bioRxiv ScienceSearch

Biology subjects

Mercier, E.

Publications and source records attributed to Mercier, E..

2 recordsLinked to original sources

TCF7L1 and TCF7 differentially regulate specific mouse ES cell genes in response to GSK-3 inhibition

The genome-wide chromatin occupancy of the TCF/LEF factors and its modulation by Wnt pathway activation remain poorly defined. Here, we describe mouse ES cell (mESC) lines expressing a single copy knock-in of the 3xFLAG epitope at the N-terminus of TCF7L1 and TCF7, the two most-highly expressed TCF/LEF factors in mESCs. TCF7L1 protein levels, detected by immunoblotting with a FLAG antibody, were much higher than TCF7 in mESCs maintained in standard serum- and LIF-supplemented medium, even in the presence of the GSK-3 inhibitor, CHIR99021 (CHIR). We used FLAG antibody-mediated ChIP-seq to determine TCF7 and TCF7L1 chromatin occupancy in mESCs cultured in standard medium with or without CHIR for 14 hours. TCF7 and TCF7L1 displayed very few overlapping ChIP peaks across the genome, with TCF7L1 binding significantly more genes than TCF7 in both culture conditions. Despite a reduction in total TCF7L1 protein after CHIR treatment, the TCF7L1 ChIP peak profiles were not uniformly attenuated. Our data demonstrate that TCF7L1 chromatin occupancy upon short-term CHIR treatment is modulated in a target-specific manner. Our findings also suggest that Wnt target genes in mESCs are not regulated by TCF/LEF switching, and TCF7L1, although often called a constitutive repressor, may serve as a transcriptional activator of certain target genes in CHIR-treated mESCs.\n\nHighlightsO_LIChIP and cytometry data suggest that TCF7L1 does not directly regulate mESC Nanog expression.\nC_LIO_LITCF7L1 remains associated with {beta}-catenin in the presence of CHIR99021.\nC_LIO_LITCF7 and TCF7L1 display different chromatin occupancies in mESCs.\nC_LIO_LITCF7L1 binding at specific genomic sites is variably altered by CHIR99021.\nC_LI

cell biology

GenPipes: an open-source framework for distributed and scalable genomic analyses

With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for High Performance Computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA-Seq, ChIP-Seq, DNA-Seq, Methyl-Seq, Hi-C, capture Hi-C, metagenomics and PacBio long read assembly. The software is available under a GPLv3 open source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has been already configured on several servers and a docker image is also available to facilitate additional installations. In summary, GenPipes offers genomic researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.

bioinformatics