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In Silico identification and characterization of circRNAs during host-pathogen interactions

Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via backsplicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infec...

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Main Authors: Selvan, Mathanakumara Ealam, Lim, Kai Shen, Teo, Chee How, Lim, Yat-Yuen
Format: Article
Published: Journal of Visualized Experiments 2022
Subjects:
S Agriculture (General)
Online Access:http://eprints.um.edu.my/40406/
https://doi.org/10.3791/64565
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spelling my.um.eprints.404062024-07-15T03:23:28Z http://eprints.um.edu.my/40406/ In Silico identification and characterization of circRNAs during host-pathogen interactions Selvan, Mathanakumara Ealam Lim, Kai Shen Teo, Chee How Lim, Yat-Yuen S Agriculture (General) Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via backsplicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wetlab techniques. To solve this issue, a step-by-step protocol of in Silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions. Journal of Visualized Experiments 2022-10 Article PeerReviewed Selvan, Mathanakumara Ealam and Lim, Kai Shen and Teo, Chee How and Lim, Yat-Yuen (2022) In Silico identification and characterization of circRNAs during host-pathogen interactions. Jove-Journal of Visualized Experiments (188). ISSN 1940-087X, DOI https://doi.org/10.3791/64565 <https://doi.org/10.3791/64565>. https://doi.org/10.3791/64565 10.3791/64565
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic S Agriculture (General)
spellingShingle S Agriculture (General)
Selvan, Mathanakumara Ealam
Lim, Kai Shen
Teo, Chee How
Lim, Yat-Yuen
In Silico identification and characterization of circRNAs during host-pathogen interactions
description Circular RNAs (circRNAs) are a class of non-coding RNAs that are formed via backsplicing. These circRNAs are predominantly studied for their roles as regulators of various biological processes. Notably, emerging evidence demonstrates that host circRNAs can be differentially expressed (DE) upon infection with pathogens (e.g., influenza and coronaviruses), suggesting a role for circRNAs in regulating host innate immune responses. However, investigations on the role of circRNAs during pathogenic infections are limited by the knowledge and skills required to carry out the necessary bioinformatic analysis to identify DE circRNAs from RNA sequencing (RNA-seq) data. Bioinformatics prediction and identification of circRNAs is crucial before any verification, and functional studies using costly and time-consuming wetlab techniques. To solve this issue, a step-by-step protocol of in Silico prediction and characterization of circRNAs using RNA-seq data is provided in this manuscript. The protocol can be divided into four steps: 1) Prediction and quantification of DE circRNAs via the CIRIquant pipeline; 2) Annotation via circBase and characterization of DE circRNAs; 3) CircRNA-miRNA interaction prediction through Circr pipeline; 4) functional enrichment analysis of circRNA parental genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). This pipeline will be useful in driving future in vitro and in vivo research to further unravel the role of circRNAs in host-pathogen interactions.
format Article
author Selvan, Mathanakumara Ealam
Lim, Kai Shen
Teo, Chee How
Lim, Yat-Yuen
author_facet Selvan, Mathanakumara Ealam
Lim, Kai Shen
Teo, Chee How
Lim, Yat-Yuen
author_sort Selvan, Mathanakumara Ealam
title In Silico identification and characterization of circRNAs during host-pathogen interactions
title_short In Silico identification and characterization of circRNAs during host-pathogen interactions
title_full In Silico identification and characterization of circRNAs during host-pathogen interactions
title_fullStr In Silico identification and characterization of circRNAs during host-pathogen interactions
title_full_unstemmed In Silico identification and characterization of circRNAs during host-pathogen interactions
title_sort in silico identification and characterization of circrnas during host-pathogen interactions
publisher Journal of Visualized Experiments
publishDate 2022
url http://eprints.um.edu.my/40406/
https://doi.org/10.3791/64565
_version_ 1805881116292284416
score 13.211869

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