scholarly journals Phenotypic Nonspecificity as the Result of Limited Specificity of Transcription Factor Function

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Anthony Percival-Smith
Keyword(s):  
Transcription Factor ◽  
Genetic Analysis ◽  
Emergent Property ◽  
Regulatory Sequences ◽  
Unexpected Result ◽  
Biological Processes ◽  
Cooperative Interactions ◽  
Sequence Recognition ◽  
Random Distributions ◽  
Factor Function

Drosophila transcription factor (TF) function is phenotypically nonspecific. Phenotypic nonspecificity is defined as one phenotype being induced or rescued by multiple TFs. To explain this unexpected result, a hypothetical world of limited specificity is explored where all TFs have unique random distributions along the genome due to low information content of DNA sequence recognition and somewhat promiscuous cooperative interactions with other TFs. Transcription is an emergent property of these two conditions. From this model, explicit predictions are made. First, many more cases of TF nonspecificity are expected when examined. Second, the genetic analysis of regulatory sequences should uncover cis-element bypass and, third, genetic analysis of TF function should generally uncover differential pleiotropy. In addition, limited specificity provides evolutionary opportunity and explains the inefficiency of expression analysis in identifying genes required for biological processes.

scholarly journals Molecular regulation of Snai2 in development and disease

2019 ◽  
Vol 132 (23) ◽  
Author(s):  
Wenhui Zhou ◽  
Kayla M. Gross ◽  
Charlotte Kuperwasser
Keyword(s):  
Transcription Factor ◽  
Cell Biology ◽  
Molecular Mechanisms ◽  
Epithelial To Mesenchymal Transition ◽  
Zinc Finger Protein ◽  
Main Role ◽  
Biological Processes ◽  
Developmental Defects ◽  
Mesenchymal Transition ◽  
Damage Repair

ABSTRACT The transcription factor Snai2, encoded by the SNAI2 gene, is an evolutionarily conserved C2H2 zinc finger protein that orchestrates biological processes critical to tissue development and tumorigenesis. Initially characterized as a prototypical epithelial-to-mesenchymal transition (EMT) transcription factor, Snai2 has been shown more recently to participate in a wider variety of biological processes, including tumor metastasis, stem and/or progenitor cell biology, cellular differentiation, vascular remodeling and DNA damage repair. The main role of Snai2 in controlling such processes involves facilitating the epigenetic regulation of transcriptional programs, and, as such, its dysregulation manifests in developmental defects, disruption of tissue homeostasis, and other disease conditions. Here, we discuss our current understanding of the molecular mechanisms regulating Snai2 expression, abundance and activity. In addition, we outline how these mechanisms contribute to disease phenotypes or how they may impact rational therapeutic targeting of Snai2 dysregulation in human disease.

scholarly journals Integrated transcription factor profiling with transcriptome analysis identifies L1PA2 transposons as global regulatory modulators in a breast cancer model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiayue-Clara Jiang ◽  
Joseph A. Rothnagel ◽  
Kyle R. Upton
Keyword(s):  
Breast Cancer ◽  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Disease Diagnosis ◽  
Integrated Analysis ◽  
Regulatory Sequences ◽  
Cancer Model ◽  
Mcf7 Cells ◽  
Epithelial Cancers ◽  
Breast Cancer Model

AbstractWhile transposons are generally silenced in somatic tissues, many transposons escape epigenetic repression in epithelial cancers, become transcriptionally active and contribute to the regulation of human gene expression. We have developed a bioinformatic pipeline for the integrated analysis of transcription factor binding and transcriptomic data to identify transposon-derived promoters that are activated in specific diseases and developmental states. We applied this pipeline to a breast cancer model, and found that the L1PA2 transposon subfamily contributes abundant regulatory sequences to co-ordinated transcriptional regulation in breast cancer. Transcription factor profiling demonstrates that over 27% of L1PA2 transposons harbour co-localised binding sites of functionally interacting, cancer-associated transcription factors in MCF7 cells, a cell line used to model breast cancer. Transcriptomic analysis reveals that L1PA2 transposons also contribute transcription start sites to up-regulated transcripts in MCF7 cells, including some transcripts with established oncogenic properties. In addition, we verified the utility of our pipeline on other transposon subfamilies, as well as on leukemia and lung carcinoma cell lines. We demonstrate that the normally quiescent regulatory activities of transposons can be activated and alter the cancer transcriptome. In particular, the L1PA2 subfamily contributes abundant regulatory sequences, and likely plays a global role in modulating breast cancer transcriptional regulation. Understanding the regulatory impact of L1PA2 on breast cancer genomes provides additional insights into cancer genome regulation, and may provide novel biomarkers for disease diagnosis, prognosis and therapy.

scholarly journals Promoter-Proximal Regulatory Elements Involved in oriP-EBNA1-Independent and -Dependent Activation of the Epstein-Barr Virus C Promoter in B-Lymphoid Cell Lines

2001 ◽  
Vol 75 (13) ◽  
pp. 5796-5811 ◽  
Author(s):  
Tina Nilsson ◽  
Henrik Zetterberg ◽  
Yuyan Camilla Wang ◽  
Lars Rymo
Keyword(s):  
Transcription Factor ◽  
Epstein Barr Virus ◽  
Regulatory Elements ◽  
Negative Regulator ◽  
Regulatory Sequences ◽  
Barr Virus ◽  
Group I ◽  
Epstein Barr ◽  
B Lymphoid ◽  
Virus C

ABSTRACT The identification of the cellular factors that control the transcription regulatory activity of the Epstein-Barr virus C promoter (Cp) is fundamental to the understanding of the molecular mechanisms that control virus latent gene expression. Using transient transfection of reporter plasmids in group I phenotype B-lymphoid cells, we have previously shown that the −248 to −55 region (−248/−55 region) of Cp contains elements that are essential fororiPI-EBNA1-dependent as well asoriPI-EBNA1-independent activation of the promoter. We now establish the importance of this region by a detailed mutational analysis of reporter plasmids carrying Cp regulatory sequences together with or without oriPI. The reporter plasmids were transfected into group I phenotype Rael cells and group III phenotype cbc-Rael cells, and the Cp activity measured was correlated with the binding of candidate transcription factors in electrophoretic mobility shift assays and further assessed in cotransfection experiments. We show that the NF-Y transcription factor interacts with the previously identified CCAAT box in the −71/−63 Cp region (M. T. Puglielli, M. Woisetschlaeger, and S. H. Speck, J. Virol. 70:5758–5768, 1996). We also show that members of the C/EBP transcription factor family interact with a C/EBP consensus sequence in the −119/−112 region of Cp and that this interaction is important for promoter activity. A central finding is the identification of a GC-rich sequence in the −99/−91 Cp region that is essential fororiPI-EBNA1-independent as well asoriPI-EBNA1-dependent activity of the promoter. This region contains overlapping binding sites for Sp1 and Egr-1, and our results suggest that Sp1 is a positive and Egr-1 is a negative regulator of Cp activity. Furthermore, we demonstrate that a reporter plasmid that in addition to oriPI contains only the −111/+76 region of Cp still retains the ability to be activated by EBNA1.

scholarly journals An Algorithm for Cellular Reprogramming

2017 ◽  
Author(s):  
Scott Ronquist ◽  
Geoff Patterson ◽  
Markus Brown ◽  
Stephen Lindsly ◽  
Haiming Chen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Cell Biology ◽  
Human Fibroblasts ◽  
Cell Types ◽  
Approximate Model ◽  
Cellular Reprogramming ◽  
Biological Processes ◽  
Moderate Complexity

AbstractThe day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton’s laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. In this paper, we describe an approach to optimizing the use of transcription factors (TFs) in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a cell cycle synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points along the cell cycle. In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the TAD expression levels. Based on this dynamical model and known bioinformatics, such as transcription factor binding sites (TFBS) and functions, we develop a methodology for identifying the top transcription factor candidates for a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. Our data-guided methodology identifies a number of transcription factors previously validated for reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes.Significance StatementReprogramming the human genome toward any desirable state is within reach; application of select transcription factors drives cell types toward different lineages in many settings. We introduce the concept of data-guided control in building a universal algorithm for directly reprogramming any human cell type into any other type. Our algorithm is based on time series genome transcription and architecture data and known regulatory activities of transcription factors, with natural dimension reduction using genome architectural features. Our algorithm predicts known reprogramming factors, top candidates for new settings, and ideal timing for application of transcription factors. This framework can be used to develop strategies for tissue regeneration, cancer cell reprogramming, and control of dynamical systems beyond cell biology.

scholarly journals Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

2019 ◽  
Author(s):  
Joanna Mitchelmore ◽  
Nastasiya Grinberg ◽  
Chris Wallace ◽  
Mikhail Spivakov
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Statistical Power ◽  
Target Genes ◽  
Allelic Variation ◽  
Regulatory Function ◽  
Regulatory Sequences ◽  
Distal Enhancer ◽  
Association Testing ◽  
Gene Regulatory

AbstractIdentifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritising such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines (LCLs) and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal over 1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localise to the promoter regions of other genes, supporting the notion of ‘epromoters’: dual-action CRMs with promoter and distal enhancer activity.

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