scholarly journals Embryonic circular RNAs at tandem duplicated genes in zebrafish present new paradigm in gene expression

2017 ◽  
Author(s):  
Vanessa Chong-Morrison ◽  
Tatjana Sauka-Spengler
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Long Range ◽  
Closed Loop ◽  
Cell Types ◽  
Circular Rnas ◽  
Loop Structure ◽  
Duplicated Genes ◽  
New Paradigm ◽  
Mrna Transcripts

AbstractCircular RNAs are a puzzling class of RNAs with covalently closed loop structure, lacking 5’ and 3’ ends. Present in all cells, no unifying theme has emerged regarding their function. Here, we use transcriptional data obtained by biotagging in zebrafish to uncover a high-resolution cohort of embryonic circRNAs expressed in nuclear and polysomal subcellular compartments in three developmental cell types. The ample presence of embryonic circRNAs on polysomes contradicts previous reports suggesting predominant nuclear localisation. We uncover a novel class of circRNAs, significantly enriched at tandem duplicated genes. Using newly-developed NGS-based approach, we simultaneously resolve the full sequence of putative "tandem-circRNAs" and their underlying mRNAs. These form by long-range cis-splicing events often between distant tandem duplicated genes, resulting in chimaeric mRNA transcripts and circRNAs containing their supernumerary excised exons, integrated from multiple tandem loci. Taken together, our results suggest that circularisation events rather than circRNAs themselves are functionally important.

scholarly journals Circular RNAs in Cardiovascular Disease: An Overview

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Ximin Fan ◽  
Xinyu Weng ◽  
Yifan Zhao ◽  
Wei Chen ◽  
Tianyi Gan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Noncoding Rna ◽  
Essential Role ◽  
Closed Loop ◽  
Regulation Of Gene Expression ◽  
Circular Rna ◽  
Circular Rnas ◽  
Mirna Sponges

Circular RNA (circRNA), a novel type of endogenous noncoding RNA (ncRNA), has become a research hotspot in recent years. CircRNAs are abundant and stably exist in creatures, and they are found with covalently closed loop structures in which they are quite different from linear RNAs. Nowadays, an increasing number of scientists have demonstrated that circRNAs may have played an essential role in the regulation of gene expression, especially acting as miRNA sponges, and have described the potential mechanisms of several circRNAs in diseases, hinting at their clinical therapeutic values. In this review, the authors summarized the current understandings of the biogenesis and properties of circRNAs and their functions and role as biomarkers in cardiovascular diseases.

scholarly journals Determinants of transcription factor regulatory range

2019 ◽  
Author(s):  
Chen-Hao Chen ◽  
Rongbin Zheng ◽  
Jingyu Fan ◽  
Myles Brown ◽  
Jun S. Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Chromatin State ◽  
Specific Cell ◽  
Regulatory Influence ◽  
State Dependent ◽  
Functional Classes

AbstractTo characterize the genomic distances over which transcription factors (TFs) influence gene expression, we examined thousands of TF and histone modification ChIP-seq datasets and thousands of gene expression profiles. A model integrating these data revealed two classes of TF: one with short-range regulatory influence, the other with long-range regulatory influence. The two TF classes also had distinct chromatin-binding preferences and auto-regulatory properties. The regulatory range of a single TF bound within different topologically associating domains (TADs) depended on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin state in specific cell types. Our results provide evidence that most TFs belong to one of these two functional classes, and that the regulatory range of long-range TFs is chromatin-state dependent. Thus, consideration of TF type, distance-to-target, and chromatin context is likely important in identifying TF regulatory targets and interpreting GWAS and eQTL SNPs.

Bmp-4 acts as a morphogen in dorsoventral mesoderm patterning in Xenopus

Development ◽  
1997 ◽  
Vol 124 (12) ◽  
pp. 2325-2334 ◽  
Author(s):  
R. Dosch ◽  
V. Gawantka ◽  
H. Delius ◽  
C. Blumenstock ◽  
C. Niehrs
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Marginal Zone ◽  
Cell Types ◽  
Dorsoventral Patterning ◽  
Mesodermal Cell ◽  
Amphibian Embryos ◽  
Mesoderm Patterning ◽  
Early Gastrula ◽  
Different Doses

The marginal zone is a ring of tissue that gives rise to a characteristic dorsoventral pattern of mesoderm in amphibian embryos. Bmp-4 is thought to play an important role in specifying ventral mesodermal fate. Here we show (1) that different doses of Bmp-4 are sufficient to pattern four distinct mesodermal cell types and to pattern gene expression in the early gastrula marginal zone into three domains, (2) that there is a graded requirement for a Bmp signal in mesodermal patterning, and (3) that Bmp-4 has long-range activity which can become graded in the marginal zone by the antagonizing action of noggin. The results argue that Bmp-4 acts as a morphogen in dorsoventral patterning of mesoderm.

scholarly journals Graph-based data integration predicts long-range regulatory interactions across the human genome

2014 ◽  
Author(s):  
Sofie Demeyer ◽  
Tom Michoel
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Regulation Of Gene Expression ◽  
Cell Types ◽  
Exon Array ◽  
Regulatory Elements ◽  
Computational Method ◽  
Open Chromatin ◽  
Transcription Start Sites ◽  
Distal Regulatory Elements

Transcriptional regulation of gene expression is one of the main processes that affect cell diversification from a single set of genes. Regulatory proteins often interact with DNA regions located distally from the transcription start sites (TSS) of the genes. We developed a computational method that combines open chromatin and gene expression information for a large number of cell types to identify these distal regulatory elements. Our method builds correlation graphs for publicly available DNase-seq and exon array datasets with matching samples and uses graph-based methods to filter findings supported by multiple datasets and remove indirect interactions. The resulting set of interactions was validated with both anecdotal information of known long-range interactions and unbiased experimental data deduced from Hi-C and CAGE experiments. Our results provide a novel set of high-confidence candidate open chromatin regions involved in gene regulation, often located several Mb away from the TSS of their target gene.

scholarly journals Effects of Circular RNA of Chicken Growth Hormone Receptor Gene on Cell Proliferation

2021 ◽  
Vol 12 ◽  
Author(s):  
Haidong Xu ◽  
Qiying Leng ◽  
Jiahui Zheng ◽  
Patricia Adu-Asiamah ◽  
Shudai Lin ◽  
...  
Keyword(s):  
Cell Proliferation ◽  
Growth Hormone Receptor ◽  
Closed Loop ◽  
Receptor Gene ◽  
Circular Rna ◽  
Circular Rnas ◽  
Loop Structure ◽  
Promote Cell Proliferation ◽  
Growth Hormone Receptor Gene ◽  
Animal Growth

Animal growth and development are regulated by neural and endocrine growth axes, in which cell proliferation plays key roles. Recently, many research showed that circular RNAs were involved in hepatocyte and myoblast proliferation. Previously, we identified a circular RNA derived from the chicken GHR gene, named circGHR. However, the function of circGHR is unclear. The objective of this study was to investigate circGHR expression pattern and its roles in cell proliferation. Results indicated that circGHR was a closed-loop structure molecule, and it was richer in the nucleus of hepatocytes and myoblast. Real-time PCR showed that circGHR was increased from E13 to the 7th week in the liver but decreased in the thigh and breast muscle. The CCK-8 assay displayed that circGHR promoted cell proliferation. Simultaneously, the biomarker genes PCNA, CCND1, and CDK2 and the linear transcripts GHR and GHBP were upregulated when circGHR was overexpressed. Altogether, these data exhibited that circGHR could promote cell proliferation possibly by regulating GHR mRNA and GHBP expression.

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 Molecular, spatial and projection diversity of neurons in primary motor cortex revealed by in situ single-cell transcriptomics

2020 ◽  
Author(s):  
Meng Zhang ◽  
Stephen W. Eichhorn ◽  
Brian Zingg ◽  
Zizhen Yao ◽  
Hongkui Zeng ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Expression Profiles ◽  
Neuronal Cell ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
Different Cell Types

AbstractA mammalian brain is comprised of numerous cell types organized in an intricate manner to form functional neural circuits. Single-cell RNA sequencing provides a powerful approach to identify cell types based on their gene expression profiles and has revealed many distinct cell populations in the brain1-3. Single-cell epigenomic profiling4,5 further provides information on gene-regulatory signatures of different cell types. Understanding how different cell types contribute to brain function, however, requires knowledge of their spatial organization and connectivity, which is not preserved in sequencing-based methods that involve cell dissociation3,6. Here, we used an in situ single-cell transcriptome-imaging method, multiplexed error-robust fluorescence in situ hybridization (MERFISH)7, to generate a molecularly defined and spatially resolved cell atlas of the mouse primary motor cortex (MOp). We profiled ∼300,000 cells in the MOp, identified 95 neuronal and non-neuronal cell clusters, and revealed a complex spatial map in which not only excitatory neuronal clusters but also most inhibitory neuronal clusters adopted layered organizations. Notably, intratelencephalic (IT) cells, the largest branch of neurons in the MOp, formed a continuous spectrum of cells with gradual changes in both gene expression profiles and cortical depth positions in a highly correlated manner. Furthermore, we integrated MERFISH with retrograde tracing to probe the projection targets for different MOp neuronal cell types and found that projections of MOp neurons to other cortical regions formed a many-to-many network with each target region receiving input preferentially from a different composition of IT clusters. Overall, our results provide a high-resolution spatial and projection map of molecularly defined cell types in the MOp. We anticipate that the imaging platform described here can be broadly applied to create high-resolution cell atlases of a wide range of systems.

scholarly journals Effective gene expression prediction from sequence by integrating long-range interactions

2021 ◽  
Vol 18 (10) ◽  
pp. 1196-1203 ◽  
Author(s):  
Žiga Avsec ◽  
Vikram Agarwal ◽  
Daniel Visentin ◽  
Joseph R. Ledsam ◽  
Agnieszka Grabska-Barwinska ◽  
...  
Keyword(s):  
Gene Expression ◽  
Long Range ◽  
Dna Sequences ◽  
Human Genetics ◽  
Cell Types ◽  
Saturation Mutagenesis ◽  
Noncoding Dna ◽  
Long Range Interactions ◽  
Disease Associations ◽  
Reporter Assays

AbstractHow noncoding DNA determines gene expression in different cell types is a major unsolved problem, and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction accuracy from DNA sequences through the use of a deep learning architecture, called Enformer, that is able to integrate information from long-range interactions (up to 100 kb away) in the genome. This improvement yielded more accurate variant effect predictions on gene expression for both natural genetic variants and saturation mutagenesis measured by massively parallel reporter assays. Furthermore, Enformer learned to predict enhancer–promoter interactions directly from the DNA sequence competitively with methods that take direct experimental data as input. We expect that these advances will enable more effective fine-mapping of human disease associations and provide a framework to interpret cis-regulatory evolution.

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