scholarly journals Evolutionary flexibility in flooding response circuitry in angiosperms

Science ◽  
2019 ◽  
Vol 365 (6459) ◽  
pp. 1291-1295 ◽  
Author(s):  
Mauricio A. Reynoso ◽  
Kaisa Kajala ◽  
Marko Bajic ◽  
Donnelly A. West ◽  
Germain Pauluzzi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
High Resolution ◽  
Gene Regulatory Networks ◽  
Wild Species ◽  
Regulatory Networks ◽  
Chromatin Accessibility ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Gene Regulatory

Flooding due to extreme weather threatens crops and ecosystems. To understand variation in gene regulatory networks activated by submergence, we conducted a high-resolution analysis of chromatin accessibility and gene expression at three scales of transcript control in four angiosperms, ranging from a dryland-adapted wild species to a wetland crop. The data define a cohort of conserved submergence-activated genes with signatures of overlapping cis regulation by four transcription factor families. Syntenic genes are more highly expressed than nonsyntenic genes, yet both can have the cis motifs and chromatin accessibility associated with submergence up-regulation. Whereas the flexible circuitry spans the eudicot-monocot divide, the frequency of specific cis motifs, extent of chromatin accessibility, and degree of submergence activation are more prevalent in the wetland crop and may have adaptive importance.

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.

scholarly journals Accurate differential analysis of transcription factor activity from gene expression

2018 ◽  
Author(s):  
Viren Amin ◽  
Murat Can Cobanoglu
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Expression Data ◽  
Differential Analysis ◽  
Gene Regulatory ◽  
Context Specific ◽  
Tf Gene ◽  
Perturbation Estimation

AbstractWe present EPEE (Effector and Perturbation Estimation Engine), a method for differential analysis of transcription factor (TF) activity from gene expression data. EPEE addresses two principal challenges in the field, namely incorporating context-specific TF-gene regulatory networks, and accounting for the fact that TF activity inference is intrinsically coupled for all TFs that share targets. Our validations in well-studied immune and cancer contexts show that addressing the overlap challenge and using state-of-the-art regulatory networks enable EPEE to consistently produce accurate results. (Accessible at: https://github.com/Cobanoglu-Lab/EPEE)

scholarly journals Modeling Transcriptional Regulation Using Gene Regulatory Networks Based on Multi-Omics Data Sources

2020 ◽  
Author(s):  
Neel Patel ◽  
William 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 BackgroundTranscriptional 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. ResultsWe 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 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 SKAT(sequence kernel association test) analyses of gene expression. ConclusionsOur models generate refined effect estimates for individual transcription factors, allow characterization of their roles across the genome, and provide a framework for integrating multiple data types into a single model of transcriptional regulation.

scholarly journals Automated generation of context-specific Gene Regulatory Networks with a weighted approach in D. melanogaster

2020 ◽  
Author(s):  
Leandro Murgas ◽  
Sebastian Contreras-Riquelme ◽  
J. Eduardo Martínez ◽  
Camilo Villaman ◽  
Rodrigo Santibáñez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Regulation Of Gene Expression ◽  
Chromatin Accessibility ◽  
Reference Network ◽  
Specific Gene ◽  
Gene Regulatory

AbstractMotivationThe regulation of gene expression is a key factor in the development and maintenance of life in all organisms. This process is carried out mainly through the action of transcription factors (TFs), although other actors such as ncRNAs are involved. In this work, we propose a new method to construct Gene Regulatory Networks (GRNs) depicting regulatory events in a certain context for Drosophila melanogaster. Our approach is based on known relationships between epigenetics and the activity of transcription factors.ResultsWe developed method, Tool for Weighted Epigenomic Networks in D. melanogaster (Fly T-WEoN), which generates GRNs starting from a reference network that contains all known gene regulations in the fly. Regulations that are unlikely taking place are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications, and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from literature. Experimental data files can be generated with several standard procedures and used solely when and if available.Fly T-WEoN is available as a Cytoscape application that permits integration with other tools, and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster.AvailabilityFly T-WEoN, together with its step-by-step guide is available at https://[email protected]

scholarly journals Constructing Gene Regulatory Networks using Epigenetic Data

2020 ◽  
Author(s):  
Abhijeet Rajendra Sonawane ◽  
Dawn L. DeMeo ◽  
John Quackenbush ◽  
Kimberly Glass
Keyword(s):  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Message Passing ◽  
Regulatory Networks ◽  
Transcription Factor Binding ◽  
Chromatin Accessibility ◽  
Sequence Motif ◽  
Epigenetic Information ◽  
Factor Binding ◽  
Gene Regulatory

AbstractThe biological processes that drive cellular function can be represented by a complex network of interactions between regulators (transcription factors) and their targets (genes). A cell’s epigenetic state plays an important role in mediating these interactions, primarily by influencing chromatin accessibility. However, effectively leveraging epigenetic information when constructing regulatory networks remains a challenge. We developed SPIDER, which incorporates epigenetic information (DNase-Seq) into a message passing framework in order to estimate gene regulatory networks. We validated SPIDER’s predictions using ChlP-Seq data from ENCODE and found that SPIDER networks were more accurate than other publicly available, epigenetically informed regulatory networks as well as networks based on methods that leverage epigenetic data to predict transcription factor binding sites. SPIDER was also able to improve the detection of cell line specific regulatory interactions. Notably, SPIDER can recover ChlP-seq verified transcription factor binding events in the regulatory regions of genes that do not have a corresponding sequence motif. Constructing biologically interpretable, epigenetically informed networks using SPIDER will allow us to better understand gene regulation as well as aid in the identification of cell-specific drivers and biomarkers of cellular phenotypes.

scholarly journals Ubx orchestrates tissue identity through regional and bidirectional changes to chromatin accessibility

2021 ◽  
Author(s):  
Ryan Loker ◽  
Jordyn E. Sanner ◽  
Richard S. Mann
Keyword(s):  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Chromatin Accessibility ◽  
Thoracic Segment ◽  
Hox Proteins ◽  
The Third ◽  
Gene Regulatory ◽  
Hox Protein ◽  
Hox Cofactors

AbstractHox proteins are homeodomain transcription factors that diversify serially homologous segments along the animal body axis, as revealed by the classic bithorax phenotype of Drosophila melanogaster where mutations in Ultrabithorax (Ubx) transform the third thoracic segment into the likeness of the second thoracic segment. To specify segment identity we show that Ubx both increases and decreases chromatin accessibility, coinciding with its role as both an activator and repressor of transcription. Surprisingly, whether Ubx functions as an activator or repressor differs depending on the proximal-distal position in the segment and the availability of Hox cofactors. Ubx-mediated changes to chromatin accessibility positively and negatively impact the binding of Scalloped (Sd), a transcription factor that is required for appendage development in both segments. These findings reveal how a single Hox protein can modify complex gene regulatory networks to transform the identity of an entire tissue.

scholarly journals Sc-compReg enables the comparison of gene regulatory networks between conditions using single-cell data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhana Duren ◽  
Wenhui Sophia Lu ◽  
Joseph G. Arthur ◽  
Preyas Shah ◽  
Jingxue Xin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Chromatin Accessibility ◽  
Lymphocytic Leukemia ◽  
Cell Subpopulation ◽  
Cell Gene Expression ◽  
Healthy Control ◽  
Gene Regulatory

AbstractThe comparison of gene regulatory networks between diseased versus healthy individuals or between two different treatments is an important scientific problem. Here, we propose sc-compReg as a method for the comparative analysis of gene expression regulatory networks between two conditions using single cell gene expression (scRNA-seq) and single cell chromatin accessibility data (scATAC-seq). Our software, sc-compReg, can be used as a stand-alone package that provides joint clustering and embedding of the cells from both scRNA-seq and scATAC-seq, and the construction of differential regulatory networks across two conditions. We apply the method to compare the gene regulatory networks of an individual with chronic lymphocytic leukemia (CLL) versus a healthy control. The analysis reveals a tumor-specific B cell subpopulation in the CLL patient and identifies TOX2 as a potential regulator of this subpopulation.

scholarly journals Evolution and multiple roles of the Pancrustacea specific transcription factor zelda in insects

2017 ◽  
Author(s):  
Lupis Ribeiro ◽  
Vitória Tobias-Santos ◽  
Danielle Santos ◽  
Felipe Antunes ◽  
Geórgia Feltran ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Chromatin Accessibility ◽  
Multiple Roles ◽  
Biological Processes ◽  
Regulatory Modules ◽  
Ancestral Function ◽  
Gene Regulatory ◽  
Whole Egg

SummaryGene regulatory networks (GRN) evolve as a result of the coevolutionary process acting on transcription factors and the cis-regulatory modules (CRMs) they bind. The zinc-finger transcription factor (TF) zelda (zld) is essential for maternal zygotic transition (MZT) in Drosophila melanogaster, where it directly binds over thousand CRMs to regulate chromatin accessibility. D. melanogaster displays a long germ type of embryonic development, where all segments are simultaneously generated along the whole egg. However, it remains unclear if zld is also involved in MZT of short-germ insects (including those from basal lineages) or in other biological processes. Here we show that zld is an innovation of the Pancrustacea lineage, being absent in more distant arthropods (e.g. chelicerates) and other organisms. To better understand zld’s ancestral function, we thoroughly investigated its roles in a short-germ beetle, Tribolium castaneum, using molecular biology and computational approaches. Our results demonstrate roles for zld not only during the MZT, but also in posterior segmentation and patterning of imaginal disc derived structures. Further, we also demonstrate that zld is critical for posterior segmentation in the hemipteran Rhodnius prolixus, indicating this function predates the origin of holometabolous insects and was subsequently lost in long-germ insects. Our results unveil new roles of zld in maintaining pluripotent state of progenitor cells at the posterior region and suggest that changes in expression of zld (and probably other pioneer TFs) are critical in the evolution of insect GRNs.

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