Transcriptomic profiling is an immensely powerful hypothesis generating tool. However, accurately predicting the transcription factors (TFs) and cofactors that drive transcriptomic differences between samples is challenging. A number of algorithms draw on ChIP-seq tracks to define TFs and cofactors behind gene changes. These approaches assign TFs and cofactors to genes via a binary designation of 'target', or 'non-target' followed by Fisher Exact Tests to assess enrichment of TFs and cofactors. ENCODE archives 2314 ChIP-seq tracks of 684 TFs and cofactors assayed across a 117 human cell lines under a multitude of growth and maintenance conditions. The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an a priori binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings: 1) A cell line expressing or lacking single TF, 2) Breast tumors divided along PAM50 designations 3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype 4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels. In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.
TCF19 is a gene that is associated with both type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in genome-wide association studies. Prior studies have demonstrated that TCF19 knockdown impairs β-cell proliferation and increases apoptosis. However, little is known about its role in diabetes pathogenesis or the effects of TCF19 gain-of-function. The aim of this study was to examine the impact of TCF19 overexpression in INS-1 β-cells on proliferation and gene expression. With TCF19 overexpression, there was an increase in nucleotide incorporation without any change in cell cycle gene expression, alluding to an alternate process of nucleotide incorporation. Analysis of RNAseq of TCF19 overexpressing cells revealed increased expression of several DNA damage response (DDR) genes, as well as a tightly linked set of genes involved in cell stress, immune system processes, and inflammation. This connectivity between DNA damage and inflammatory gene expression has not been well studied in the β-cell, and suggests a novel role for TCF19 in regulating these pathways. Future studies determining how TCF19 may modulate these pathways may provide potential targets for β-cell survival.
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