Blog
About

6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transcriptome Analysis Reveals Long Intergenic Noncoding RNAs Contributed to Growth and Meat Quality Differences between Yorkshire and Wannanhua Pig

      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

          There are major differences between Yorkshire (lean-type) and Wannanhua pig (fat-type) in terms of growth performance and meat quality. Long intergenic noncoding RNAs (lincRNAs) are a class of regulators that are involved in numerous biological processes and widely identified in many species. However, the role of lincRNAs in pig is largely unknown, and the mechanisms by which they affect growth and meat quality are elusive. In this study, we used published data to identify 759 lincRNAs in porcine longissimus dorsi muscle. These putative lincRNAs shared many features with mammalian lincRNAs, such as shorter length and fewer exons. Gene ontology and pathway analysis indicated that many potential target genes (PTGs) of lincRNAs were involved in muscle growth-related and meat quality-related biological processes. Moreover, we constructed a co-expression network between differentially expressed lincRNAs (DELs) and their PTGs, and found a potential mechanism that most DELs can use to upregulate their PTGs, which may finally contribute to the growth and meat quality differences between the two breeds through an unknown manner. This work details some lincRNAs and their PTGs related to muscle growth or meat quality, and facilitates future research on the roles of lincRNAs in these two types of pig, as well as molecular-assisted breeding for pig.

          Related collections

          Most cited references 64

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

          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                18 August 2017
                August 2017
                : 8
                : 8
                Affiliations
                Key Lab of Agriculture Animal Genetics, Breeding, and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; zzcy873704025@ 123456163.com (C.Z.); lovguyls@ 123456163.com (S.L.); 15171492670@ 123456163.com (L.D.); gy963967268@ 123456163.com (Y.G.); dakelchan@ 123456163.com (D.C.); yuanxiongkun@ 123456126.com (X.Y.); phillislis@ 123456163.com (T.X.); xinglinhe@ 123456yeah.net (X.H.); shansyw799@ 123456163.com (Y.S.)
                Author notes
                [†]

                These authors contributed equally to this work.

                Article
                genes-08-00203
                10.3390/genes8080203
                5575666
                28820450
                © 2017 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                Categories
                Article

                Comments

                Comment on this article