The evolutionary acquisition and mode of functions of promoter-associated non-coding RNAs (pancRNAs) for mammalian development

2021 ◽  
Author(s):  
Boyang An ◽  
Tomonori Kameda ◽  
Takuya Imamura
Keyword(s):  
Gene Regulation ◽  
Neural Differentiation ◽  
Single Copy ◽  
Research Progress ◽  
Mammalian Development ◽  
Comparative Epigenomics ◽  
Specific Manner ◽  
A Cell ◽  
Non Coding Rnas ◽  
Mammalian Embryonic Development

Abstract Increasing evidence has shown that many long non-coding RNAs (lncRNAs) are involved in gene regulation in a variety of ways such as transcriptional, post-transcriptional and epigenetic regulation. Promoter-associated non-coding RNAs (pancRNAs), which are categorized into the most abundant single-copy lncRNA biotype, play vital regulatory roles in finely tuning cellular specification at the epigenomic level. In short, pancRNAs can directly or indirectly regulate downstream genes to participate in the development of organisms in a cell-specific manner. In this review, we will introduce the evolutionarily acquired characteristics of pancRNAs as determined by comparative epigenomics and elaborate on the research progress on pancRNA-involving processes in mammalian embryonic development, including neural differentiation.

scholarly journals C-reactive protein is expressed in a cell-type specific manner in the murine thymus.

2020 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Inflammatory Responses ◽  
Ectopic Expression ◽  
Cell Type ◽  
Mammalian Development ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Specific Manner ◽  
A Cell ◽  
Cell Type Specific ◽  
Self Antigen

C-reactive protein, or CRP, is an acute phase protein (1, 2) synthesized and released from the liver (3). CRP is transcriptionally induced during systemic inflammatory responses (1, 2). CRP expression in the thymus has previously been reported but in the context of promiscuous gene expression of self-antigen during negative selection (4, 5) or after ectopic expression (6). Here, by comparing the transcriptomes of mTEC and cTEC from the thymuses of mice at 1, 3 and 6 months using a published dataset (7), we found that CRP was among the genes whose expression changed most significantly between cTEC and mTEC at 3 months of murine life. CRP was expressed at significantly higher amounts in mTEC compared to cTEC. Thus, CRP, a molecule typically thought of as expressed by the liver and induced during systemic inflammatory responses, is expressed in a cell-type specific manner during mammalian development in the thymus.

scholarly journals Epigenetic Regulation of Alternative Splicing: How LncRNAs Tailor the Message

2021 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Giuseppina Pisignano ◽  
Michael Ladomery
Keyword(s):  
Alternative Splicing ◽  
Epigenetic Regulation ◽  
Cell Type ◽  
Splice Isoforms ◽  
Cellular Processes ◽  
Specific Manner ◽  
Protein Functions ◽  
Alternatively Spliced ◽  
A Cell ◽  
Non Coding Rnas

Alternative splicing is a highly fine-tuned regulated process and one of the main drivers of proteomic diversity across eukaryotes. The vast majority of human multi-exon genes is alternatively spliced in a cell type- and tissue-specific manner, and defects in alternative splicing can dramatically alter RNA and protein functions and lead to disease. The eukaryotic genome is also intensively transcribed into long and short non-coding RNAs which account for up to 90% of the entire transcriptome. Over the years, lncRNAs have received considerable attention as important players in the regulation of cellular processes including alternative splicing. In this review, we focus on recent discoveries that show how lncRNAs contribute significantly to the regulation of alternative splicing and explore how they are able to shape the expression of a diverse set of splice isoforms through several mechanisms. With the increasing number of lncRNAs being discovered and characterized, the contribution of lncRNAs to the regulation of alternative splicing is likely to grow significantly.

scholarly journals Clues of in vivo nuclear gene regulation by mitochondrial short non-coding RNAs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Marco Passamonti ◽  
Marco Calderone ◽  
Manuel Delpero ◽  
Federico Plazzi
Keyword(s):  
Gene Regulation ◽  
Nuclear Gene ◽  
Non Coding Rnas ◽  
Nuclear Gene Regulation

scholarly journals Advances in the role of miRNAs in the occurrence and development of osteosarcoma

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 1003-1011
Author(s):  
Guanyu Zhang ◽  
Yiran Li ◽  
Jiasheng Xu ◽  
Zhenfang Xiong
Keyword(s):  
Target Gene ◽  
Early Stage ◽  
Research Direction ◽  
Research Progress ◽  
Skeletal System ◽  
Translation Process ◽  
Non Coding Rnas ◽  
New Research ◽  
Post Transcriptional Regulation

AbstractOsteosarcoma (OS) is the most common primary malignant tumor of the skeletal system in the clinic. It mainly occurs in adolescent patients and the pathogenesis of the disease is very complicated. The distant metastasis may occur in the early stage, and the prognosis is poor. MicroRNAs (miRNAs) are non-coding RNAs of about 18–25 nt in length that are involved in post-transcriptional regulation of genes. miRNAs can regulate target gene expression by promoting the degradation of target mRNAs or inhibiting the translation process, thereby the proliferation of OS cells can be inhibited and the apoptosis can be promoted; in this way, miRNAs can affect the metabolism of OS cells and can also participate in the occurrence, invasion, metastasis, and recurrence of OS. Some miRNAs have already been found to be closely related to the prognosis of patients with OS. Unlike other reviews, this review summarizes the miRNA molecules closely related to the development, diagnosis, prognosis, and treatment of OS in recent years. The expression and influence of miRNA molecule on OS were discussed in detail, and the related research progress was summarized to provide a new research direction for early diagnosis and treatment of OS.

scholarly journals Syntaxin 1A Gene Is Negatively Regulated in a Cell/Tissue Specific Manner by YY1 Transcription Factor, Which Binds to the −183 to −137 Promoter Region Together with Gene Silencing Factors Including Histone Deacetylase

Biomolecules ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 146
Author(s):  
Takahiro Nakayama ◽  
Toshiyuki Fukutomi ◽  
Yasuo Terao ◽  
Kimio Akagawa
Keyword(s):  
Transcription Factor ◽  
Gene Silencing ◽  
Protein Complex ◽  
Promoter Region ◽  
Neuronal Cell ◽  
Syntaxin 1A ◽  
Tissue Specific ◽  
Cell Tissue ◽  
Specific Manner ◽  
A Cell

The HPC-1/syntaxin 1A (Stx1a) gene, which is involved in synaptic transmission and neurodevelopmental disorders, is a TATA-less gene with several transcription start sites. It is activated by the binding of Sp1 and acetylated histone H3 to the −204 to +2 core promoter region (CPR) in neuronal cell/tissue. Furthermore, it is depressed by the association of class 1 histone deacetylases (HDACs) to Stx1a–CPR in non-neuronal cell/tissue. To further clarify the factors characterizing Stx1a gene silencing in non-neuronal cell/tissue not expressing Stx1a, we attempted to identify the promoter region forming DNA–protein complex only in non-neuronal cells. Electrophoresis mobility shift assays (EMSA) demonstrated that the −183 to −137 OL2 promoter region forms DNA–protein complex only in non-neuronal fetal rat skin keratinocyte (FRSK) cells which do not express Stx1a. Furthermore, the Yin-Yang 1 (YY1) transcription factor binds to the −183 to −137 promoter region of Stx1a in FRSK cells, as shown by competitive EMSA and supershift assay. Chromatin immunoprecipitation assay revealed that YY1 in vivo associates to Stx1a–CPR in cell/tissue not expressing Stx1a and that trichostatin A treatment in FRSK cells decreases the high-level association of YY1 to Stx1a-CPR in default. Reporter assay indicated that YY1 negatively regulates Stx1a transcription. Finally, mass spectrometry analysis showed that gene silencing factors, including HDAC1, associate onto the −183 to −137 promoter region together with YY1. The current study is the first to report that Stx1a transcription is negatively regulated in a cell/tissue-specific manner by YY1 transcription factor, which binds to the −183 to −137 promoter region together with gene silencing factors, including HDAC.

lncLocator 2.0: a cell-line-specific subcellular localization predictor for long non-coding RNAs with interpretable deep learning

2021 ◽  
Author(s):  
Yang Lin ◽  
Xiaoyong Pan ◽  
Hong-Bin Shen
Keyword(s):  
Subcellular Localization ◽  
Cell Line ◽  
Cell Lines ◽  
Short Term Memory ◽  
Computational Method ◽  
Language Models ◽  
Supplementary Information ◽  
Deep Model ◽  
A Cell ◽  
Non Coding Rnas

Abstract Motivation Long non-coding RNAs (lncRNAs) are generally expressed in a tissue-specific way, and subcellular localizations of lncRNAs depend on the tissues or cell lines that they are expressed. Previous computational methods for predicting subcellular localizations of lncRNAs do not take this characteristic into account, they train a unified machine learning model for pooled lncRNAs from all available cell lines. It is of importance to develop a cell-line-specific computational method to predict lncRNA locations in different cell lines. Results In this study, we present an updated cell-line-specific predictor lncLocator 2.0, which trains an end-to-end deep model per cell line, for predicting lncRNA subcellular localization from sequences.We first construct benchmark datasets of lncRNA subcellular localizations for 15 cell lines. Then we learn word embeddings using natural language models, and these learned embeddings are fed into convolutional neural network, long short-term memory and multilayer perceptron to classify subcellular localizations. lncLocator 2.0 achieves varying effectiveness for different cell lines and demonstrates the necessity of training cell-line-specific models. Furthermore, we adopt Integrated Gradients to explain the proposed model in lncLocator 2.0, and find some potential patterns that determine the subcellular localizations of lncRNAs, suggesting that the subcellular localization of lncRNAs is linked to some specific nucleotides. Availability The lncLocator 2.0 is available at www.csbio.sjtu.edu.cn/bioinf/lncLocator2 and the source code can be found at https://github.com/Yang-J-LIN/lncLocator2. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Rel Induces Interferon Regulatory Factor 4 (IRF-4) Expression in Lymphocytes

2000 ◽  
Vol 191 (8) ◽  
pp. 1281-1292 ◽  
Author(s):  
Raelene J. Grumont ◽  
Steve Gerondakis
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Nuclear Factor Κb ◽  
Wild Type ◽  
Cell Type ◽  
Regulatory Factor ◽  
Specific Manner ◽  
A Cell ◽  
Cell Type Specific ◽  
Interferon Regulatory Factor 4

In lymphocytes, the Rel transcription factor is essential in establishing a pattern of gene expression that promotes cell proliferation, survival, and differentiation. Here we show that mitogen-induced expression of interferon (IFN) regulatory factor 4 (IRF-4), a lymphoid-specific member of the IFN family of transcription factors, is Rel dependent. Consistent with IRF-4 functioning as a repressor of IFN-induced gene expression, the absence of IRF-4 expression in c-rel−/− B cells coincided with a greater sensitivity of these cells to the antiproliferative activity of IFNs. In turn, enforced expression of an IRF-4 transgene restored IFN modulated c-rel−/− B cell proliferation to that of wild-type cells. This cross-regulation between two different signaling pathways represents a novel mechanism that Rel/nuclear factor κB can repress the transcription of IFN-regulated genes in a cell type–specific manner.

scholarly journals Optimal transcriptional regulation of cellular responses to sudden environmental shifts

2020 ◽  
Author(s):  
Daniel Schultz ◽  
Lev S. Tsimring
Keyword(s):  
Gene Expression ◽  
Gene Regulation ◽  
Cell Response ◽  
Cellular Responses ◽  
Natural Systems ◽  
Selective Pressures ◽  
Regulatory Strategies ◽  
Regulatory Strategy ◽  
A Cell ◽  
The Many

ABSTRACTCellular responses to sudden changes in their environment require prompt expression of the correct levels of the appropriate enzymes. These enzymes are typically regulated by transcription factors that sense the presence of inducers and control gene expression for the duration of the response. The specific choice of regulatory strategy depends on the characteristics of each cell response, with the pattern of gene expression dictated by parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about how gene regulation determines the dynamics of cell responses, we still lack a framework to understand how the many different regulatory strategies evolved in natural systems relate to the constraints imposed by the selective pressures acting in each particular case. Here, we analyze a dynamical model of a cell response where expression of a transcriptionally repressed enzyme is induced by a sudden exposure to its substrate. We identify strategies of gene regulation that optimize the response for different types of selective pressures, which we define as a set of costs associated with substrate, enzyme and repressor intracellular concentrations during the response. We find that regulated responses happen within a defined region in the parameter space. While responses to costly (toxic) substrates favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly than its substrate favor the usage of constitutively expressed repressors. There is only a very narrow range of selective pressures that would favor weakly self-regulated repressors. This framework can be used to infer which costs and benefits are most critical in the evolution of natural examples of cellular responses, and to predict how a response can optimize its regulation when transported to a new environment with different demands.

scholarly journals Epigenomics of Plant’s Responses to Environmental Stress

2017 ◽  
Author(s):  
Suresh Kumar
Keyword(s):  
Gene Expression ◽  
Nuclear Dna ◽  
Environmental Stresses ◽  
Transcriptional Level ◽  
Epigenetic Changes ◽  
Post Translational Modifications ◽  
Genome Wide ◽  
A Cell ◽  
Non Coding Rnas ◽  
Function Activity

Genome-wide epigenetic changes in plants are being reported during the development and environmental stresses, which are often correlated with gene expression at the transcriptional level. Sum total of the biochemical changes in nuclear DNA, post-translational modifications in histone proteins and variations in the biogenesis of non-coding RNAs in a cell is known as epigenome. These changes are often responsible for variation in expression of the gene without any change in the underlying nucleotide sequence. The changes might also cause variation in chromatin structure resulting into the changes in function/activity of the genome. The epigenomic changes are dynamic with respect to the endogenous and/or environmental stimuli which affect phenotypic plasticity of the organism. Both, the epigenetic changes and variation in gene expression might return to the pre-stress state soon after withdrawal of the stress. However, a part of the epigenetic changes may be retained which is reported to play role in acclimatization, adaptation as well as in the evolutionary processes. Understanding epigenome-engineering for improved stress tolerance in plants has become essential for better utilization of the genetic factors. This review delineates the importance of epigenomics towards possible improvement of plant’s responses to environmental stresses for climate resilient agriculture.

scholarly journals Host Non-Coding RNA Regulates Influenza A Virus Replication

Viruses ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 51
Author(s):  
Yuejiao Liao ◽  
Shouqing Guo ◽  
Geng Liu ◽  
Zhenyu Qiu ◽  
Jiamin Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Influenza A Virus ◽  
Influenza A ◽  
Janus Kinase ◽  
Research Progress ◽  
Receptor Signaling ◽  
Non Coding Rna ◽  
Receptor Signaling Pathway ◽  
Non Coding Rnas ◽  
Virus Interactions

Outbreaks of influenza, caused by the influenza A virus (IAV), occur almost every year in various regions worldwide, seriously endangering human health. Studies have shown that host non-coding RNA is an important regulator of host–virus interactions in the process of IAV infection. In this paper, we comprehensively analyzed the research progress on host non-coding RNAs with regard to the regulation of IAV replication. According to the regulation mode of host non-coding RNAs, the signal pathways involved, and the specific target genes, we found that a large number of host non-coding RNAs directly targeted the PB1 and PB2 proteins of IAV. Nonstructural protein 1 and other key genes regulate the replication of IAV and indirectly participate in the regulation of the retinoic acid-induced gene I-like receptor signaling pathway, toll-like receptor signaling pathway, Janus kinase signal transducer and activator of transcription signaling pathway, and other major intracellular viral response signaling pathways to regulate the replication of IAV. Based on the above findings, we mapped the regulatory network of host non-coding RNAs in the innate immune response to the influenza virus. These findings will provide a more comprehensive understanding of the function and mechanism of host non-coding RNAs in the cellular anti-virus response as well as clues to the mechanism of cell–virus interactions and the discovery of antiviral drug targets.

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