@article {127, title = {xcore: an R package for inference of gene expression regulators.}, journal = {BMC Bioinformatics}, volume = {24}, year = {2023}, month = {2023 Jan 11}, pages = {14}, abstract = {

BACKGROUND: Elucidating the Transcription Factors (TFs) that drive the gene expression changes in a given experiment is a common question asked by researchers. The existing methods rely on the predicted Transcription Factor Binding Site (TFBS) to model the changes in the motif activity. Such methods only work for TFs that have a motif and assume the TF binding profile is the same in all cell types.

RESULTS: Given the wealth of the ChIP-seq data available for a wide range of the TFs in various cell types, we propose that gene expression modeling can be done using ChIP-seq "signatures" directly, effectively skipping the motif finding and TFBS prediction steps. We present xcore, an R package that allows TF activity modeling based on ChIP-seq signatures and the user{\textquoteright}s gene expression data. We also provide xcoredata a companion data package that provides a collection of preprocessed ChIP-seq signatures. We demonstrate that xcore leads to biologically relevant predictions using transforming growth factor beta induced epithelial-mesenchymal transition time-courses, rinderpest infection time-courses, and embryonic stem cells differentiated to cardiomyocytes time-course profiled with Cap Analysis Gene Expression.

CONCLUSIONS: xcore provides a simple analytical framework for gene expression modeling using linear models that can be easily incorporated into differential expression analysis pipelines. Taking advantage of public ChIP-seq databases, xcore can identify meaningful molecular signatures and relevant ChIP-seq experiments.

}, keywords = {Animals, Binding Sites, Chromatin Immunoprecipitation, Chromatin Immunoprecipitation Sequencing, Gene Expression, Protein Binding, Transcription Factors}, issn = {1471-2105}, doi = {10.1186/s12859-022-05084-0}, author = {Migda{\l}, Maciej and Arakawa, Takahiro and Takizawa, Satoshi and Furuno, Masaaki and Suzuki, Harukazu and Arner, Erik and Winata, Cecilia Lanny and Kaczkowski, Bogumi{\l}} } @article {118, title = {Fish-Ing for Enhancers in the Heart.}, journal = {Int J Mol Sci}, volume = {22}, year = {2021}, month = {2021 Apr 10}, abstract = {

Precise control of gene expression is crucial to ensure proper development and biological functioning of an organism. Enhancers are non-coding DNA elements which play an essential role in regulating gene expression. They contain specific sequence motifs serving as binding sites for transcription factors which interact with the basal transcription machinery at their target genes. Heart development is regulated by intricate gene regulatory network ensuring precise spatiotemporal gene expression program. Mutations affecting enhancers have been shown to result in devastating forms of congenital heart defect. Therefore, identifying enhancers implicated in heart biology and understanding their mechanism is key to improve diagnosis and therapeutic options. Despite their crucial role, enhancers are poorly studied, mainly due to a lack of reliable way to identify them and determine their function. Nevertheless, recent technological advances have allowed rapid progress in enhancer discovery. Model organisms such as the zebrafish have contributed significant insights into the genetics of heart development through enabling functional analyses of genes and their regulatory elements in vivo. Here, we summarize the current state of knowledge on heart enhancers gained through studies in model organisms, discuss various approaches to discover and study their function, and finally suggest methods that could further advance research in this field.

}, keywords = {Animals, Binding Sites, Enhancer Elements, Genetic, Gene Expression Regulation, Developmental, Gene Regulatory Networks, Heart, Humans, Mutation, Transcription Factors, Zebrafish}, issn = {1422-0067}, doi = {10.3390/ijms22083914}, author = {Parisi, Costantino and Vashisht, Shikha and Winata, Cecilia Lanny} }