Project description:The first 4 samples belong to the RNA-IP using in situ TAP tagged ZC3H30 in procyclic (insect) form of the parasite T. brucei Lister 427, 2 samples are Elu or eluate, and 2 are FL or flowthrough (unbound) sample. The other 8 samples are also from procyclic cells. 4 samples belong to DKO(ZC3H30 gene double knockout), 2 are non-stressed and 2 are heat shocked samples; the rest 4 samples are DKO-ectopic (ZC3H30 double knockouts, expressing, ectopic copy of ZC3H30) 2 are non-stressed and 2 are heat shocked samples. Heat Shock experiment was done at 39 degree Celsius.
Project description:Exponentially growing cells (OD 0.5-0.8) from the TAP-tagged strain were harvested by ultracentrifugation followed by of washing and flash freezing in liquid nitrogen and breakage in FastPrep24 (ZYmoresearch S6005). The lysate was subjected to IP with Dyna M280 sheep anti rabbit IgG beads for 2h at 4C. An aliquot was taken before the IP as an input control. The IP of the RNA-protein complex was subjected to cleavage by TEV protease to cleave the TAP-tag off the protein. The bound RNA was then precipitated in phenol/chloroform/isoamyl-alcohol and sequenced using 3' T-filling protocol as described by Wilkening et al 2013 to obtain accurate quantification of 3' isoforms. We used the R Bioconductor package DESeq2 (Anders and Huber 2010) to call for differential log change between the Input and the RNA-IP sample and took all those isoforms as differentially regulated which had more than 4-fold change at a FDR of 10% as reported by the package.
Project description:This SuperSeries is composed of the following subset Series: GSE40910: Genome-wide nucleosome positioning during embryonic stem cell development [MNase-Seq] GSE40948: Genome-wide nucleosome positioning during embryonic stem cell development [RNA-Seq] GSE40951: Genome-wide nucleosome positioning during embryonic stem cell development [ChIP-Seq] Refer to individual Series
Project description:We determined genome-wide nucleosome occupancy in mouse embryonic stem cells and their neural progenitor and embryonic fibroblast counterparts to assess features associated with nucleosome positioning during lineage commitment. Cell type and protein specific binding preferences of transcription factors to sites with either low (e.g. Myc, Klf4, Zfx) or high (e.g. Nanog, Oct4 and Sox2) nucleosome occupancy as well as complex patterns for CTCF were identified. Nucleosome depleted regions around transcription start and termination sites were broad and more pronounced for active genes, with distinct patterns for promoters classified according to their CpG-content or histone methylation marks. Throughout the genome nucleosome occupancy was dependent on the presence of certain histone methylation or acetylation modifications. In addition, the average nucleosome-repeat length increased during differentiation by 5-7 base pairs, with local variations for specific genomic regions. Our results reveal regulatory mechanisms of cell differentiation acting through nucleosome repositioning. The Total RNA from ESCs, NPCs and MEFs was extracted by guanidinisothiocyanat/phenol extraction with the Trifast kit (Peqlab). Total RNA preparations were treated with DNase I, phenol/chloroform extracted and precipitated before further processing. RNAs were depleted of 5S, 5.8S, 18S and 28S rRNAs using the Human/Mouse/Rat Ribo-Zero rRNA Removal Kit (Epicentre) according to the manufacturer’s protocol. After rRNA depletion, RNAs were fragmented with a kit from Ambion. Libraries for Solexa sequencing were generated according to the standard Illumina protocol that comprised first strand cDNA synthesis, second strand cDNA synthesis, end repair, addition of a single A base, and adapter ligation. Sequencing was performed on the Illumina GAIIx (replicate 1) and Illumina HiSeq 2000 (replicate 2) platforms at the sequencing core facilities of the BioQuant in Heidelberg, Germany. RNA reads were aligned with TopHat. Further expression analysis was with the Genomatix software suite (Genomatix, Munich, Germany) and the Eldorado gene annotation. For each transcript a normalized expression value was calculated from the read distribution that accounts for the length differences using the program DEseq for the analysis of differential expression.