scholarly journals Long-Range Interactions in Riboswitch Control of Gene Expression

2017 ◽  
Vol 46 (1) ◽  
pp. 455-481 ◽  
Author(s):  
Christopher P. Jones ◽  
Adrian R. Ferré-D'Amaré
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Control Of Gene Expression ◽  
Long Range Interactions

scholarly journals The Role of RNA Polymerase II Contiguity and Long-Range Interactions in the Regulation of Gene Expression in Human Pluripotent Stem Cells

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Livia Eiselleova ◽  
Viktor Lukjanov ◽  
Simon Farkas ◽  
David Svoboda ◽  
Karel Stepka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Long Range ◽  
Pluripotent Stem Cells ◽  
Human Pluripotent Stem Cells ◽  
Transcription Factories ◽  
Long Range Interactions ◽  
Rnap Ii

The eukaryotic nucleus is a highly complex structure that carries out multiple functions primarily needed for gene expression, and among them, transcription seems to be the most fundamental. Diverse approaches have demonstrated that transcription takes place at discrete sites known as transcription factories, wherein RNA polymerase II (RNAP II) is attached to the factory and immobilized while transcribing DNA. It has been proposed that transcription factories promote chromatin loop formation, creating long-range interactions in which relatively distant genes can be transcribed simultaneously. In this study, we examined long-range interactions between the POU5F1 gene and genes previously identified as being POU5F1 enhancer-interacting, namely, CDYL, TLE2, RARG, and MSX1 (all involved in transcriptional regulation), in human pluripotent stem cells (hPSCs) and their early differentiated counterparts. As a control gene, RUNX1 was used, which is expressed during hematopoietic differentiation and not associated with pluripotency. To reveal how these long-range interactions between POU5F1 and the selected genes change with the onset of differentiation and upon RNAP II inhibition, we performed three-dimensional fluorescence in situ hybridization (3D-FISH) followed by computational simulation analysis. Our analysis showed that the numbers of long-range interactions between specific genes decrease during differentiation, suggesting that the transcription of monitored genes is associated with pluripotency. In addition, we showed that upon inhibition of RNAP II, long-range associations do not disintegrate and remain constant. We also analyzed the distance distributions of these genes in the context of their positions in the nucleus and revealed that they tend to have similar patterns resembling normal distribution. Furthermore, we compared data created in vitro and in silico to assess the biological relevance of our results.

scholarly journals Integrating long-range regulatory interactions to predict gene expression using graph convolutional neural networks

2020 ◽  
Author(s):  
Jeremy Bigness ◽  
Xavi Loinaz ◽  
Shalin Patel ◽  
Erica Larschan ◽  
Ritambhara Singh
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Histone Modifications ◽  
3D Structure ◽  
Myelogenous Leukemia ◽  
Graph Representation ◽  
Regulatory Factors ◽  
Long Range Interactions ◽  
Genomic Regions ◽  
Predict Gene Expression

Long-range spatial interactions among genomic regions are critical for regulating gene expression and their disruption has been associated with a host of diseases. However, when modeling the effects of regulatory factors on gene expression, most deep learning models either neglect long-range interactions or fail to capture the inherent 3D structure of the underlying biological system. This prevents the field from obtaining a more comprehensive understanding of gene regulation and from fully leveraging the structural information present in the data sets. Here, we propose a graph convolutional neural network (GCNN) framework to integrate measurements probing spatial genomic organization and measurements of local regulatory factors, specifically histone modifications, to predict gene expression. This formulation enables the model to incorporate crucial information about long-range interactions via a natural encoding of spatial interaction relationships into a graph representation. Furthermore, we show that our model is interpretable in terms of the observed biological regulatory factors, highlighting both the histone modifications and the interacting genomic regions that contribute to a gene's predicted expression. We apply our GCNN model to datasets for GM12878 (lymphoblastoid) and K562 (myelogenous leukemia) cell lines and demonstrate its state-of-the-art prediction performance. We also obtain importance scores corresponding to the histone mark features and interacting regions for some exemplar genes and validate them with evidence from the literature. Our model presents a novel setup for predicting gene expression by integrating multimodal datasets.

scholarly journals Chiari I malformation in a Waardenburg phenotype with multiple malformations and 1q21.1 microdeletion

2021 ◽  
Vol 93 (2) ◽  
Author(s):  
Agostino Berio ◽  
Gian Luigi Mariottini ◽  
Marco Frascio ◽  
Enrico Calcagno ◽  
Giacomo Garlaschi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Crest ◽  
Long Range ◽  
Boundary Region ◽  
Chiari I Malformation ◽  
Posterior Cranial Fossa ◽  
Control Of Gene Expression ◽  
Contiguous Gene ◽  
Chiari I ◽  
Cranial Fossa

The authors report on a patient with Chiari I malformation associated to Waardenburg phenotype, multiple malformations, osteochondrodysplasia and microdeletion of 1q21,1 chromosome, of which they underline the rarity. The pathogenesis connected to the features of neural crest cells-derived structures with mesodermal-derived tissues, mainly in the facial and boundary region of malformed posterior cranial fossa, is discussed. The authors hypothesize that chromosomal microdeletion, acting directly or on contiguous gene(s) or by long range control of gene expression, have modified the function of some developmental genes, causing consequently the association of symptoms observed in the patient.

scholarly journals Predicting CTCF-mediated chromatin interactions by integrating genomic and epigenomic features

2017 ◽  
Author(s):  
Yan Kai ◽  
Jaclyn Andricovich ◽  
Zhouhao Zeng ◽  
Jun Zhu ◽  
Alexandros Tzatsos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Zinc Finger Protein ◽  
Cell Types ◽  
Learning Framework ◽  
Chromatin Interactions ◽  
Long Range Interactions ◽  
Extensive Cell ◽  
Cell Type Specific ◽  
And Function

AbstractThe CCCTC-binding zinc finger protein (CTCF)-mediated network of long-range chromatin interactions is important for genome organization and function. Although this network has been considered largely invariant, we found that it exhibits extensive cell-type-specific interactions that contribute to cell identity. Here we present Lollipop—a machine-learning framework—which predicts CTCF-mediated long-range interactions using genomic and epigenomic features. Using ChIA-PET data as benchmark, we demonstrated that Lollipop accurately predicts CTCF-mediated chromatin interactions both within and across cell-types, and outperforms other methods based only on CTCF motif orientation. Predictions were confirmed computationally and experimentally by Chromatin Conformation Capture (3C). Moreover, our approach reveals novel determinants of CTCF-mediated chromatin wiring, such as gene expression within the loops. Our study contributes to a better understanding about the underlying principles of CTCF-mediated chromatin interactions and their impact on gene expression.

scholarly journals Long-range control of gene expression via RNA-directed DNA methylation

PLoS Genetics ◽  
2017 ◽  
Vol 13 (5) ◽  
pp. e1006749 ◽  
Author(s):  
M. Jordan Rowley ◽  
M. Hafiz Rothi ◽  
Gudrun Böhmdorfer ◽  
Jan Kuciński ◽  
Andrzej T. Wierzbicki
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Long Range ◽  
Control Of Gene Expression
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