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      Profiling and Functional Analysis of Circular RNAs in Porcine Fast and Slow Muscles

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          Abstract

          The different skeletal muscle fiber types exhibit distinctively different physiological and metabolic properties, and have been linked to both human metabolic diseases and meat quality traits in livestock. Circular RNAs (circRNAs) are a new class of endogenous RNA regulating gene expression, but regulatory mechanisms of skeletal muscle fibers involved in circRNAs remain poorly understood. Here, we constructed circRNA expression profiles of three fast-twitch biceps femoris (Bf) and three slow-twitch soleus (Sol) muscles in pigs using RNA-seq and identified 16,342 distinct circRNA candidates. Notably, 242 differentially expressed (DE) circRNAs between Bf and Sol muscles were identified, including 105 upregulated and 137 downregulated circRNAs, and are thus potential candidates for the regulation of skeletal muscle fiber conversion. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of host genes of DE circRNAs revealed that host genes were mainly involved in skeletal muscle fiber-related GO terms (e.g., muscle contraction, contractile fiber part, and Z disk) and skeletal muscle fiber-related signaling pathways (e.g., AMPK and cGMP-PKG). We also constructed co-expression networks of DE circRNA-miRNA-mRNA using previously acquired high-throughput sequencing mRNA and miRNA data, from which 112 circRNA-miRNA and 95 miRNA-mRNA interactions were identified. Multiple circRNAs essentially serve as a sponge for miR-499-5p, which is preferentially expressed in slow-twitch muscle and reduces the severity of Duchenne muscular dystrophy (DMD). Taken together, a series of novel candidate circRNAs involved in the growth and development of porcine skeletal muscle was identified. Furthermore, they provide a comprehensive circRNA resource for further in-depth research on the regulatory mechanisms of circRNA in the formation of skeletal muscle fiber, and may provide insights into human skeletal muscle diseases.

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          Most cited references 28

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          Genome-wide analysis of drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation.

          Circularization was recently recognized to broadly expand transcriptome complexity. Here, we exploit massive Drosophila total RNA-sequencing data, >5 billion paired-end reads from >100 libraries covering diverse developmental stages, tissues, and cultured cells, to rigorously annotate >2,500 fruit fly circular RNAs. These mostly derive from back-splicing of protein-coding genes and lack poly(A) tails, and the circularization of hundreds of genes is conserved across multiple Drosophila species. We elucidate structural and sequence properties of Drosophila circular RNAs, which exhibit commonalities and distinctions from mammalian circles. Notably, Drosophila circular RNAs harbor >1,000 well-conserved canonical miRNA seed matches, especially within coding regions, and coding conserved miRNA sites reside preferentially within circularized exons. Finally, we analyze the developmental and tissue specificity of circular RNAs and note their preferred derivation from neural genes and enhanced accumulation in neural tissues. Interestingly, circular isoforms increase substantially relative to linear isoforms during CNS aging and constitute an aging biomarker. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
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            CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

            Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0571-3) contains supplementary material, which is available to authorized users.
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              Muscle-specific microRNA miR-206 promotes muscle differentiation

              Three muscle-specific microRNAs, miR-206, -1, and -133, are induced during differentiation of C2C12 myoblasts in vitro. Transfection of miR-206 promotes differentiation despite the presence of serum, whereas inhibition of the microRNA by antisense oligonucleotide inhibits cell cycle withdrawal and differentiation, which are normally induced by serum deprivation. Among the many mRNAs that are down-regulated by miR-206, the p180 subunit of DNA polymerase α and three other genes are shown to be direct targets. Down-regulation of the polymerase inhibits DNA synthesis, an important component of the differentiation program. The direct targets are decreased by mRNA cleavage that is dependent on predicted microRNA target sites. Unlike small interfering RNA–directed cleavage, however, the 5′ ends of the cleavage fragments are distributed and not confined to the target sites, suggesting involvement of exonucleases in the degradation process. In addition, inhibitors of myogenic transcription factors, Id1-3 and MyoR, are decreased upon miR-206 introduction, suggesting the presence of additional mechanisms by which microRNAs enforce the differentiation program.
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                Author and article information

                Contributors
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                26 May 2020
                2020
                : 8
                Affiliations
                1Department of Animal Genetics, Breeding and Reproduction, College of Animal Science and Technology, Nanjing Agricultural University , Nanjing, China
                2College of Animal Science and Veterinary Medicine, Shenyang Agricultural University , Shenyang, China
                3College of Agronomy and Biotechnology, Hebei Normal University of Science and Technology , Qinhuangdao, China
                Author notes

                Edited by: Boris Novakovic, Royal Children’s Hospital, Australia

                Reviewed by: Eric Joo, The University of Melbourne, Australia; Amy Osborne, University of Canterbury, New Zealand

                *Correspondence: Wangjun Wu, wangjunwu4062@ 123456163.com

                This article was submitted to Epigenomics and Epigenetics, a section of the journal Frontiers in Cell and Developmental Biology

                Article
                10.3389/fcell.2020.00322
                7264268
                32528948
                Copyright © 2020 Li, Yin, Li, Zhang, Zhang, Li, Li, Hou, Liu and Wu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 6, Tables: 0, Equations: 0, References: 61, Pages: 13, Words: 0
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Categories
                Cell and Developmental Biology
                Original Research

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