We describe an effort ("Codebook") to determine the sequence specificity of 332 putative and largely uncharacterized human transcription factors (TFs), as well as 61 control TFs. Nearly 5,000 independent experiments across multiple and assays produced motifs for just over half of the putative TFs analyzed (177, or 53%), of which most are unique to a single TF. The data highlight the extensive contribution of transposable elements to TF evolution, both in and , and identify tens of thousands of conserved, base-level binding sites in the human genome.
View Article and Find Full Text PDFA DNA sequence pattern, or "motif", is an essential representation of DNA-binding specificity of a transcription factor (TF). Any particular motif model has potential flaws due to shortcomings of the underlying experimental data and computational motif discovery algorithm. As a part of the Codebook/GRECO-BIT initiative, here we evaluated at large scale the cross-platform recognition performance of positional weight matrices (PWMs), which remain popular motif models in many practical applications.
View Article and Find Full Text PDFMost of the human genome is thought to be non-functional, and includes large segments often referred to as "dark matter" DNA. The genome also encodes hundreds of putative and poorly characterized transcription factors (TFs). We determined genomic binding locations of 166 uncharacterized human TFs in living cells.
View Article and Find Full Text PDFMotivation: Prediction and identification of core promoter elements and transcription factor binding sites is essential for understanding the mechanism of transcription initiation and deciphering the biological activity of a specific locus. Thus, there is a need for an up-to-date tool to detect and curate core promoter elements/motifs in any provided nucleotide sequences.
Results: Here, we introduce ElemeNT 2023-a new and enhanced version of the Elements Navigation Tool, which provides novel capabilities for assessing evolutionary conservation and for readily evaluating the quality of high-throughput transcription start site (TSS) datasets, leveraging preferential motif positioning.
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults, but first-line immunochemotherapy fails to produce a durable response in about one-third of the patients. Because tumor cells often reprogram their metabolism, we investigated the importance of glutaminolysis, a pathway converting glutamine to generate energy and various metabolites, for the growth of DLBCL cells. Glutaminase-1 (GLS1) expression was robustly detected in DLBCL biopsy samples and cell lines.
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