scholarly journals Integrating Peak Colocalization and Motif Enrichment Analysis for the Discovery of Genome-Wide Regulatory Modules and Transcription Factor Recruitment Rules

2020 ◽  
Vol 11 ◽  
Author(s):  
Mirko Ronzio ◽  
Federico Zambelli ◽  
Diletta Dolfini ◽  
Roberto Mantovani ◽  
Giulio Pavesi
Keyword(s):  
Transcription Factor ◽  
Enrichment Analysis ◽  
Regulatory Modules ◽  
Motif Enrichment ◽  
Genome Wide

scholarly journals Genome-Wide Identification and Transcriptional Expression Profiles of Transcription Factor WRKY in Common Walnut (Juglans regia L.)

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1444
Author(s):  
Fan Hao ◽  
Ge Yang ◽  
Huijuan Zhou ◽  
Jiajun Yao ◽  
Deruilin Liu ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Gene Family ◽  
Expression Profiles ◽  
Juglans Regia ◽  
Enrichment Analysis ◽  
Wrky Gene ◽  
Genome Wide ◽  
Plant Pathogen Interaction ◽  
High Degree ◽  
Common Walnut

The transcription factor WRKY is widely distributed in the plant kingdom, playing a significant role in plant growth, development and response to stresses. Walnut is an economically important temperate tree species valued for both its edible nuts and high-quality wood, and its response to various stresses is an important factor that determines the quality of its fruit. However, in walnut trees themselves, information about the WRKY gene family remains scarce. In this paper, we perform a comprehensive study of the WRKY gene family in walnut. In total, we identified 103 WRKY genes in the common walnut that are clustered into 4 groups and distributed on 14 chromosomes. The conserved domains all contained a WRKY domain, and motif 2 was observed in most WRKYs, suggesting a high degree of conservation and similar functions within each subfamily. However, gene structure was significantly differentiated between different subfamilies. Synteny analysis indicates that there were 56 gene pairs in J. regia and A. thaliana, 76 in J. regia and J. mandshurica, 75 in J. regia and J. microcarpa, 76 in J. regia and P. trichocarpa, and 33 in J. regia and Q. robur, indicating that the WRKY gene family may come from a common ancestor. GO and KEGG enrichment analysis showed that the WRKY gene family was involved in resistance traits and the plant-pathogen interaction pathway. In anthracnose-resistant F26 fruits (AR) and anthracnose-susceptible F423 fruits (AS), transcriptome and qPCR analysis results showed that JrWRKY83, JrWRKY73 and JrWRKY74 were expressed significantly more highly in resistant cultivars, indicating that these three genes may be important contributors to stress resistance in walnut trees. Furthermore, we investigate how these three genes potentially target miRNAs and interact with proteins. JrWRKY73 was target by the miR156 family, including 12 miRNAs; this miRNA family targets WRKY genes to enhance plant defense. JrWRKY73 also interacted with the resistance gene AtMPK6, showing that it may play a crucial role in walnut defense.

scholarly journals Transcription factor enrichment analysis (TFEA) quantifies the activity of multiple transcription factors from a single experiment

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jonathan D. Rubin ◽  
Jacob T. Stanley ◽  
Rutendo F. Sigauke ◽  
Cecilia B. Levandowski ◽  
Zachary L. Maas ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Regulatory Networks ◽  
Time Series Data ◽  
Effective Means ◽  
Enrichment Analysis ◽  
Cost Effective ◽  
Computational Method ◽  
Series Data ◽  
Single Experiment ◽  
Motif Enrichment

AbstractDetecting changes in the activity of a transcription factor (TF) in response to a perturbation provides insights into the underlying cellular process. Transcription Factor Enrichment Analysis (TFEA) is a robust and reliable computational method that detects positional motif enrichment associated with changes in transcription observed in response to a perturbation. TFEA detects positional motif enrichment within a list of ranked regions of interest (ROIs), typically sites of RNA polymerase initiation inferred from regulatory data such as nascent transcription. Therefore, we also introduce muMerge, a statistically principled method of generating a consensus list of ROIs from multiple replicates and conditions. TFEA is broadly applicable to data that informs on transcriptional regulation including nascent transcription (eg. PRO-Seq), CAGE, histone ChIP-Seq, and accessibility data (e.g., ATAC-Seq). TFEA not only identifies the key regulators responding to a perturbation, but also temporally unravels regulatory networks with time series data. Consequently, TFEA serves as a hypothesis-generating tool that provides an easy, rigorous, and cost-effective means to broadly assess TF activity yielding new biological insights.

scholarly journals High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Cancer Cells ◽  
High Throughput ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Chromatin Accessibility ◽  
Regulatory Regions ◽  
Factor Binding ◽  
Genome Wide

AbstractChromatin accessibility profiling can identify putative regulatory regions genome wide; however, pooled single-cell methods for assessing the effects of regulatory perturbations on accessibility are limited. Here, we report a modified droplet-based single-cell ATAC-seq protocol for perturbing and evaluating dynamic single-cell epigenetic states. This method (Spear-ATAC) enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at once. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations reveals the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles.

scholarly journals Subtype-associated epigenomic landscape and 3D genome structure in bladder cancer

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tejaswi Iyyanki ◽  
Baozhen Zhang ◽  
Qixuan Wang ◽  
Ye Hou ◽  
Qiushi Jin ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Transcription Factor ◽  
Cancer Cell ◽  
Genome Structure ◽  
Transcription Factor Binding ◽  
Specific Gene ◽  
Open Chromatin ◽  
Factor Binding ◽  
3D Genome ◽  
Genome Wide

Abstract Muscle-invasive bladder cancers are characterized by their distinct expression of luminal and basal genes, which could be used to predict key clinical features such as disease progression and overall survival. Transcriptionally, FOXA1, GATA3, and PPARG are shown to be essential for luminal subtype-specific gene regulation and subtype switching, while TP63, STAT3, and TFAP2 family members are critical for regulation of basal subtype-specific genes. Despite these advances, the underlying epigenetic mechanisms and 3D chromatin architecture responsible for subtype-specific regulation in bladder cancer remain unknown. Result We determine the genome-wide transcriptome, enhancer landscape, and transcription factor binding profiles of FOXA1 and GATA3 in luminal and basal subtypes of bladder cancer. Furthermore, we report the first-ever mapping of genome-wide chromatin interactions by Hi-C in both bladder cancer cell lines and primary patient tumors. We show that subtype-specific transcription is accompanied by specific open chromatin and epigenomic marks, at least partially driven by distinct transcription factor binding at distal enhancers of luminal and basal bladder cancers. Finally, we identify a novel clinically relevant transcription factor, Neuronal PAS Domain Protein 2 (NPAS2), in luminal bladder cancers that regulates other subtype-specific genes and influences cancer cell proliferation and migration. Conclusion In summary, our work identifies unique epigenomic signatures and 3D genome structures in luminal and basal urinary bladder cancers and suggests a novel link between the circadian transcription factor NPAS2 and a clinical bladder cancer subtype.

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