Diverse endometrial mRNA signatures during the window of implantation in patients with repeated implantation failure

Enrichment of cell cycle pathways in progesterone-treated endometrial organoids of infertile women compared to fertile women

PURPOSE

To investigate whether the transcriptome profile differs between progesterone-treated infertile and fertile endometrial organoids.

METHODS

Endometrial biopsies were obtained from 14 infertile and seven fertile women, after which organoids were generated from isolated epithelial cells. To mimic the secretory phase, organoids were sequentially treated with 17β-estradiol (E2) and progesterone (P4) and subjected to RNA sequencing. Differentially expressed genes (DEGs) were identified using DESeq2 (lfcThreshold = 0, log2 Fold Change ≥ 1.0 or ≤ -1.0), and a principal component analysis (PCA) plot was generated. Functional enrichment analysis was performed by overrepresentation analysis and Gene Set Enrichment Analysis (GSEA). To functionally assess proliferation, OrganoSeg surface measurements were performed before (T0) and after (T1) differentiation of organoids, and T1/T0 ratios were calculated to determine the proliferation rate.

RESULTS

Although the PCA plot did not show clear clustering of the fertile and infertile samples, 363 significant DEGs (129 upregulated and 234 downregulated) were detected in infertile compared to fertile organoids. Mainly cell cycle processes were highly enriched in infertile organoids. Thus, we hypothesised that proliferative activity during differentiation may be higher in infertile organoids compared to fertile organoids. However, this could not be validated by cell surface measurements.

CONCLUSIONS

This study revealed that cell cycle processes were enriched in E2/P4-treated infertile endometrial organoids as compared to fertile organoids. This could reflect persistently higher proliferative activity of the endometrial epithelial cells in differentiated infertile organoids compared to fertile organoids. To confirm this hypothesis, further studies are warranted.

The endometrial transcriptome of infertile women with and without implantation failure

INTRODUCTION

Implantation failure after transferring morphologically "good-quality" embryos in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) may be explained by impaired endometrial receptivity. Analyzing the endometrial transcriptome analysis may reveal the underlying processes and could help in guiding prognosis and using targeted interventions for infertility. This exploratory study investigated whether the endometrial transcriptome profile was associated with short-term or long-term implantation outcomes (ie success or failure).

MATERIAL AND METHODS

Mid-luteal phase endometrial biopsies of 107 infertile women with one full failed IVF/ICSI cycle, obtained within an endometrial scratching trial, were subjected to RNA-sequencing and differentially expressed genes analysis with covariate adjustment (age, body mass index, luteinizing hormone [LH]-day). Endometrial transcriptomes were compared between implantation failure and success groups in the short term (after the second fresh IVF/ICSI cycle) and long term (including all fresh and frozen cycles within 12 months). The short-term analysis included 85/107 women (33 ongoing pregnancy vs 52 no pregnancy), excluding 22/107 women. The long-term analysis included 46/107 women (23 'fertile' group, ie infertile women with a live birth after ≤3 embryos transferred vs 23 recurrent implantation failure group, ie no live birth after ≥3 good quality embryos transferred), excluding 61/107 women not fitting these categories. As both analyses drew from the same pool of 107 samples, there was some sample overlap. Additionally, cell type enrichment scores and endometrial receptivity were analyzed, and an endometrial development pseudo-timeline was constructed to estimate transcriptomic deviations from the optimum receptivity day (LH + 7), denoted as ΔWOI (window of implantation).

RESULTS

There were no significantly differentially expressed genes between implantation failure and success groups in either the short-term or long-term analyses. Principal component analysis initially showed two clusters in the long-term analysis, unrelated to clinical phenotype and no longer distinct following covariate adjustment. Cell type enrichment scores did not differ significantly between groups in both analyses. However, endometrial receptivity analysis demonstrated a potentially significant displacement of the WOI in the non-pregnant group compared with the ongoing pregnant group in the short-term analysis.

CONCLUSIONS

No distinct endometrial transcriptome profile was associated with either implantation failure or success in infertile women. However, there may be differences in the extent to which the WOI is displaced.

Current Status of Ovarian and Endometrial Biomarkers in Predicting ART Outcomes

This review evaluates the role of ovarian and endometrial biomarkers in predicting outcomes in assisted reproductive technology (ART). It highlights established ovarian biomarkers such as the anti-Müllerian hormone (AMH) and follicle-stimulating hormone (FSH), alongside emerging ones like growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15), connexin, and granulosa cell gene profiles. Additionally, the paper explores endometrial biomarkers such as ERA, BCL6, and immune markers, as well as the potential for genomic and proteomic technologies in customizing implantation. It concludes that while many of these biomarkers show promise, their clinical integration requires rigorous research and validation to confirm their safety and utility in ART.

Meta-analysis of endometrial transcriptome data reveals novel molecular targets for recurrent implantation failure

PURPOSE

Gene expression analysis of the endometrium has been shown to be a useful approach for identifying the molecular signatures and pathways involved in recurrent implantation failure (RIF). Nevertheless, individual studies have limitations in terms of study design, methodology and analysis to detect minor changes in expression levels or identify novel gene signatures associated with RIF.

METHOD

To overcome this, we conducted an in silico meta-analysis of nine studies, the systematic collection and integration of gene expression data, utilizing rigorous selection criteria and statistical techniques to ensure the robustness of our findings.

RESULTS

Our meta-analysis successfully unveiled a meta-signature of 49 genes closely associated with RIF. Of these genes, 38 were upregulated and 11 downregulated in RIF patients' endometrium and believed to participate in key processes like cell differentiation, communication, and adhesion. GADD45A, IGF2, and LIF, known for their roles in implantation, were identified, along with lesser-studied genes like OPRK1, PSIP1, SMCHD1, and SOD2 related to female infertility. Many of these genes are involved in MAPK and PI3K-Akt pathways, indicating their role in inflammation. We also investigated to look for key miRNAs regulating these 49 dysregulated mRNAs as potential diagnostic biomarkers. Along with this, we went to associate protein-protein interactions of 49 genes, and we could recognize one cluster consisting of 11 genes (consisted of 22 nodes and 11 edges) with the highest score (p = 0.001). Finally, we validated some of the genes by qRT-PCR in our samples.

CONCLUSION

In summary, the meta-signature genes hold promise for improving RIF patient identification and facilitating the development of personalized treatment strategies, illuminating the multifaceted nature of this complex condition.

lncRNA TTTY14 participates in the progression of repeated implantation failure by regulating the miR-6088/SEMA5A axis

PURPOSE

To identify potential biomarkers and the molecular mechanisms associated with repeated implantation failure (RIF), three microarray datasets, GSE71331 (lncRNA + mRNA), GSE111974 (lncRNA + mRNA), and GSE71332 (miRNA), were retrieved from the Gene Expression Omnibus (GEO) database.

METHODS

The differentially expressed mRNAs (DEMs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between normal control samples (C group) and RIF samples (RIF group) were identified, and then a module partition analysis was performed based on weighted correlation network analysis (WGCNA). Following enrichment analysis of the genes, the lncRNA-miRNA-mRNA interactions (ceRNA) were examined. The mRNAs in the ceRNA network were evaluated using the GSE58144 dataset. Finally, the key RNAs were verified using reverse transcription-quantitative polymerase chain reaction (RT-qPCR).

RESULTS

Fifty-three DEmiRNAs, 327 DEMs, and 13 DElncRNAs were identified between the C and RIF groups. According to WGCNA, the magenta module was positively correlated with RIF disease status. The lncRNA-mRNA interaction analysis based on genes in the magenta module revealed the intersecting lncRNAs, including peptidylprolyl isomerase E-like pseudogene (PPIEL) and the testis-specific transcript, y-Linked 14 (TTTY14); these lncRNAs are mainly involved in functions, such as plasma membrane organization. The ceRNA network analysis revealed several interactions, such as TTTY14-miR-6088-semaphorin 5 A (SEMA5A). Finally, SEMA5A and the zinc finger protein 555 (ZNF555) were identified to be significantly upregulated in the RIF group compared with those in the C group in the GSE58144 dataset. The RT-qPCR results aligned with the above results.

CONCLUSIONS

Overall, TTTY14, ZNF555, SEMA5A, PPIEL, and miR-6088 could serve as novel biomarkers of RIF.

An unbiased approach of molecular characterization of the endometrium: toward defining endometrial-based infertility

Infertility is a complex condition affecting millions of couples worldwide. The current definition of infertility, based on clinical criteria, fails to account for the molecular and cellular changes that may occur during the development of infertility. Recent advancements in sequencing technology and single-cell analysis offer new opportunities to gain a deeper understanding of these changes. The endometrium has a potential role in infertility and has been extensively studied to identify gene expression profiles associated with (impaired) endometrial receptivity. However, limited overlap among studies hampers the identification of relevant downstream pathways that could play a role in the development of endometrial-related infertility. To address these challenges, we propose sequencing the endometrial transcriptome of healthy and infertile women at the single-cell level to consistently identify molecular signatures. Establishing consensus on physiological patterns in endometrial samples can aid in identifying deviations in infertile patients. A similar strategy has been used with great success in cancer research. However, large collaborative initiatives, international uniform protocols of sample collection and processing are crucial to ensure reliability and reproducibility. Overall, the proposed approach holds promise for an objective and accurate classification of endometrial-based infertility and has the potential to improve diagnosis and treatment outcomes.

Deciphering a shared transcriptomic regulation and the relative contribution of each regulator type through endometrial gene expression signatures

BACKGORUND

While various endometrial biomarkers have been characterized at the transcriptomic and functional level, there is generally a poor overlap among studies, making it unclear to what extent their upstream regulators (e.g., ovarian hormones, transcription factors (TFs) and microRNAs (miRNAs)) realistically contribute to menstrual cycle progression and function. Unmasking the intricacies of the molecular interactions in the endometrium from a novel systemic point of view will help gain a more accurate perspective of endometrial regulation and a better explanation the molecular etiology of endometrial-factor infertility.

METHODS

An in-silico analysis was carried out to identify which regulators consistently target the gene biomarkers proposed in studies related to endometrial progression and implantation failure (19 gene lists/signatures were included). The roles of these regulators, and of genes related to progesterone and estrogens, were then analysed in transcriptomic datasets compiled from samples collected throughout the menstrual cycle (n = 129), and the expression of selected TFs were prospectively validated in an independent cohort of healthy participants (n = 19).

RESULTS

A total of 3,608 distinct genes from the 19 gene lists were associated with endometrial progression and implantation failure. The lists' regulation was significantly favoured by TFs (89% (17/19) of gene lists) and progesterone (47% (8 /19) of gene lists), rather than miRNAs (5% (1/19) of gene lists) or estrogen (0% (0/19) of gene lists), respectively (FDR < 0.05). Exceptionally, two gene lists that were previously associated with implantation failure and unexplained infertility were less hormone-dependent, but primarily regulated by estrogen. Although endometrial progression genes were mainly targeted by hormones rather than non-hormonal contributors (odds ratio = 91.94, FDR < 0.05), we identified 311 TFs and 595 miRNAs not previously associated with ovarian hormones. We highlight CTCF, GATA6, hsa-miR-15a-5p, hsa-miR-218-5p, hsa-miR-107, hsa-miR-103a-3p, and hsa-miR-128-3p, as overlapping novel master regulators of endometrial function. The gene expression changes of selected regulators throughout the menstrual cycle (FDR < 0.05), dually validated in-silico and through endometrial biopsies, corroborated their potential regulatory roles in the endometrium.

CONCLUSIONS

This study revealed novel hormonal and non-hormonal regulators and their relative contributions to endometrial progression and pathology, providing new leads for the potential causes of endometrial-factor infertility.

Homocysteine serum levels correlate with the number of failed IVF cycles even when within normal range

INTRODUCTION

Repeated implantation failure is a common challenge in daily practice. Homocysteine and vitamin B12 have been associated with reproductive processes among patients undergoing in vitro fertilization; however, their involvement in repeated implantation failure has not been assessed. We explored possible associations of serum homocysteine and vitamin B12 with repeated implantation failure.

MATERIAL AND METHODS

A retrospective analysis of 127 women who underwent ≥ 3 unsuccessful embryo transfers during 2005-2016, at the Fertility and In Vitro Fertilization Unit at Carmel Medical Center. After at least 3 IVF failures serum levels of homocysteine and vitamin B12 were measured.

RESULTS

The mean patient age was 33.5 ± 5.2 years. The mean number of embryo transfers was 4.6 ± 1.5. The mean total cumulative number of embryos transferred was 10.4 ± 5.2. Mean serum levels of homocysteine were 8.6 ± 3.7 µM/L, and of vitamin B12 were 302.5 ± 155.3 pg/ml. Homocysteine levels were within the normal range (< 14 µM/L) in 95.8% of the patients. Yet, the levels of homocysteine correlated with both the number of failed embryo transfers (r = 0.34, p = 0.004) and the total cumulative number of transferred embryos (r = 0.36, p = 0.002).

CONCLUSIONS

Our findings suggest an association between serum homocysteine levels and the occurrence of repeated implantation failure, even when homocystein levels were within the normal range. It should be studied whether nutritional supplementation to modulate serum homocysteine levels may improve treatment outcome.

Screening genes related to embryo implantation in Dazu black goats (Capra Hircus) by morphological and transcriptome analyses

Embryo implantation is a critical step in the establishment of pregnancy. However, the mechanisms of embryo implantation during early pregnancy in goats remain unclear due to the lack of published studies examining the genes involved in embryo implantation. As a popular goat breed in southwest China, Dazu black goats (DBGs) are highly adaptable and exhibit high fertility, making this breed a good model in which to study reproductive performance of goats. Here, morphological analysis showed that compared with the non-pregnant (NP) groups, the endometrial thickness of the goats in the P15 and P19 groups (15 and 19-day pregnant groups, respectively) were increased (P < 0.01). Proliferating Cell Nuclear Antigen (PCNA) staining showed that PCNA was expressed in the NP, P15, and P19 groups. Transcriptome analysis was then conducted to identify gene expression patterns in uterine tissue during DBG embryo implantation. By comparing uterine tissue at different stages of embryonic implantation, 48 in NP_vs._P15, 318 in NP_vs._P19, and 1439 in P15_vs._P19, differentially expressed mRNAs were identified. Gene Ontology (GO) enrichments of the differentially expressed genes were enriched in the extracellular region, extracellular space, transporter activity, extracellular region, immune system process, immune response, and defense response etc. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the biological metabolic pathways with which the differentially expressed genes are associated were explored. Through KEGG analysis, the DBGs were associated with oxidative phosphorylation, complement and coagulation cascades, arginine and proline metabolism, metabolic pathways, arachidonic acid metabolism, and ECM-receptor interaction. These candidate genes (CSF1, C1S, CST6, SLC24A4, HOXA10, HOXA11, MMP9, and ITGA11) and enriched signaling pathways could be valuable references for exploring the molecular mechanisms underlying goat embryo implantation.

Identification of key genes and immune cell infiltration in recurrent implantation failure: A study based on integrated analysis of multiple microarray studies

PROBLEM

Recurrent implantation failure (RIF) refers to a challenging topic in assisted reproductive technology (ART), the etiology of which may be attributed to impaired endometrial receptivity; however, the precise pathogenesis of RIF has not been thoroughly elucidated.

METHOD OF STUDY

Four RIF microarray datasets were obtained from the Gene Expression Omnibus database and integrated by the "sva" R package. The differentially expressed genes (DEGs) were analyzed using the "limma" package and then GO, KEGG, GSEA, and GSVA were applied to perform functional and pathway enrichment analysis. The immune cell infiltration in the RIF process was evaluated by the CIBERSORT algorithm. Finally, the hub genes were identified through the CytoHubba and subsequently verified using two items of external endometrial data.

RESULTS

236 genes were differentially expressed in the endometrium of the RIF group. Functional enrichment analysis demonstrated that the biological functions of DEGs were mainly correlated to the immune-related pathways, including immune response, TNF signaling pathway, complement and coagulation cascades. Among the immune cells, γδ T cells decreased significantly in the endometrium of RIF patients. In addition, the key DEGs such as PTGS2, FGB, MUC1, SST, VCAM1, MMP7, ERBB4, FOLR1, and C3 were screened and identified as the hub genes involved in the pathogenesis of RIF.

CONCLUSIONS

Abnormal immune response regulation of endometrium contributes to the occurrence of RIF, and γδ T cells may be the pivotal immune cells causing RIF. At the same time, the novel hub genes identified will provide effective targets for the prediction and therapy of RIF.

Contributions of artificial intelligence reported in Obstetrics and Gynecology journals: a systematic review

Background

The applications of artificial intelligence (AI) processes have grown significantly in all medical disciplines during the last decades. Two main types of AI have been applied in medicine: symbolic AI (eg, knowledge base and ontologies) and nonsymbolic AI (eg, machine learning and artificial neural networks). Consequently, AI has also been applied across most obstetrics and gynecology (OB/GYN) domains, including general obstetrics, gynecology surgery, fetal ultrasound, and assisted reproductive medicine, among others.

Objective

The aim of this study was to provide a systematic review to establish the actual contributions of AI reported in OB/GYN discipline journals.

Methods

The PubMed database was searched for citations indexed with “artificial intelligence” and at least one of the following medical subject heading (MeSH) terms between January 1, 2000, and April 30, 2020: “obstetrics”; “gynecology”; “reproductive techniques, assisted”; or “pregnancy.” All publications in OB/GYN core disciplines journals were considered. The selection of journals was based on disciplines defined in Web of Science. The publications were excluded if no AI process was used in the study. Review, editorial, and commentary articles were also excluded. The study analysis comprised (1) classification of publications into OB/GYN domains, (2) description of AI methods, (3) description of AI algorithms, (4) description of data sets, (5) description of AI contributions, and (6) description of the validation of the AI process.

Results

The PubMed search retrieved 579 citations and 66 publications met the selection criteria. All OB/GYN subdomains were covered: obstetrics (41%, 27/66), gynecology (3%, 2/66), assisted reproductive medicine (33%, 22/66), early pregnancy (2%, 1/66), and fetal medicine (21%, 14/66). Both machine learning methods (39/66) and knowledge base methods (25/66) were represented. Machine learning used imaging, numerical, and clinical data sets. Knowledge base methods used mostly omics data sets. The actual contributions of AI were method/algorithm development (53%, 35/66), hypothesis generation (42%, 28/66), or software development (3%, 2/66). Validation was performed on one data set (86%, 57/66) and no external validation was reported. We observed a general rising trend in publications related to AI in OB/GYN over the last two decades. Most of these publications (82%, 54/66) remain out of the scope of the usual OB/GYN journals.

Conclusions

In OB/GYN discipline journals, mostly preliminary work (eg, proof-of-concept algorithm or method) in AI applied to this discipline is reported and clinical validation remains an unmet prerequisite. Improvement driven by new AI research guidelines is expected. However, these guidelines are covering only a part of AI approaches (nonsymbolic) reported in this review; hence, updates need to be considered.

Identifying and optimizing human endometrial gene expression signatures for endometrial dating

STUDY QUESTION

What are the key considerations for developing an enhanced transcriptomic method for secretory endometrial tissue dating?

SUMMARY ANSWER

Multiple gene expression signature combinations can serve as biomarkers for endometrial dating, but their predictive performance is variable and depends on the number and identity of the genes included in the prediction model, the dataset characteristics and the technology employed for measuring gene expression.

WHAT IS KNOWN ALREADY

Among the new generation of transcriptomic endometrial dating (TED) tools developed in the last decade, there exists variation in the technology used for measuring gene expression, the gene makeup and the prediction model design. A detailed study, comparing prediction performance across signatures for understanding signature behaviour and discrepancies in gene content between them, is lacking.

STUDY DESIGN, SIZE, DURATION

A multicentre prospective study was performed between July 2018 and October 2020 at five different centres from the same group of clinics (Spain). This study recruited 281 patients and finally included in the gene expression analysis 225 Caucasian patients who underwent IVF treatment. After preprocessing and batch effect filtering, gene expression measurements from 217 patients were combined with artificial intelligence algorithms (support vector machine, random forest and k-nearest neighbours) allowing evaluation of different prediction models. In addition, secretory-phase endometrial transcriptomes from gene expression omnibus (GEO) datasets were analysed for 137 women, to study the endometrial dating capacity of genes independently and grouped by signatures. This provided data on the consistency of prediction across different gene expression technologies and datasets.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Endometrial biopsies were analysed using a targeted TruSeq (Illumina) custom RNA expression panel called the endometrial dating panel (ED panel). This panel included 301 genes previously considered relevant for endometrial dating as well as new genes selected for their anticipated value in detecting the secretory phase. Final samples (n = 217) were divided into a training set for signature discovery and an independent testing set for evaluation of predictive performance of the new signature. In addition, secretory-phase endometrial transcriptomes from GEO were analysed for 137 women to study endometrial dating capacity of genes independently and grouped by signatures. Predictive performance among these signatures was compared according to signature gene set size.

MAIN RESULTS AND THE ROLE OF CHANCE

Testing of the ED panel allowed development of a model based on a new signature of 73 genes, which we termed 'TED' and delivers an enhanced tool for the consistent dating of the secretory phase progression, especially during the mid-secretory endometrium (3-8 days after progesterone (P) administration (P + 3-P + 8) in a hormone replacement therapy cycle). This new model showed the best predictive capacity in an independent test set for staging the endometrial tissue in the secretory phase, especially in the expected window of implantation (average of 114.5 ± 7.2 h of progesterone administered; range in our patient population of 82-172 h). Published sets of genes, in current use for endometrial dating and the new TED genes, were evaluated in parallel in whole-transcriptome datasets and in the ED panel dataset. TED signature performance was consistently excellent for all datasets assessed, frequently outperforming previously published sets of genes with a smaller number of genes for dating the endometrium in the secretory phase. Thus, this optimized set exhibited prediction consistency across datasets.

LARGE SCALE DATA

The data used in this study is partially available at GEO database. GEO identifiers GSE4888, GSE29981, GSE58144, GSE98386.

LIMITATIONS, REASONS FOR CAUTION

Although dating the endometrial biopsy is crucial for investigating endometrial progression and the receptivity process, further studies are needed to confirm whether or not endometrial dating methods in general are clinically useful and to guide the specific use of TED in the clinical setting.

WIDER IMPLICATIONS OF THE FINDINGS

Multiple gene signature combinations provide adequate endometrial dating, but their predictive performance depends on the identity of the genes included, the gene expression platform, the algorithms used and dataset characteristics. TED is a next-generation endometrial assessment tool based on gene expression for accurate endometrial progression dating especially during the mid-secretory.

STUDY FUNDING/COMPETING INTEREST(S)

Research funded by IVI Foundation (1810-FIVI-066-PD). P.D.-G. visiting scientist fellowship at Oxford University (BEFPI/2010/032) and Josefa Maria Sanchez-Reyes' predoctoral fellowship (ACIF/2018/072) were supported by a program from the Generalitat Valenciana funded by the Spanish government. A.D.-P. is supported by the FPU/15/01398 predoctoral fellowship from the Ministry of Science, Innovation and Universities (Spanish Government). D.W. received support from the NIHR Oxford Biomedical Research Centre. The authors do not have any competing interests to declare.

Transcriptome analysis of eutopic endometrium in adenomyosis after GnRH agonist treatment

BACKGROUND

Adenomyosis is a chronic gynecological disease characterized by invasion of the uterine endometrium into the muscle layer. In assisted reproductive technology (ART), gonadotropin-releasing hormone agonist (GnRHa) is often used to improve pregnancy rates in patients with adenomyosis, but the underlying mechanisms are poorly understood.

METHODS

Eutopic endometrial specimens were collected from patients with adenomyosis before and after GnRHa treatment in the midsecretory phase. RNA sequencing (RNA-Seq) of these specimens was performed for transcriptome analysis. The differentially expressed genes (DEGs) of interest were confirmed by real-time PCR and immunohistochemistry.

RESULTS

A total of 132 DEGs were identified in the endometrium of patients with adenomyosis after GnRHa treatment compared with the control group. Bioinformatics analysis predicted that immune system-associated signal transduction changed significantly after GnRHa treatment. Chemokine (C-C motif) ligand 21 (CCL21) was found to be highly expressed in the eutopic endometrium after GnRHa treatment, which may be involved in the improvement of endometrial receptivity in adenomyosis.

CONCLUSION

This study suggests that molecular regulation related to immune system-associated signal transduction is an important mechanism of GnRHa treatment in adenomyosis. Immunoreactive CCL21 is thought to regulate inflammatory events and participate in endometrial receptivity in adenomyosis.

Integrated Analysis of Multiple Microarrays Based on Raw Data Identified Novel Gene Signatures in Recurrent Implantation Failure

BACKGROUND

Recurrent implantation failure (RIF) is an intricate complication following IVF-ET, which refers to the situation that good-quality embryos repeatedly fail to implant following two or more IVF cycles. Intrinsic molecular mechanisms underlying RIF have not yet been fully elucidated. With enormous improvement in high-throughput technologies, researchers screened biomarkers for RIF using microarray. However, the findings of published studies are inconsistent. An integrated study on the endometrial molecular determinants of implantation will help to improve pregnancy outcomes.

OBJECTIVE

To identify robust differentially expressed genes (DEGs) and hub genes in endometrium associated with RIF, and to investigate the diagnostic role of hub genes in RIF.

METHODS

Raw data from five GEO microarrays regarding RIF were analyzed. Integrated genetic expression analyses were performed using the Robust Rank Aggregation method to identify robust DEGs. Enrichment analysis and protein-protein interaction (PPI) analysis were further performed with the robust DEGs. Cytohubba was used to screen hub genes based on the PPI network. GSE111974 was used to validate the expression and diagnostic role of hub genes in RIF.

RESULTS

1532 Robust DEGs were identified by integrating four GEO datasets. Enrichment analysis showed that the robust DEGs were mainly enriched in processes associated with extracellular matrix remodeling, adhesion, coagulation, and immunity. A total of 18 hub genes (HMGCS1, SQLE, ESR1, LAMC1, HOXB4, PIP5K1B, GNG11, GPX3, PAX2, TF, ALDH6A1, IDH1, SALL1, EYA1, TAGLN, TPD52L1, ST6GALNAC1, NNMT) were identified. 10 of the 18 hub genes were significantly differentially expressed in RIF patients as validated by GSE111974. The 10 hub genes (SQLE, LAMC1, HOXB4, PIP5K1B, PAX2, ALDH6A1, SALL1, EYA1, TAGLN, ST6GALNAC1) were effective in predicting RIF with an accuracy rate of 85%, specificity rate of 100%, and sensitivity rate of 88.9%.

CONCLUSIONS

Our integrated analysis identified novel robust DEGs and hub genes in RIF. The hub genes were effective in predicting RIF and will contribute to the understanding of comprehensive molecular mechanisms in RIF pathogenesis.

OUP accepted manuscript

STUDY QUESTION

Is the composition of microRNAs (miRNAs) in uterine fluid (UF) of women with recurrent implantation failure (RIF) different from that of healthy fertile women?

SUMMARY ANSWER

The composition of miRNAs in UF of women with RIF is different from that of healthy fertile women and the dysregulated miRNAs are associated with impaired endometrial receptivity and embryo implantation.

WHAT IS KNOWN ALREADY

It has previously been demonstrated that the miRNAs secreted from endometrial cells into the UF contribute to the achievement of endometrial receptivity. Endometrial miRNAs are dysregulated in women with RIF.

STUDY DESIGN, SIZE, DURATION

In this descriptive laboratory case–control study, miRNA abundancy was compared between UF collected during implantation phase from healthy fertile women (n = 17) and women with RIF (n = 34), which was defined as three failed IVF cycles with high-quality embryos.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Recruitment of study subjects and sampling of UF were performed at two university clinics in Stockholm, Sweden and Tartu, Estonia. The study participants monitored their menstrual cycles using an LH test kit. The UF samples were collected on Day LH + 7–9 by flushing with saline. Samples were processed for small RNA sequencing and mapped for miRNAs. The differential abundance of miRNAs in UF was compared between the two groups using differential expression analysis (DESeq2). Further downstream analyses, including miRNA target gene prediction (miRTarBase), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (g:Profiler) and external validation using relevant published data, were performed on the dysregulated miRNAs. Two miRNAs were technically validated with quantitative real-time PCR (RT-PCR).

MAIN RESULTS AND THE ROLE OF CHANCE

After processing of the sequencing data, there were 15 samples in the healthy fertile group and 33 samples in the RIF group. We found 61 differentially abundant UF miRNAs (34 upregulated and 27 downregulated) in RIF compared to healthy women with a false discovery rate of <0.05 and a fold change (FC) of ≤−2 or ≥2. When analyzed with published literature, we found that several of the differentially abundant miRNAs are expressed in endometrial epithelial cells and have been reported in endometrial extracellular vesicles and in association with endometrial receptivity and RIF. Their predicted target genes were further expressed both in the trophectodermal cells of blastocyst-stage embryos and endometrial mid-secretory epithelial cells, as assessed by publicly available single-cell transcriptome-sequencing studies. Pathway analysis further revealed that 25 pathways, having key roles in endometrial receptivity and implantation, were significantly enriched. Hsa-miR-486-5p (FC −20.32; P-value = 0.004) and hsa-miR-92b-3p (FC −9.72; P-value = 0.004) were successfully technically validated with RT-PCR.

LARGE SCALE DATA

The data are available in Gene Expression Omnibus (GEO) at https://www.ncbi.nlm.nih.gov/geo/ with GEO accession number: GSE173289.

LIMITATIONS, REASONS FOR CAUTION

This is a descriptive study with a limited number of study participants. Moreover, the identified differentially abundant miRNAs should be validated in a larger study cohort, and the predicted miRNA target genes and enriched pathways in RIF need to be confirmed and further explored in vitro.

WIDER IMPLICATIONS OF THE FINDINGS

RIF is a major challenge in the current IVF setting with no diagnostic markers nor effective treatment options at hand. For the first time, total miRNAs have been extensively mapped in receptive phase UF of both healthy women with proven fertility and women diagnosed with RIF. Our observations shed further light on the molecular mechanisms behind RIF, with possible implications in future biomarker and clinical treatment studies.

STUDY FUNDING/COMPETING INTEREST(S)

This work was financially supported by the Swedish Research Council (2017-00932), a joint grant from Region Stockholm and Karolinska Institutet (ALF Medicine 2020, FoUI-954072), Estonian Research Council (PRG1076), Horizon 2020 innovation (ERIN, EU952516) and European Commission and Enterprise Estonia (EU48695). The authors have no competing interests to declare for the current study.

Effectiveness comparison between Endometrial Receptivity Array, Immune Profiling and the combination in treating patients with multiple implantation failure

PROBLEM

The clinical value of endometrial receptivity array (ERA), endometrial immune profiling, or a combination of both for multiple implantation failure patients is unclear.

METHOD OF STUDY

One hundred and seventy-two women with a history of at least two or more consecutive implantation failures in IVF/ICSI treatment were included. According to patients' willingness, they were divided into four groups, 'no treatment', 'Immune Profiling', 'ERA' and 'ERA + Immune Profiling'. Endometrial biopsy was examined by ERA, immune profiling alone, or combination, and intention was adopted accordingly. Pregnancy outcomes were compared, and the association between ERA phases and endometrial immune profiling was also assessed.

RESULTS

The overall incidence rate of the displaced window of implantation (WOI) and endometrial immune dysregulations were 84.9% and 75.3%, respectively. Implantation rate was significantly higher in the 'ERA + Immune Profiling' group than the 'no treatment' group (P = 0.007). Clinical pregnancy rate was somewhat improved in the three treatment groups but with a borderline significance (P = 0.071). After controlling for other confounders, 'ERA + Immune Profiling' treatment was associated with a higher pregnancy rate [aOR (95%CI)  =  3.412 (1.387-8.395), P = 0.008]. There was no association between endometrial immune profiling and ERA phases.

CONCLUSIONS

Our findings highlight the high incidence of displaced WOI and endometrial immune dysregulation in multiple implantation failure patients. The combination of ERA and endometrial immune profiling is more likely to have clinical value than ERA or immune profiling alone. These data suggested the unsubstitutability of ERA and endometrial immune profiling on the treatment outcome for multiple implantation failure patients. This article is protected by copyright. All rights reserved.

MAML1: a coregulator that alters endometrial epithelial cell adhesive capacity

BACKGROUND

Abnormalities in endometrial receptivity has been identified as a major barrier to successful embryo implantation. Endometrial receptivity refers to the conformational and biochemical changes occurring in the endometrial epithelial layer which make it adhesive and receptive to blastocyst attachment. This takes place during the mid-secretory phase of woman's menstrual cycle and is a result of a delicate interplay between numerous hormones, cytokines and other factors. Outside of this window, the endometrium is refractory to an implanting blastocyst. It has been shown that Notch ligands and receptors are dysregulated in the endometrium of infertile women. Mastermind Like Transcriptional Coactivator 1 (MAML1) is a known coactivator of the Notch signaling pathway. This study aimed to determine the role of MAML1 in regulating endometrial receptivity.

METHODS

The expression and localization of MAML1 in the fertile human endometrium (non-receptive proliferative phase versus receptive mid-secretory phase) were determined by immunohistochemistry. Ishikawa cells were used as an endometrial epithelial model to investigate the functional consequences of MAML1 knockdown on endometrial adhesive capacity to HTR8/SVneo (trophoblast cell line) spheroids. After MAML1 knockdown in Ishikawa cells, the expression of endometrial receptivity markers and Notch dependent and independent pathway members were assessed by qPCR. Two-tailed unpaired or paired student's t-test were used for statistical analysis with a significance threshold of P < 0.05.

RESULTS

MAML1 was localized in the luminal epithelium, glandular epithelium and stroma of human endometrium and the increased expression identified in the mid-secretory phase was restricted only to the luminal epithelium (P < 0.05). Functional analysis using Ishikawa cells demonstrated that knockdown of MAML1 significantly reduced epithelial adhesive capacity (P < 0.01) to HTR8/SVneo (trophoblast cell line) spheroids compared to control. MAML1 knockdown significantly affected the expression of classical receptivity markers (SPP1, DPP4) and this response was not directly via hormone receptors. The expression level of Hippo pathway target Ankyrin repeat domain-containing protein 1 (ANKRD1) was also affected after MAML1 knockdown in Ishikawa cells.

CONCLUSION

Our data strongly suggest that MAML1 is involved in regulating the endometrial adhesive capacity and may facilitate embryo attachment, either directly or indirectly through the Notch signaling pathway.

Hsa_circ_0038383-mediated competitive endogenous RNA network in recurrent implantation failure

BACKGROUND

Inadequate endometrial receptivity contributes to recurrent implantation failure (RIF) during IVF-embryo transfer. Though multiple circRNAs have been confirmed differentially expression in RIF, the potential function of novel circRNAs needed to be detected.

RESULTS

The top ten DEcircRNAs were selected as initial candidates. A ceRNA network was conducted on the basis of circRNA-miRNA-mRNA potential interaction, consisting of 10 DEcircRNAs, 28 DEmiRNAs and 59 DEmRNAs. Three down-regulation circRNAs with high degree of connectivity were verified by RT-qPCR, and results suggested that only hsa_circ_0038383 was significantly downregulation in RIF compared with control group. Subsequently, three hub genes (HOXA3, HOXA9 and PBX1) were identified as hub genes. Ultimately, a subnetwork was determined based on one DEcircRNA (hsa_circ_0038383), two DEmiRNAs (has-miR-196b-5p and has-miR-424-5p), and three DEmRNAs (HOXA3, HOXA9 and PBX1). Following verification, hsa_circ_0038383/miR-196b-5p/HOXA9 axis may be a key pathway in affecting RIF.

CONCLUSION

In summary, a hsa_circ_0038383-mediated ceRNA network related to RIF was proposed. This network provided new insight into exploring potential biomarkers for diagnosis and clinical treatment of RIF.

METHODS

We retrieved the expression profiles of RIF from GEO databases (circRNA, microRNA and mRNA) and constructed a competing endogenous RNAs (ceRNA) network based on predicted circRNA-miRNA and miRNA-mRNA pairs. The expression levels of three hub DEcircRNAs identified by cytoscape were validated by RT-qPCR.

The mechanism of action of oxytocin antagonist nolasiban in ART in healthy female volunteers

RESEARCH QUESTION

What are the effects of the oxytocin receptor (OTR) antagonist nolasiban on uterine contractions, endometrial perfusion and endometrial mRNA expression?

DESIGN

Randomized, double-blind, parallel-group, mechanism-of-action study with nolasiban. Forty-five healthy, pre-menopausal women were treated with placebo, 900 mg or 1800 mg nolasiban on the day corresponding to blastocyst transfer. Ultrasonographic uterine contraction frequency and endometrial perfusion were assessed, and endometrial biopsies analysed by next-generation sequencing.

RESULTS

Both doses of nolasiban showed decreased contraction frequency and increased endometrial perfusion depending on the time point assessed. At 1800 mg, 10 endometrial genes (DPP4, CNTNAP3, CNTN4, CXCL12, TNXB, CTSE, OLFM4, KRT5, KRT6A, IDO2) were significantly differentially expressed (adjusted P < 0.05). Of these, OLFM4, DPP4 and CXCL12 were regulated in the same direction as genes involved in implantation during the window of implantation. In addition, three genes (DPP4, CXCL12 and IDO2) were associated with decidualization and endometrial receptivity.

CONCLUSIONS

These data expand our knowledge of the mechanism of action of nolasiban in increasing pregnancy rates after embryo transfer. The results suggest more marked effects of nolasiban 1800 mg compared with the 900 mg dose, supporting testing at higher doses in IVF patients.

The genomic analysis of endometrial mitochondrial DNA copy number variation on recurrent implantation failure

OBJECTIVE

Aim of this study was to define the relationship between RIF (Recurrent Implantation Failure) and endometrial mtDNA copy number.

STUDY DESIGN

A total of 50 women of reproductive age including twenty-five patients clinically diagnosed with RIF and twenty-five fertile women as healthy controls were recruited into the study. Endometrial biopsy samples were obtained with a pipelle at the 20-24 days of the menstrual cycle of each participant. Total genomic DNA samples were isolated from endometrial tissues; MT-ND1 (mitochondrially encoded NADH dehydrogenase I) and MT-CO2 (mitochondrially encoded cytochrome C oxidase II) target genes were amplified by droplet digital PCR (ddPCR). Nuclear GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase) gene was also used for study normalization. The study has been conducted between February 2019 and June 2019.

RESULT(S)

Droplet digital PCR results were analyzed in "QuantaSoft" software. The concentration amount (copies/μl) of each participant's mitochondrial gene was normalized according to the GAPDH gene concentrations as nuclear reference. mtDNA amounts were compared between RIF patients and healthy controls. Normalized data was statistically evaluated using Mann-Whitney U test and ROC curve analysis.

CONCLUSION(S)

It was concluded that the mitochondrial target gene (MT-ND1 and MT-CO2) copy number amount of RIF patients was higher than the one obtained from the healthy group in endometrial tissues. It is thought that higher mtDNA copy number at the RIF group may be related to increased oxidative stress in the endometrium. This stress factors may influence receptivity negatively and cause implantation failure. The receptivity of the endometrium is associated with the number of mtDNA copies and difference can be used as a biomarker for receptivity analysis.

Weighted Gene Correlation Network Meta-Analysis Reveals Functional Candidate Genes Associated with High- and Sub-Fertile Reproductive Performance in Beef Cattle

Improved reproductive efficiency could lead to economic benefits for the beef industry, once the intensive selection pressure has led to a decreased fertility. However, several factors limit our understanding of fertility traits, including genetic differences between populations and statistical limitations. In the present study, the RNA-sequencing data from uterine samples of high-fertile (HF) and sub-fertile (SF) animals was integrated using co-expression network meta-analysis, weighted gene correlation network analysis, identification of upstream regulators, variant calling, and network topology approaches. Using this pipeline, top hub-genes harboring fixed variants (HF × SF) were identified in differentially co-expressed gene modules (DcoExp). The functional prioritization analysis identified the genes with highest potential to be key-regulators of the DcoExp modules between HF and SF animals. Consequently, 32 functional candidate genes (10 upstream regulators and 22 top hub-genes of DcoExp modules) were identified. These genes were associated with the regulation of relevant biological processes for fertility, such as embryonic development, germ cell proliferation, and ovarian hormone regulation. Additionally, 100 candidate variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs)) were identified within those genes. In the long-term, the results obtained here may help to reduce the frequency of subfertility in beef herds, reducing the associated economic losses caused by this condition.

Aquaporin-3 mediates ovarian steroid hormone-induced motility of endometrial epithelial cells

STUDY QUESTION

How does aquaporin-3 (AQP3) affect endometrial receptivity?

SUMMARY ANSWER

AQP3, which is regulated by the combination and estrogen (E2) and progesterone (P4), induces epithelial-mesenchymal transition (EMT) of endometrial epithelial cells.

WHAT IS KNOWN ALREADY

Embryo implantation is an extremely complex process, and endometrial receptivity is essential for successful embryo implantation. Estrogen and progesterone regulate endometrial receptivity. AQP3, which is regulated by estrogen (E2), increases cell migration and invasion ability by regulating the expression of EMT-related factors and influencing the reorganization of the actin cytoskeleton.

STUDY DESIGN, SIZE, DURATION

This study investigated the pathophysiological significance of AQP3 in human endometrial function during different phases of the menstrual cycle.

PARTICIPANTS/MATERIALS, SETTING, METHODS

AQP3 expression levels during different phases of the menstrual cycle were measured using immunohistochemical assays. In cells of different receptivity (high-receptive RL95-2 cells and low-receptive HEC-1A cells), the expression of AQP3 was measured using western blotting, qRT-PCR and immunofluorescence assays. Activities of AQP3, and its regulation by E2 and P4, were studied through in-vitro experiments using RL95-2 cells.

MAIN RESULTS AND THE ROLE OF CHANCE

AQP3 expression in the mid- and late-secretory phases of the human endometrium is significantly higher than in other phases. Since AQP3 expression levels were higher in RL95-2 cells than in HEC-1A cells, mechanisms of AQP3 regulation by E2 and P4 were studied using RL95-2 cells. We provided the first report that P4 up-regulates AQP3 by directly targeting the promoter of the AQP3 gene. The up-regulation of AQP3 expression by a combination of E2 and P4 is significantly higher than that caused by either E2 or P4 alone. Together E2 and P4 promote RL95-2 cell migration and invasion by inducing EMT through AQP3. We also found that AQP3 co-localizes with ezrin and affects the formation of filopodia and lamellipodia during the E2 and P4-induced EMT process but has no effect on the expression of ezrin and F-actin.

LARGE SCALE DATA

N/A.

LIMITATIONS, REASONS FOR CAUTION

It is still unclear whether AQP3 is a main regulator of endometrial receptivity or one of several factors influencing the process.

WIDER IMPLICATIONS OF THE FINDINGS

Further investigation on AQP3 may contribute to a greater understanding of endometrial receptivity.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the National Natural Scientific Grants of China (No. 31570798), the Program for Liaoning Excellent Talents in University (LR2017042), the Doctoral Scientific Research Foundation of Liaoning province (201601236), and the Liaoning Provincial Program for Top Discipline of Basic Medical Sciences. There are no conflicts of interest.

Comparative evaluation of NOTCH signaling molecules in the endometrium of women with various gynecological diseases during the window of implantation

OBJECTIVES

NOTCH signaling pathway is well known for its role in cell fate, cell survival, cell differentiation, and apoptosis. Some of the NOTCH signaling genes are critical for endometrial function and implantation in animals and appear to play a similar role in humans. The purpose of the current study was to investigate the potential roles of some main components of the NOTCH family in human endometrium during implantation period in common gynecological diseases.

MATERIALS AND METHODS

Endometrial NOTCH receptors NOTCH1, 3, 4 and ligand JAG1, 2 and survivin mRNA expression were investigated using the Q-PCR technique and the amount of the JAG1, 2 proteins was also determined by Western blot. Samples were obtained from 12 patients with endometriosis, 12 patients with repeated implantation failure (RIF), 12 patients with Polycystic Ovary Syndrome (PCOS) and 10 healthy fertile women as a control group. Data were analyzed using SPSS version 18. Group comparisons were performed by one-way ANOVA or Kruskal-Wallis.

RESULTS

All patient groups failed to show the expected mid-luteal increase in NOTCH1, JAG 1, 2, and survivin expression as documented in the control group. Moreover, a significant rise in NOTCH3 expression levels was found only in PCOS women. There was a direct correlation between gene expression and protein level for JAG 1, 2.

CONCLUSION

Aberrant NOTCH signaling molecules expression suggests that altered development of the endometrium at the molecular level may be associated with the impaired decidualization and implantation failure in gynecological disorders such as endometriosis, PCOS, and RIF.

Asynchronous and pathological windows of implantation: two causes of recurrent implantation failure

STUDY QUESTION

Is endometrial recurrent implantation failure (RIF) only a matter of an asynchronous (displaced) window of implantation (WOI), or could it also be a pathological (disrupted) WOI?

SUMMARY ANSWER

Our predictive results demonstrate that both displaced and disrupted WOIs exist and can present independently or together in the same RIF patient.

WHAT IS KNOWN ALREADY

Since 2002, many gene expression signatures associated with endometrial receptivity and RIF have been described. Endometrial transcriptomics prediction has been applied to the human WOI in two previous studies. One study describes endometrial RIF to be the result of a temporal displacement of the WOI. The other indicates that endometrial RIF can also result from a molecularly disrupted WOI without temporal displacement.

STUDY DESIGN, SIZE, DURATION

Retrospective analysis was undertaken to compare WOI endometrial transcriptomics predictions in controls (n = 72) and RIF patients (n = 43). RIF was clinically designated by the absence of implantation after four or more transfers of high quality embryos or after the placement of 10 or more embryos in multiple transfers. Endometrial tissue samples were collected from LH + 5 to LH + 8. We compared the two molecular causes of RIF to signatures currently described in the literature. We propose a new transcriptomic RIF taxonomy to fill the gap between the two hypotheses and to guide the development of clinical detection and determination of both types of RIF.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Utilizing 115 gene expression profiles, two different predictive designs were developed: one considering RIF versus controls removing menstrual cycle timing, called the disrupted or pathological model, and another stratifying the WOI in transcriptomic profiles related to timing for predicting displacements. The predictive value of each model was compared between all signatures selected. We propose a new genomic approach that distinguishes between both types of RIF in the same sample cohort.

MAIN RESULTS AND THE ROLE OF CHANCE

From the 16 signatures analysed, we clearly predicted two causes of RIF-both a displaced WOI and an on-time but pathologically disrupted WOI. A high predictive value related to WOI profiles associated with menstrual cycle timing was found in most of the signatures. Specifically, 69% of the signatures analysed presented an accuracy higher than expected by chance in a range from 0.87 to 0.97. Displacements and disruptions were not molecularly independent, as some signatures were moderately associated with both causes. The gene and functional comparison between signatures revealed that they were not similar, although we did find functions in common and a cluster of moderate functional concordance between some of the signatures that predicted displacements (the highest Cohen's Kappa index were between 0.55 and 0.62 depending on the functional database). We propose a new transcriptomic RIF taxonomy to fill the gap between these prior studies and to establish methodology for detecting and distinguishing both types of RIF in clinical practice. Our findings indicate these two phenotypes could present independently or together in the same RIF patient. RIF patients designated by clinical criteria have been stratified transcriptomically as 18.6% with only a displaced WOI, 53.5% with a displaced and pathological WOI, 23.3% with only a disrupted WOI, and 4.7% could be a clinical RIF with non-endometrial origin. The new RIF transcriptomic taxonomy avoids menstrual cycle timing as a confounding variable that should be controlled for, distinguishing clearly between a disrupted and a displaced WOI for precision medicine in RIF.

LIMITATIONS REASONS FOR CAUTION

The main objective of this study was to use transcriptomics to detect both RIF causes and to understand the role of transcriptomic signatures in these phenotypes. The predictive value in absolute terms for each signature was not indicative in these prediction designs; instead, the comparison between signatures was most important for prediction capability in the same sample cohort for both RIF causes. Clinical follow up of the RIF taxonomies proposed has not been analysed in this study, so further prospective clinical studies are necessary to determine the prevalence and penetrance of these phenotypes.

WIDER IMPLICATIONS OF THE FINDINGS

The main insight from this study is a new understanding of RIF taxonomy. Understanding how to classify RIF patients to distinguish clinically between a patient who could benefit from a personalized embryo transfer day and a patient with a disrupted WOI will enable identification and stratification for the research and development of new treatments. In addition, we demonstrate that basic research designs in endometrial transcriptomics cause masking of the study variable by the menstrual cycle timing.

STUDY FUNDING/COMPETING INTEREST(S)

This research has been funded by IVI-RMA; the authors do not have any competing interests.

Construction of implantation failure related lncRNA-mRNA network and identification of lncRNA biomarkers for predicting endometrial receptivity

Insufficient endometrial receptivity is a major factor leading to implantation failure (IF), and the traditional way of morphological observation of endometrium cannot determine the condition of receptivity sufficiently. Considering that long-noncoding RNAs (lncRNAs) regulate endometrial receptivity and competing endogenous RNA (ceRNA) mechanism works in plenty of biological processes, ceRNA is likely to function in the pathology of IF. In the present study, we aim to construct an implantation failure related lncRNA-mRNA network (IFLMN), and to identify the key lncRNAs as the candidates for predicting endometrial receptivity. The global background network was constructed based on the presumed lncRNA-miRNA and miRNA-mRNA pairs obtained from lncRNASNP and miRTarBase. Differentially expressed genes (DEGs) of IF were calculated using the data of GSE26787, and then re-annotated as differentially expressed mRNAs (DEMs) and lncRNAs (DELs). IFLMN was constructed by hypergeometric test, including 255 lncRNA-mRNA pairs, 10 lncRNAs, and 212 mRNAs. Topological analysis determined the key lncRNAs with the highest centroid. Functional enrichment analyses were performed by unsupervised clustering, GO classification, KEGG pathway, and co-expression module analyses, achieving six key lncRNAs and their ceRNA sub-networks, which were involved in immunological activity, growth factor binding, vascular proliferation, apoptosis, and steroid biosynthesis in uterus and prepared endometrium for embryo implantation. Sixteen endometrial samples were collected during mid-luteal phase, including 8 recurrent implantation failure (RIF) or recurrent miscarriage (RM) women and 8 controls who conceived successfully. Quantitative real-time PCR was performed to compare the expression of the above six lncRNAs, which validated that the expression of all these lncRNAs was significantly elevated in endometrium of RIF/RM patients. Further studies are needed to investigate the underlying mechanism, and the lncRNAs may be developed into predictive biomarkers for endometrial receptivity.

Characterization of transcriptional complexity during pre-implantation development of the yak (Bos grunniens) using RNA-Seq

The objective of this study was to investigate the mechanism that regulates pre-implantation development of the yak (Bos grunniens). We determined the transcriptomes of in vitro-produced yak embryos at two-cell, four-cell, eight-cell stages, and morula and blastocyst using the Illumina RNA-seq for the first time. We obtained 47.36-50.86 million clean reads for each stage, of which, 85.65%-90.02% reads were covered in the reference genome. A total of 17,368 genes were expressed during the two-cell stage to blastocyst of the yak, of which 7,236 genes were co-expressed at all stages, whereas 10,132 genes were stage-specific expression. Transcripts from 9,827 to 14,893 different genes were detected in various developmental stages. When |log₂ ratio| ≥ 1 and q-value <0.05 were set as thresholds for identifying differentially expressed genes (DEGs), we detected a total of 6,922-10,555 DEGs between any two consecutive stages. The GO distributions of these DEGs were classified into three categories: biological processes (23 terms), cellular components (22 terms) and molecular functions (22 terms). Pathway analysis revealed 310 pathways of the DEGs that were operative in early pre-implantation yak development, of which 32 were the significantly enriched pathways. In conclusion, this is the first report to investigate the mechanism that regulates yak embryonic development using high-throughput sequencing, which provides a comprehensive framework of transcriptome landscapes of yak pre-implantation embryos.