The indirect antiviral potential of long non-coding RNAs encoded by IFITM pseudogenes

2021 ◽  
Author(s):  
Kazi Rahman ◽  
Alex A. Compton

The interferon-induced transmembrane ( IFITM ) family performs multiple functions in immunity, including inhibition of virus entry into cells. The IFITM repertoire varies widely between species and consists of protein-coding genes and pseudogenes. The selective forces driving pseudogenization within gene families are rarely understood. In this issue, the human pseudogene IFITM4P is characterized as a virus-induced, long non-coding RNA that contributes to restriction of Influenza A virus by regulating mRNA levels of IFITM1 , IFITM2 , and IFITM3 .

2021 ◽  
Author(s):  
David Staněk

Abstract In this review I focus on the role of splicing in long non-coding RNA (lncRNA) life. First, I summarize differences between the splicing efficiency of protein-coding genes and lncRNAs and discuss why non-coding RNAs are spliced less efficiently. In the second half of the review, I speculate why splice sites are the most conserved sequences in lncRNAs and what additional roles could splicing play in lncRNA metabolism. I discuss the hypothesis that the splicing machinery can, besides its dominant role in intron removal and exon joining, protect cells from undesired transcripts.


2019 ◽  
Vol 21 (2) ◽  
pp. 637-648 ◽  
Author(s):  
Aritro Nath ◽  
Paul Geeleher ◽  
R Stephanie Huang

Abstract Long non-coding RNAs (lncRNAs) play an important role in gene regulation and are increasingly being recognized as crucial mediators of disease pathogenesis. However, the vast majority of published transcriptome datasets lack high-quality lncRNA profiles compared to protein-coding genes (PCGs). Here we propose a framework to harnesses the correlative expression patterns between lncRNA and PCGs to impute unknown lncRNA profiles. The lncRNA expression imputation (LEXI) framework enables characterization of lncRNA transcriptome of samples lacking any lncRNA data using only their PCG profiles. We compare various machine learning and missing value imputation algorithms to implement LEXI and demonstrate the feasibility of this approach to impute lncRNA transcriptome of normal and cancer tissues. Additionally, we determine the factors that influence imputation accuracy and provide guidelines for implementing this approach.


2020 ◽  
Vol 6 (3) ◽  
pp. 40
Author(s):  
Paola Briata ◽  
Roberto Gherzi

Although mammals possess roughly the same number of protein-coding genes as worms, it is evident that the non-coding transcriptome content has become far broader and more sophisticated during evolution. Indeed, the vital regulatory importance of both short and long non-coding RNAs (lncRNAs) has been demonstrated during the last two decades. RNA binding proteins (RBPs) represent approximately 7.5% of all proteins and regulate the fate and function of a huge number of transcripts thus contributing to ensure cellular homeostasis. Transcriptomic and proteomic studies revealed that RBP-based complexes often include lncRNAs. This review will describe examples of how lncRNA-RBP networks can virtually control all the post-transcriptional events in the cell.


2020 ◽  
Vol 11 (20) ◽  
pp. 6140-6156
Author(s):  
Xiang-Kun Wang ◽  
Xi-Wen Liao ◽  
Rui Huang ◽  
Jian-Lu Huang ◽  
Zi-Jun Chen ◽  
...  

2017 ◽  
Author(s):  
Hyosun Hong ◽  
Han-Ha Chai ◽  
Kyoungwoo Nam ◽  
Dajeong Lim ◽  
Kyung-Tai Lee ◽  
...  

AbstractThe Yeonsan Ogye (Ogye) is a rare Korean domestic chicken breed, the entire body of which, including its feathers and skin, has a unique black coloring. Although some protein-coding genes related to this unique feature have been examined, non-coding elements have not been globally investigated. In this study, high-throughput RNA sequencing and DNA methylation sequencing were performed to dissect the expression landscape of 14,264 Ogye protein-coding and 6900 long non-coding RNA (lncRNA) genes along with DNA methylation landscape in twenty different Ogye tissues. About 75% of Ogye lncRNAs showed tissue-specific expression whereas about 45% of protein-coding genes did. For some genes, the tissue-specific expression levels were inversely correlated with DNA methylation levels in their promoters. About 39% of the tissue-specific lncRNAs displayed functional association with proximal or distal protein-coding genes. In particular, heat shock transcription factor 2 (HSF2)-associated lncRNAs were discovered to be functionally linked to protein-coding genes that are specifically expressed in black skin tissues, tended to be more syntenically conserved in mammals, and were differentially expressed in black tissues relative to white tissues. Our results not only facilitate understanding how the non-coding genome regulates unique phenotypes but also should be of use for future genomic breeding of chickens.


eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Anna Lozano-Ureña ◽  
Sacri R Ferrón

A long non-coding RNA called lnc-NR2F1 regulates several neuronal genes, including some involved in autism and intellectual disabilities.


2021 ◽  
Vol 12 ◽  
Author(s):  
Erica L. Kleinbrink ◽  
Nardhy Gomez-Lopez ◽  
Donghong Ju ◽  
Bogdan Done ◽  
Anton-Scott Goustin ◽  
...  

In the post-genomic era, our understanding of the molecular regulators of physiologic and pathologic processes in pregnancy is expanding at the whole-genome level. Longitudinal changes in the known protein-coding transcriptome during normal pregnancy, which we recently reported (Gomez-Lopez et al., 2019), have improved our definition of the major operant networks, yet pregnancy-related functions of the non-coding RNA transcriptome remain poorly understood. A key finding of the ENCODE (Encyclopedia of DNA Elements) Consortium, the successor of the Human Genome Project, was that the human genome contains approximately 60,000 genes, the majority of which do not encode proteins. The total transcriptional output of non-protein-coding RNA genes, collectively referred to as the non-coding transcriptome, is comprised mainly of long non-coding RNA (lncRNA) transcripts (Derrien et al., 2012). Although the ncRNA transcriptome eclipses its protein-coding counterpart in abundance, it has until recently lacked a comprehensive, unbiased, genome-scale characterization over the timecourse of normal human pregnancy. Here, we annotated, characterized, and selectively validated the longitudinal changes in the non-coding transcriptome of maternal whole blood during normal pregnancy to term. We identified nine long non-coding RNAs (lncRNAs), including long intergenic non-coding RNAs (lincRNAs) as well as lncRNAs antisense to or otherwise in the immediate vicinity of protein-coding genes, that were differentially expressed with advancing gestation in normal pregnancy: AL355711, BC039551 (expressed mainly in the placenta), JHDM1D-AS1, A2M-AS1, MANEA-AS1, NR_034004, LINC00649, LINC00861, and LINC01094. By cross-referencing our dataset against major public pseudogene catalogs, we also identified six transcribed pseudogenes that were differentially expressed over time during normal pregnancy in maternal blood: UBBP4, FOXO3B, two Makorin (MKRN) pseudogenes (MKRN9P and LOC441455), PSME2P2, and YBX3P1. We also identified three non-coding RNAs belonging to other classes that were modulated during gestation: the microRNA MIR4439, the small nucleolar RNA (snoRNA) SNORD41, and the small Cajal-body specific ncRNA SCARNA2. The expression profiles of most hits were broadly suggestive of functions in pregnancy. These time-dependent changes of the non-coding transcriptome during normal pregnancy, which may confer specific regulatory impacts on their protein-coding gene targets, will facilitate a deeper molecular understanding of pregnancy and lncRNA-mediated molecular pathways at the maternal-fetal interface and of how these pathways impact maternal and fetal health.


Author(s):  
Duc-Hau Le

Since last decade, we have been witnessing the raise of non-coding RNAs (ncRNAs) in biomedical research. Many ncRNAs have been identified and classified into different classes based on their length in number of base pairs (bp). In parallel, our understanding about functions of ncRNAs is gradually increased. However, only small set among tens of thousands of ncRNAs have been well studied about their functions and their roles in development of diseases. This raises a pressing need to develop computational methods to associate diseases and ncRNAs. Two most widely studied ncRNAs are microRNA (miRNA) and long non-coding RNA (lncRNA), since miRNAs are the regulators of most protein-coding genes and lncRNAs are the most ubiquitously found in mammalian. To date, many computational methods have been also proposed for prediction of disease-associated miRNAs and lncRNAs, and recently comprehensively reviewed. However, in the previous reviews, these computational methods were described separately, thus this limits our understanding about their underlying computational aspects. Therefore, in this study, we propose a general computational framework for prediction of disease-associated ncRNAs. The framework demonstrates a whole computational process from data preparation to computational models.


2021 ◽  
Vol 10 ◽  
Author(s):  
Shenqi Han ◽  
Yongqiang Qi ◽  
Yiming Luo ◽  
Xiaoping Chen ◽  
Huifang Liang

Exosomes are small membranous vesicles released by many kinds of cells, and are indispensable in cell-to-cell communication by delivering functional biological components both locally and systemically. Long non-coding RNAs (lncRNAs) are long transcripts over 200 nucleotides that exhibit no or limited protein-coding potentials. LncRNAs are dramatic gene expression regulators, and can be selectively sorted into exosomes. Exosomal lncRNAs derived from cancer cells and stromal cells can mediate the generation of pre-metastatic niches (PMNs) and thus promote the progression of cancer. In this review, we summarized the fundamental biology and characteristics of exosomal lncRNAs. Besides, we provided an overview of current research on functions of exosomal lncRNAs between cancer cells and non-cancer cells. A deep understanding of exosomal lncRNAs’ role in cancer will be facilitated to find important implications for cancer development and treatment.


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