Project description:To identify the underlying mechanism causing the defects in light-dependent behavioral rhythm formation and the reduced locomotor activity in DKO and TKO zebrafish, a microarray analysis was conducted.
Project description:mRNA profiles of 4 week-old contol and Mst1/2 dKO and Mst1/2; Yap tKO Initial segments of Epididymis were generated by deep sequencing, in triplicate, using Illumina HiSeq platform.
Project description:Interferon-regulatory factors (IRFs) are a family of transcription factors (TFs) that play critical roles in translating viral recognition into antiviral responses, including type I IFN production. Dengue virus (DENV) and other clinically important flaviviruses are controlled by functional type I interferon (IFN) responses. Using an experimental model of DENV infection that recapitulates key aspects of the human disease in mice, we demonstrate that while mice lacking the type I IFN receptor (Ifnar1-/-) succumb to DENV infection, mice that are deficient in IRF-3, IRF-5, and IRF-7 – the three transcription factors thought to regulate type I IFN production – survive DENV challenge. Genome-wide RNA-seq analysis of WT, Irf3(-/-)×Irf7(-/-) (DKO), Irf3-/-xIrf5-/-xIrf7-/- (TKO), and Ifnar1-/- (AB6) splenocytes identified minimal type I IFN production but a robust type II IFN (IFN-γ) response in DKO and TKO mice later shown to be dependent on IRF-1. These results reveal a key role for IRF-1 in antiviral defense by activating both type I and II IFN responses during DENV infection.
Project description:Transcriptional profiling of light response in the zebrafish at several organizational levels: the whole animal, the organ and the cell. Exposure of larvae, heart organ cultures and cell culture cells to light pulses of 1 and 3 hours duration and measurement of changes in gene expression compared to controls kept in the dark.
Project description:We investigate how DNA methylation absence impact transcriptionnal regulation during epiblast differentiation. More specifically, how synchronous is the naïve to primed transitioning in TKO cells compared to WT, and if there is a "germline-competent" TKO subpopulation of EpiLCs. To this end, we used in vitro Epiblast-like cell (EpiLC) differentiation WT and TKO at D0, D1, D2 and D4. We next performed single-cell SMARTseq2 RNA sequencing.
Project description:To better characterize the effects of USP7 on DNA methylation, we performed reduced representative bisulfite sequencing (RRBS) analysis for a genome-wide comparison of DNA methylation in wild-type, USP7-KO-1, DNMT3A/3B-DKO and DNMT3A/DNMT3B/USP7-TKO HeLa cell lines. RRBS analysis showed increased DNA methylation in USK7-KO cells and loss of USP7 elevates DNA methylation on pre-existing sites and de novo methylation.
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare the genes expression difference at transcriptome level; Methods: Total RNA was extracted from whole cells with the mirVana miRNA Isolation Kit according to the manufacturer’s protocol. RNA quality and integrity were evaluated with an Agilent 2100 Bioanalyzer. Samples with an RNA integrity number (RIN) ≥ 7 were considered to be of high quality and were processed further and subjected to subsequent analysis. Total RNA-seq libraries were generated using 4 μg of total RNA, which was analyzed using the TruSeq Stranded mRNA LTSample Prep Kit. These libraries were then sequenced using the Illumina sequencing platform (HiSeqTM 2500 or Illumina HiSeq X Ten), and 125-bp/150-bp paired-end reads were generated. Results: The raw reads containing adaptors and the low-quality reads from the raw data were removed using Trimmomatic to obtain clean reads. Transcriptome sequencing was conducted by OE Biotech Co., Ltd. (Shanghai, China), and clean reads were provided. The clean reads were mapped to the hg38 reference genome using hisat2 (version 2.1.0). The output BAM files were converted to SAM files using SAMtools 1.9. The final TPM values were obtained using Stringtie 1.3.5. Conclusions: To understand the mechanistic basis of GPI biosynthesis upregulation by the CD55 precursor, we performed RNA- sequencing (RNA-seq) of samples of parental PIGS-HRD1-DKO, PIGS-HRD1-CD55-TKO, and PIGS-HRD1-CD55-TKO stably overexpressed HA-CD55 stably overexpressing cells. Total RNA was extracted and analyzed. The expression profile of GPI biosynthesis -related genes was not significantly affected by CD55.