DNA binding specificity of all four Saccharomyces cerevisiae forkhead transcription factors

• Published in: Nucleic acids research Vol. 51; no. 11; pp. 5621 - 5633
• Main Authors: Cooper, Brendon H, Dantas Machado, Ana Carolina, Gan, Yan, Aparicio, Oscar M, Rohs, Remo
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 23.06.2023
• Subjects: Binding Sites; DNA - genetics; DNA - metabolism; DNA-Binding Proteins - metabolism; Forkhead Transcription Factors - metabolism; Genomics; Nucleotides - metabolism; Protein Binding; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - metabolism; Saccharomyces cerevisiae Proteins - metabolism
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkad372

Abstract Quantifying the nucleotide preferences of DNA binding proteins is essential to understanding how transcription factors (TFs) interact with their targets in the genome. High-throughput in vitro binding assays have been used to identify the inherent DNA binding preferences of TFs in a controlled environment isolated from confounding factors such as genome accessibility, DNA methylation, and TF binding cooperativity. Unfortunately, many of the most common approaches for measuring binding preferences are not sensitive enough for the study of moderate-to-low affinity binding sites, and are unable to detect small-scale differences between closely related homologs. The Forkhead box (FOX) family of TFs is known to play a crucial role in regulating a variety of key processes from proliferation and development to tumor suppression and aging. By using the high-sequencing depth SELEX-seq approach to study all four FOX homologs in Saccharomyces cerevisiae, we have been able to precisely quantify the contribution and importance of nucleotide positions all along an extended binding site. Essential to this process was the alignment of our SELEX-seq reads to a set of candidate core sequences determined using a recently developed tool for the alignment of enriched k-mers and a newly developed approach for the reprioritization of candidate cores. Graphical Abstract Graphical Abstract