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

Cheng, Lixin; Leung, Kwong‐Sak

doi:10.1093/bioinformatics/bty399

Cited by 32 publications

(30 citation statements)

References 55 publications

(80 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Long non-coding RNAs (lncRNAs) are a type of transcripts with more than 200 nucleotides that have low proteincoding potential, which function in a variety of cellular processes and usually serve as disease diagnostic and prognostic markers [17,18]. Numerous studies have implicated the mutations and dysregulations of lncRNAs contribute to the development of immunity diseases and cancers [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Cheng

Nan

Kang

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Sepsis is a fatal disease referring to the presence of a known or strongly suspected infection coupled with systemic and uncontrolled immune activation causing multiple organ failure. However, current knowledge of the role of lncRNAs in sepsis is still extremely limited. Methods: We performed an in silico investigation of the gene coexpression pattern for the patients response to all-cause sepsis in consecutive intensive care unit (ICU) admissions. Sepsis coexpression gene modules were identified using WGCNA and enrichment analysis. lncRNAs were determined as sepsis biomarkers based on the interactions among lncRNAs and the identified modules. Results: Twenty-three sepsis modules, including both differentially expressed modules and prognostic modules, were identified from the whole blood RNA expression profiling of sepsis patients. Five lncRNAs, FENDRR, MALAT1, TUG1, CRNDE, and ANCR, were detected as sepsis regulators based on the interactions among lncRNAs and the identified coexpression modules. Furthermore, we found that CRNDE and MALAT1 may act as miRNA sponges of sepsis related miRNAs to regulate the expression of sepsis modules. Ultimately, FENDRR, MALAT1, TUG1, and CRNDE were reannotated using three independent lncRNA expression datasets and validated as differentially expressed lncRNAs. Conclusion: The procedure facilitates the identification of prognostic biomarkers and novel therapeutic strategies of sepsis. Our findings highlight the importance of transcriptome modularity and regulatory lncRNAs in the progress of sepsis.

show abstract

Section: Introductionmentioning

confidence: 99%

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Cheng

Nan

Kang

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Since the interactions among lncRNAs and target genes are far from complete, the discovery of sepsis lncRNAs is limited by the interaction coverage [16,17]. An alternative strategy is to produce the genome-wide RNA-seq data including both coding and non-coding genes, then a coding-non-coding network can be constructed and the association among coding and non-coding genes would be well established [45].…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Long non-coding RNAs (lncRNAs) are a type of transcripts with more than 200 nucleotides that have low protein-coding potential, which function in a variety of cellular processes and usually serve as disease diagnostic and prognostic markers [16,17]. Numerous studies have implicated the mutations and dysregulations of lncRNAs contribute to the development of immunity diseases and cancers [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…The resulting modules showed high correspondence with known modules and canonical pathways. Moreover, a computational framework was proposed to predict moonlighting lncRNAs by clustering the protein interaction network to determine modules with independent functions [16].Long non-coding RNAs (lncRNAs) are a type of transcripts with more than 200 nucleotides that have low protein-coding potential, which function in a variety of cellular processes and usually serve as disease diagnostic and prognostic markers [16,17]. Numerous studies have implicated the mutations and dysregulations of lncRNAs contribute to the development of immunity diseases and cancers [18][19][20].…”

mentioning

confidence: 99%

See 2 more Smart Citations

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Cheng

Nan

Kang

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Background: Sepsis is a fatal disease referring to the presence of a known or strongly suspected infection coupled with systemic and uncontrolled immune activation causing multiple organ failure. However, neither pathogenic long non-coding RNAs (lncRNAs) nor biological network analysis in sepsis draws enough attention to the society of sepsis studies. Methods: We performed an in-silico investigation of the gene coexpression pattern for the patients response to all-cause sepsis in consecutive intensive care unit (ICU) admissions. Sepsis coexpression gene modules were identified using WGCNA and enrichment analysis. lncRNAs were determined as sepsis biomarkers based on the interactions among lncRNAs and the identified modules. Results: Twenty-three sepsis modules, including both differentially expressed modules and prognostic modules, were identified from the whole blood RNA expression profilings of sepsis patients. Five lncRNAs, FENDRR, MALAT1, TUG1, CRNDE, and ANCR, were detected as sepsis regulators based on the interactions among lncRNAs and the identified coexpression modules. Furthermore, we found that CRNDE and MALAT1 may act as miRNA sponges of sepsis related miRNAs to regulate the expression of sepsis modules. Ultimately, FENDRR, MALAT1, TUG1, and CRNDE were reannotated using three independent lncRNA expression datasets and validated as differentially expressed lncRNAs. Conclusion: The procedure facilitates the identification of prognostic biomarkers and novel therapeutic strategies of sepsis. Our findings highlight the importance of transcriptome modularity and regulatory lncRNAs in the progress of sepsis.

show abstract

A long non‐coding RNA signature for diagnostic prediction of sepsis upon ICU admission

Liu

Zheng

Wang

et al. 2020

Clinical & Translational Med

View full text Add to dashboard Cite

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

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 32 publications

References 55 publications

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

A long non‐coding RNA signature for diagnostic prediction of sepsis upon ICU admission

Contact Info

Product

Resources

About