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Transcriptome analysis of gene expression in control and Kiaa1429Zp3cKO samples (RNA-Seq)

ABSTRACT: The goals of this study are to compare transcriptome profiling (RNA-seq) data and quantitative reverse transcription polymerase chain reaction (qPCR) methods and to evaluate protocols for optimal high-throughput data analysis. The sequencing libraries from control and Kiaa1429Zp3cKO oocytes were generated according to protocols of Smart-seq2. For all samples the concentration of sequencing libraries was quantified using qPCR. All samples showed a concentration of higher than 3nM and were sequenced using HiSeq XTen (Illumina) with paired-end 150-bp sequencing.RNA-seq data were aligned to the mouse genome mm10 using STAR 2-pass mode with the annotations of Ensembl version 90 and parameter ‘--outFilterMismatchNmax 6’. SAMtools was used to extract uniquely mapped reads with mapping quality more than or equal to 20. The number of reads mapped to each gene was counted using the HTSeq python package with the ‘union’ overlap resolution mode and –stranded = no. The expressions of genes were quantified as RPKM by edgeR . Genes with RPKM more than 1 in at least three control samples were considered as expressed. Only expressed genes were kept for the subsequent analysis. Differentially expressed genes were identified by DESeq2 using two criteria: fold change of expression should be higher than 2 and the adjusted p-value should be lower than 0.05. Enriched GO terms were obtained with P-value less than 0.05 from DAVID.The analysis of data revealed a total of 1081 genes were significant differentially expressed. 448 genes were upregulated and 633 downregulated in Kiaa1429Zp3cKO oocytes.We found that Kiaa1429 deletion altered expression pattern of many oocyte-derived factors (Ccnb1ip1, Lysmd2, Vav3, sohlh2, Id3, Anks4b, Scel, Cfap53, Olfm4, Fgf8, Susd3, Clip4, Fam124b, Gfra1, Nedd4l, Bmp15), which have been reported to be involved in signaling pathways of the oocyte-granulosa cell dialog and play important roles in oocyte survival and folliculogenesis. These oocyte-derived factors selected randomly were validated by qPCR in the GV oocytes from 20-day-old mice.

ORGANISM(S): Mus musculus

PROVIDER: GSE129714 | GEO | 2019/12/31

REPOSITORIES: GEO

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Project description:Study Question: What effects do maternal age and oocyte maturation stage have on the human oocyte transcriptome that may be associated with oocyte developmental potential? Summary Answer: Although polyadenylated transcript abundance changes during human oocyte maturation irrespective of age, young (YNG) and advanced maternal age (AMA) metaphase II (MII) oocytes exhibit divergent transcriptomes. What is known already: Maternal age and maturation stage affect oocyte polyadenylated transcript abundance in human oocytes. Although RNA-Seq analysis of single human MII oocytes has been conducted, comparison of the germinal vesicle (GV) and MII oocyte transcriptomes has not been investigated using RNA-Seq, a technique that could provide novel insight into oocyte maturation and age-associated aberrations in gene expression. Participants / materials, settings, methods: Patients undergoing infertility treatment at the Colorado Center for Reproductive Medicine (Lone Tree, CO, USA) underwent ovarian stimulation with FSH and received hCG for final follicular maturation prior to ultrasound guided egg retrieval. Unused GV oocytes obtained at retrieval were donated for transcriptome analysis. Single oocytes were stored (at -80°C in PicoPure RNA Extraction Buffer; Thermo Fisher Scientific, USA) immediately upon verification of immaturity or after undergoing in vitro oocyte maturation (24 hour incubation), representing GV and MII samples, respectively. After isolating RNA and generating single oocyte RNA-Seq libraries (SMARTer Ultra Low Input RNA HV kit; Clontech, USA), Illumina sequencing (100 bp paired-end reads in HiSeq 2500) and bioinformatics analysis (CLC Genomics Workbench, DESeq2, Weighted Gene Correlation Network Analysis (WGCNA), 3’UTR motif analysis, Ingenuity Pathway Analysis) were performed. Main results and the role of chance: Within the 12,770 expressed genes in human oocytes (reads per kilobase per million mapped reads (RPKM) > 0.4 in at least 3 of 5 replicates for a minimum of one sample type), 458 and 3,506 genes significantly (adjusted p < 0.05 and log2 fold change > 1) increased and decreased in polyadenylated transcript abundance during oocyte maturation, respectively. The differentially expressed genes were enriched (FDR < 0.05) for biological functions and canonical pathways related to cell cycle and mitochondrial function. The majority (76%) and minority (25%) of up- and down-regulated transcripts with a complete 3’UTR were predicted to be targets of cytoplasmic polyadenylation (910 total genes), respectively. Differential gene expression analysis between young and advanced maternal age oocytes (within stage) identified 1 and 255 genes that significantly differed (adjusted p < 0.1 and log2 fold change > 1) in polyadenylated transcript abundance for GV and MII oocytes, respectively. These genes included CDK1, NLRP5, and PRDX1, which have been reported to affect oocyte developmental potential and be markers of oocyte quality. Despite similarity in transcript abundance between GV oocytes irrespective of age, divergent expression patterns emerged during oocyte maturation. These age-specific differentially expressed genes were enriched (FDR < 0.05) for functions and pathways associated with mitochondria, cell cycle, and cytoskeleton. Gene modules generated by WGCNA (based on gene expression) and patient traits related to oocyte quality (e.g. age and blastocyst development) were determined to be correlated (p < 0.05) and enriched (FDR < 0.05) for functions and pathways associated with oocyte maturation. Limitations, reasons for caution: The human oocytes used in the current study were obtained from patients with varying causes of infertility (e.g. decreased oocyte quality and oocyte quality-independent factors), possibly affecting oocyte gene expression. Oocytes in this study were retrieved at the GV stage following hCG administration and the MII oocytes were derived by in vitro maturation of patient oocytes, which has the benefit of identifying intrinsic differences between samples, but may not be completely representative of in vivo matured oocytes. Thus, these factors should be considered when interpreting the results. Wider Implications of the findings: Transcriptome profiles of young and advanced maternal age oocytes, particularly at the MII stage, suggest aberrant transcript abundance contributes to the age-associated decline in fertility.

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Transcriptome analysis of gene expression in control and Kiaa1429Zp3cKO samples (RNA-Seq)

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