scholarly journals Evidences for functional trans-acting eRNA-promoter R-loops at Alu sequences

2021 ◽  
Author(s):  
Xue Bai ◽  
Feifei Li ◽  
Zhihua Zhang
Keyword(s):  
Transcription Factors ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Sequence Similarity ◽  
Genomic Data ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Alu Elements ◽  
Alu Sequences ◽  
Evolution Of Gene Regulation

AbstractEnhancers modulate gene expression by interacting with promoters. Models of enhancer-promoter interactions (EPIs) in the literature involve the activity of many components, including transcription factors and nucleic acid. However, the role that sequence similarity plays in EPIs, remains largely unexplored. Herein, we report that Alu-derived sequences dominate sequence similarity between enhancers and promoters. After rejecting the alternative DNA:DNA and DNA:RNA triplex models, we proposed that enhancer-associated RNAs, or eRNAs, may directly contact their targeted promoters by forming trans-acting R-loops at those Alu sequences. We showed how the characteristic distribution of functional genomic data, such as RNA-DNA proximate ligation reads, binding of transcription factors, and RNA-binding proteins, align with the Alu sequences of EPIs. We also showed that these aligned Alu sequences may be subject to the constraint of coevolution, further implying the functional significance of these R-loop hybrids. Finally, our results showed that eRNA and Alu elements associate in a manner previously unrecognized in the EPIs and the evolution of gene regulation networks in mammals.

scholarly journals Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks

2008 ◽  
Vol 40 (7) ◽  
pp. 854-861 ◽  
Author(s):  
Jun Zhu ◽  
Bin Zhang ◽  
Erin N Smith ◽  
Becky Drees ◽  
Rachel B Brem ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Large Scale ◽  
Genomic Data ◽  
Functional Genomic ◽  
Functional Genomic Data

scholarly journals Testing the Ortholog Conjecture with Comparative Functional Genomic Data from Mammals

2011 ◽  
Vol 7 (6) ◽  
pp. e1002073 ◽  
Author(s):  
Nathan L. Nehrt ◽  
Wyatt T. Clark ◽  
Predrag Radivojac ◽  
Matthew W. Hahn
Keyword(s):  
Genomic Data ◽  
Functional Genomic ◽  
Functional Genomic Data

scholarly journals ?Cradle?to?grave? regulation of mRNA fate

2007 ◽  
Vol 28 (2) ◽  
pp. 85
Author(s):  
Traude H Beilharz ◽  
Thomas Preiss
Keyword(s):  
Transcription Factors ◽  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Data Sets ◽  
Genome Wide ◽  
Cellular Localisation ◽  
Gene Modules ◽  
Microarray Studies ◽  
Mrna Fate

Microarray studies in Saccharomyces cerevisiae have set the benchmark for genome-wide analyses, available data-sets covering practically every stage of gene expression from DNA-binding by transcription factors to mRNA export, sub-cellular localisation, translation and decay. A theme to emerge from such data has been the prevalence of coordinate gene regulation. Thus, gene modules or ?regulons? are well recognised at the level of gene transcription and the activity of transcription factors provides an obvious molecular explanation for such coordination. More surprising was the organisation of mRNAs into co-regulated ?post-transcriptional operons?. RNA-binding proteins (RBPs), but also ribonucleoprotein (RNP) complexes involving noncoding RNA, have been proposed as the conceptual equivalent of transcription factors at this level.

scholarly journals Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data for Chinese Glioma Patients

2020 ◽  
Author(s):  
Zheng Zhao ◽  
Ke’nan Zhang ◽  
Qiangwei Wang ◽  
Guanzhang Li ◽  
Fan Zeng ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Survival Data ◽  
Messenger Rna ◽  
Genomic Data ◽  
Biological Research ◽  
Analysis Tool ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Who Grade ◽  
Genome Atlas

AbstractGliomas are the most common and malignant intracranial tumours in adults. Recent studies have shown that functional genomics greatly aids in the understanding of the pathophysiology and therapy of glioma. However, comprehensive genomic data and analysis platforms are relatively limited. In this study, we developed the Chinese Glioma Genome Atlas (CGGA, http://www.cgga.org.cn), a user-friendly data portal for storage and interactive exploration of multi-dimensional functional genomic data that includes nearly 2,000 primary and recurrent glioma samples from Chinese cohorts. CGGA currently provides access to whole-exome sequencing (286 samples), messenger RNA sequencing (1,018 samples) and microarray (301 samples), DNA methylation microarray (159 samples), and microRNA microarray (198 samples) data, as well as detailed clinical data (e.g., WHO grade, histological type, critical molecular genetic information, age, sex, chemoradiotherapy status and survival data). In addition, we developed an analysis tool to allow users to browse mutational, mRNA/microRNA expression, and DNA methylation profiles and perform survival and correlation analyses of specific glioma subtypes. CGGA greatly reduces the barriers between complex functional genomic data and glioma researchers who seek rapid, intuitive, and high-quality access to data resources and enables researchers to use these immeasurable data sources for biological research and clinical application. Importantly, the free provision of data will allow researchers to quickly generate and provide data to the research community.

scholarly journals Structure and functional implications of WYL-domain-containing transcription factor PafBC involved in the mycobacterial DNA damage response

2019 ◽  
Author(s):  
Andreas U. Müller ◽  
Marc Leibundgut ◽  
Nenad Ban ◽  
Eilika Weber-Ban
Keyword(s):  
Dna Damage ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Structural Information ◽  
Rna Molecules ◽  
Bacterial Transcription ◽  
Arthrobacter Aurescens

AbstractIn mycobacteria, transcriptional activator PafBC is responsible for upregulating the majority of genes induced by DNA damage. Understanding the mechanism of PafBC activation is impeded by a lack of structural information on this transcription factor that contains a widespread, but poorly understood WYL domain frequently encountered in bacterial transcription factors. Here, we determined the crystal structure ofArthrobacter aurescensPafBC. The protein consists of two modules, each harboring an N-terminal helix-turn-helix DNA binding domain followed by a central WYL and a C-terminal extension (WCX) domain. The WYL domains exhibit Sm-folds, while the WCX domains adopt ferredoxin-like folds, both characteristic for RNA binding proteins. Our results suggest a mechanism of regulation in which WYL domain-containing transcription factors may be activated by binding RNA molecules. Using anin vivomutational screen inMycobacterium smegmatis, we identify potential co-activator binding sites on PafBC.

scholarly journals Pairwise comparisons across species are problematic when analyzing functional genomic data

2017 ◽  
Author(s):  
Casey W. Dunn ◽  
Felipe Zapata ◽  
Catriona Munro ◽  
Stefan Siebert ◽  
Andreas Hejnol
Keyword(s):  
Gene Expression ◽  
Evolutionary Process ◽  
Opportunity To Learn ◽  
Genomic Data ◽  
The Other ◽  
Evolutionary Relationships ◽  
Pairwise Comparisons ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Comparative Functional Genomics

AbstractThere is considerable interest in comparing functional genomic data across species. One goal of such work is to provide an integrated understanding of genome and phenotype evolution. Most comparative functional genomic studies have relied on multiple pairwise comparisons between species, an approach that does not incorporate information about the evolutionary relationships among species. The statistical problems that arise from not considering these relationships can lead pairwise approaches to the wrong conclusions, and are a missed opportunity to learn about biology that can only be understood in an explicit phylogenetic context. Here we examine two recently published studies that compare gene expression across species with pairwise methods, and find reason to question the original conclusions of both. One study interpreted pairwise comparisons of gene expression as support for the ortholog conjecture, the hypothesis that orthologs tend to be more similar than paralogs. The other study interpreted pairwise comparisons of embryonic gene expression across distantly related animals as evidence for a distinct evolutionary process that gave rise to phyla. In each study, distinct patterns of pairwise similarity among species were originally interpreted as evidence of particular evolutionary processes, but instead we find they reflect species relationships. These reanalyses concretely demonstrate the inadequacy of pairwise comparisons for analyzing functional genomic data across species. It will be critical to adopt phylogenetic comparative methods in future functional genomic work. Fortunately, phylogenetic comparative biology is also a rapidly advancing field with many methods that can be directly applied to functional genomic data.SignificanceComparisons of genome function between species are providing important insight into the evolutionary origins of diversity. Here we demonstrate that comparative functional genomics studies can come to the wrong conclusions if they do not take the relationships of species into account and instead rely on pairwise comparisons between species, as is common practice. We re-examined two previously published studies and found problems with pairwise comparisons that draw both their original conclusions into question. One study had found support for the ortholog conjecture and the other had concluded that the evolution of gene expression was different between animal phyla than within them. Our results demonstrate that to answer evolutionary questions about genome function, it is critical to consider evolutionary relationships.

scholarly journals Continuous-trait probabilistic model for comparing multi-species functional genomic data

2018 ◽  
Author(s):  
Yang Yang ◽  
Quanquan Gu ◽  
Yang Zhang ◽  
Takayo Sasaki ◽  
Julianna Crivello ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Molecular Mechanisms ◽  
Probabilistic Models ◽  
Phenotypic Diversity ◽  
Genomic Data ◽  
Primate Species ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Continuous Trait ◽  
A Genome

SummaryA large amount of multi-species functional genomic data from high-throughput assays are becoming available to help understand the molecular mechanisms for phenotypic diversity across species. However, continuous-trait probabilistic models, which are key to such comparative analysis, remain underexplored. Here we develop a new model, called phylogenetic hidden Markov Gaussian processes (Phylo-HMGP), to simultaneously infer heterogeneous evolutionary states of functional genomic features in a genome-wide manner. Both simulation studies and real data application demonstrate the effectiveness of Phylo-HMGP. Importantly, we applied Phylo-HMGP to analyze a new cross-species DNA replication timing (RT) dataset from the same cell type in five primate species (human, chimpanzee, orangutan, gibbon, and green monkey). We demonstrate that our Phylo-HMGP model enables discovery of genomic regions with distinct evolutionary patterns of RT. Our method provides a generic framework for comparative analysis of multi-species continuous functional genomic signals to help reveal regions with conserved or lineage-specific regulatory roles.

scholarly journals Continuous-Trait Probabilistic Model for Comparing Multi-species Functional Genomic Data

Cell Systems ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 208-218.e11 ◽  
Author(s):  
Yang Yang ◽  
Quanquan Gu ◽  
Yang Zhang ◽  
Takayo Sasaki ◽  
Julianna Crivello ◽  
...  
Keyword(s):  
Probabilistic Model ◽  
Genomic Data ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Continuous Trait

scholarly journals Pairwise comparisons across species are problematic when analyzing functional genomic data

2018 ◽  
Vol 115 (3) ◽  
pp. E409-E417 ◽  
Author(s):  
Casey W. Dunn ◽  
Felipe Zapata ◽  
Catriona Munro ◽  
Stefan Siebert ◽  
Andreas Hejnol
Keyword(s):  
Gene Expression ◽  
Evolutionary Process ◽  
Opportunity To Learn ◽  
Genomic Data ◽  
Pairwise Comparisons ◽  
Functional Genomic ◽  
Functional Genomic Data ◽  
Genomic Studies ◽  
Compare Gene Expression ◽  
Missed Opportunity

There is considerable interest in comparing functional genomic data across species. One goal of such work is to provide an integrated understanding of genome and phenotype evolution. Most comparative functional genomic studies have relied on multiple pairwise comparisons between species, an approach that does not incorporate information about the evolutionary relationships among species. The statistical problems that arise from not considering these relationships can lead pairwise approaches to the wrong conclusions and are a missed opportunity to learn about biology that can only be understood in an explicit phylogenetic context. Here, we examine two recently published studies that compare gene expression across species with pairwise methods, and find reason to question the original conclusions of both. One study interpreted pairwise comparisons of gene expression as support for the ortholog conjecture, the hypothesis that orthologs tend to have more similar attributes (expression in this case) than paralogs. The other study interpreted pairwise comparisons of embryonic gene expression across distantly related animals as evidence for a distinct evolutionary process that gave rise to phyla. In each study, distinct patterns of pairwise similarity among species were originally interpreted as evidence of particular evolutionary processes, but instead, we find that they reflect species relationships. These reanalyses concretely show the inadequacy of pairwise comparisons for analyzing functional genomic data across species. It will be critical to adopt phylogenetic comparative methods in future functional genomic work. Fortunately, phylogenetic comparative biology is also a rapidly advancing field with many methods that can be directly applied to functional genomic data.

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