Transcriptome analysis of PCOS arrested 2-cell embryos

ABSTRACT

In an attempt to explore the early developmental arrest in embryos from polycystic ovarian syndrome (PCOS) patients, we sequenced the transcriptome profiles of PCOS arrested 2-cell embryos, non-PCOS arrested 2-cell embryos and non-arrested 2-cell embryos using single-cell RNA-Seq technique. Differential expression analysis was performed using the DEGSeq R package. Gene Ontology (GO) enrichment was analyzed using the GOseq R package. Data revealed 62 differentially expressed genes between non-PCOS arrested and PCOS arrested embryos and 2217 differentially expressed genes between PCOS arrested and non-arrested 2-cell embryos. A total of 49 differently expressed genes (DEGs) were annotated with GO terms in the up-regulated genes between PCOS arrested and non-PCOS arrested embryos after GO enrichment. A total of 29 DEGs were annotated with GO terms in the down-regulated genes between PCOS arrested and non-arrested 2-cell embryos after GO enrichment. These data can provide a reference for screening specific genes involved in the arrest of PCOS embryos.

KEYWORDS:

• PCOS
• embryo arrest
• transcriptome

Introduction

Despite the use of in vitro fertilization (IVF) as an assisted reproductive technology for over 30 years, early developmental failure of embryos occurs with a high frequency. More than 50% of IVF embryos do not reach the blastocyst stage of development. After transfer, some embryos are unable to sustain development. Although culture conditions have significantly improved over the years, 10–15% of embryos enter a permanent state of cell cycle arrest, and 40% of patients have at least one arrested embryo per cycle [1].

Polycystic ovarian syndrome (PCOS) is the most common metabolic dysfunction and heterogeneous endocrine disorder in women of reproductive age. This condition is characterized by oligo-ovulation or anovulation, hyperandrogenism and multicystic ovaries [2]. A community-based epidemiological study has shown that the prevalence of PCOS in Chinese women of reproductive age is about 5.6% [3]. Although the number of retrieved oocytes increases during IVF treatment, those of PCOS patients often have lower cleavage rates [4]. In a murine PCOS model induced by dehydroepiandrosterone (DHEA), embryo developmental competence was decreased compared with that of control mice [5]. The underlying mechanism of embryo arrest in PCOS patients remains unclear. To explore this issue, we sequenced the transcriptome profiles of PCOS arrested embryos using the single-cell RNA-Seq technique.

Results

The total transcriptomes were extracted and amplified. The Illumina HiSeq platform was used to sequence the RNA transcriptomes. Clean data were obtained from the non-arrested 2-cell embryo, non-PCOS arrested embryo and PCOS arrested embryo (10.55 Gb, 9.08 GB and 15.32 Gb, respectively) (Table 1). Differential expression analysis was performed using the DESeq R package (1.18.0). P-values were adjusted using the Benjamini and Hochberg method for controlling the false discovery rate. Genes with adjusted P < 0.05 were assigned as differentially expressed. Relative to gene expression in the non-arrested 2-cell embryo, 3648 genes were up-regulated and 2064 genes were down-regulated in the non-PCOS arrested embryo (Figure 1(a)), and 1929 genes were up-regulated and 1805 genes were down-regulated in the PCOS arrested embryo (Figure 1(b)). In addition, gene expression differences were analysed between the non-PCOS and PCOS arrested embryos. Relative to gene expression in the PCOS arrested 2-cell embryo, 642 genes were up-regulated and 35 genes were down-regulated in the non-PCOS arrested embryo (Figure 1(c)). Details regarding gene expression in each group are shown in Supplementary Datasets 1–6.

Table 1. Summary of the sequence assembly after Illumina sequencing.

Sample name	Raw reads	Clean reads	Clean bases	Error rate (%)	Q20 (%)	Q30 (%)	GC content (%)
Normal 2-cell 1	44346717	34559454	3.46G	0.04	97.07	91.28	43.58
Normal 2-cell 2	43138152	33947088	3.40G	0.04	97.13	91.38	43.70
Normal 2-cell 3	47009259	36844353	3.69G	0.04	96.98	90.88	43.39
Non-PCOS arrest 1	33403676	22702894	2.83G	0.03	96.46	92.70	49.45
Non-PCOS arrest 2	37950082	23810672	2.97G	0.03	95.97	91.74	46.20
Non-PCOS arrest 3	69520534	26313142	3.28G	0.05	96.02	91.98	48.06
PCOS arrest 1	50948968	26618254	3.32G	0.04	95.88	91.60	48.36
PCOS arrest 2	63678672	23465086	2.92G	0.04	96.16	92.26	47.94
PCOS arrest 3	85369950	72645034	9.08G	0.03	95.80	91.42	46.33

Notes: Q20, percentage of bases with a Phred value of at least 20; Q30, percentage of bases with a Phred value of at least 30.

Figure 1. Count of differentially expressed genes between non-PCOS arrested and non-arrested 2-cell embryos (a), PCOS arrested and non-arrested 2-cell embryos (b) and between non-PCOS and PCOS arrested embryos (c). The x-axis shows the fold-change in gene expression, and the y-axis shows significant statistical differences. Red, up-regulated genes; green, down-regulated genes.

The DEGSeq R package (1.18.0) was used to determine the differentially expressed genes between groups using the sequenced libraries. The hierarchical clustering of all differentially expressed genes was performed as shown in Figure 2(a). There were 62 differentially expressed genes (DEGs) between non-PCOS and PCOS arrested embryos, 3683 DEGs between non-PCOS arrested and non-arrested 2-cell embryos and 2217 DEGs between PCOS arrested and non-arrested 2-cell embryos (Figure 2(b)). Details regarding gene expression in each group are shown in Supplementary Dataset 7.

Figure 2. Cluster analysis of DEGs. A, hierarchical cluster analysis of DEGs of PCOS, non-PCOS arrested and non-arrested 2-cell embryos; B, Venn diagram showing the overlaps between groups. Red, high gene expression levels; blue, low gene expression levels.

To further analyze differential gene expression in these embryos, GO enrichment analysis was performed using the GOseq R package and five representative GO terms in representive biological process were showed in Figure 3. Functional annotation of DEGs in the down-regulated genes between PCOS arrested and non-arrested 2-cell embryos is shown in Table 2 and functional annotation of DEGs in the up-regulated genes between PCOS and non-PCOS arrested embryos is shown in Table 3. The enrichment of differentially expressed genes in the KEGG pathways was analysed using KOBAS software. The terms systemic lupus erythematosus, transcriptional misregulation in cancer, spliceosome and alcoholism were significantly enriched in up-regulated genes between PCOS and non-PCOS arrested embryos (P < 0.05, Figure 4(d)). The terms ribosome, RNA transport, ubiquitin-mediated proteolysis, Huntington’s disease, Parkinson’s disease, cell cycle, oxidative phosphorylation, metabolic pathways, legionellosis and Alzheimer’s disease were significantly enriched in down-regulated genes between PCOS arrested and 2-cell embryos (P < 0.05, Figure 4(e)). The representative cell cycle pathway differed significantly between PCOS arrested and non-arrested 2-cell embryos was shown in Figure 5.

Table 2. Functional annotation of DEGs in the down-regulated genes between PCOS arrested and 2-cell embryo.

GO accession	Description	Term types	Adjusted P values
GO:0005622	intracellular	Cellular component	5.86E-07
GO:0005623	cell	Cellular component	2.56E-06
GO:0044464	cell part	Cellular component	2.56E-06
GO:0009058	biosynthetic process	Biological process	0.0047284
GO:0003924	GTPase activity	Molecular function	0.0063557
GO:0008152	metabolic process	Biological process	0.0065239
GO:0044249	cellular biosynthetic process	Biological process	0.0065239
GO:1901576	organic substance biosynthetic process	Biological process	0.0065239
GO:0005737	cytoplasm	Cellular component	0.010424
GO:0044237	cellular metabolic process	Biological process	0.015558
GO:0044271	cellular nitrogen compound biosynthetic process	Biological process	0.034668
GO:0071704	organic substance metabolic process	Biological process	0.035282
GO:0018130	heterocycle biosynthetic process	Biological process	0.036328
GO:0043227	membrane-bounded organelle	Cellular component	0.036328
GO:0003824	catalytic activity	Molecular function	0.04082
GO:0043231	intracellular membrane-bounded organelle	Cellular component	0.04082
GO:0005525	GTP binding	Molecular function	0.04082
GO:0032561	guanyl ribonucleotide binding	molecular_function	0.041541
GO:0097159	organic cyclic compound binding	Molecular function	0.045173
GO:1901362	organic cyclic compound biosynthetic process	Biological process	0.045967
GO:0007018	microtubule-based movement	Biological process	0.045967
GO:0017111	nucleoside-triphosphatase activity	Molecular function	0.045967
GO:0019438	aromatic compound biosynthetic process	Biological process	0.045967
GO:0019001	guanyl nucleotide binding	Molecular function	0.045967
GO:0046148	pigment biosynthetic process	Biological process	0.04854
GO:0042440	pigment metabolic process	Biological process	0.04854
GO:1901363	heterocyclic compound binding	Molecular function	0.04854
GO:0010467	gene expression	Biological process	0.04854
GO:0016818	hydrolase activity, acting on acid anhydrides, in phosphorus- containing anhydrides	Molecular function	0.04854

Table 3. Functional annotation of DEGs in the up-regulated genes between PCOS and non-PCOS arrested embryo.

GO accession	Description	Term types	Adjusted P values
GO:0003676	nucleic acid binding	Molecular function	4.99E-07
GO:0043565	sequence-specific DNA binding	Molecular function	3.19E-06
GO:0005488	binding	Molecular function	3.19E-06
GO:0016070	RNA metabolic process	Biological process	1.44E-05
GO:0003677	DNA binding	Molecular function	3.58E-05
GO:0090304	nucleic acid metabolic process	Biological process	5.98E-05
GO:0006351	transcription, DNA-dependent	Biological process	0.00018512
GO:0032774	RNA biosynthetic process	Biological process	0.00019373
GO:0008270	zinc ion binding	Molecular function	0.00019373
GO:1901363	heterocyclic compound binding	Molecular function	0.00019373
GO:0097159	organic cyclic compound binding	Molecular function	0.00019373
GO:0034654	Nucleobase containing compound biosynthetic process	Biological process	0.00057696
GO:0006139	nucleobase-containing compound metabolic process	Biological process	0.00057696
GO:2000112	regulation of cellular macromolecule biosynthetic process	Biological process	0.00057696
GO:0010556	regulation of macromolecule biosynthetic process	Biological process	0.00057696
GO:0031326	regulation of cellular biosynthetic process	Biological process	0.00057696
GO:0009889	regulation of biosynthetic process	Biological process	0.00057696
GO:0006355	regulation of transcription, DNA-dependent	Biological process	0.00057696
GO:0051252	regulation of RNA metabolic process	Biological process	0.00057696
GO:2001141	regulation of RNA biosynthetic process	Biological process	0.00057696
GO:0010468	regulation of gene expression	Biological process	0.00073122
GO:0060255	regulation of macromolecule metabolic process	Biological process	0.0011985
GO:0019438	aromatic compound biosynthetic process	Biological process	0.0014888
GO:0046483	heterocycle metabolic process	Biological process	0.0015037
GO:0006725	cellular aromatic compound metabolic process	Biological process	0.0015037
GO:0018130	heterocycle biosynthetic process	Biological process	0.0019823
GO:0031323	regulation of cellular metabolic process	Biological process	0.0021782
GO:1901360	organic cyclic compound metabolic process	Biological process	0.0022871
GO:0044271	cellular nitrogen compound biosynthetic process	Biological process	0.0022949
GO:0019219	regulation of nucleobase-containing compound metabolic process	Biological process	0.0022949
GO:0051171	regulation of nitrogen compound metabolic process	Biological process	0.0022949
GO:0080090	regulation of primary metabolic process	Biological process	0.0024321
GO:0019222	regulation of metabolic process	Biological process	0.0024394
GO:1901362	organic cyclic compound biosynthetic process	Biological process	0.0024457
GO:0001071	nucleic acid binding transcription factor activity	Molecular function	0.0025382
GO:0003700	sequence-specific DNA binding transcription factor activity	Molecular function	0.0025382
GO:0034641	cellular nitrogen compound metabolic process	Biological process	0.0035068
GO:0046872	metal ion binding	Molecular function	0.0057461
GO:0043169	cation binding	Molecular function	0.0068433
GO:0046914	transition metal ion binding	Molecular function	0.0071118
GO:0010467	gene expression	Biological process	0.0093075
GO:0022613	ribonucleoprotein complex biogenesis	Biological process	0.011344
GO:0006807	nitrogen compound metabolic process	Biological process	0.014291
GO:0006367	transcription initiation from RNA polymerase II promoter	biological process	0.016731
GO:0042254	ribosome biogenesis	Biological process	0.025702
GO:0005515	protein binding	Molecular function	0.029572
GO:0006396	RNA processing	Biological process	0.04445
GO:0005634	nucleus	Cellular component	0.044722
GO:0005622	intracellular	Cellular component	0.046387

Figure 3. GO enrichment in biological process analysis of DEGs. The x-axis shows −log10 (pvalue), and the y-axis shows the five representative GO terms in biological process. A, down-regulated genes between non-PCOS arrested and non-arrested 2-cell embryos; B, up-regulated genes between non-PCOS arrested and non-arrested 2-cell embryos; C, down-regulated genes between non-PCOS and PCOS arrested embryos; D, up-regulated genes between non-PCOS and PCOS arrested embryos; E, down-regulated genes between PCOS arrested and non-arrested 2-cell embryos; F, up-regulated genes between PCOS arrested and non-arrested 2-cell embryos.

Figure 4. KEGG enrichment analyses of DEGs. The ratio of the number of DEGs to the total gene number is represented by the enrichment factor. Size of dots: gene number; colour of dots: range of P-values. A, representative terms between non-PCOS arrested and non-arrested 2-cell embryos in down-regulated genes; B, representative terms between non-PCOS arrested and non-arrested 2-cell embryos in up-regulated genes; C, representative terms between non-PCOS and PCOS arrested embryos in down-regulated genes; D, representative terms between non-PCOS and PCOS arrested embryos in up-regulated genes; E, representative terms between PCOS arrested and non-arrested 2-cell embryos in down-regulated genes; F, representative terms between PCOS arrested and non-arrested 2-cell embryos in up-regulated genes.

Figure 5. Representative cell cycle pathway between PCOS arrested and non-arrested 2-cell embryos. Red, down-regulated gene names.

To validate the transcripts, the relative mRNA levels of 5 genes involved in mitochondria and the cell cycle were analysed by QPCR. As shown in Figure 6, these genes were significantly down-regulated in PCOS arrested embryos compared with non-arrested 2-cell embryos, which is consistent with the transcript data.

Figure 6. Relative expression of 5 selected genes by Q-PCR. The relative gene expression levels were calculating using the 2^−ΔΔCt method. R.Q., relative expression; *P < 0.05 indicates that the genes were significantly down-regulated in PCOS and non-PCOS arrested embryos relative to the non-arrested 2-cell embryo.

Discussion

In the present study, we used single-cell transcriptome sequencing to profile gene expression of a PCOS arrested embryo. The results indicate that 1929 genes were up-regulated and 1805 genes were down-regulated in the PCOS arrested embryo relative to that of the non-arrested 2-cell embryo.

It is well known that developmental arrest was involved in permanent cell-cycle arrest at the 2–4 cell stage [1]. After fertilization, the zygote develops into a 16-cell morula by undergoing multiple cell doublings. Embryonic genome activation (EGA) plays an important role in the success of preimplantation embryo development [6]. The quality of the oocyte is essential for early embryo development. The early stages of embryo development are driven by the maternal genome. Maternal RNA transcripts influence early embryo developmental kinetics until EGA. The altered gene expression profile was found in human PCOS cumulus cells of MII mature oocytes [7]. Therefore, it is possible that PCOS embryos may have a reduced capacity to complete earlier stages of development because of the abnormality of RNA transcriptome.

During the embryo preimplantation stage, the major role of mitochondria is ATP production through oxidative phosphorylation. Gradually, as the embryo grows from 1 cell to a blastocyst, oxygen consumption increases to support cellular biosynthetic activities, plasma membrane production and morphodynamic processes [8]. Mitochondria are inherited entirely maternally and do not replicate until after implantation. Mitochondrial structural abnormalities in the oocyte have adverse effects on embryo competence because metabolic activity and ATP production are decreased [9].

It had been reported that oocytes of PCOS patients had a higher NADPH content, glucose and pyruvate consumption than control oocytes [10], which could indicate elevated reactive oxygen species (ROS) production in PCOS oocytes. The level of intracellular ROS was elevated and the frequency of embryo arrest was higher in embryos cultured in 20% oxygen conditions than in those cultured in 5% oxygen conditions [11]. Our previous data have shown that oocytes from PCOS mice have lower mtDNA copy numbers, ATP content and inner mitochondrial membrane potential compared with control mice [5]. Jia L et al. found that PCOS in gilts results in hypermethylation of mitochondrial DNA, lower DNA copy number and oocyte malfunction [12]. Development of the preimplantation embryo is a dynamic process requiring energy to fuel mitosis. Mitochondrial ATP generation affects the ATP supply/demand balance in the cytoplasm [13]. An imbalance between ATP supply and demand leads to the arrest of cell division by inducing cell cycle arrest. Therefore, the slower development in early embryos from PCOS women might in part relate to mitochondrial dysfunction in their oocytes. In this study, our results also had showed that genes involved in the oxidative phosphorylation pathway were significantly down-regulated in the PCOS arrested embryos.

The gene ontology and pathway analysis in our results supplied the consistent data that the cellular biosynthetic process and metabolic process were down-regulated and lipopolysaccharide biosynthetic process and glutamate catabolic process were up-regulated in PCOS arrested group than control embryos. Wissing ML et al. examined embryos cleavage kinetics by time-lapse system and found that embryos of PCOS patients took longer to reach the four cell stage than control embryos [14]. The arrested 2-cell embryos were obtained in the present study on Days 3, a long time period with little possibility because of developmental delay. However, it is limit that only embryos from IVF patient were dissected in the present study. The normal pattern of embryonic gene expression of embryos in non-IVF patients need further research in the future.

Altogether, in the present study we identified more than 3000 genes and transcripts that differed between the PCOS arrested embryo and the non-arrested 2-cell embryo. These data provide a reference for screening specific genes involved in PCOS embryo arrest. More research is needed to explore the mechanism underlying the arrest of PCOS embryos.

Methods

Embryo collection

This study was approved by the Ethics Committee of Peking University Third Hospital. Informed consent confirmed that the couple donors were voluntarily donating embryos for research on the arrest mechanism of PCOS embryos, with no monetary payment (No. 2008013). All methods used in the present study were performed in accordance with the relevant guidelines and regulations.

IVF and intracytoplasmic sperm injection were performed according to routine laboratory insemination procedures on the day of oocyte retrieval (Day 0). The presence of two pronuclei was observed 16–18 h after insemination or injection, and the zygotes were then cultured in 25 µL of pre-equilibrated cleavage medium. The embryos were cultured in incubators at 37°C under 5% or 6% CO₂. Embryo morphology was evaluated 68–72 h (Day 3) after insemination. The embryos with less than 4 cells were named arrested embryos. In the present study, PCOS arrested embryos and non-PCOS arrested embryos were two-cell embryos on Day 3 with less than 10% fragmentation and no multinucleation. The average maternal age was 30 years and all had tubal factor infertility.

Preparation of single-cell cDNAs

The single-cell RNA-Seq method was used as described previously [15,16]. Briefly, every single embryos were transferred into lysate buffer by mouth pipette and a reverse transcription reaction was performed on the whole-cell lysate. We use terminal deoxynucleotidyl transferase to add a poly (A) tail to the 3ʹ end of the first-strand cDNA, and then perform 20 + 10 cycles of PCR to amplify the single-cell cDNA.

RNA-Seq library preparation

After the generation of cDNA from a single cell, 200 ng of cDNA was sheared into 150- to 350-bp fragments by Covaris S2, and a TrueSeq DNA library preparation kit (Illumina) was used to prepare a sequencing library following the manufacturer’s suggested procedures. The fragmented cDNA was end-repaired, dA-tailed, adaptor ligated and then subjected to 10–12 cycles of PCR amplification. The PCR products were purified (AMPure XP system; Beckman Coulter, Brea, CA, USA), and the library quality was assessed using the Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA).

Clustering and sequencing

Clustering of index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform. We obtained 30–80 million 150-bp reads for each individual embryo.

Data analysis

Differential expression analysis of the two groups was performed using the DEGSeq R package (1.18.0). DEGSeq analysis provides statistical routines for determining differential gene expression using a model based on the negative binomial distribution. The P-values were adjusted using the Benjamini and Hochberg method for controlling the false discovery rate. Genes with adjusted P < 0.05 were assigned as differentially expressed.

Gene Ontology (GO) enrichment analysis was performed using the GOseq R package with correction for gene length bias. GO terms with corrected P < 0.05 were considered significantly enriched by differentially expressed genes. The enrichment of differentially expressed genes in KEGG pathways was analysed using KOBAS software. The data for non-arrested 2-cell embryos was acquired from our previous study [16].

Quantitative real-time PCR

Quantitative real-time PCR (QPCR) was performed using an ABI model 7700 real-time PCR system (ABI). Each group including three different sequenced samples and were analyzed for each gene, and RPS24 was used as the internal control gene. The expression level was evaluated by ∆∆Ct method. The primers are listed in Supplementary Datasets 8.

Author contributions

Conceived and designed the study: SLL, HBC and CLL; coordinated embryo collection: SLL, YPW, HBC and LNW; analysed the data: SLL, CLL, SH, LLY, XF, PL and JQ; wrote the manuscript: SLL; all authors interpreted the data.

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Peking University Third Hospital (No. 2008013).

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 81200437, 81601275, 31401256 and 81501325].