Single Cell Transcriptome Technique And Its Application In The Study Of Primordial Follicles Activation

Chapter I Study on the Mechanism of Follicle Activation Using Single Oocyte qPCRObjective:The early stages of oocytes are difficult to study because they are small in size and tightly close to the surrounding granulosa cells.In most studies,researchers usually use ovary tissue as the experimental object to study the follicle development and may be disturbed by other types of cells in ovary tissue.In this study,we used single cell qPCR technique to study the changes of gene expression during the process of primordial follicle activation.In this way,we could study the mechanism of follicle activation more accurately,because there is no influence from other kinds of ovarian cells.In addition,through bioinformatics analysis,we will predict the follicle activation-related signaling pathways and upstream regulators.Methods:91 candidate genes of follicle activation and 5 endogenous genes were selected from the Ingenuity Pathway Analysis(IPA)software and Ovarian Kaleidoscope Database(OKdb)to customize a Taqman array card.40 oocytes from primordial follicles and 40 oocytes from primary follicles were picked up from C57BL/6 mice based on their morphology.Then the single oocytes were prepared using Single Cell-to-Ct Kit and loaded to Taqman array card for qPCR.The gene expression data was analyzed with StatMiner software.Following that significate changed genes which fold change more than 5 times were inputted to the IPA software for core analysis.Results:Among the selected genes,14 undetermined genes were excluded firstly and the remaining 82 genes were used for data analysis.The results showed that there was a significant difference in gene expression between oocytes before and after follicle activation.The hierarchical clustering and principal component analysis(PCA)were performed,and the results showed that the two stages of oocytes were separated obviously.Following that,the core analysis was conducted using IPA software,numbers of related pathways and upstream regulators were predicted which might related to the follicle activation.Among them,the most relevant signaling pathway was PTEN signaling pathway(P = 8.92×10-6).By analyzing the signal network of differential genes,we predicted that Rela was the most important gene.Conclusion:The results of single oocyte qPCR can clearly distinguish the primordial and primary follicle oocytes.The top related pathway predicted by software is PTEN signaling pathway.Besides,the Rela gene which predicted as the top regulator ofthebuilt networks might be a novel gene related to follicle activation.Chapter II Effect of Rela Gene on Follicle Activation and Identification of Reference Genes for qPCR in Granulosa CellsPart I Effect of Rela Gene on Follicle ActivationObjective:The RELA is a subunit of NF-kB complex which is a ubiquitous transcription factor involved in several biological processes.However,no previous study was reported about the role and function during the follicle development.Predicted by our single oocyte qPCR,the Rela might be a new gene related to follicle activation.In this chapter,we usedthe ovary in vitro culture system and c.elegans to study the role of Rela and NF-kB signaling pathway in the process of follicle activationand tostudy the mechanism of Rela in ovarian cells.Methods:The location of Rela gene on mice ovary were conducted by immunohistochemicall(IHC).Rela gene-specific agonist,inhibitor and siRNA were selected to treat the cultured ovary and granulosa cells,and ovarian phenotype changes were observed by follicle counting.Western blot and single cell qPCR were used to study the protein and gene expression after ovary culture.Besides,we also observe the reproductive phenotype of Rela gene effecting on C.elegans by treating the c.elegans with agonist and inhibitor.Results:The RELA protein was observed widely expressed in various stages of oocytes and granulosa cells by IHC,while there is no expression of RELA protein in ovary theca and interstitial cells.Up-regulation of Rela and NF-kB signalingwill result in andecrease in the proportion of primordial follicles,a increase in the proportion of developing follicles while down-regulation of Rela will result in an increase in the proportion of primordial follicles,a decrease in the proportion of developing follicles,and an increase in the number of atresia follicles.The single cell qPCR results showed that the activation of NF-kB pathway in the oocytes can increase the expression of Gdf9 and decrease the expression of Pten,while inhibiting the Rela gene can lead to the down-regulation of Nobox and Bcl211 genes.After up-regulation and down-regulation of Rela in primary granulosa cells,the expression of downstream genes such as 116 and Bcl211 of the NF-kB pathway was significantly changed both at the protein level and at the RNA level.Besides,after treatment by Rela activator,the blood size of c.elegans were significant increase in day 2 during culture.Conclusion:Rela is widely expressed in various stages of oocytes and granulosa cells.And this gene may play a role during the reproductive development in mice and c.elegans.The experimental results show that NF-kB and Rela may regulate follicle activation by affecting Pten signaling,and may also affect primordial follicle atresia by regulating the apoptosis of oocytes and granulosa cells.In addition,we speculate that there is a complex interaction between RELA and AKT that together affect the balance of the follicle activation process.Part II Identification of Reference Genes for qPCR in OvarianGranulosa CellsObjective:Ovarian granulosa cells play an important role in follicle development and ovarian diseases and are the most commonly used cells in reproductive research.In gene expression experiment,the selection of reference genes determines the accuracy of the experiment.However,there are still no studies on the selection of optimal reference genes for mouse and human ovarian granulosa cells.In this study,we assessed the stability of reference genes of mouse and human granulosa cells by three algorithms.In this way,the most suitable reference genes and combinations were selected for the mouse and human granulosa cells.Methods:RNAs were extracted from mice primary granulosa cells under different drug-treated,primary granulosa cells from PCOS patients and control women for RNA extraction.15 commonly used reference genes were selected as candidate genes.qPCR was used to detect the genes expression in the collected mouse and human primary granulosa cells.Three statistical algorithms were then used:GeNorm,NormFinder,and BestKeeper to evaluate the stability of selected reference genes.Through the comprehensive scoring of the three algorithms,we identified the most stable reference genes and combinations in granulosa cells.Results:Comprehensive analysis of the results of the three algorithms,showed that Hprt,Tfrc and Rplp0 are the three best stable reference genes in mouse granulosa cells treated with different drugsamong the 15 candidate reference genes.In the granulosa cells of PCOS patients and normal control women,the three most stable reference genes were HPRT1,RPLPO,and HMBS,and the use of three reference genes at the same time for normalization was the best.Among them,the most stable reference gene in mouse and human granulosa cells is Hprt/HPRT1.Conclusion:In this study,we firstly studied the stability of reference genes in mouse and human ovarian granulosa cells in qPCR experiments.We found that the stability of the reference genes in granulosa cells is affected by different experimental conditions and diseases.Through data analysis,we identified the most stable reference genes in granulosa cells under different conditions.This study provided the best choice and experimental basis for the selection of reference genes in the qPCR gene expression experiments in mouse and human granulosa cells.Chapter III Study on the Mechanism of Follicle Activation Using Single Oocyte RNA SequencingObjective:In the chapter I,we studied the changes in gene expression profiles of oocytes before and after activation by single cellqPCR.However,the number of genes that the TaqMan arrycardcan detect is limited,and the changes in the wholetranscriptome cannot be analyzed.Therefore,we used the single-cell transcriptome sequencing(scRNA-Seq)technique to study changes in the wholetranscriptome of oocytesduring follicle activation.In this way,we have a more comprehensive understanding of the mechanismof follicle activation and construct a signal network of follicle activation.Besides,heterogeneity of early stages of oocytes were also analyzed by scRNA-Seq.Methods:36 oocytes from primordial follicles and 36 oocytes from primary follicles were picked up by single cell Micro Pick and Place System.SMART-Seq method were used to conduct the reverse transcription of mRNA from single oocyte and cDNA pre-amplification.Agencourt AMPure XP magnetic beads were used to purify the cDNA.After quality control,the qualified samples will be used for library construction and sequencing on the illumina HiSeq 4000 platform.After quality control of the sequencing data,we analyzed the differential genes and observed the relationship between samples by cluster analysis and PCA.The mechanism during follicle activation process was studied with the signal pathway analysis,disease enrichment analysis and GO enrichment analysis,Results:Through quality control 34 primordial follicle oocytes and 34 primary follicle oocytes were preformed scRNA-Seq.Quality control were conducted before sequencing data analysis.Two samples were filtered out because of large portion of mitochondrial genes and the remaining 66 samples were used for further analysis.After filtering low abundance expression genes,a total number of 14869 genes were detected.The results showed that the gene expression of oocytes during the follicle activation were changed significantly.Through PCA and cluster analysis,it showed that the two stages of oocyteswere clearly divided into two groups.According to bioinformatics analysis,mTOR signal is the most relevant signaling pathway during follicle activation.By analysis of diseases and functional disorders,it is concluded that the differential genes are closely related to the occurrence of tumors and reproductive diseases.In addition,through the network construction of differential genes,we have predicted follicle activation-related genes.Conclusion:In this study,we firstly investigated the gene changes in the ovary transcriptome during follicle activation by using scRNA-Seq technique.We predicted that mTOR signaling is the most relevant signaling pathway during follicle activationwith bioinformatics analysis.Through the network construction of differential genes,we further predicted the genes involved in follicle activation.These results will provide a prospect for further functional studies of follicle activation mechanisms.