Correlation Between High Throughput Gene Expression Profile And Outcome Of In Vitro Fertilization And Embryo Transfer

BackgroundIn recent years, with the rapid development of the economy and society, environmental pollution such as air, water,food and other have been becoming more and more serious. Gradually changing people’s life style and living habits, work pressure, artificial and drug abortion, late marriage and late childbirth, sterilization, etc. will result in varying degree of impact the human fertility.Due to a decline in fertility, the incidence of infertility increasing gradually, has become a global public health and social problems. According to the survey of World Health Organization (WHO) in the late 1980s about 33 Research Center in 25 countries, organized a by standard diagnosis of infertile couples,the results showed that 5-8% couples in developed countries had infertility. Some infertility disease rate in developing countries can be as high as 30%. The infertility incidence rate in each province of China is also large, from minimum of about 4% to maximum of about 19%, an average of about 10-15%. Infertility has become the third largest killer after cardiovascular disease and cancer in China. And, with the two children policy release, people with the new requirements, the number of infertility will further increase. In most regions of China, infertility treatment not in the scope of medical insurance, so infertile couples have done with tremendous economic and psychological pressure.In the last century, the researches of reproductive medicine gradually improve, being the hope of infertile couples, mainly based on the theory of reproductive endocrine, assisted human assisted reproductive technology, artificial operation of the gamete, zygote and the embryo, so as to complete conception, the full name of artificial method to complete the natural process. The invention and application of IVF-ET have successfully solved the problem of the global infertility patients, which provides a good way to solve the problem of public society. IVF-ET assisted reproductive technologies brings the hope for infertility in women. However, pregnancy outcome of IVF-ET is affected by many factors including genetic factors and each cycle pregnancy rate remained at about 30%, although birth of efficient ovulation drugs, improvement of ova harvest, cultured agent and laboratory conditions increase rates of obtained oocyte, fertility, and cleavage.The use of molecular biomarkers as rapid, cost-effective and sensitive diagnostic tool for predicting the outcome of in vitro fertilization-embryo transfer have greatly potential. Gene expression data with bioinformation analysis can provide mechanistic insights into the occurrence of pregnancy failure. With the advancement of molecular biology technology, differential gene expression methods are being used more frequently to select better molecular biomarker options. High-throughput RNA-sequencing (RNA-seq) technologies have led to a revolution in the fields of transcriptomics and genome characterization in recent years. RNA-seq is transcriptome sequencing technology, also known as the whole transcriptome shotgun sequencing, RNA-seq technology development called transcriptome sequencing revolutionary progress. RNA-seq can be used to measure the mRNA, RNA and RNA non-coding, or some of them with high throughput sequencing technology to sequence them out, reflecting their expression level. So it can be used to detect and analyze almost all of the RNA components in the sample, so it provides a new tool for the exploration of various diseases. The HiSeqTM 2000 sequencing system can generate up to two billion paired-end reads with an average length of 100 bp at 99.5% accuracy per run.In this study, we performed the gene expression analysis on the human pregnancy outcome based on the HiSeqTM 2000 sequencing system from a total of 10 infertile patients with IVF-ET (5 pregnancy success and 5 pregnancy failure) during three different stages:before IVF-ET (Stage I), after ovarian stimulation (Stage II), and day 15 after embryo transfer (Stage III). Quantitative real-time PCR (qRT-PCR) was performed to verify several selected differentially expressed genes and expound the molecular mechanism coping with pregnancy outcome. Furthermore, genes associated with pregnancy success identified in this attempt may be potential biomarkers for pregnancy outcome monitoring in patients with IVF-ET.MethodsEnrolment occurred between January 2014 and June 2014. All patients who signed written informed consent were undergoing IVF treatment at the Department of Reproductive Medicine, affiliated hospital of Dali University. A total of 10 infertile patients were collected and assigned into 2 groups according to the pregnancy outcome, including 5 infertile patients with pregnancy success (pregnancy success group) and 5 infertile patients with pregnancy failure (pregnancy failure group). All relevant clinical data of patients were recorded, including age, height, weight, family history and other general information, as well as other diseases, medication history, family history.Ovarian stimulation was undertaken using the gonadotropin releasing hormone agonist long protocol and recombinant follicle stimulating hormone. IVF and embryo culture have been described previously. Oocytes and embryos were cultured in sequential embryo culture media. Fertilization check was performed 18 h after insemination. The presence of two pronuclei was defined as normal fertilization and normally fertilized oocytes were continuously cultured in Early Cleavage Medium for two more days. The Crinone gel was taken once a day vaginally, while the Utrogestan was taken orally three times a day. The quality of cleavage embryos was assessed on the morning of day 3. A good quality embryo day 3 was defined as having more than 7 blastomeres of equal size and less than 20% fragmentation. Serum β-hCG was measured for diagnosis of pregnancy 15 days after embryo transfer and then was tested serially to monitor the rise in its titre. Clinical pregnancy was judged by observation of the gestational sac with fetal heart activity on vaginal ultrasonography after 35 days of gestation. Ectopic pregnancy was not counted as implantation and clinical pregnancy. Before IVF-ET (Stage I), after ovarian stimulation (Stage II), and day 15 after embryo transfer (Stage III), patients samples for RNA-Seq from both pregnancy success and failure groups were pooled together and analyzed. The FastQC package was used to assess the quality of raw reads, which were then mapped to human genome assembly hgl9 using TopHat version 2.0.312. Quality control was performed on all samples. Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy N and low quality reads from raw data. All the downstream analyses were based on the clean data with high quality. TopHat removes a few low-quality score reads then aligns the reads that are directly mapped to the reference genome. Five genes were selected for the confirmation of differential expressed gene data by Quantitative real-time PCR (qRT-PCR).Results1 Clinical data between the two groups, including age, BMI, FSF/LH, E2, P, and serum T level were not significantly different (P> 0.05).2 A total of 126 oocytes were retrieved from all patients and 107 of them were matured oocytes (matured oocyte rate,84.9%).62 oocytes were retrieved from pre group, and 52 of them were matured oocytes.64 oocytes were retrieved from non pre group, and 55 of them were matured oocytes. Matured oocyte rate between both groups was not significantly different (P> 0.05).3 Gn days, Total Gn, FSH,2PN, ET embryos,and high quality embryos was not significantly different between the two groups (P> 0.05).4 Before IVF-ET (Stage I), after ovarian stimulation (Stage II), and day 15 after embryo transfer (Stage III). A total of 11698976 (98.62% of raw data) and 26502828 (98.4% of raw data) clean reads in pregnancy success group and pregnancy failure group in stage I,3175521 (98.55% of raw data) and 12139689 (98.37% of raw data) in stage Ⅱ, and 10769344 (98.62% of raw data) and 17021605 (98.51% of raw data) in stage III were left after removing reads with adaptors, reads containing poly N and low quality reads from raw data, respectively.5 In gene expression profiles of pregnancy success and failure,45.43% and 50.14% in stage Ⅰ,50.17% and 50.34% in stage Ⅱ, and 48.72% and 53.24% in stage Ⅲ of the clean reads were mapped to gene in the reference database. The number of clean reads mapped to a gene was normalized to RPKM values to accurately measure the gene expression level.6 Results showed that 28%-38% of 100 bp paired-end reads were obtained per sample with at least 90%-100% coverage distribution of genes, and that mRNAs transcribed from the major type of genes were represented in low values, and only a small proportion of genes was highly expressed.7 PCA analysis showed that both the pregnancy success and failure groups in stage Ⅰ and stage Ⅱ had similar characteristics, respectively.8 A total of 282,208, and 372 differentially expressed genes in stage Ⅰ, stage Ⅱ, and stage Ⅲ between the pregnancy success group and the pregnancy failure group were detected, of which 130 were upregulated and 152 were downregulated in stage I,90 were upregulated and 118 were downregulated in stage Ⅱ, and 100 were upregulated and 272 were downregulated in stage Ⅲ.9 The scatter image of RPKM value of the pregnancy success group vs. the pregnancy failure group showed that only a small portion of genes were differentially expressed genes.10 In stage Ⅰ, genes related to "rhythmic process" and "protein tag" were all upregulated, and genes related to "electron carrier activity" were all downregulated. In stage Ⅱ, genes related to "synapse part", "synapse", "structural molecule activity", and "antioxidant activity" were all downregulated. In stage III, "rhythmic process", "synapse part", "synapse", and "chemorepellent activity" were all downregulated.11 KEGG assignments were used to classify functional annotations of the identified differentially expressed genes to further understand the biological functions. Among the differentially expressed genes in stage I,282 differentially expressed genes were assigned to 23 pathways (P<0.05). Among the differentially expressed genes in stage Ⅱ,208 differentially expressed genes were assigned to 32 significantly enriched pathways (P<0.05). Among the differentially expressed genes in stage III,372 differentially expressed genes were assigned to 17 pathways(.P<0.05).12 Especially, the pathways related to the IVF-ET outcome, such as "Chemokine signaling pathway" and "cell adhesion molecules" pathways in stage I, and "chemokine signaling pathway" pathway in stage Ⅱ, and "Oocyte meiosis" and "progesterone-mediated oocyte maturation" pathways in stage III, were significantly enriched. In addition, most of the differentially expressed genes was related to pathways "chemokine signaling pathway" and "cell adhesion molecular" in Stage I, "cytokine-cytokine receptor interaction", "chemokine signaling pathway" and "leishmariasis" in stage II, and "cell cycle" and "oocyte meiosis" in stage III.13 The relative mRNA expression level of 5 genes from differentially expressed gene profiles were detected by qRT-PCR, based on the relation with the KEGG pathways that could be important for the pregnancy outcome.14 HLA-A in pregnancy failure group was reduced in stage II, but was dramatically increased in stage III. In pregnancy success group, HLA-A was gradually decreased with pregnancy duration, and much lower than that in pregnancy failure group. HLA-DQAl was increased with the development duration of pregnancy in pregnancy failure group, and was gradually reduced in the pregnancy success group but was still much greater than that in pregnancy failure group. IL-1β was increased with the development duration of pregnancy in pregnancy failure group. In stage I, the expression of IL-1β in pregnancy success group was higher than that in pregnancy failure group, it was decrease dramatically in stage Ⅱ, and then were elevated in stage Ⅲ but still lower than that in pregnancy failure group. HBD was decreased with the development duration of pregnancy in pregnancy failure group, and maintained in a lower level in stage I and II but dramatically increased to a much higher level in stage III in pregnancy success group. MCM4 was significantly increased in stage III in pregnancy failure group, but was not significantly increased in pregnancy success group.ConclusionThe gene expression analysis was examined on the human pregnancy outcome based on the HiSeqTM 2000 sequencing system from a total of 10 infertile patients with IVF-ET (5 pregnancy success and 5 pregnancy failure) during three different stages:before FVF-ET (Stage I), after ovarian stimulation (Stage II), and day 15 after embryo transfer (Stage III). The results demonstrated that the gene expression between pregnancy success and pregnancy failure has distinct different. The altered expression of genes implicated in immune response and inflammation, oocyte meiosis, rhythmic process, and so on. In this study, we also performed qRT-PCR to verify selected differentially expressed genes and identified the potential biomarker for pregnancy outcome. Regarding HBD and MCM4 as pregnancy outcome biomarker was rarely reported. Moreover, HLA-A and HLA-DQA1 was associated well with the pregnancy development duration, which would put forward new evidence about making HLA-A and HLA-DQA1 as biomarker in pregnancy prediction. The current results provides a strong basis for future research to expound the molecular mechanism coping with pregnancy outcome.