes in treated relative to control samples. The criteria of significance used for the RT-PCR results were the same as used for the Illumina miRNA arrays.

              Results

              Demographic characteristics

              Demographic characteristics for all study participants were similar in all treatment groups. The mean age of the study participants was 24 years and mean body mass index was 21.3 ± 1.2 kg/m2. Overall, the baseline serum FSH, LH and E2 levels, the length of the stimulation , total amount of gonadotropins used, peak estradiol levels, and number of oocytes retrieved were comparable (P > 0.05) between the groups (Table 1).
              Table 1

              Group characteristics

              Characteristics

              Group IIa (no support)

              Group IIb (P support)

              Group IIc (P + E support)

              P

              N

              3

              3

              3

               

              Age (yr)

              25.7 ± 3.2

              23.6 ± 0.8

              22.8 ± 1.2

              0.494

              BMI (kg/m 2 )

              23.3 ± 1.4

              21.6 ± 1.8

              20.2 ± 1.2

              0.096

              Day 2 FSH (mIU/ml)

              4.5 ± 0.9

              5.6 ± 1.1

              4.0 ± 0.3

              0.178

              Day 2 LH (mIU/ml)

              2.4 ± 0.8

              4.0 ± 1.3

              5.2 ± 0.2

              0.507

              Day 2 E2 (pg/ml)

              36.7 ± 11.6

              34.5 ± 12.5

              20.5 ± 3.5

              0.646

              Gonadotropins used (IU)

              2850 ± 525

              2400 ± 645

              2625 ± 675

              0.387

              Peak E2 level (pg/ml)

              1928 ± 100.0

              2514 ± 400

              2625 ± 480

              0.563

              Days of stimulation

              10.3 ± 1.1

              9.3 ± 1.2

              10.1 ± 0.7

              0.588

              No. of oocytes

              14.5 ± 5

              18.4 ± 3

              16.0 ± 4

              0.398

              MiRNA profiles and comparisons between groups

              To establish endometrial miRNA profiles, we used a microarray platform consisting of 526 miRNA probes. Triplicates of each group samples were used, which proved that genes from same condition of samples are reproducible. Levels of miRNA expression are similar in the same sample groups including the samples from either day 3 or day5. The fluorescent intensity of each expressed transcript in each sample group was compared to the median fluorescence intensity of each transcript in the paired comparison group. Individual transcripts with increased (red) and decreased (green) miRNA abundance in the given comparisons were identified, as shown in the hierarchical clustering map in Figure 1. It is demonstrated that there is a high degree of overall concordance between and within treatments for later versus early luteal phase and, in particular a striking concordance, for hormone treated versus non-treated groups at days 3–5 after oocyte retrieval. Following global normalization, the mean expression value for each group was subjected to statistical analysis. A 2 fold change in the expression was arbitrarily selected as a cut-off level. Individual miRNAs that have shown a significant change in their expression (greater than 2fold and/or p < 0.05 between the comparison groups) are shown in an Additional file 1: Table S1 with a total of 248 miRNAs listed.
              http://static-content.springer.com/image/art%3A10.1186%2F1477-7827-10-72/MediaObjects/12958_2012_Article_999_Fig1_HTML.jpg
              Figure 1

              Hierarchical clustering map of miRNA genes in all comparison groups: day 3–5 vs. day 0. (grpIIa-grpI = no luteal support vs. no luteal support; grpIIb-grpI = P support vs. no luteal support; grpIIc-grpI = P + E support vs. no luteal support) and day 3–5 vs. day 3–5 (grpIIb-grpIIa = P support vs. no support; grpIIc-grpI = P + E support vs. no support; grpIIc-grpIIb = P + E support vs. P support only). Increased (red), decreased (green), and unchanged (yellow) miRNA levels from each transcript are indicated for each comparison group.

              Initially we compared miRNA expression in the endometrial samples obtained on the day of retrieval to those obtained 3–5 days later (Figure 2, the 3 comparison columns on the left). In the group with no luteal phase support, 14 miRNAs (HS_202.1, HS_209.1, HS_284.1, hsa-miR-202*:9.1, hsa-miR-346, hsa-miR-363*, hsa-miR-504, hsa-miR-569, hsa-miR-302d, hsa-miR-632, HS_17, HS_145.1, hsa-miR-133b, hsa-miR-144:9.1) were down-regulated and 5 miRNAs were up-regulated (HS_130, hsa-miR-876-5p, hsa-miR-876-3p, hsa-miR-122, hsa-miR-9) at greater than 2 fold changes. In the P alone group, 4 miRNAs (hsa-miR-144:9.1, hsa-miR-486-5p, HS_97, HS_203) were down regulated and 7 (HS_163, hsa-miR-614, hsa-miR-610, hsa-miR-559, hsa-miR-876-5p, HS_18, hsa-miR-876-3p) were up regulated, while in the P + E support group, 1 miRNA (hsa-miR-449a) was underexpressed and 5 (HS_276.1, hsa-miR-876-5p, HS_18, HS_111, hsa-miR-876-3p) were overexpressed .
              http://static-content.springer.com/image/art%3A10.1186%2F1477-7827-10-72/MediaObjects/12958_2012_Article_999_Fig2_HTML.jpg
              Figure 2

              Numbers of miRNA genes with more than 2 fold changes between comparison groups. no = no steroid supplementation; P = progesterone support; P + E = progesterone + estrogen support.

              Subsequently, we compared miRNA gene expression between the different treatment groups during mid-luteal phase at 3–5 days after retrieval, as shown in Figure 2, the 3 comparison columns on the right. In the progesterone support group an overexpression (more than 2 fold increase) was observed for 33 miRNAs (HS_149, HS_166.1, HS_175, HS_202.1, HS_209.1, HS_284.1, HS_41, hsa-miR-1468, hsa-miR-202*:9.1,hsa-miR-346, hsa-miR-504, hsa-miR-512-5p, hsa-miR-560:9.1, hsa-miR-563, hsa-miR-638, hsa-miR-663, hsa-miR-302d, hsa-miR-302b*, hsa-miR-632, hsa-miR-622, HS_17, HS_163, hsa-miR-518b, HS_108.1, hsa-miR-614, hsa-miR-610, HS_263.1, HS_30, hsa-miR-512-3p, HS_32, HS_282, HS_169, HS_145.1) and in the P + E support group for 6 miRNAs (HS_149, HS_276.1, HS_41, hsa-miR-563, HS_17, hsa-miR-144:9.1) as compared to the no steroid supplementation group. On the other hand, underexpression of 3 miRNAs (HS_176, HS_97, HS_203) were seen only in P support group. In the comparison between E + P and P supplementation groups, 5 miRNAs (hsa-miR-144:9.1, hsa-miR-486-5p, HS_176, HS_97, HS_203) were up-regulated and none were down regulated at greater than 2 fold levels.

              Venn diagram analysis of differentially expressed miRNA genes

              A total of 216 miRNAs were differentially regulated (p < 0.05) between the study groups. MiRNAs with significant changes in common (shared miRNAs) between groups are shown in Figure 3. Panel A shows changes in miRNA expressions between day 3–5 and day of retrieval. Among the 3 comparison groups, 3 miRNAs (hsa-miR-876-3p, hsa-miR-155, and hsa-miR-503) were shared by all 3 groups and 5, 10 and 13 miRNAs respectively were shared in each pair of groups. Panel B compares groups on day 3–5 at all possible combinations. Group IIb vs. IIa and Group IIc vs. IIa shared 4 miRNAs (HS_241.1, hsa-miR-346, hsa-miR-503, and hsa-miR-99a); Group IIc vs. IIa and Group IIc vs. IIb shared 1 miRNA (hsa-miR-766) and Group IIb vs. IIa and Group IIc vs. IIb shared 3 miRNAs (hsa-miR-501-5p, hsa-miR-512-5p and hsa-miR-146a).
              http://static-content.springer.com/image/art%3A10.1186%2F1477-7827-10-72/MediaObjects/12958_2012_Article_999_Fig3_HTML.jpg
              Figure 3

              Venn diagram illustrations of differentially expressed miRNA genes in six comparison groups. Number of miRNA genes that were differentially expressed (p < 0.05) in the endometrium with and without luteal phase support as compared 3–5 days after oocyte retrieval versus day of retrieval (A) and at 3–5 days after oocyte retrieval (B) among groups. no = no steroid supplementation; P = progesterone supplementation; P + E = progesterone + estrogen supplementation.

              Validation analysis

              Array based RT-PCR with 88 miRNAs was used to validate our Illumina array expression findings. We were able to map 19 miRNAs between the two platforms. Of these, 14/19 demonstrated concordance at the level of the direction of regulation (increased or decreased) at a hypergeometric probability of p < 0.014. Nine representative miRNAs were selected for groups IIa vs. I and IIc vs. IIa as indicated in Figure 4. The trends for up-regulation and down- regulation of these miRNAs were consistent between the two array measurements.
              http://static-content.springer.com/image/art%3A10.1186%2F1477-7827-10-72/MediaObjects/12958_2012_Article_999_Fig4_HTML.jpg
              Figure 4

              Validation results of the microarray findings for 9 miRNAs.

              MiRNA and target genes

              To explore the biological relationship between differentially expressed miRNAs and their regulated genes, we used differentially regulated (p < 0.05) miRNAs on day 3–5 after oocyte retrieval against an established miRNA database for predicted target genes (Sanger miRBase, v9.1, February 2007 release). Interestingly, there are large numbers of predicted target genes for a given miRNA per miRBase. We were able to identify nineteen miRNAs and their selected target genes in this defined study categories which are shown in Table 2.
              Table 2

              Selected miRNAs and gene targets (comparisons are at day3-5 after oocyte retrieval)

              miRNA

              P vs. no

              P + E vs. no

              P + E vs. P

              Predicted target genes

              hsa-miR-335

              ↑↑

                

              IMP2,CD79B,WWP1,AP3S1,HOXD8,MAX,SP1,MAP2,MAK3,STARD7,CAP350,PANK2,SRPR,PPP6C,LASS5,ATP1B1

              hsa-miR-346

               

              IMP1,EIF3S1,BCL6,ABCC12,LIF,FSTL4,KGFLP2,KRAS,RAF7,FGF7,TMEM28,IGSF4B,PPP1R9B,COL2A1,HCG3, CALN1,HBP1,SF1

              hsa-miR-448

                

              DOCK9,PPM2C,NTF3,CAP1,MAP2K6,ITM1,PRKAR2B,PAPPA,CDC2L6,CNTN4,IGF1R,SOCS5,CLK1,HOXA11,WWP1,FOXJ3,WDR22,MPPED2,ADD1,PRKA2

              hsa-miR-504

                

              DCX,ATP1B4,IL1RAPL1,MNT,KLF13,PRKAR2A,IL16,LIF,FXR2,NRF1,CAMK2G,MMD,LOC284296,DND1,CNTFR, SORT1,NFIX

              hsa-miR-512-5p

              ↑↑

               

              PIK3R1,CTNNB1,EMX2,SOX21,RIPK5,MBD6,SRPK, VNN3,ERP29,PHF15,FBXW11,LOC285074,MAP1A,CHD9

              hsa-miR-520 g

              ↑↑

                

              ETF1,CAMK2N1,NLK,TNFSF11,CNR1,EFTUD1,HMGB3,FBN2,ENC1,MARK4,TFEB,TNFSF12,PRKAR2A,TNKS1BP1,EIF4E,PPP3CA,IMP1,MAP3K14,TMTC2,TTN,GTF2IRD2,PTK2B,DNAJB5,TNRC6A,VEGF,EIF4G2,FOXO1A,MAP3K9

              hsa-miR-204

                

              RUNX2,SOX4,NRBF2,MAP1LC3B,CDC42,ATP2B1,AKAP1,MAP3K3,CENTD1,IGF2R,NTRK2,TGFBR2,AP3M1,

                  

              NEUROG1,P53CSV,TCF7L1,CDH2, CDC25B,TCF12,ELF2

              hsa-miR-369-3p

                

              TCF8,PKIA,TLN1,CHD7,NCK2,CD2AP,CDC2L6,ELMOD1,CCNE2,FOXG1B,HOXB3,ADAMTS19,GIT2,ADAMTS3,TCF12, SRPK2,ADAMTS6,MAP2,ADAM10,FOXO1A,VEGFC

              hsa-miR-328

                

              AK6,ITGA5,PRX,IGSF4C,MAX,SOX11,PTPN9,DPH2, HIST1H4D,USP37,VSIG4,RPP14,SF4,ULK2,FGD1,PLAG1

              hsa-miR-186

                

              APLP2,ITGA6,RPS6KB1,CDC42,PRDM10,IGSF11,EFCBP1,TCF20,CAST,LMBR1,TMED2,TGFBR2,ICMT,IL2,CCNT2,HOXB8,PAK7,FOXD1,PTGES3,MAP3K2,VEGF,COL3A1, SRPK2,MAPKAP1,C16orf52,MAP2

              hsa-miR-517a

                

              AMMECR1,ACACA,NPAS4,BSN,HNRPU,PTK2B,CDKN2A,CBLN2,RAPGEFL1,LOC201895,FOXJ3,PHF13,TMCC1

              hsa-miR-365

                

              ↓↓

              EIF4E3,MAP2K7,LAMP2,ENTPD7,PCNP,ADAMTS6, COL7A1,PPP5C,REV3L,PTGDR,KCNH2,RBM12,PKD2L2

              hsa-miR-221

              ↓↓

                

              CDC2L6,TIMP3,EIF4E3,NTF3,IMP2,HTLF,CDV3,NL,EIF5A2,NRK,PAK1,CDKN1C,FAT2,LIFR,TMCC1,MAP3K10,VGLL4,FAM13A1,TCF12,HOXC10,MAPK10,HMGCLL1,ADAM11,CD4,CTCF

              hsa-miR-495

              ↓↓

                

              MAPK6,CDK6,EML4,ILF3,PTK9,PRR7,HBEGF,HOMER1,MARK3,SP4,TGFB2,LHX2,HOXC6,PRKX,AP3M1,SOX9,GMFB,HMGCLL1,FOXO3A,EDG3,NKRF,HOXB9,TIMP2, IGSF4,CD164,TNFRSF21

              hsa-miR-146a

               

              FBXL10,IRAK1,TRAF6,CD79B,SP8,FLJ33814,SFRS6,NPAS4,CXorf22,EIF4G2,MMP16,USP3,KCTD15,SMAD4,LOC440944,SEC23IP,BCORL1,TM6SF2,DLGA1

              hsa-miR-99a

               

              EPDR1,FZD8,HS3ST2,EIF2C2,HS3ST3B1,FGFR3,BAZ2A,MBNL1,CYP26B1,KBTBD8,SMARCA5,FRAP1,ZZEF1,ICMT,C4orf16,ADCY1,MTMR3,CTDSPL,HOXA,RAVER2, INSM1,TRIB2,SLC44A1

              hsa-miR-181c,d

              ↑↑

                

              ETF1,COL16A1,NLK,TNFSF11,MAP3K3,MAP2K1,ITGA3,TCERG1,MAPT,MAPK1,MAP1B,CDH13,ITGB8,PCGF2,ADAMTS18,LMBRD2,MMP14,CD163,LIF,ADAMTS6, TNFRSF11B,CDC42BPA

              hsa-miR-200b

                

              TCF8,NTF3,CYLN2,HMGB3,PRKAR2B,MPP5,GIT2,MAP4K3,FLJ21103,E2F3,CSNK1G3,MMD2,ZNF53, EIF5B,ERRFI1

              hsa-miR-196b

               

               

              IMP1,CDYL,COL14A1,SSR1,IMP3,CDV3,CALM3,COL24A1,CDKN1B,ELF4,HOXC8,HMGA2,HOXA5,MAP4K3,PARP6,COL3A1,HOXA1,TNFSF12,COL1A2, HOXA7,HOXB6

              or = up or down regulated, p < 0.05; ↑↑ or ↓↓= up or down regulated, p < 0.01.

              See website http://​www.​mirbase.​org (http://​microrna.​sanger.​ac.​uk) regarding additional predicted target genes.

              In order to further investigate the possible biological implications for those miRNAs which were cross validated by both QRT-PCR and Illumina array data (Figure 4), the relationship of these microRNAs and their known gene targets was evaluated using the IPA miRNA Target Filter software. This group of miRNAs is regulated between day 3–5 and day 0 and also at day 3–5 between P + E (Grps IIc) and no support (Grps IIa) groups. IPA was able to identify 7 out of the 9 miRNAs from Figure 4 (excluding hsa-miR-144, and hsa-mir-181b). The gene targets were identified for these miRNAs based upon the selection of the most stringent criteria requiring experimental observation of a given miRNA and its target. Gene targets were further filtered for known involvement in endocrine system disorders. The results of this analysis (Table 3) that shows pathway enrichments were calculated for the entire gene set. The findings of the analysis demonstrated a significant involvement of genes of extracellular matrix, cell proliferation, and response to steroid hormone stimulus between days 3–5 versus day 0 at no steroid support groups (Table 3, Grps IIa-I). Interestingly, this effect was almost completely abrogated by progesterone and estrogen treatment (Table 3, GrpsIIc-IIa) for genes of cellular proliferation and response to steroid hormones but not for extracellular matrix.
              Table 3

              Cross validated miRNAs and their selected target genes

              Symbol

              GrpsIIa-I [ILL-FC]

              GrpsIIc-IIa [ILL-FC]

              Source

              Symbol

              Entrez gene name

              Pathway (enrichment)

              P Value

              FDR

              miR-223-3p (GUCAGUU)

              1.389

              1.111

              1

              VIM

              vimentin

                 

              miR-223-3p (GUCAGUU)

              1.389

              1.111

              1,2

              RHOB

              ras homolog family member B

                 

              miR-223-3p (GUCAGUU)

              1.389

              1.111

              1

              IRS1

              insulin receptor substrate 1

                 

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              2,3

              TUBB2A

              tubulin, beta 2A class IIa

                 

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2,3,4

              SPARC

              secreted protein, acidic, cysteine-rich (osteonectin)

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2,3

              PIK3R1

              phosphoinositide-3-kinase, regulatory subunit 1 (alpha)

                 

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              2,3

              MYBL2

              v-myb myeloblastosis viral oncogene homolog (avian)-like 2

                 

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2

              COL5A3

              collagen, type V, alpha 3

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              32,3

              COL5A2

              collagen, type V, alpha 2

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2,4

              COL4A1

              collagen, type IV, alpha 1

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2,3,4

              COL1A2

              collagen, type I, alpha 2

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-29b-3p (AGCACCA)

              1.375

              1.068

              1,2,4

              COL15A1

              collagen, type XV, alpha 1

              extracellular matrix

              1.29E-07

              4.44E-06

              miR-9-5p (CUUUGGU)

              2.104

              −1.802

              1

              NFKB1

              nuclear factor of kappa light polypeptide gene enhancer in B-cells 1

                 

              miR-9-5p (CUUUGGU)

              2.104

              −1.802

              1,2

              FOXO1

              forkhead box O1

                 

              miR-9-5p (CUUUGGU)

              2.104

              −1.802

              1,2

              FOXG1

              forkhead box G1

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-9-5p (CUUUGGU)

              2.104

              −1.802

              1,2,3

              CDH1

              cadherin 1, type 1, E-cadherin (epithelial)

                 

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,4

              TRA@

              T cell receptor alpha locus

                 

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              TIMP3

              TIMP metallopeptidase inhibitor 3

                 

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              NOTCH4

              notch 4

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              KRAS

              v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2,4

              HOXA11

              homeobox A11

                 

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              GATA6

              GATA binding protein 6

                 

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              ESR1

              estrogen receptor 1

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2

              CDKN1B

              cyclin-dependent kinase inhibitor 1B (p27, Kip1)

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-181a-5p (ACAUUCA)

              1.376

              −1.24

              1,2,3,4

              BCL2

              B-cell CLL/lymphoma 2

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-196a-5p (AGGUAGU)

              1.092

              −1.342

              1

              IKBKB

              inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta

                 

              miR-196a-5p (AGGUAGU)

              1.092

              −1.342

              1,2,4

              HOXC8

              homeobox C8

                 

              miR-196a-5p (AGGUAGU)

              1.092

              −1.342

              1,3

              ANXA1

              annexin A1

                 

              miR-99a-5p (ACCCGUA)

              1.427

              −1.48

              1,2,3

              MTOR

              mechanistic target of rapamycin (serine/threonine kinase)

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-99a-5p (ACCCGUA)

              1.427

              −1.48

              1,2,3

              IGF1R

              insulin-like growth factor 1 receptor

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-99a-5p (ACCCGUA)

              1.427

              −1.48

              1,2,3

              FGFR3

              fibroblast growth factor receptor 3

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-128 (CACAGUG)

              1.184

              −1.345

              1,2

              TXNIP

              thioredoxin interacting protein

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-128 (CACAGUG)

              1.184

              −1.345

              2,3

              TGFBR1

              transforming growth factor, beta receptor 1

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-128 (CACAGUG)

              1.184

              −1.345

              1,2

              LDLR

              low density lipoprotein receptor

              response to steroid hormone stimulus

              6.24E-07

              4.65E-05

              miR-128 (CACAGUG)

              1.184

              −1.345

              1,2

              E2F3

              E2F transcription factor 3

              positive regulation of cell proliferation

              1.21E-08

              1.67E-06

              miR-128 (CACAGUG)

              1.184

              −1.345

              1,2

              ADORA2B

              adenosine A2b receptor

                 

              Ingenuity Pathway Analysis (Ingenuity® Systems, http://​www.​ingenuity.​com). MiRNA Target Filter was applied using the strictest criteria (experimentally observed microRNA/gene targets only) filtered for genes previously identified for involvement in endocrine system disorders. Each of the seven miRNAs has multiple gene targets. Fold changes between groups as determined by Illumina miRNA array measurements are shown. Ingenuity target identifications are generated from multiple databases (Source). Pathway enrichments were calculated for the entire gene set using the NIAID DAVID functional enrichment tool [31, 32]. Genes that feature in both the cellular proliferation and the steroid hormone pathways are in bold (KRAS, BCL2, TGFBR1).

              [ILL-FC] = Illumina array-fold change; Source = 1.miRecords, 2.TargetScan Human, 3.Ingenuity Expert Findings, 4.TarBase; FDR = False Discover Rate.

              Discussion

              In the past few years, the field of miRNA research has evolved rapidly. Various studies have provided strong evidence for the widespread expression and the regulatory functions of miRNAs on gene expression under either physiologic or pathologic conditions. MicroRNAs have now been recognized as key players in the process of cell proliferation and differentiation. Global analysis of miRNAs in human tissues have showed that, in addition to the brain, the uterus, the cervix, and the ovaries have the highest restricted enrichment in individual miRNAs [34]. The identification of miRNA as well as the functional analysis of individual expressed miRNA in the uterus has shed light onto the cycling changes that occur in response to steroids and during pregnancy. The impact of the ovarian steroids on miRNA expression and regulation in the uterus has been evidenced by the fact that treatment with 17β estradiol or RU-486 resulted in differential regulation of miRNAs in the myometrium and leiomyomas [35].

              In the present study, we have examined 526 different miRNAs in the human endometrium following COS and identified a rich number of miRNAs with at least 2 fold changes in the level of expression during the luteal phase (Figure 2, Additional file 1: Table S1). Statistical analysis identified that the changes were significant (p < 0.05) for 216 of miRNAs ( Additional file 1: Table S1). These changes were observed not only in the within the group analysis at different times during luteal phase (comparison between day 0 and day 3–5) but also in the analysis between groups at the same time frame (comparison between the treatment groups at day 3–5). As demonstrated in Figure 1and Figure 2, there was a substantial increase in miRNA expression in the groups treated with progesterone alone as compared to the no supplementation group. In genome-wide identification of endometrial miRNA in natural and stimulated cycles reported by Sha et al.[36], 22 miRNAs were significantly dysregulated on the day of hCG + 7 in stimulated cycles as compared with day of LH + 7 in natural cycles. Among those, 11 miRNAs exhibited putative estrogen response elements or progesterone response elements in the promoters. In a study of examining gene expression profile in natural cycle and stimulated cycles during luteal phase (LH + 2 or 7; hCG + 2 or 7), Haouzi et al.[37] demonstrated that COS regimens altered endometrial receptivity in comparison with natural cycle. These and our studies indicate that ovarian stimulation or altered steroid hormone levels may affect miRNA profiles, consequently, affect endometrial receptivity. Furthermore, we found that the addition of estradiol in the regimen resulted in a significant attenuation of effect of progestone (Figure 1, Figure 2) on the level of miRNA expression. These findings support the notion that the well known anti-proliferative effect of progesterone on the endometrium could be possibly exerted by a localized increase in miRNA expression. The addition of estradiol at the same time could reverse this effect partially by attenuating this increase. Whether this effect is directly or indirectly associated with ovarian stimulation or the type of drug delivery for luteal support (estradiol was administered orally whereas progesterone was administered vaginally in this study) requires further investigation.

              By microarray, Northen blot and in situ hybridization, Hu et al. [38] was able to identify eight specific miRNAs that were significantly up-regulated at implantation sites. Chakrabarty et al. have showed in the mouse uterus, that two specific miRNAs, the mmu-miR-101a and the mmu-miR-199a*, were differentially expressed during implantation in coordination with the expression of cyclooxygenase-2(Cox-2), a gene critical for implantation [39]. Studies on temporal and spatial regulation of miRNAs in the rat uterus, during embryo implantation, have identified the let-7a and mir-320 specifically in the uterine endometrium with higher expression level on gestation day 6–7 [26, 27]. These evidences and our findings of differential expression of miRNAs in the peri-implantation period with and without luteal phase support suggest role(s) of miRNAs during the remodeling process of endometrium in association with implantation.

              Neo-angiogenesis is a pivotal process in reproductive function where it regulates endometrial regeneration, corpus luteum formation and finally placentation. The regulatory function of miRNAs in the process of neo-angiogenesis has been illustrated in several in vitro and in vivo models [9]. For example, the role of miRNAs in the neo-angiogenesis has been reported in experiments with Dicerex ½ mouse embryos (altered function of Dicer required for miRNA processing) which suffer from defective angiogenesis, due to disruption in the expression of vascular endothelial growth factor (VEGF) as well as to its receptor flt-1 [40]. We have noticed in our study that several miRNAs including miR-520 g, miR-369-3p, and miR-186 (Table 2), with VEGF as predicted target gene, were differentially regulated during the peri-implantation period. More specifically there was a significant increase in the expression of miR-520 g in the group that received only progesterone as compared to the other groups. In contrast, in the same group, there was a pronounced suppression of miR-221, which is known to regulate endothelial nitric oxide synthase, one of the key regulators of endothelial biology and angiogenesis [41]. Whereas our findings support the regulatory effect of miRNAs in the process of neo-angiogenesis, the precise impact of this action remains obscure. Individual targets of specific miRNAs responsible for the phenotypes have been proposed in experimental settings, although it is likely that many miRNAs function through cooperative regulation of multiple mRNAs [7]. Indeed, Revel et al. evaluated the expression of miRNAs in the secretory endometrium of repeated implantation failure patients and identified 13 miRNAs were differentially expressed (10 were overexpressed and 3 were underexpressed), which putatively regulated the expression of 3800 genes.

              In addition, in this study, based on the most stringent criteria requiring experimental observations, IPA miRNA Target analysis for cross validated microRNAs identified 7 out of 9 miRNAs and their gene targets which were further subjected for pathway analysis. The results revealed significant involvement of genes of extracellular matrix, cell proliferation, and response to steroid hormone stimulus from day 0 to day 3–5 after oocyte retrieval in a group with no steroid support (Table 3). Conversely, this effect was almost completely abolished by supplementation of progesterone and estrogen (Table 3, GrpsIIc-IIa) for genes of cellular proliferation and response to steroid hormones bur not for genes of extracellular matrix.

              Under the influence of the ovarian steroids the human endometrium undergoes cyclic changes. Estradiol promotes epithelial cell proliferation, while progesterone inhibits this estrogen-induced effect, promotes differentiation, and has decidualizing effects on endometrial stroma later in the secretary phase. We hypothesize that ovarian steroids may regulate multiple genes related to the uterine tissue remodeling and endometrial receptivity, at least in part, through modulating miRNA expression profiles.

              We realize that there are several limitations in this study. The relatively small sample size due to limited number of donors that have agreed to participate could represent one of those. Unfortunately due to the design of our experiment it was extremely difficult to obtain more specimens. Furthermore, due to the fact that the same women were biopsied twice during the same COS cycle the first biopsy may induce gene expression differences that are likely to be reflected in the miRNA expression profile of the second biopsy. Additional group(s) with only one biopsy for each subject for a given group and given day of biopsy would provide another layer of control to strengthen the findings in this study. On the other hand, the limited sample size also reflects the difficulty in obtaining these samples. In addition, although group II contains 3 samples in each sub-group, there are 2 samples from day 3 and 1 sample from day 5 which may potentially affect miRNA profiles. However, after normalization and careful comparison, samples from day 3 and day 5 showed similar expression level on miRNAs profile in the same treatment group. Since day 3–5 are all in mid-secretory period of the cycle, we combined day 3 and day5 samples as one stage of the luteal phase for analysis.

              Despite these limitations nevertheless, our array-based global miRNA profiling describes, for the first time, the miRNA expression profile in the human endometrium during the luteal phase following COS for IVF and luteal support with steroid supplementation. We have shown that this profile is under considerable influence by ovarian steroids, even though the molecular mechanism of this interaction still remains unclear. Importantly, several miRNAs found to have enriched or depleted transcript load during the luteal phase may have specific roles in the control of endometrial receptivity. Further studies are necessary to create a detailed expression profile for these miRNAs in relation to their target genes in the endometrium throughout the natural cycle as well as the stimulated cycle for IVF. We plan to further investigate several significantly regulated miRNAs and associated target gene pathways in relation to endometrial receptivity and implantation. Functional study will also be designed to link the imperative miRNAs in potential clinical applications.

              Conclusions

              The array-based study presented here has revealed several findings: 1) there is an expression of a unique set of miRNAs in the endometium following controlled ovarian stimulation; 2) the level of expression for these miRNAs undergoes significant changes during the peri-implantation period; 3) the expression is influenced by ovarian steroids; 4) expression of miRNAs may be associated with target genes and gene pathways. The miRNAs found to have enriched or depleted transcript load during the luteal phase may have specific roles in the control of endometrial receptivity during the peri- implantation period through regulation of their target genes. Further studies are necessary to create a detailed expression profile for these miRNAs as well as their associated target genes throughout the natural cycle and the stimulated cycle for IVF in the endometrium. Studies for specifically regulated miRNAs and their target genes as well specific gene pathways in relation to endometrial receptivity and implantation are also proposed.

              Abbreviations

              miRNA: 

              MicroRNAs

              COS: 

              Controlled ovarian stimulation

              GnRH: 

              Gonadotropic releasing hormones

              IVF: 

              In vitro fertilization

              hCG: 

              Human chorionic gonadotropin

              LH: 

              Luteinizing hormone

              FSH: 

              Follicle-stimulating hormone

              P: 

              Progesterone

              P + E: 

              Progesterone plus 17-beta-estradiol

              IPA: 

              Ingenuity pathway analysis.

              Declarations

              Acknowledgement

              This study was supported by Schering - Plough Research Institute grant #90048620.

              We thank Johns Hopkins REI fellows for endometrial biopsies and Ms Tonya Watkins of Department of Medicine for technical assistance in microarray analysis.

              Authors’ Affiliations

              (1)
              Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine
              (2)
              Department of Medicine, Johns Hopkins University School of Medicine
              (3)
              Department of Obstetrics and Gynecology, The First Affiliated Hospital, Harbin Medical University
              (4)
              2nd Department of Obstetrics and Gynecology, Aretaieion Hospital, University of Athens School of Medicine

              References

              1. Bueno MJ, de Castro Pérez I, Malumbres M: Control of cell proliferation pathways by microRNAs. Cell Cycle. 2008, 20: 3143-3148.View Article
              2. Engels BM, Hutvagner G: Principles and effects of microRNA-mediated post-transcriptional gene regulation. Oncogene. 2006, 25: 6163-6169. 10.1038/sj.onc.1209909.View ArticlePubMed
              3. Jovanovic M, Hengartner MO: miRNAs and apoptosis: RNAs to die for. Oncogene. 2006, 25: 6176-6187. 10.1038/sj.onc.1209912.View ArticlePubMed
              4. Friedman RC, Farh KK, Burge CB, Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009, 19: 92-105.PubMed CentralView ArticlePubMed
              5. Ambros V, Chen X: The regulation of genes and genomes by small RNAs. Development. 2007, 134: 1635-1641. 10.1242/dev.002006.View ArticlePubMed
              6. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004, 116: 281-297. 10.1016/S0092-8674(04)00045-5.View ArticlePubMed
              7. Lim LP, Lau NC, Garrett-Engele P, Grimson A, Schelter JM, Castle J, Bartel DP, Linsley PS, Johnson JM: Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature. 2005, 433: 769-773. 10.1038/nature03315.View ArticlePubMed
              8. Revel A, Achache H, Stevens J, Smith Y, Reich R: MicroRNAs are associated with human embryo implantation defects. Hum Reprod. 2011, 26: 2830-2840. 10.1093/humrep/der255.View ArticlePubMed
              9. Pan Q, Luo X, Toloubeydokhti T, Chegini N: The expression profile of micro-RNA in endometrium and endometriosis and the influence of ovarian steroids on their expression. Mol Hum Reprod. 2007, 13 (11): 797-806. 10.1093/molehr/gam063.View ArticlePubMed
              10. Pan Q, Chegini N: MicroRNA signature and regulatory functions in the endometrium during normal and disease states. Semin Reprod Med. 2008, 26: 479-493. 10.1055/s-0028-1096128.PubMed CentralView ArticlePubMed
              11. Ohlsson Teague EM, Van der Hoek KH, Van der Hoek MB, Perry N, Wagaarachchi P, Robertson SA, Print CG, Hull LM: MicroRNA-regulated pathways associated with endometriosis. Mol Endocrinol. 2009, 23: 265-275.View ArticlePubMed
              12. Hawkins SM, Creighton CJ, Han DY, Zariff A, Anderson ML, Gunaratne PH, Matzuk MM: Functional MicroRNA involved in endometriosis. Mol Endocrinol. 2011, 25: 821-832. 10.1210/me.2010-0371.PubMed CentralView ArticlePubMed
              13. Ohlsson Teague EM, Print CG, Hull ML: The role of microRNAs in endometriosis and associated reproductive conditions. Hum Reprod Update. 2010, 16: 142-165. 10.1093/humupd/dmp034.View Article
              14. Kovalevsky G, Patrizio P: High rates of embryo wastage with use of assisted reproductive technology: a look at the trends between 1995 and 2001 in the United States. Fertil Steril. 2005, 84: 325-330. 10.1016/j.fertnstert.2005.04.020.View ArticlePubMed
              15. Tavaniotou A, Albano C, Smitz J, Devroey P: Comparison of LH concentrations in the early and mid-luteal phase in IVF cycles after treatment with HMG alone or in association with the GnRH antagonist Cetrorelix. Hum Reprod. 2001, 16: 663-667. 10.1093/humrep/16.4.663.View ArticlePubMed
              16. Pabuccu R, Akar ME: Luteal phase support in assisted reproductive technology. Curr Opin Obstet Gynecol. 2005, 17: 277-281. 10.1097/01.gco.0000169105.62257.e3.View ArticlePubMed
              17. Posaci C, Smitz J, Camus M, Osmanagaoglu K, Devroey P: Progesterone for the luteal support of assisted reproductive technologies: clinical options. Hum Reprod Suppl. 2000, 1: 129-148.View Article
              18. Pritts EA, Atwood AK: Luteal phase support in infertility treatment: a meta-analysis of the randomized trials. Hum Reprod. 2002, 17: 2287-2299. 10.1093/humrep/17.9.2287.View ArticlePubMed
              19. Kolibianakis EM, Venetis CA, Papanikolaou EG, Diedrich K, Tarlatzis BC, Griesinger G: Estrogen addition to progesterone for luteal phase support in cycles stimulated with GnRH analogues and gonadotrophins for IVF: a systematic review and meta-analysis. Hum Reprod. 2008, 23: 1346-1354. 10.1093/humrep/den115.View ArticlePubMed
              20. Navot D, Veeck LL, Scott RT, Lui HC, Droesch K, Rosenwaks Z: The window of embryo transfer and efficiency of human conception in vitro. Ferti Steril. 1991, 55: 114-118.
              21. Zhao Y, Garcia J, Kolp L, Cheadle C, Rodriguez A, Vlahos NF: The impact of luteal phase support on gene expression of extracellular matrix protein and adhesion molecules in the human endometrium during the window of implantation following controlled ovarian stimulation with a GnRH antagonist protocol. Fertil Steril. 2010, 94: 2264-2271. 10.1016/j.fertnstert.2010.01.068.View ArticlePubMed
              22. Liu Y, Lee KF, Ng EH, Yeung WS, Ho PC: Gene expression profiling of human peri-implantation endometria between natural and stimulated cycles. Fertil Steril. 2008, 90: 2152-2164. 10.1016/j.fertnstert.2007.10.020.View ArticlePubMed
              23. Reddy KV, Mangale SS: Integrin receptors: the dynamic modulators of endometrial function. Tissue Cell. 2003, 35: 260-273. 10.1016/S0040-8166(03)00039-9.View ArticlePubMed
              24. Kuokkanen S, Chen B, Ojalvo L, Benard L, Santoro N, Pollard JW: Genomic profiling of microRNAs and messenger RNAs reveals hormonal regulation in microRNA expression in human endometrium. Biol Reprod. 2010, 82: 791-801. 10.1095/biolreprod.109.081059.PubMed CentralView ArticlePubMed
              25. Qian K, Hu L, Chen H, Li H, Liu N, Li Y, Ai J, Zhu G, Tang Z, Zhang H: Hsa-miR-222 is involved in differentiation of endometrial stromal cells in vitro. Endocrinology. 2009, 150: 4734-4743. 10.1210/en.2008-1629.View ArticlePubMed
              26. Xia HF, Jin XH, Song PP, Cui Y, Liu CM, Ma X: Temporal and spatial regulation of miR-320 in the uterus during embryo implantation in the Rat. Int J Mol Sci. 2010, 11: 719-730. 10.3390/ijms11020719.PubMed CentralView ArticlePubMed
              27. Xia HF, Jin XH, Song PP, Cui Y, Liu CM, Ma X: Temporal and spatial regulation of Let-7a in the uterus during embryo implantation in the Rat. J Reprod Dev. 2010, 56: 73-78. 10.1262/jrd.09-088K.View ArticlePubMed
              28. Altmäe S, Martinez-Conejero JA, Esteban FJ, Ruiz-Alonso M, Stavreus-Evers A, Horcajadas JA, Salumets A: MicroRNAs miR-30b, miR-30d, and miR-494 Regulate Human Endometrial Receptivity. Reprod Sci. 2012, [Epub ahead of print]
              29. American Society for Reproductive Medicine: Guidelines for oocyte donation. Fertil Steril. 2002, 77 (Suppl 5): S6-S8.
              30. Vlahos NF, Lipari CW, Bankowski B, Lai TH, King JA, Shih IM, Fragakis K, Zhao Y: Effect of luteal-phase support on endometrial L-selectin ligand expression after recombinant follicle-stimulating hormone and ganirelix acetate for in vitro fertilization. J Clin Endocrinol Metab. 2006, 91: 4043-4049. 10.1210/jc.2006-0520.View ArticlePubMed
              31. Huang DW, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Protoc. 2009, 4: 44-57.View Article
              32. Huang DW, Sherman BT, Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Re. 2009, 37: 1-13. 10.1093/nar/gkn923.View Article
              33. Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)). Methods. 2001, 25: 402-408. 10.1006/meth.2001.1262.View ArticlePubMed
              34. Shingara J, Keiger K, Shelton J, Laosinchai-Wolf W, Powers P, Conrad R, et al: An optimized isolation and labeling platform for accurate microRNA expression profiling. RNA. 2005, 11: 1461-1470. 10.1261/rna.2610405.PubMed CentralView ArticlePubMed
              35. Pan Q, Luo X, Chegini N: Differential expression of microRNAs in myometrium and leiomyomas and regulation by ovarian steroids. J Cell Mol Med. 2008, 12: 227-240.PubMed CentralView ArticlePubMed
              36. Sha AG, Liu JL, Jiang XM, Ren JZ, Ma CH, Lei W, Su RW, Yang ZM: Genome-wide identification of micro-ribonucleic acids associated with human endometrial receptivity in natural and stimulated cycles by deep sequencing. Fertil Steril. 2011, 96: 150-155. 10.1016/j.fertnstert.2011.04.072.View ArticlePubMed
              37. Haouzi D, Assou S, Mahmoud K, Tondeur S, Rème T, Hedon B, De Vos J, Hamamah S: Gene expression profile of human endometrial receptivity: comparison between natural and stimulated cycles for the same patients. Hum Reprod. 2009, 24: 1436-1445. 10.1093/humrep/dep039.PubMed CentralView ArticlePubMed
              38. Hu S, Ren G, Liu JL, Zhao ZA, Yu YS, Su RW, Ma XH, Ni H, Lei W, Yang ZM: MicroRNA Expression and Regulation in Mouse Uterus during Embryo Implantation. J Bio Chem. 2008, 283: 23473-23484. 10.1074/jbc.M800406200.View Article
              39. Chakrabarty A, Tranguch S, Daikoku T, Jensen K, Furneaux H, Dey S: MicroRNA Regulation of cyclooxygenase-2 during embryo implantation. PNAS. 2007, 104: 15144-15149. 10.1073/pnas.0705917104.PubMed CentralView ArticlePubMed
              40. Yang WJ, Yang DD, Na S, Sandusky GE, Zhang Q, Zhao G: Dicer is required for embryonic angiogenesis during mouse development. J Biol Chem. 2005, 280: 9330-9335.View ArticlePubMed
              41. Suárez Y, Fernández-Hernando C, Pober JS, Sessa WC: Dicer dependent microRNAs regulate gene expression and functions in human endothelial cells. Circ Res. 2007, 100: 1164-1173. 10.1161/01.RES.0000265065.26744.17.View ArticlePubMed

              Copyright

              © Zhao et al.; licensee BioMed Central Ltd. 2012

              This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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