Transcription-Austin最新文献

{"title":"TFBSFootprinter: a multiomics tool for prediction of transcription factor binding sites in vertebrate species.","authors":"Harlan R Barker, Seppo Parkkila, MarttiE E Tolvanen","doi":"10.1080/21541264.2025.2521764","DOIUrl":"10.1080/21541264.2025.2521764","url":null,"abstract":"<p><strong>Background: </strong>Transcription factor (TF) proteins play a critical role in the regulation of eukaryotic gene expression via sequence-specific binding to genomic locations known as transcription factor binding sites (TFBSs). Accurate prediction of TFBSs is essential for understanding gene regulation, disease mechanisms, and drug discovery. These studies are therefore relevant not only in humans but also in model organisms and domesticated and wild animals. However, current tools for the automatic analysis of TFBSs in gene promoter regions are limited in their usability across multiple species. To our knowledge, no tools currently exist that allow for automatic analysis of TFBSs in gene promoter regions for many species.</p><p><strong>Methodology and findings: </strong>The TFBSFootprinter tool combines multiomic transcription-relevant data for more accurate prediction of functional TFBSs in 317 vertebrate species. In humans, this includes vertebrate sequence conservation (GERP), proximity to transcription start sites (FANTOM5), correlation of expression between target genes and TFs predicted to bind promoters (FANTOM5), overlap with ChIP-Seq TF metaclusters (GTRD), overlap with ATAC-Seq peaks (ENCODE), eQTLs (GTEx), and the observed/expected CpG ratio (Ensembl). In non-human vertebrates, this includes GERP, proximity to transcription start sites, and CpG ratio.TFBSFootprinter analyses are based on the Ensembl transcript ID for simplicity of use and require minimal setup steps. Benchmarking of the TFBSFootprinter on a manually curated and experimentally verified dataset of TFBSs produced superior results when using all multiomic data (average area under the receiver operating characteristic curve, 0.881), compared with DeepBind (0.798), DeepSEA (0.682), FIMO (0.817) and traditional PWM (0.854). The results were further improved by selecting the best overall combination of multiomic data (0.910). Additionally, we determined combinations of multiomic data that provide the best model of binding for each TF. TFBSFootprinter is available as Conda and Python packages.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":"16 2-3","pages":"204-223"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258250/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144620874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of lncRNA in plant growth and domestication.","authors":"Vijay Gahlaut, Vandana Jaiswal","doi":"10.1080/21541264.2025.2473224","DOIUrl":"10.1080/21541264.2025.2473224","url":null,"abstract":"<p><p>The lncRNAs have deepened our understanding of crop domestication and improvement. These regulators influence key traits like yield, germination, and stress response. Future research should identify functional lncRNAs, explore their interactions, and use CRISPR for targeted improvements. Understanding their roles in polyploid crops may enhance resilience and productivity.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"169-175"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258212/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding complexity: tackling the challenge of how many transcription factors regulate a plant gene.","authors":"John Gray, Erich Grotewold","doi":"10.1080/21541264.2025.2521767","DOIUrl":"10.1080/21541264.2025.2521767","url":null,"abstract":"<p><p>The regulation of transcription is a major control point in the flow of information from the genome to the phenome. Central to this regulation are transcription factors (TFs), which bind specific DNA motifs in gene regulatory regions. In both metazoans and plants, 5-7% of all genes encode TFs. Although individual TFs can recognize and regulate thousands of target genes, an important question remains: how many TFs are required to precisely control the expression of a single gene? In this review, we compare the regulation of gene expression in plants and metazoans, outline key methodologies for identifying genes recognized or regulated by TFs, and explore what is currently known about the number of TFs needed to define the expression of any given plant gene. As the volume of high-throughput sequencing data continues to grow exponentially, it becomes increasingly clear that transcriptional regulatory networks exhibit remarkable complexity, characterized by many targets influenced by each TF; and that many TFs, often several dozens, contribute to the regulation of individual genes.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"261-283"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258188/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144498360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rho-dependent termination: a bacterial evolutionary capacitor for stress resistance.","authors":"Sarah B Worthan, Megan I Grant, Megan G Behringer","doi":"10.1080/21541264.2025.2474367","DOIUrl":"10.1080/21541264.2025.2474367","url":null,"abstract":"<p><p>Since the Modern Synthesis, interest has grown in resolving the \"black box\" between genotype and phenotype. Contained within this black box are highly plastic RNA and proteins with global effects on chromosome integrity and gene expression that serve as evolutionary capacitors - elements that enable the accumulation and buffering of genetic variation in normal conditions and reveal hidden genetic variation when induced by environmental stress. Discussion of evolutionary capacitors has primarily focused on eukaryotic translation factors and chaperones, such as Hsp90 and PSI+ prion. However, due to the coupling of transcription and translation in prokaryotes, transcription factors can be equally impactful in the modulation of gene expression and phenotypes. In this review, we discuss the prokaryotic transcription terminator Rho and how mutagenesis and plasticity of Rho influence epistasis, evolvability, and adaptation to stress in bacteria. We discuss the effects of variation in Rho generated by nature, laboratory mutagenesis, and experimental evolution; and how this variation is constrained or encouraged by Rho's extensive network of protein interactors. Exploring Rho's role as an evolutionary capacitor, along with identifying additional elements that can serve this function, can significantly advance our understanding of how organisms adapt to thrive in diverse environments.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"176-189"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orphan nuclear receptor transcription factors as drug targets.","authors":"Stephen Safe, Arafat R Oany, Wai Ning Tsui, Miok Lee, Vinod Srivastava, Srijana Upadhyay, Amanuel Hailemariam, Evan Farkas, Sarah Kakwan, Caitrina Kearns, Gargi Sivaram","doi":"10.1080/21541264.2025.2521766","DOIUrl":"10.1080/21541264.2025.2521766","url":null,"abstract":"<p><p>The nuclear receptor (NR) superfamily of ligand-activated receptors plays a key role in maintaining cellular homeostasis and in pathophysiology. NRs can be subdivided into functional activities structural similarity and the existence of endogenous ligands. Most NRs are classified as those that are adopted orphan or orphan receptors which have only possible ligands or no identified endogenous ligands, respectively. In this review, the activities of the complete orphan receptor sub-family of transcription factors have been reviewed with a focus on the effects of possible endogenous (biochemicals), natural product-derived and synthetic ligands. Despite their lack of a bona-fide ligand, the orphan receptors bind structurally diverse compounds that exhibit tissue-specific agonist, antagonist and inverse agonist activities with potential for future development as clinical therapeutics for the treatment of multiple diseases.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":"16 2-3","pages":"224-260"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144620873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GATA3 and E2F6 negatively regulate WDR77 expression to inhibit prostate cancer cell growth.","authors":"Robin Brice, Zhengxin Wang","doi":"10.1080/21541264.2025.2476848","DOIUrl":"10.1080/21541264.2025.2476848","url":null,"abstract":"<p><p>The WD repeat domain 77 (WDR77) protein plays a critical role in prostate development and dysregulation of WDR77 expression is associated with prostate tumorigenesis. This study investigated the regulatory effects of GATA3 and E2F6 on WDR77 gene expression. A negative correlation between GATA3/E2F6 and WDR77 expression at both mRNA and protein levels was observed during prostate development and prostate tumorigenesis. Prostate cancer cells lost expression of GATA3 and E2F6 and re-expression of GATA3 and E2F6 resulted in a dose-dependent reduction in WDR77 expression and cell growth. Exogenous expression of WDR77 relieved the growth inhibition by GATA3. GATA3 and E2F6 directly interact with the promoter of the WDR77 gene in vitro and in vivo and repress WDR77 promoter activity. These results provide valuable insights into the molecular mechanisms governing WDR77 expression during prostate development and prostate tumorigenesis.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"190-203"},"PeriodicalIF":3.6,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12258259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing transcription factors for therapeutic purposes.","authors":"Joaquin M Espinosa","doi":"10.1080/21541264.2025.2460249","DOIUrl":"10.1080/21541264.2025.2460249","url":null,"abstract":"","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"1-2"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143415825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hypoxia-inducible transcription factors: architects of tumorigenesis and targets for anticancer drug discovery.","authors":"Alexander McDermott, Ali Tavassoli","doi":"10.1080/21541264.2024.2417475","DOIUrl":"10.1080/21541264.2024.2417475","url":null,"abstract":"<p><p>Hypoxia-inducible factors (HIFs) play a pivotal role as master regulators of tumor survival and growth, controlling a wide array of cellular processes in response to hypoxic stress. Clinical data correlates upregulated HIF-1 and HIF-2 levels with an aggressive tumor phenotype and poor patient outcome. Despite extensive validation as a target in cancer, pharmaceutical targeting of HIFs, particularly the interaction between α and βsubunits that forms the active transcription factor, has proved challenging. Nonetheless, many indirect inhibitors of HIFs have been identified, targeting diverse parts of this pathway. Significant strides have also been made in the development of direct inhibitors of HIF-2, exemplified by the FDA approval of Belzutifan for the treatment of metastatic clear cell renal carcinoma. While efforts to target HIF-1 using various therapeutic modalities have shown promise, no clinical candidates have yet emerged. This review aims to provide insights into the intricate and extensive role played by HIFs in cancer, and the ongoing efforts to develop therapeutic agents against this target.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"86-117"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142523307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting bacterial transcription factors for infection control: opportunities and challenges.","authors":"Ahmed Al-Tohamy, Anne Grove","doi":"10.1080/21541264.2023.2293523","DOIUrl":"10.1080/21541264.2023.2293523","url":null,"abstract":"<p><p>The rising threat of antibiotic resistance in pathogenic bacteria emphasizes the need for new therapeutic strategies. This review focuses on bacterial transcription factors (TFs), which play crucial roles in bacterial pathogenesis. We discuss the regulatory roles of these factors through examples, and we outline potential therapeutic strategies targeting bacterial TFs. Specifically, we discuss the use of small molecules to interfere with TF function and the development of transcription factor decoys, oligonucleotides that compete with promoters for TF binding. We also cover peptides that target the interaction between the bacterial TF and other factors, such as RNA polymerase, and the targeting of sigma factors. These strategies, while promising, come with challenges, from identifying targets to designing interventions, managing side effects, and accounting for changing bacterial resistance patterns. We also delve into how Artificial Intelligence contributes to these efforts and how it may be exploited in the future, and we touch on the roles of multidisciplinary collaboration and policy to advance this research domain.<b>Abbreviations:</b> AI, artificial intelligence; CNN, convolutional neural networks; DTI: drug-target interaction; HTH, helix-turn-helix; IHF, integration host factor; LTTRs, LysR-type transcriptional regulators; MarR, multiple antibiotic resistance regulator; MRSA, methicillin resistant <i>Staphylococcus aureus</i>; MSA: multiple sequence alignment; NAP, nucleoid-associated protein; PROTACs, proteolysis targeting chimeras; RNAP, RNA polymerase; TF, transcription factor; TFD, transcription factor decoying; TFTRs, TetR-family transcriptional regulators; wHTH, winged helix-turn-helix.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"141-168"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970743/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138832205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing p53 for targeted cancer therapy: new advances and future directions.","authors":"Zdenek Andrysik, Joaquin M Espinosa","doi":"10.1080/21541264.2025.2452711","DOIUrl":"10.1080/21541264.2025.2452711","url":null,"abstract":"<p><p>The transcription factor p53 is the most frequently impaired tumor suppressor in human cancers. In response to various stress stimuli, p53 activates transcription of genes that mediate its tumor-suppressive functions. Distinctive characteristics of p53 outlined here enable a well-defined program of genes involved in cell cycle arrest, apoptosis, senescence, differentiation, metabolism, autophagy, DNA repair, anti-viral response, and anti-metastatic functions, as well as facilitating autoregulation within the p53 network. This versatile, anti-cancer network governed chiefly by a single protein represents an immense opportunity for targeted cancer treatment, since about half of human tumors retain unmutated p53. During the last two decades, numerous compounds have been developed to block the interaction of p53 with the main negative regulator MDM2. However, small molecule inhibitors of MDM2 only induce a therapeutically desirable apoptotic response in a limited number of cancer types. Moreover, clinical trials of the MDM2 inhibitors as monotherapies have not met expectations and have revealed hematological toxicity as a characteristic adverse effect across this drug class. Currently, combination treatments are the leading strategy for enhancing efficacy and reducing adverse effects of MDM2 inhibitors. This review summarizes efforts to identify and test therapeutics that work synergistically with MDM2 inhibitors. Two main types of drugs have emerged among compounds used in the following combination treatments: first, modulators of the p53-regulated transcriptome (including chromatin modifiers), translatome, and proteome, and second, drugs targeting the downstream pathways such as apoptosis, cell cycle arrest, DNA repair, metabolic stress response, immune response, ferroptosis, and growth factor signaling. Here, we review the current literature in this field, while also highlighting overarching principles that could guide target selection in future combination treatments.</p>","PeriodicalId":47009,"journal":{"name":"Transcription-Austin","volume":" ","pages":"3-46"},"PeriodicalIF":3.6,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143543957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}