Marker for predicting copy number variation of egg cells and application thereof

Abstract

The invention discloses a marker for predicting copy number variation of egg cells and application of the marker. The marker comprises a combination of CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO proteins. By adopting the marker disclosed by the invention, the expression level of granular cell secreted protein can be determined through granular cell transcriptome sequencing, and the genome CNV condition of corresponding egg cells can be deduced. According to the technical scheme, the detection object is the waste granular cells in the assisted reproduction technology, so that the egg cells cannot be influenced at all, and the method is non-invasive; the research is transcriptome and methylation group detection performed from the single cell level, and has the characteristic of high throughput, and all granular cells and egg cells are paired one by one, and can reflect the difference between COCs at the single cell level.

Description

Technical Field

[0001] The present invention belongs to the field of reproductive technology, and in particular relates to markers for predicting egg cell copy number variation and applications thereof. Background Art

[0002] Oocyte quality is a basic indicator for evaluating women's fertility. Unlike other mammals, the proportion of abnormal copy number of human oocytes is relatively high, and this phenomenon is particularly evident in women of high childbearing age (generally referring to women over 35 years old). Abnormal copy number of oocyte chromosomes will directly lead to abnormal embryonic development after fertilization and cause pregnancy failure. Clinical assisted reproductive technology first obtains fertilized eggs that can be transplanted by selecting healthy oocytes through in vitro fertilization. Therefore, effective prediction of oocyte chromosome copy number and exclusion of abnormal oocytes are crucial to the success of assisted reproductive technology. At present, some studies have used high-throughput sequencing of polar bodies and PGT to obtain chromosomal abnormality information of oocytes or early embryos, but the operation is complicated and expensive. In addition, studies have reported that the follicular microenvironment during oocyte development has an important influence on oocyte development. Granulosa cells are in direct contact with oocytes in spatial structure, and the signal factors and nutrients secreted by granulosa cells directly act on oocytes, which plays a key role in the normal development and maturation of oocytes. Abnormalities in granulosa cells will lead to an imbalance in the signal factors they secrete, thereby affecting the quality of oocytes.

[0003] In Anderson, RA, et al. "Cumulus gene expression as a predictor of human oocyte fertilization, embryo development and competence to establish apregnancy." Reproduction 138.4 (2009): 629-637, the researchers first clarified the feasibility of using granulosa cells to assess the developmental potential of oocytes. The experimental study obtained 674 COC samples from 75 women participating in ICSI, and further separated the granulosa cells to analyze gene expression by quantitative RT-PCR. The study found that the oocytes corresponding to granulosa cells with high expression of GREM1 were more suitable for subsequent ICSI and transplantation (49% vs 33%, P<0.02). It was also found that the oocytes corresponding to granulosa cells with low expression of BDNF had a higher normal fertilization rate. Because the traditional qPCR detection used by the authors only supports six genes (HAS2, BDNF, GREM1, PTGS2, TNFAIP6 and PTX3), the throughput is low and there are fewer potential targets that can be screened. In addition, the authors themselves also pointed out that the expression level of GREM1 in granulosa cells is not significantly correlated with the pregnancy rate. They only made it clear that the expression level of GREM1 will affect the embryo transplantation rate and cryopreservation selection, and the method in the article did not involve the prediction of oocyte copy number variation (CNV).

[0004] In Assidi, M., et al. "Biomarkers of human oocyte developmental competence expressed in cumulus cells before ICSI: a preliminary study." Journal of Assisted Reproduction & Genetics 28.2 (2011): 173-188, the authors first clarified that the morphological characteristics of granulosa cells can be used to reflect the quality of oocytes. These morphologically good COCs are associated with their pregnancy outcomes. The differentially expressed genes in granulosa cells corresponding to oocytes of successful and failed pregnancies were further determined by gene expression chip methods, and potential granulosa cell markers that can predict oocyte quality and pregnancy outcomes were screened. qPCR was further used to verify that the expression levels of DPP8, HIST1H4C, UBQLN1, CALM1, NRP1 and PSMD6 in granulosa cells can be used as markers for evaluating the developmental potential of oocytes. This article also predicts the developmental potential of oocytes through granulosa cells and adopts the detection method of high-throughput gene expression chip to solve the problem of small number of potential genes available for screening. However, the detection indicators for the developmental potential of oocytes in this study are still relatively few. It is relatively one-sided to evaluate the quality of oocytes only from the perspective of pregnancy or not, and the physiological state of oocytes is not clear. The article does not propose a method to detect oocyte CNV through granulosa cells, nor does it explain the specific molecular mechanism of the influence of granulosa cells on oocyte function.

[0005] Therefore, how to obtain markers for predicting abnormalities in oocyte copy number as a clinical evaluation indicator for female fertility remains a technical problem that needs to be urgently solved by technicians in this field. Summary of the invention

[0006] Based on the above reasons, the present invention proposes a marker for predicting oocyte copy number variation and its application. Specifically, in order to achieve the purpose of the present invention, the present invention intends to adopt the following technical solutions:

[0007] The present invention relates to a marker for predicting oocyte copy number variation, wherein the marker comprises a combination of CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO proteins.

[0008] CLEC11A: This gene encodes a member of the C-type lectin superfamily (C-type lectin domain family 11, type A). The encoded protein is a secreted sulfated glycoprotein that acts as a growth factor for primitive hematopoietic progenitor cells.

[0009] P4HB: This gene encodes the beta subunit of prolyl 4-hydroxylase, a highly abundant multifunctional enzyme that belongs to the protein disulfide isomerase family.

[0010] EFEMP2: EGF-containing fibrin-like extracellular matrix protein 2, this gene encodes a protein containing four EGF2 domains and six calcium-binding EGF2 domains. This gene is essential for the formation of elastic fibers and the development of connective tissue. Defects in this gene are the cause of autosomal recessive cutis laxa syndrome.

[0011] IL32: This gene encodes interleukin 32, a member of the cytokine superfamily. The protein contains a tyrosine sulfation site, three potential N-myristoylation sites, multiple putative phosphorylation sites, and an RGD cell attachment sequence. The expression of this protein increases after mitogen activation of T cells or IL-2 activation of NK cells. This protein can induce TNFα production by macrophages.

[0012] FTL: This gene encodes the light chain subunit of ferritin, the major intracellular iron storage protein in prokaryotes and eukaryotes.

[0013] FLNA: Filamin A gene, the protein encoded by this gene is an actin-binding protein that cross-links actin filaments and connects actin filaments to membrane glycoproteins. The encoded protein is involved in the remodeling of the cytoskeleton to affect changes in cell shape and migration.

[0014] COL6A3: This gene encodes type VI collagen alpha 3 chain, which is one of the three alpha chains of type VI collagen, a beaded, filamentous collagen found in most connective tissues.

[0015] ACPP: Acid phosphatase 3 gene, which encodes an enzyme that catalyzes the conversion of orthophosphate monoesters into alcohol and orthophosphate. It is synthesized under the regulation of androgens and secreted by prostate epithelial cells.

[0016] APOO: This gene is a member of the apolipoprotein family. Members of this protein family are involved in the transport and metabolism of lipids. The encoded protein is associated with HDL, LDL, and VLDL lipoproteins and is characterized by chondroitin sulfate glycosylation. This protein may be involved in preventing lipid accumulation in the myocardium of patients with obesity and diabetes.

[0017] In a preferred embodiment of the present invention, the marker is a secretory protein in granulosa cells. In the process of assisted reproduction, the present invention only requires oocytes provided by the patient, and granulosa cells are discarded because they do not participate in the operation process of assisted reproductive technology. Therefore, by evaluating the relevant secretory proteins in granulosa cells, relevant auxiliary detection work can be easily obtained and performed. Any evaluation and detection of granulosa cells will not affect oocytes, so evaluating the developmental potential of oocytes through granulosa cells is non-invasive and will not cause any adverse effects on the outcome of assisted reproduction.

[0018] Another aspect of the present invention also relates to the use of the above markers in the preparation of diagnostic reagents for predicting abnormalities in oocyte copy number.

[0019] In a preferred embodiment of the present invention, the diagnostic reagent is used to evaluate the expression levels of secretory proteins CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO in granulosa cells.

[0020] In a preferred embodiment of the present invention, the diagnostic reagent is used to evaluate female fertility.

[0021] In a preferred embodiment of the present invention, the female is over 35 years old.

[0022] Beneficial Effects

[0023] By using the markers of the present invention, the expression level of granulosa cell secretory proteins can be determined through granulosa cell transcriptome sequencing, and the genomic CNV of the corresponding oocyte can be inferred. The detection object of this technical solution is the discarded granulosa cells in assisted reproductive technology, so it will not have any effect on the oocytes and is non-invasive; this study is a transcriptome and methylation group detection at the single cell level, which has the characteristics of high throughput, and all granulosa cells and oocytes are paired one by one, which can reflect the differences between COCs at the single cell level. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The chromosome copy number of normal oocytes;

[0025] Figure 2 The copy number of chromosomes in oocytes with abnormal copy number;

[0026] Figure 3 are differentially expressed genes in the granulosa cell transcriptome, among which those with gene names displayed are potential secretory protein markers;

[0027] Figure 4 for differentially expressed secretory proteins in granulosa cells;

[0028] Figure 5 for abnormal granulosa cells (n=2) differentially expressed secretory proteins;

[0029] Figure 6 This is the test data of chromosome copy number in normal oocytes;

[0030] Figure 7 The data are the test data for chromosome copy number in oocytes with abnormal copy number. DETAILED DESCRIPTION

[0031] In order to further understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in combination with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Unless otherwise specified, the reagents involved in the embodiments of the present invention are all commercially available products and can be purchased through commercial channels.

[0033] Embodiment 1:

[0034] The research object of the present embodiment is the oocytes donated by a group of volunteers participating in assisted reproductive medical services (all volunteers have signed informed consent). The physical indications of the volunteers were strictly screened, and the volunteers could not have the following indications: suffering from polycystic ovarian syndrome (PCOS), previous ovarian surgery history, ovarian cysts, ovarian teratoma, endometriosis, thyroid dysfunction, diabetes, obesity, and all patients' body mass index was within the normal range (22.13 ± 2.73). The ovulation induction scheme includes: long scheme, short scheme, antagonist scheme and natural cycle egg extraction. When the follicle diameter reaches 20mm, COCs are aspirated by vaginal ultrasound aspiration needle 36h after HCG injection. Genome methylation sequencing is carried out on the oocyte, and the purpose is to determine the chromosome copy number characteristics of these oocytes, and to use this as an indicator for evaluating the quality of the oocyte. At the same time, transcriptome sequencing is carried out on the periovulatory granulosa cells, and the state of the periovulatory granulosa cell transcriptome corresponding to the oocytes of different quality is clarified, and the secretory protein that can affect the quality of the oocytes secreted by the granulosa cells is screened out, and the index is raised as the clinical female fertility assessment.

[0035] 1. Granulosa Cell Transcriptome Amplification and Sequencing

[0036] First, the oocytes in the COC were peeled off and removed, and the remaining translucent cloud was a granular cell cluster, which was washed in PBS buffer and digested with 3‰ hyaluronidase to separate into single-cell granular cells. 20-30 granular cells were randomly selected from each sample and transferred to the pre-configured mRNA extraction lysis buffer. The smart-seq2 single-cell library construction technology was used to prepare the RNA-seq sequencing library (the commercial library construction kit was used to construct the second-generation sequencing library). The library was sequenced using the Illumina-NovaSeq sequencer, and the sequencing method was double-end 150bp. The sequencing volume of each RNA sample was 3G.

[0037] 2. Preparation of single-cell transcriptome and methylation libraries using Trio-seq method

[0038] After the oocytes stripped of granulosa cells were treated in a neutral PBS solution with 3‰ HCL for 2-3s to remove the zona pellucida, they were transferred to the Trio-Seq lysis buffer (at the same time, 20-30 granulosa cell samples corresponding to the oocytes were transferred to the Smart-Seq lysis buffer to ensure the one-to-one correspondence between granulosa cells and oocytes in COC). The oocytes were picked into the Trio-Seq lysis buffer, the magnetic stand was precooled at 4°C, and after oscillation and mixing for 2min, they were placed on the magnetic stand for 5min. CA beads were observed to be adsorbed on one side of the magnetic stand. At this time, the DNA in the nucleus of the oocyte was adsorbed by CA beads in the original tube. The oocyte nucleus retained in the 0.2ml centrifuge tube was used for methylome library preparation (PBAT method, commercial library construction kit). The library was sequenced using the Illumina-NovaSeq sequencer, and the sequencing method was double-end 150bp. The sequencing amount of each PBAT library was 6G.

[0039] 3. Sequencing data cleaning, alignment and post-alignment processing

[0040] The obtained RNA sequencing data (reads) were trim_galore with default parameters to remove the second-generation sequencing adapter sequences and low-quality bases. Only sequences with a length greater than 36 bp after processing were retained. The processed sequences were aligned to the gencode hg38 human reference genome using STAR software with default parameters. The aligned sequences were used to count the number of gene expressions using featureCounts software, and the standardized TPM values ​​were calculated. For the PBAT methylation sequencing data (reads), trim_galore was also used for cleaning, and then bismark software was used to align to the gencode hg38 genome with default parameters. After alignment, the sequences were picard software to remove low alignment quality sequences and PCR repeat sequences in the results. The only non-repetitive sequences aligned to the reference genome were obtained. Since oocytes and granulosa cells are closely adhered, there may be mutual contamination during the library construction process. We confirmed the reliability of the granulosa cell transcriptome library by evaluating the mRNA expression levels of granulosa cell and oocyte marker genes. The methylation sequencing results were used to analyze and compare the methylation levels of the oocyte landmark DMR regions verified in previously published literature, verifying that the oocyte methylation library in this study was complete and reliable.

[0041] 4. Inferring the chromosome copy number of oocytes through PBAT methylation data

[0042] First, calculate the alignment sequence count, window GC content, and alignment rate in the reference genome window. Divide the reference genome into 1Mb windows and use readCounter to count the number of alignment sequences in each window. Use gcCounter to calculate the GC content of each window of the reference genome. Use mapCounter to calculate the alignment rate of each window of the reference genome. Use R software 'hmmcopy' to calculate the chromosome copy number of the oocyte. The results are as follows: Figure 1 and Figure 2 shown.

[0043] 5. Analyze the transcriptome differences of granulosa cells corresponding to copy number difference oocytes and mine signature secretory proteins

[0044] After inferring oocyte chromosome CNV through oocyte PBAT methylation data, the granulosa cells corresponding to oocytes with normal CNV were used as the control group (n=9), and the granulosa cells corresponding to oocytes with abnormal CNV were used as the experimental group (n=5) ( Figure 1), and differential gene analysis was performed using R software Seurat. The specific steps were as follows: first, the standardized TPM value was log2-converted, then a seurat object was created, the gene expression data distribution was adjusted using the scaledata command, and then the findmarker command (specific parameters: min.pct = 0.3, logfc.threshold = 1, test.use = 'wilcox') was used to obtain genes with significant differences, and then the genes with significant differences of p < 0.05 were screened. Finally, the genes with significant differences were compared with the human follicular fluid protein and human secretory protein gene sets obtained from published literature, and then the differential secretory proteins between the granulosa cells in the case of abnormal oocyte CNV and the granulosa cells in normal oocytes were found. The results are shown in Figure 2. Figure 3 and Figure 4 shown.

[0045] Example 2: Application of marker genes of granulosa cells to predict oocyte quality

[0046] We obtained 4 COC samples from the IVF laboratory, and further used the relevant transcriptome sequencing library construction and analysis methods in Example 1 above to find that the expression trends of the 10 marker genes screened in Example 1 above in granulosa cell samples were significantly different, and two of the samples had low expression of CLEC11A, P4HB, EFEMP2, IL32, FTL and FLNA, and high expression of COL6A3, ACPP and APOO ( Figure 5 ), and it is speculated that the oocytes corresponding to these two COC samples have CNV abnormalities. We further constructed a methylation library for the oocytes in these four COC samples to infer the genomic CNV situation. We found that the oocytes corresponding to the granulosa cells with abnormal expression of CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO in the above two cases had CNV abnormalities. One of the COC sample oocytes had a copy number amplification of chromosome 6, and the other COC sample had a copy number loss of chromosome 4 and a copy number amplification of chromosome 15 ( Figure 6 and Figure 7 ), which is consistent with our speculation. In this case, by evaluating the expression levels of secretory proteins CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP, and APOO in granulosa cells, we obtained accurate information on the genomic CNV status of oocytes.

[0047] The above describes the preferred embodiments of the present invention, but it is not intended to limit the present invention. Those skilled in the art may make improvements and changes to the embodiments disclosed herein without departing from the scope and spirit of the present invention.

Claims

1. A marker for predicting oocyte copy number variation, the marker comprising a combination of CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO proteins. The marker according to claim 1 , which is a secretory protein in granulosa cells.

3. Use of the marker according to claim 1 or 2 in the preparation of a diagnostic reagent for predicting abnormal oocyte copy number.

4. The use according to claim 3, wherein the diagnostic reagent is used to evaluate the expression levels of secretory proteins CLEC11A, P4HB, EFEMP2, IL32, FTL, FLNA, COL6A3, ACPP and APOO in granulosa cells.

5. The use according to claim 3, wherein the diagnostic reagent is used to evaluate female fertility.

6. The use according to claim 5, wherein the female is over 35 years old.

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