Comparing the Transcriptomes of wild type (WT) oocytes with Dpagt1-Mutant (MUT), Dpagt1F/FAmhr2-CER/+ (Amcko) and Dpagt1F/FGdf9-CER/+ (GCKO) oocytes by RNA-Seq Analysis

The goal of this study is to reveal the globle effect of point mutation of Dpagt1, oocyte-specific deletion of Dpagt1 and granulosa cell-specific deletion of Dpagt1 in mice on gene expression in GV-stage fully-grown oocytes (FGOs) by comparing the corresponding transcriptomes via RNA-Seq Analysis. Overall design: Dpagt1 missense point mutant mice were produced by applying the “ENU-induced mutagenesis”-based forward genetic approach and producing an A to G transition of base 209 in exon 3 of Dpagt1, which resulted in the mis-sense mutation of aspartic acid 166 into glycine.Dpagt1oocyte-cKO and granulose-cKO mice were produced by crossing female mice carrying the conditional allele of Dpagt1 with male Tg(Gdf9-icre)5092Coo and Amhr2tm3(cre)Bhr mice expressing the transgene for Cre recombinase specifically in oocytes and granulosa cells,respectively. Then the oocytes were collected in lysis buffer to release all RNAs, which then were reverse transcribed into first cDNA strands by SuperScript II reverse transcriptase(Invitrogen) and random primers. These cDNAs were amplificated according to Smart-seq2 procedures for construct Illumina sequencing library. 3 replictates of each treatment, with 20 oocyte per samples, were collected for the experiment. The library was constructed using KAPA Hyper Prep Kit for Illumina (Roche) according to the instruction manual, which includes end repair, dA-tailing, adapter ligation, post-ligation cleanup, library amplification and post-amplification cleanup. The libraries were sequenced on an Illumina HiSeq X Ten platform with 150bp pair-end reads. All reads passed filter were trimmed to remove low-quality bases and adaptor sequences. Reads were then aligned to the mm10 reference genome using tophat2 (v2.0.13), and FPKMs were calculated and normalized using cufflinks (v2.2.1). The differentially expressed genes were calculated using default parameter of cuffdiff (v2.2.1). Hierarchical clustering was carried on log2(FPKM+1) across samples. Genes used for clustering were selected by maximum FPKM=1 and with top 10% standard deviation of log2(FPKM+1).