{"title":"CICADA: a circRNA effort toward the ghost proteome.","authors":"Liyuan Fan, Xinyuan Zhou, Mian Li, Anwei Gao, Haojie Yu, Hui Tian, Liandi Liao, Liyan Xu, Liang Sun","doi":"10.1093/nar/gkae1179","DOIUrl":null,"url":null,"abstract":"<p><p>Recent studies have confirmed that certain circRNAs encode proteins that are integral to various biological functions. In this study, we present CICADA, an algorithm specifically designed to assess the protein-coding potential and coding products of circRNAs at high throughput, which enables the identification of previously unknown circRNA-encoded proteins. By harnessing the potential of this algorithm, we identified a variety of functional, protein-coding circRNAs in esophageal squamous cell carcinoma and established circRNA translation profiles for diverse types of cancer. This advancement innovatively explores the hidden proteome within the genome, poised to catalyze discoveries in biomarkers and therapies for cancers and complex diseases. CICADA is accessible as a Python module (https://github.com/SunLab-biotool/CICADA).</p>","PeriodicalId":19471,"journal":{"name":"Nucleic Acids Research","volume":" ","pages":""},"PeriodicalIF":16.6000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleic Acids Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/nar/gkae1179","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Recent studies have confirmed that certain circRNAs encode proteins that are integral to various biological functions. In this study, we present CICADA, an algorithm specifically designed to assess the protein-coding potential and coding products of circRNAs at high throughput, which enables the identification of previously unknown circRNA-encoded proteins. By harnessing the potential of this algorithm, we identified a variety of functional, protein-coding circRNAs in esophageal squamous cell carcinoma and established circRNA translation profiles for diverse types of cancer. This advancement innovatively explores the hidden proteome within the genome, poised to catalyze discoveries in biomarkers and therapies for cancers and complex diseases. CICADA is accessible as a Python module (https://github.com/SunLab-biotool/CICADA).
期刊介绍：
Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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