3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Assembling mitogenome of Himalayan Black Bear ( U. t. laniger) from low depth reads and its application in drawing phylogenetic inferences

      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 complete mitogenome of Himalayan black bear ( Ursus thibetanus laniger) from Indian Himalayan region was assembled following the modified approach of mitochondrial baiting and mapping using the next-generation sequencing reads. The complete mitogenome was of 16,556 bp long, consisted of 37 genes that contained 13 protein-coding genes, 22 tRNAs, 2 rRNAs and 1 control region. The complete base composition was 31.33% A, 15.24% G, 25.45%C, and 27.98%T and gene arrangement was similar to the other sub-species of Asiatic black bear. The relative synonymous codon usage analysis revealed the maximum abundance of Isoleucine, Tyrosine, Leucine and Threonine. The assembled mitogenome of U. t. laniger exhibited 99% similarity with the mitogenomes of Himalayan black bear available from Nepal and Tibetan Plateau-Himalaya region. The findings of the present study has proven low depth sequencing data, adequate and highly efficient in rapid recovering the mitochondrial genome by overcoming the conventional strategies of obtaining long-range PCR and subsequently drawing phylogenetic inferences.

          Related collections

          Most cited references37

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

          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Tandem repeats finder: a program to analyze DNA sequences.

            G. Benson (1999)
            A tandem repeat in DNA is two or more contiguous, approximate copies of a pattern of nucleotides. Tandem repeats have been shown to cause human disease, may play a variety of regulatory and evolutionary roles and are important laboratory and analytic tools. Extensive knowledge about pattern size, copy number, mutational history, etc. for tandem repeats has been limited by the inability to easily detect them in genomic sequence data. In this paper, we present a new algorithm for finding tandem repeats which works without the need to specify either the pattern or pattern size. We model tandem repeats by percent identity and frequency of indels between adjacent pattern copies and use statistically based recognition criteria. We demonstrate the algorithm's speed and its ability to detect tandem repeats that have undergone extensive mutational change by analyzing four sequences: the human frataxin gene, the human beta T cellreceptor locus sequence and two yeast chromosomes. These sequences range in size from 3 kb up to 700 kb. A World Wide Web server interface atc3.biomath.mssm.edu/trf.html has been established for automated use of the program.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.

              We describe a program, tRNAscan-SE, which identifies 99-100% of transfer RNA genes in DNA sequence while giving less than one false positive per 15 gigabases. Two previously described tRNA detection programs are used as fast, first-pass prefilters to identify candidate tRNAs, which are then analyzed by a highly selective tRNA covariance model. This work represents a practical application of RNA covariance models, which are general, probabilistic secondary structure profiles based on stochastic context-free grammars. tRNAscan-SE searches at approximately 30 000 bp/s. Additional extensions to tRNAscan-SE detect unusual tRNA homologues such as selenocysteine tRNAs, tRNA-derived repetitive elements and tRNA pseudogenes.
                Bookmark

                Author and article information

                Contributors
                thamukesh@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 January 2021
                12 January 2021
                2021
                : 11
                : 730
                Affiliations
                GRID grid.473833.8, ISNI 0000 0001 2291 2164, Zoological Survey of India, ; New Alipore, Kolkata, West Bengal 700053 India
                Article
                76872
                10.1038/s41598-020-76872-y
                7803731
                33436634
                62ab476a-45a0-4bb4-bd7c-2bf49627ae63
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 31 January 2020
                : 4 November 2020
                Funding
                Funded by: 1. National Mission on Himalayan Studies 2. Department of Science and Technology
                Award ID: 1.NMHS/2017-18/LG09/02
                Award ID: 1.NMHS/2017-18/LG09/02
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                evolutionary biology,genomics,sequencing,conservation biology,evolutionary ecology,molecular ecology

                Comments

                Comment on this article