Biology subjects

Thomson, J.

Publications and source records attributed to Thomson, J..

2 recordsLinked to original sources

bioRxiv2017

CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiationin vivo

Regulation of eukaryotic gene expression is coordinated by dynamic changes to chromatin states throughout development. Measurements of accessible chromatin are used extensively to identify genomic regulatory elements. Whilst the chromatin landscapes of pluripotent stem cells are well characterised, chromatin accessibility changes in the development of somatic stem cell lineages are not well defined. Here we show that tissue specific chromatin accessibility data can be produced via ectopic expression of E. coli Dam methylase in vivo, without the requirement for cell-sorting. We have profiled chromatin accessibility in individual cell types of the Drosophila neural and midgut stem cell lineages. Functional cell-type specific enhancers were identified, as well as novel motifs enriched at diferent stages of development. Finally, we show global changes in the accessibility of chromatin between stem-cells and their diferentiated progeny. Our results demonstrate the dynamic nature of chromatin accessibility in somatic tissues during stem cell diferentiation and provide a novel approach to understanding the gene regulatory mechanisms underlying development.

developmental biology↗

bioRxiv2017

Trendy: Segmented regression analysis of expression dynamics for high-throughput ordered profiling experiments

AbstractHigh throughput expression profiling experiments with ordered conditions (e.g. time-course or spatial-course) are becoming more common for profiling detailed differentiation processes or spatial patterns. Identifying dynamic changes at both the individual gene and whole transcriptome level can provide important insights about genes, pathways, and critical time-points. We present an R package, Trendy, which utilizes segmented regression models to simultaneously characterize each genes expression pattern and summarize overall dynamic activity in ordered condition experiments. For each gene, Trendy finds the optimal segmented regression model and provides the location and direction of dynamic changes in expression. We demonstrate the utility of Trendy to provide biologically relevant results on both microarray and RNA-seq datasets. Trendy is a flexible R package which characterizes gene-specific expression patterns and summarizes changes of global dynamics over ordered conditions. Trendy is freely available as an R package with a full vignette at https://github.com/rhondabacher/Trendy.

genomics↗