scholarly journals Identification and characterization of moonlighting long non-coding RNAs based on RNA and protein interactome

2018 ◽  
Author(s):  
Lixin Cheng ◽  
Kwong-Sak Leung
Keyword(s):  
Protein Interactions ◽  
Cellular Localization ◽  
A Priori ◽  
Specific Sequence ◽  
Nuclear Compartment ◽  
Protein Interactome ◽  
Moonlighting Proteins ◽  
Non Coding Rnas ◽  
Identification And Characterization

AbstractMoonlighting proteins are a class of proteins having multiple distinct functions, which play essential roles in a variety of cellular and enzymatic functioning systems. Although there have long been calls for computational algorithms for the identification of moonlighting proteins, research on approaches to identify moonlighting long non-coding RNAs (lncRNAs) has never been undertaken. Here, we introduce a methodology, MoonFinder, for the identification of moonlighting lncRNAs. MoonFinder is a statistical algorithm identifying moonlighting lncRNAs without a priori knowledge through the integration of protein interactome, RNA-protein interactions, and functional annotation of proteins. We identify 155 moonlighting lncRNA candidates and uncover that they are a distinct class of lncRNAs characterized by specific sequence and cellular localization features. The non-coding genes that transcript moonlighting lncRNAs tend to have shorter but more exons and the moonlighting lncRNAs have a localization tendency of residing in the cytoplasmic compartment in comparison with the nuclear compartment. Moreover, moonlighting lncRNAs and moonlighting proteins are rather mutually exclusive in terms of both their direct interactions and interacting partners. Our results also shed light on how the moonlighting candidates and their interacting proteins implicated in the formation and development of cancers and other diseases.

scholarly journals Identification and characterization of long non-coding RNAs involved in embryo development of Ginkgo biloba

2019 ◽  
Vol 14 (12) ◽  
pp. 1674606 ◽  
Author(s):  
Huiru Jiang ◽  
Zhichao Jia ◽  
Sian Liu ◽  
Beibei Zhao ◽  
Weixing Li ◽  
...  
Keyword(s):  
Embryo Development ◽  
Ginkgo Biloba ◽  
Non Coding Rnas ◽  
Identification And Characterization

Identification and characterization of protein interactions using the yeast 2-hybrid system

1998 ◽  
pp. 95-124 ◽  
Author(s):  
Susanne E. Kohalmi ◽  
Laura J. V. Reader ◽  
Alon Samach ◽  
Jacek Nowak ◽  
George W. Haughn ◽  
...  
Keyword(s):  
Hybrid System ◽  
Protein Interactions ◽  
Identification And Characterization

scholarly journals Genome-Wide Identification and Characterization of Long Non-Coding RNAs in Peanut

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 536 ◽  
Author(s):  
Xiaobo Zhao ◽  
Liming Gan ◽  
Caixia Yan ◽  
Chunjuan Li ◽  
Quanxi Sun ◽  
...  
Keyword(s):  
Large Scale ◽  
Target Genes ◽  
Sequencing Data ◽  
Regulatory Processes ◽  
Genome Wide ◽  
Non Coding Rnas ◽  
Identification And Characterization ◽  
Lower Expression ◽  
Weighted Correlation

Long non-coding RNAs (lncRNAs) are involved in various regulatory processes although they do not encode protein. Presently, there is little information regarding the identification of lncRNAs in peanut (Arachis hypogaea Linn.). In this study, 50,873 lncRNAs of peanut were identified from large-scale published RNA sequencing data that belonged to 124 samples involving 15 different tissues. The average lengths of lncRNA and mRNA were 4335 bp and 954 bp, respectively. Compared to the mRNAs, the lncRNAs were shorter, with fewer exons and lower expression levels. The 4713 co-expression lncRNAs (expressed in all samples) were used to construct co-expression networks by using the weighted correlation network analysis (WGCNA). LncRNAs correlating with the growth and development of different peanut tissues were obtained, and target genes for 386 hub lncRNAs of all lncRNAs co-expressions were predicted. Taken together, these findings can provide a comprehensive identification of lncRNAs in peanut.

scholarly journals Computational Identification and Characterization of Putative miRNAs in Nasonia Species

2010 ◽  
Vol 2 ◽  
pp. IJIS.S4197
Author(s):  
Ganesh Sathyamurthy ◽  
N. Ramachandra Swamy
Keyword(s):  
Statistical Characteristics ◽  
Folding Energy ◽  
Sequential Method ◽  
Mirna Genes ◽  
Non Coding Rnas ◽  
Post Transcriptional Regulation ◽  
Near Future ◽  
Identification And Characterization ◽  
Cross Species Comparison

MicroRNAs are important at post transcriptional regulation in eukaryotes. Nasonia genus is becoming increasingly popular model in present days due to genetic advantages it possesses over Drosophila. Nasonia species are found distributed throughout the world, expect for N. longicornis, and N. giraulti. In this study, we use the sequential method of blasting all known invertebrate miRNA genes against the Nasonia vitripennis, Nasonia longicornis, and Nasonia giraulti genomes. We identify 40, 31 and 29 putative pre-miRNAs and mature sequences in N. vitripennis, N. giraulti and N. longicornis respectively. A cross species comparison of putative miRNA sequences and their statistical characteristics reveals that there are no huge differences between the species, except for few miRNAs which are reported. We also find that the minimal folding energy index for three Nasonia species pre-miRNA's average is around -0.85 ± 0.11. Further, we report that U is predominant at the 5‘ end of mature sequence, which being a typical characteristic of plant miRNAs. Using MiRanda, we predict nearly 471 potential sites in the N. vitripennis genome. Thus concluding our study to be the beginning of understanding the Nasonia's non coding RNAs and may play an important role in effective pest management in near future.

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