@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 {74, title = {Impaired development of neural-crest cell-derived organs and intellectual disability caused by MED13L haploinsufficiency.}, journal = {Hum Mutat}, volume = {35}, year = {2014}, month = {2014 Nov}, pages = {1311-20}, abstract = {

MED13L is a component subunit of the Mediator complex, an important regulator of transcription that is highly conserved across eukaryotes. Here, we report MED13L disruption in a translocation t(12;19) breakpoint of a patient with Pierre-Robin syndrome, moderate intellectual disability, craniofacial anomalies, and muscular defects. The phenotype is similar to previously described patients with MED13L haploinsufficiency. Knockdown of MED13L orthologue in zebrafish, med13b, showed early defective migration of cranial neural crest cells (NCCs) that contributed to cartilage structure deformities in the later stage, recapitulating craniofacial anomalies seen in human patients. Notably, we observed abnormal distribution of developing neurons in different brain regions of med13b morphant embryos, which could be rescued upon introduction of full-length human MED13L mRNA. To compare with mammalian system, we suppressed MED13L expression by short-hairpin RNA in ES-derived human neural progenitors, and differentiated them into neurons. Transcriptome analysis revealed differential expression of components of Wnt and FGF signaling pathways in MED13L-deficient neurons. Our finding provides a novel insight into the mechanism of overlapping phenotypic outcome targeting NCCs derivatives organs in patients with MED13L haploinsufficiency, and emphasizes a clinically recognizable syndromic phenotype in these patients.

}, keywords = {Animals, Cell Differentiation, Cell Movement, Child, Preschool, Chromosome Breakpoints, Disease Models, Animal, Embryonic Stem Cells, Female, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Developmental, Gene Knockdown Techniques, Genetic Association Studies, Haploinsufficiency, Humans, Intellectual Disability, Mediator Complex, Neural Crest, Neurons, Phenotype, RNA, Messenger, Sequence Analysis, DNA, Transcriptome, Translocation, Genetic, Zebrafish}, issn = {1098-1004}, doi = {10.1002/humu.22636}, author = {Utami, Kagistia Hana and Winata, Cecilia L and Hillmer, Axel M and Aksoy, Irene and Long, Hoang Truong and Liany, Herty and Chew, Elaine G Y and Mathavan, Sinnakaruppan and Tay, Stacey K H and Korzh, Vladimir and Sarda, Pierre and Davila, Sonia and Cacheux, Valere} } @article {32, title = {Normalization of RNA-sequencing data from samples with varying mRNA levels.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e89158}, abstract = {

Methods for normalization of RNA-sequencing gene expression data commonly assume equal total expression between compared samples. In contrast, scenarios of global gene expression shifts are many and increasing. Here we compare the performance of three normalization methods when polyA(+) RNA content fluctuates significantly during zebrafish early developmental stages. As a benchmark we have used reverse transcription-quantitative PCR. The results show that reads per kilobase per million (RPKM) and trimmed mean of M-values (TMM) normalization systematically leads to biased gene expression estimates. Biological scaling normalization (BSN), designed to handle differences in total expression, showed improved accuracy compared to the two other methods in estimating transcript level dynamics. The results have implications for past and future studies using RNA-sequencing on samples with different levels of total or polyA(+) RNA.

}, keywords = {Animals, Base Sequence, Gene Expression, Gene Expression Profiling, Polymerase Chain Reaction, RNA, Messenger, Sequence Analysis, RNA, Zebrafish}, issn = {1932-6203}, doi = {10.1371/journal.pone.0089158}, author = {Aanes, H{\r a}vard and Winata, Cecilia L and Moen, Lars F and {\O}strup, Olga and Mathavan, Sinnakaruppan and Collas, Philippe and Rognes, Torbj{\o}rn and Alestr{\"o}m, Peter} }