scholarly journals Predicting context specific enhancer-promoter interactions from ChIP-Seq time course data

Author(s):  
Tomasz Dzida ◽  
Mudassar Iqbal ◽  
Iryna Charapitsa ◽  
George Reid ◽  
Henk Stunnenberg ◽  
...  

We have developed a machine learning approach to predict context specific enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

2017 ◽  
Author(s):  
Tomasz Dzida ◽  
Mudassar Iqbal ◽  
Iryna Charapitsa ◽  
George Reid ◽  
Henk Stunnenberg ◽  
...  

We have developed a machine learning approach to predict context specific enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.


PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3742 ◽  
Author(s):  
Tomasz Dzida ◽  
Mudassar Iqbal ◽  
Iryna Charapitsa ◽  
George Reid ◽  
Henk Stunnenberg ◽  
...  

We have developed a machine learning approach to predict stimulation-dependent enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.


2021 ◽  
Vol 9 (8) ◽  
pp. 1570
Author(s):  
Chien-Hsun Huang ◽  
Chih-Chieh Chen ◽  
Yu-Chun Lin ◽  
Chia-Hsuan Chen ◽  
Ai-Yun Lee ◽  
...  

The current taxonomy of the Lactiplantibacillus plantarum group comprises of 17 closely related species that are indistinguishable from each other by using commonly used 16S rRNA gene sequencing. In this study, a whole-genome-based analysis was carried out for exploring the highly distinguished target genes whose interspecific sequence identity is significantly less than those of 16S rRNA or conventional housekeeping genes. In silico analyses of 774 core genes by the cano-wgMLST_BacCompare analytics platform indicated that csbB, morA, murI, mutL, ntpJ, rutB, trmK, ydaF, and yhhX genes were the most promising candidates. Subsequently, the mutL gene was selected, and the discrimination power was further evaluated using Sanger sequencing. Among the type strains, mutL exhibited a clearly superior sequence identity (61.6–85.6%; average: 66.6%) to the 16S rRNA gene (96.7–100%; average: 98.4%) and the conventional phylogenetic marker genes (e.g., dnaJ, dnaK, pheS, recA, and rpoA), respectively, which could be used to separat tested strains into various species clusters. Consequently, species-specific primers were developed for fast and accurate identification of L. pentosus, L. argentoratensis, L. plantarum, and L. paraplantarum. During this study, one strain (BCRC 06B0048, L. pentosus) exhibited not only relatively low mutL sequence identities (97.0%) but also a low digital DNA–DNA hybridization value (78.1%) with the type strain DSM 20314T, signifying that it exhibits potential for reclassification as a novel subspecies. Our data demonstrate that mutL can be a genome-wide target for identifying and classifying the L. plantarum group species and for differentiating novel taxa from known species.


Metabolites ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 20
Author(s):  
Priyanka Baloni ◽  
Wikum Dinalankara ◽  
John C. Earls ◽  
Theo A. Knijnenburg ◽  
Donald Geman ◽  
...  

Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism, and reactive oxygen species (ROS) detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach.


Genetics ◽  
2003 ◽  
Vol 164 (1) ◽  
pp. 247-258 ◽  
Author(s):  
Jinghong Li ◽  
Willis X Li

Abstract Overactivation of receptor tyrosine kinases (RTKs) has been linked to tumorigenesis. To understand how a hyperactivated RTK functions differently from wild-type RTK, we conducted a genome-wide systematic survey for genes that are required for signaling by a gain-of-function mutant Drosophila RTK Torso (Tor). We screened chromosomal deficiencies for suppression of a gain-of-function mutation tor (torGOF), which led to the identification of 26 genomic regions that, when in half dosage, suppressed the defects caused by torGOF. Testing of candidate genes in these regions revealed many genes known to be involved in Tor signaling (such as those encoding the Ras-MAPK cassette, adaptor and structural molecules of RTK signaling, and downstream target genes of Tor), confirming the specificity of this genetic screen. Importantly, this screen also identified components of the TGFβ (Dpp) and JAK/STAT pathways as being required for TorGOF signaling. Specifically, we found that reducing the dosage of thickveins (tkv), Mothers against dpp (Mad), or STAT92E (aka marelle), respectively, suppressed torGOF phenotypes. Furthermore, we demonstrate that in torGOF embryos, dpp is ectopically expressed and thus may contribute to the patterning defects. These results demonstrate an essential requirement of noncanonical signaling pathways for a persistently activated RTK to cause pathological defects in an organism.


Endocrinology ◽  
2018 ◽  
Vol 160 (1) ◽  
pp. 38-54 ◽  
Author(s):  
Keiichi Itoi ◽  
Ikuko Motoike ◽  
Ying Liu ◽  
Sam Clokie ◽  
Yasumasa Iwasaki ◽  
...  

Abstract Glucocorticoids (GCs) are essential for stress adaptation, acting centrally and in the periphery. Corticotropin-releasing factor (CRF), a major regulator of adrenal GC synthesis, is produced in the paraventricular nucleus of the hypothalamus (PVH), which contains multiple neuroendocrine and preautonomic neurons. GCs may be involved in diverse regulatory mechanisms in the PVH, but the target genes of GCs are largely unexplored except for the CRF gene (Crh), a well-known target for GC negative feedback. Using a genome-wide RNA-sequencing analysis, we identified transcripts that changed in response to either high-dose corticosterone (Cort) exposure for 12 days (12-day high Cort), corticoid deprivation for 7 days (7-day ADX), or acute Cort administration. Among others, canonical GC target genes were upregulated prominently by 12-day high Cort. Crh was upregulated or downregulated most prominently by either 7-day ADX or 12-day high Cort, emphasizing the recognized feedback effects of GC on the hypothalamic-pituitary-adrenal (HPA) axis. Concomitant changes in vasopressin and apelin receptor gene expression are likely to contribute to HPA repression. In keeping with the pleotropic cellular actions of GCs, 7-day ADX downregulated numerous genes of a broad functional spectrum. The transcriptome response signature differed markedly between acute Cort injection and 12-day high Cort. Remarkably, six immediate early genes were upregulated 1 hour after Cort injection, which was confirmed by quantitative reverse transcription PCR and semiquantitative in situ hybridization. This study may provide a useful database for studying the regulatory mechanisms of GC-dependent gene expression and repression in the PVH.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Chunmei He ◽  
Jaime A. Teixeira da Silva ◽  
Jianwen Tan ◽  
Jianxia Zhang ◽  
Xiaoping Pan ◽  
...  

2019 ◽  
Author(s):  
Zeineb Achour ◽  
Johann Joets ◽  
Martine Leguilloux ◽  
Hélène Sellier ◽  
Jean-Philippe Pichon ◽  
...  

ABSTRACTCharacterizing the molecular processes developed by plants to respond to environmental cues is a major task to better understand local adaptation. DNA methylation is a chromatin mark involved in the transcriptional silencing of transposable elements (TEs) and gene expression regulation. While the molecular bases of DNA methylation regulation are now well described, involvement of DNA methylation in plant response to environmental cues remains poorly characterized. Here, using the TE-rich maize genome and analyzing methylome response to prolonged cold at the chromosome and feature scales, we investigate how genomic architecture affects methylome response to stress in a cold-sensitive genotype. Interestingly, we show that cold stress induces a genome-wide methylation increase through the hypermethylation of TE sequences and centromeres. Our work highlights a cytosine context-specific response of TE methylation that depends on TE types, chromosomal location and proximity to genes. The patterns observed can be explained by the parallel transcriptional activation of multiple DNA methylation pathways that methylate TEs in the various chromatin locations where they reside. Our results open new insights into the possible role of genome-wide DNA methylation in phenotypic response to stress.


2002 ◽  
Vol 22 (8) ◽  
pp. 2642-2649 ◽  
Author(s):  
Stéphane Le Crom ◽  
Frédéric Devaux ◽  
Philippe Marc ◽  
Xiaoting Zhang ◽  
W. Scott Moye-Rowley ◽  
...  

ABSTRACT Yrr1p is a recently described Zn2Cys6 transcription factor involved in the pleiotropic drug resistance (PDR) phenomenon. It is controlled in a Pdr1p-dependent manner and is autoregulated. We describe here a new genome-wide approach to characterization of the set of genes directly regulated by Yrr1p. We found that the time-course production of an artificial chimera protein containing the DNA-binding domain of Yrr1p activated the 15 genes that are also up-regulated by a gain-of-function mutant of Yrr1p. Gel mobility shift assays showed that the promoters of the genes AZR1, FLR1, SNG1, YLL056C, YLR346C, and YPL088W interacted with Yrr1p. The putative consensus Yrr1p binding site deduced from these experiments, (T/A)CCG(C/T)(G/T)(G/T)(A/T)(A/T), is strikingly similar to the PDR element binding site sequence recognized by Pdr1p and Pdr3p. The minor differences between these sequences are consistent with Yrr1p and Pdr1p and Pdr3p having different sets of target genes. According to these data, some target genes are directly regulated by Pdr1p and Pdr3p or by Yrr1p, whereas some genes are indirectly regulated by the activation of Yrr1p. Some genes, such as YOR1, SNQ2, and FLR1, are clearly directly controlled by both classes of transcription factor, suggesting an important role for the corresponding membrane proteins.


2020 ◽  
Author(s):  
Tao Zhong ◽  
Cheng Wang ◽  
Jiangtao Hu ◽  
Xiaoyong Chen ◽  
Lili Niu ◽  
...  

Abstract Background: Rumen is an important digestive organ of ruminant. From fetal to adult stage, the morphology, structure and function of rumen have changed significantly. But the intrinsic genetic regulation is still limited. We previously reported a genome-wide expression profile of miRNAs in prenatal goat rumens. In the present study, we rejoined analyzed the transcriptomes of rumen miRNAs during prenatal (E60 and E135) and postnatal (D30 and D150) stages.Results: A total of 66 differentially expressed miRNAs (DEMs) were identified in the rumen tissues from D30 and D150 goats. Of these, 17 DEMs were consistently highly expressed in the rumens at the preweaning stages (E60, E135 and D30), while down-regulated at D150. Noteworthy, annotation analysis revealed that the target genes regulated by the DEMs were mainly enriched in MAPK signaling pathway, Jak-STAT signaling pathway and Ras signaling pathway. Interestingly, the expression of miR-148a-3p was significantly high in the embryonic stage and down-regulated at D150. The potential binding sites between miR-148a-3p and QKI were predicted by the TargetScan and verified by the dual luciferase report assay. The co-localization of miR-148a-3p and QKI was observed not in intestinal tracts but in rumen tissues by in situ hybridization. Moreover, the expression of miR-148a-3p in the epithelium was significantly higher than that in the other layers, suggesting that miR-148a-3p involve in the development of rumen epithelial cells by targeting QKI. Subsequently, miR-148a-3p inhibitor was found to induce the proliferation of GES-1 cells.Conclusions: Taken together, these results identified the DEMs involved in the development of rumen and provided an insight into the regulation mechanism of goat rumens during development.


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