11
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genome-wide profiling of Sus scrofa circular RNAs across nine organs and three developmental stages

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The spatio-temporal expression patterns of Circular RNA (circRNA) across organs and developmental stages are critical for its function and evolution analysis. However, they remain largely unclear in mammals. Here, we comprehensively analysed circRNAs in nine organs and three skeletal muscles of Guizhou miniature pig ( S. scrofa), a widely used biomedical model animal. We identified 5,934 circRNAs and analysed their molecular properties, sequence conservation, spatio-temporal expression pattern, potential function, and interaction with miRNAs. S. scrofa circRNAs show modest sequence conservation with human and mouse circRNAs, are flanked by long introns, exhibit low abundance, and are expressed dynamically in a spatio-temporally specific manner. S. scrofa circRNAs show the greatest abundance and complexity in the testis. Notably, 31% of circRNAs harbour well-conserved canonical miRNA seed matches, suggesting that some circRNAs act as miRNAs sponges. We identified 149 circRNAs potentially associated with muscle growth and found that their host genes were significantly involved in muscle development, contraction, chromatin modification, cation homeostasis, and ATP hydrolysis-coupled proton transport; moreover, this set of genes was markedly enriched in genes involved in tight junctions and the calcium signalling pathway. Finally, we constructed the first public S. scrofa circRNA database, allowing researchers to query comprehensive annotation, expression, and regulatory networks of circRNAs.

          Related collections

          Most cited references42

          • Record: found
          • Abstract: found
          • Article: not found

          A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

          Heng Li (2011)
          Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Diversifying microRNA sequence and function.

              MicroRNAs (miRNAs) regulate the expression of most genes in animals, but we are only now beginning to understand how they are generated, assembled into functional complexes and destroyed. Various mechanisms have now been identified that regulate miRNA stability and that diversify miRNA sequences to create distinct isoforms. The production of different isoforms of individual miRNAs in specific cells and tissues may have broader implications for miRNA-mediated gene expression control. Rigorously testing the many discrepant models for how miRNAs function using quantitative biochemical measurements made in vivo and in vitro remains a major challenge for the future.
                Bookmark

                Author and article information

                Journal
                DNA Res
                DNA Res
                dnares
                DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes
                Oxford University Press
                1340-2838
                1756-1663
                October 2017
                29 May 2017
                29 May 2017
                : 24
                : 5
                : 523-535
                Affiliations
                [1 ]State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
                [2 ]Department of Pig Genomic Design and Breeding, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
                [3 ]Shenzhen Key Laboratory of Phenotype Analysis and Utilization of Agricultural Genome, Agricultural Genome Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
                Author notes
                [* ]To whom correspondence should be addressed. Tel. +86 10 6281 8180. Fax. +86 10 6281 8180. Email: zhonglinqy_99@ 123456sina.com (Z.T.); likui@ 123456caas.cn (K.L.)
                [*]

                Edited by Dr. Minoru Ko

                Article
                dsx022
                10.1093/dnares/dsx022
                5737845
                28575165
                af67f947-12ed-466e-93db-54252967fe6d
                © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 28 October 2016
                : 03 May 2017
                Page count
                Pages: 13
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31171192, 31330074
                Categories
                Full Papers

                Genetics
                circrnas,pig,profiling,organs,skeletal muscle
                Genetics
                circrnas, pig, profiling, organs, skeletal muscle

                Comments

                Comment on this article