Comparative genomics on MCM8 orthologous genes reveals the transcriptional regulation by transcription factor E2F

Gene ◽  
2006 ◽  
Vol 367 ◽  
pp. 126-134 ◽  
Author(s):  
Reiko Hayashi ◽  
Yuya Goto ◽  
Ayaka Haga ◽  
Daisuke Kobayashi ◽  
Ryuji Ikeda ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Comparative Genomics ◽  
Orthologous Genes ◽  
Transcription Factor E2f

scholarly journals RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis

2018 ◽  
Author(s):  
Xin Chen ◽  
Anjun Ma ◽  
Adam McDermaid ◽  
Hanyuan Zhang ◽  
Chao Liu ◽  
...  
Keyword(s):  
Transcriptional Regulation ◽  
Stress Response ◽  
Comparative Genomics ◽  
Gene Regulatory Network ◽  
Lactococcus Lactis ◽  
Regulatory Network ◽  
Acid Stress ◽  
Orthologous Genes ◽  
Gene Regulatory ◽  
Acid Stress Response

ABSTRACTRegulons, which serve as co-regulated gene groups contributing to the transcriptional regulation of microbial genomes, have the potential to aid in understanding of underlying regulatory mechanisms. In this study, we designed a novel computational pipeline, RECTA, for regulon prediction related to the gene regulatory network under certain conditions. To demonstrate the effectiveness of this tool, we implemented RECTA onLactococcus lactisMG1363 data to elucidate acid-response regulons.Lactococcus lactisis one of the most important Gram-positive lactic acid-producing bacteria, widely used in food industry and has been proved to have advantages in oral delivery of drug and vaccine. The pipeline carries out differential gene expression, gene co-expression analysis,cis-regulatory motif finding, and comparative genomics to predict and validate regulons related to acid stress response. A total of 51 regulonswere identified, 14 of which have computational-verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response with (i) known transcriptional factors in MEME suite database successfully mapped inLactococcus lactisMG1363; and (ii) differentially expressed genes between pH values of 6.5 (control) and 5.1 (treatment). Validated by 36 literature confirmed acid stress response related proteins and genes, 33 genes inLactococcus lactisMG1363 were found having orthologous genes using BLAST, associated to six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A,rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated to acid stress. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network through regulon elucidation. The predicted response pathways could serve as promising candidates for better acid tolerance engineering inLactococcus lactis. RECTA has strong application power and can be effectively applied to other bacterial genomes where the elucidation of the transcriptional regulation network is needed.

scholarly journals Novel Transcriptional Regulons for Autotrophic Cycle Genes in Crenarchaeota

2015 ◽  
Vol 197 (14) ◽  
pp. 2383-2391 ◽  
Author(s):  
Semen A. Leyn ◽  
Irina A. Rodionova ◽  
Xiaoqing Li ◽  
Dmitry A. Rodionov
Keyword(s):  
Carbon Dioxide ◽  
Transcriptional Regulation ◽  
Comparative Genomics ◽  
Dna Binding ◽  
Transcriptional Control ◽  
Binding Assays ◽  
Promoter Regions ◽  
Content Type ◽  
Genome Context

ABSTRACTAutotrophic microorganisms are able to utilize carbon dioxide as their only carbon source, or, alternatively, many of them can grow heterotrophically on organics. Different variants of autotrophic pathways have been identified in various lineages of the phylumCrenarchaeota. Aerobic members of the orderSulfolobalesutilize the hydroxypropionate-hydroxybutyrate cycle (HHC) to fix inorganic carbon, whereas anaerobicThermoprotealesuse the dicarboxylate-hydroxybutyrate cycle (DHC). Knowledge of transcriptional regulation of autotrophic pathways inArchaeais limited. We applied a comparative genomics approach to predict novel autotrophic regulons in theCrenarchaeota. We report identification of two novel DNA motifs associated with the autotrophic pathway genes in theSulfolobales(HHC box) andThermoproteales(DHC box). Based on genome context evidence, the HHC box regulon was attributed to a novel transcription factor from the TrmB family named HhcR. Orthologs of HhcR are present in allSulfolobalesgenomes but were not found in other lineages. A predicted HHC box regulatory motif was confirmed byin vitrobinding assays with the recombinant HhcR protein fromMetallosphaera yellowstonensis. For the DHC box regulon, we assigned a different potential regulator, named DhcR, which is restricted to the orderThermoproteales. DhcR inThermoproteus neutrophilus(Tneu_0751) was previously identified as a DNA-binding protein with high affinity for the promoter regions of two autotrophic operons. The global HhcR and DhcR regulons reconstructed by comparative genomics were reconciled with available omics data inMetallosphaeraandThermoproteusspp. The identified regulons constitute two novel mechanisms for transcriptional control of autotrophic pathways in theCrenarchaeota.IMPORTANCELittle is known about transcriptional regulation of carbon dioxide fixation pathways inArchaea. We previously applied the comparative genomics approach for reconstruction of DtxR family regulons in diverse lineages ofArchaea. Here, we utilize similar computational approaches to identify novel regulatory motifs for genes that are autotrophically induced in microorganisms from two lineages ofCrenarchaeotaand to reconstruct the respective regulons. The predicted novel regulons in archaeal genomes control the majority of autotrophic pathway genes and also other carbon and energy metabolism genes. The HhcR regulon was experimentally validated by DNA-binding assays inMetallosphaeraspp. Novel regulons described for the first time in this work provide a basis for understanding the mechanisms of transcriptional regulation of autotrophic pathways inArchaea.

scholarly journals Ferroptosis is controlled by the coordinated transcriptional regulation of glutathione and labile iron metabolism by the transcription factor BACH1

2019 ◽  
Vol 295 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Hironari Nishizawa ◽  
Mitsuyo Matsumoto ◽  
Tomohiko Shindo ◽  
Daisuke Saigusa ◽  
Hiroki Kato ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Iron Metabolism ◽  
Labile Iron

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.

The Transcription Factor E2F-1 in SV40 T Antigen-Induced Cerebellar Purkinje Cell Degeneration

1998 ◽  
Vol 12 (1-2) ◽  
pp. 16-28 ◽  
Author(s):  
Maria C. Athanasiou ◽  
Wael Yunis ◽  
Natalie Coleman ◽  
Robert Ehlenfeldt ◽  
H.Brent Clark ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Purkinje Cell ◽  
T Antigen ◽  
Cerebellar Purkinje Cell ◽  
Sv40 T Antigen ◽  
Cell Degeneration ◽  
Purkinje Cell Degeneration ◽  
Transcription Factor E2f

scholarly journals Molecular cloning of cellular genes encoding retinoblastoma-associated proteins: identification of a gene with properties of the transcription factor E2F.

1992 ◽  
Vol 12 (12) ◽  
pp. 5620-5631 ◽  
Author(s):  
B Shan ◽  
X Zhu ◽  
P L Chen ◽  
T Durfee ◽  
Y Yang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Mammalian Cells ◽  
Leucine Zipper ◽  
T Antigen ◽  
Transactivation Domain ◽  
Recognition Sequence ◽  
Cellular Genes ◽  
Genes Encoding ◽  
Associated Proteins ◽  
Transcription Factor E2f

The retinoblastoma protein interacts with a number of cellular proteins to form complexes which are probably crucial for its normal physiological function. To identify these proteins, we isolated nine distinct clones by direct screening of cDNA expression libraries using purified RB protein as a probe. One of these clones, Ap12, is expressed predominantly at the G1-S boundary and in the S phase of the cell cycle. The nucleotide sequence of Ap12 has features characteristic of transcription factors. The C-terminal region binds to unphosphorylated RB in regions similar to those to which T antigen binds and contains a transactivation domain. A region containing a potential leucine zipper flanked by basic residues is able to bind an E2F recognition sequence specifically. Expression of Ap12 in mammalian cells significantly enhances E2F-dependent transcriptional activity. These results suggest that Ap12 encodes a protein with properties known to be characteristic of transcription factor E2F.

scholarly journals Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcriptional Regulation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Prediction Models ◽  
Long Distance ◽  
Chromatin Looping ◽  
Gene Regulatory ◽  
The Impact

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.

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