Quantifying full-length circular RNAs in cancer

Yu, Ken Hung-On; Shi, Christina Huan; Wang, Bo; Chow, Savio Ho-Chit; Chung, Grace Tin‐Yun; Lung, Raymond Wai Ming; Tan, Ke-En; Lim, Yat-Yuen; Tsang, Anna Chi‐Man; Lo, Kwok‐Wai; Yip, Kevin Y.

doi:10.1101/gr.275348.121

Cited by 11 publications

(9 citation statements)

References 70 publications

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“…The expression level of each circRNA was identified using the psirc-quant program [ 73 ] based on likelihood maximization by mapping the rRNA-depleted reads to the integrated circRNAs. The TPM was calculated to normalize the expression level of each circRNA by the following formula:

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Section: Methodsmentioning

confidence: 99%

A Combination of a Genome-Wide Association Study and a Transcriptome Analysis Reveals circRNAs as New Regulators Involved in the Response to Salt Stress in Maize

Liu

Zhu

Líu

et al. 2022

IJMS

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Salinization seriously threatens the normal growth of maize, especially at the seedling stage. Recent studies have demonstrated that circular RNAs (circRNAs) play vital roles in the regulation of plant stress resistance. Here, we performed a genome-wide association study (GWAS) on the survival rate of 300 maize accessions under a salt stress treatment. A total of 5 trait-associated SNPs and 86 candidate genes were obtained by the GWAS. We performed RNA sequencing for 28 transcriptome libraries derived from 2 maize lines with contrasting salt tolerance under normal and salt treatment conditions. A total of 1217 highly expressed circRNAs were identified, of which 371 were responsive to a salt treatment. Using PCR and Sanger sequencing, we verified the reliability of these differentially expressed circRNAs. An integration of the GWAS and RNA-Seq analyses uncovered two differentially expressed hub genes (Zm00001eb013650 and Zm00001eb198930), which were regulated by four circRNAs. Based on these results, we constructed a regulation model of circRNA/miRNA/mRNA that mediated salt stress tolerance in maize. By conducting hub gene-based association analyses, we detected a favorable haplotype in Zm00001eb198930, which was responsible for high salt tolerance. These results help to clarify the regulatory relationship between circRNAs and their target genes as well as to develop salt-tolerant lines for maize breeding.

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…”

Section: Methodsmentioning

confidence: 99%

A Combination of a Genome-Wide Association Study and a Transcriptome Analysis Reveals circRNAs as New Regulators Involved in the Response to Salt Stress in Maize

Liu

Zhu

Líu

et al. 2022

IJMS

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“…For quantifying expression values, we use psirc [20], which in turn employs kallisto [34] considering both linear and circular transcripts in the expectation-maximization step to yield comparable expression values. If the data has been sampled from different conditions (e.g., case and control), the quantified linear transcripts and circRNAs can be used to perform a differential expression analysis using DESeq2 [33].…”

Section: Pipeline Architecturementioning

confidence: 99%

“…Identification of circRNAs relies on the detection of back-splicing junctions (BSJ) among the unmapped reads, which allows for the estimation of circRNA abundance. By focusing on the back-splicing junction alone, the expression of circRNAs in relation to their linear counterparts is typically underestimated [20]. Several approaches for circRNA analysis have been proposed.…”

Section: Introductionmentioning

confidence: 99%

circRNA-sponging: a pipeline for extensive analysis of circRNA expression and their role in miRNA sponging

Hoffmann

Schwartz

Ciora

et al. 2023

Preprint

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Motivation: Circular RNAs (circRNAs) are long non-coding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systematically assess the sponging potential of circRNAs. Results: We developed circRNA-sponging, a nextflow pipeline that (1) identifies circRNAs via back-splicing junctions detected in RNA-seq data, (2) quantifies their expression values in relation to their linear counterparts spliced from the same gene, (3) performs differential expression analysis, (4) identifies and quantifies miRNA expression from miRNA-sequencing (miRNA-seq) data, (5) predicts miRNA binding sites on circRNAs, (6) systematically investigates potential circRNA-miRNA sponging events, (7) creates a network of competing endogenous RNAs, and (8) identifies potential circRNA biomarkers. We showed the functionality of the circRNA-sponging pipeline using RNA sequencing data from brain tissues where we identified two distinct types of circRNAs characterized by a distinct ratio of the binding site length. The circRNA-sponging pipeline is the first end-to-end pipeline to identify circRNAs and their sponging systematically with raw total RNA-seq and miRNA-seq files, allowing us to better indicate the functional impact of circRNAs as a routine aspect in transcriptomic research. Availability: https://github.com/biomedbigdata/circRNA-sponging.

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“…CIRI-full (Y. and CircAST (Wu et al, 2019) first locate the back-splicing junction positions suggested by other BSJ methods such as CIRI2 and perform local reads assembly to obtain full-length circRNAs. In 2021, psirc was published (Yu et al, 2021) with similar features to quantify full-length circRNAs while emphasizing application potentials in cancer samples.…”

Section: High-throughput Approaches To Characterize Circrnas In Full-...mentioning

confidence: 99%

Characterization of circular RNAs with advanced sequencing technologies in human complex diseases

2022

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Circular RNAs (circRNAs) are one category of non‐coding RNAs that do not possess 5′ caps and 3′ free ends. Instead, they are derived in closed circle forms from pre‐mRNAs by a non‐canonical splicing mechanism named “back‐splicing.” CircRNAs were discovered four decades ago, initially called “scrambled exons.” Compared to linear RNAs, the expression levels of circRNAs are considerably lower, and it is challenging to identify circRNAs specifically. Thus, the biological relevance of circRNAs has been underappreciated until the advancement of next generation sequencing (NGS) technology. The biological insights of circRNAs, such as their tissue‐specific expression patterns, biogenesis factors, and functional effects in complex diseases, namely human cancers, have been extensively explored in the last decade. With the invention of the third generation sequencing (TGS) with longer sequencing reads and newly designed strategies to characterize full‐length circRNAs, the panorama of circRNAs in human complex diseases could be further unveiled. In this review, we first introduce the history of circular RNA detection. Next, we describe widely adopted NGS‐based methods and the recently established TGS‐based approaches capable of characterizing circRNAs in full‐length. We then summarize data resources and representative circRNA functional studies related to human complex diseases. In the last section, we reviewed computational tools and discuss the potential advantages of utilizing advanced sequencing approaches to a functional interpretation of full‐length circRNAs in complex diseases. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Disease

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Quantifying full-length circular RNAs in cancer

Cited by 11 publications

References 70 publications

A Combination of a Genome-Wide Association Study and a Transcriptome Analysis Reveals circRNAs as New Regulators Involved in the Response to Salt Stress in Maize

A Combination of a Genome-Wide Association Study and a Transcriptome Analysis Reveals circRNAs as New Regulators Involved in the Response to Salt Stress in Maize

circRNA-sponging: a pipeline for extensive analysis of circRNA expression and their role in miRNA sponging

Characterization of circular RNAs with advanced sequencing technologies in human complex diseases

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