Identify the critical protein‐coding genes and long noncoding RNAs in cardiac myxoma

2019 ◽  
Vol 120 (8) ◽  
pp. 13441-13452 ◽  
Author(s):  
Nan Cheng ◽  
Yuanbin Wu ◽  
Huajun Zhang ◽  
Yi Guo ◽  
Huimin Cui ◽  
...  
Keyword(s):  
Cardiac Myxoma ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Protein Coding ◽  
Protein Coding Genes

scholarly journals When Long Noncoding RNAs Meet Genome Editing in Pluripotent Stem Cells

2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Fuquan Chen ◽  
Jiaojiao Ji ◽  
Jian Shen ◽  
Xinyi Lu
Keyword(s):  
Stem Cells ◽  
Transcriptional Regulation ◽  
Genome Editing ◽  
Pluripotent Stem Cells ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Biological Processes ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
The Past

Most of the human genome can be transcribed into RNAs, but only a minority of these regions produce protein-coding mRNAs whereas the remaining regions are transcribed into noncoding RNAs. Long noncoding RNAs (lncRNAs) were known for their influential regulatory roles in multiple biological processes such as imprinting, dosage compensation, transcriptional regulation, and splicing. The physiological functions of protein-coding genes have been extensively characterized through genome editing in pluripotent stem cells (PSCs) in the past 30 years; however, the study of lncRNAs with genome editing technologies only came into attentions in recent years. Here, we summarize recent advancements in dissecting the roles of lncRNAs with genome editing technologies in PSCs and highlight potential genome editing tools useful for examining the functions of lncRNAs in PSCs.

scholarly journals RNA sequencing analysis of altered expression of long noncoding RNAs associated with Schistosoma japonicum infection in the murine liver and spleen

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Tianqi Xia ◽  
Bikash Ranjan Giri ◽  
Jingyi Liu ◽  
Pengfei Du ◽  
Xue Li ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Schistosoma Japonicum ◽  
Target Genes ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Protein Coding ◽  
Altered Expression ◽  
Protein Coding Genes

Abstract Background Schistosomiasis is a chronic, debilitating infectious disease caused by members of the genus Schistosoma. Previous findings have suggested a relationship between infection with Schistosoma spp. and alterations in the liver and spleen of infected animals. Recent reports have shown the regulatory role of noncoding RNAs, such as long noncoding RNAs (lncRNAs), in different biological processes. However, little is known about the role of lncRNAs in the mouse liver and spleen during Schistosoma japonicum infection. Methods In this study, we identified and investigated lncRNAs using standard RNA sequencing (RNA-Seq). The biological functions of the altered expression of lncRNAs and their target genes were predicted using bioinformatics. Ten dysregulated lncRNAs were selected randomly and validated in reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) experiments. Results Our study identified 29,845 and 33,788 lncRNAs from the liver and spleen, respectively, of which 212 were novel lncRNAs. We observed that 759 and 789 of the lncRNAs were differentially expressed in the respective organs. The RT-qPCR results correlated well with the sequencing data. In the liver, 657 differentially expressed lncRNAs were predicted to target 2548 protein-coding genes, whereas in the spleen 660 differentially expressed lncRNAs were predicted to target 2673 protein-coding genes. Moreover, functional annotation showed that the target genes of the differentially expressed lncRNAs were associated with cellular processes, metabolic processes, and binding, and were significantly enriched in metabolic pathways, the cell cycle, ubiquitin-mediated proteolysis, and pathways in cancer. Conclusions Our study showed that numerous lncRNAs were differentially expressed in S. japonicum-infected liver and spleen compared to control liver and spleen; this suggested that lncRNAs may be involved in pathogenesis in the liver and spleen during S. japonicum infection.

scholarly journals GIC: A computational method for predicting the essentiality of long noncoding lncRNAs

2017 ◽  
Author(s):  
Pan Zeng ◽  
Ji Chen ◽  
Yuan Zhou ◽  
Jichun Yang ◽  
Qinghua Cui
Keyword(s):  
Computational Methods ◽  
High Performance ◽  
Noncoding Rnas ◽  
Web Server ◽  
Long Noncoding Rnas ◽  
Computational Method ◽  
Biological Molecules ◽  
Sequence Information ◽  
Protein Coding ◽  
Protein Coding Genes

ABSTRACTMeasuring the essentiality of genes is critically important in biology and medicine. Some bioinformatic methods have been developed for this issue but none of them can be applied to long noncoding RNAs (lncRNAs), one big class of biological molecules. Here we developed a computational method, GIC (Gene Importance Calculator), which can predict the essentiality of both protein-coding genes and lncRNAs based on RNA sequence information. For identifying the essentiality of protein-coding genes, GIC is competitive with well-established computational scores. More important, GIC showed a high performance for predicting the essentiality of lncRNAs. In an independent mouse lncRNA dataset, GIC achieved an exciting performance (AUC=0.918). In contrast, the traditional computational methods are not applicable to lncRNAs. As a public web server, GIC is freely available at http://www.cuilab.cn/gic/.

scholarly journals Defining Essentiality Score of Protein-Coding Genes and Long Noncoding RNAs

2018 ◽  
Vol 9 ◽  
Author(s):  
Pan Zeng ◽  
Ji Chen ◽  
Yuhong Meng ◽  
Yuan Zhou ◽  
Jichun Yang ◽  
...  
Keyword(s):  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Protein Coding ◽  
Protein Coding Genes

scholarly journals Comparative genomics in the search for conserved long noncoding RNAs

2021 ◽  
Author(s):  
Michał Wojciech Szcześniak ◽  
Magdalena Regina Kubiak ◽  
Elżbieta Wanowska ◽  
Izabela Makałowska
Keyword(s):  
Comparative Genomics ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Model Organisms ◽  
Biological Functions ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Homologous Genes ◽  
Four Levels ◽  
Review Current

Abstract Long noncoding RNAs (lncRNAs) have emerged as prominent regulators of gene expression in eukaryotes. The identification of lncRNA orthologs is essential in efforts to decipher their roles across model organisms, as homologous genes tend to have similar molecular and biological functions. The relatively high sequence plasticity of lncRNA genes compared with protein-coding genes, makes the identification of their orthologs a challenging task. This is why comparative genomics of lncRNAs requires the development of specific and, sometimes, complex approaches. Here, we briefly review current advancements and challenges associated with four levels of lncRNA conservation: genomic sequences, splicing signals, secondary structures and syntenic transcription.

scholarly journals Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Yun Xiao ◽  
Yanling Lv ◽  
Hongying Zhao ◽  
Yonghui Gong ◽  
Jing Hu ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Regulatory Network ◽  
Noncoding Rnas ◽  
Nervous System Development ◽  
Long Noncoding Rnas ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Rna Seq ◽  
Protein Coding ◽  
Protein Coding Genes

Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, our method can provide comparable predicted functions of lncRNAs. Overall, our method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.

Protein-coding genes and long noncoding RNAs are differentially expressed in dasatinib-treated chronic myeloid leukemia patients with resistance to imatinib

Hematology ◽  
2013 ◽  
Vol 19 (1) ◽  
pp. 31-41 ◽  
Author(s):  
Rosana A. Silveira ◽  
Angela A. Fachel ◽  
Yuri B. Moreira ◽  
Carmino A. De Souza ◽  
Fernando F. Costa ◽  
...  
Keyword(s):  
Chronic Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Differentially Expressed ◽  
Protein Coding ◽  
Protein Coding Genes

scholarly journals Identification and Functional Characterization of Novel MYC-Regulated Long Noncoding RNAs in Group 3 Medulloblastoma

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3853
Author(s):  
Jessica Rea ◽  
Annamaria Carissimo ◽  
Daniela Trisciuoglio ◽  
Barbara Illi ◽  
Daniel Picard ◽  
...  
Keyword(s):  
Functional Characterization ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Driver Gene ◽  
Cancer Type ◽  
Protein Coding ◽  
Primary Tumors ◽  
Protein Coding Genes ◽  
Group 3 ◽  
The Impact

The impact of protein-coding genes on cancer onset and progression is a well-established paradigm in molecular oncology. Nevertheless, unveiling the contribution of the noncoding genes—including long noncoding RNAs (lncRNAs)—to tumorigenesis represents a great challenge for personalized medicine, since they (i) constitute the majority of the human genome, (ii) are essential and flexible regulators of gene expression and (iii) present all types of genomic alterations described for protein-coding genes. LncRNAs have been increasingly associated with cancer, their highly tissue- and cancer type-specific expression making them attractive candidates as both biomarkers and therapeutic targets. Medulloblastoma is one of the most common malignant pediatric brain tumors. Group 3 is the most aggressive subgroup, showing the highest rate of metastasis at diagnosis. Transcriptomics and reverse genetics approaches were combined to identify lncRNAs implicated in Group 3 Medulloblastoma biology. Here we present the first collection of lncRNAs dependent on the activity of the MYC oncogene, the major driver gene of Group 3 Medulloblastoma. We assessed the expression profile of selected lncRNAs in Group 3 primary tumors and functionally characterized these species. Overall, our data demonstrate the direct involvement of three lncRNAs in Medulloblastoma cancer cell phenotypes.

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