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      In silico identification of conserved miRNAs and their selective target gene prediction in indicine ( Bos indicus) cattle

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          Abstract

          The modern cattle was domesticated from aurochs, sharing its physiological traits into two subspecies Bos taurus and Bos indicus. MicroRNAs (miRNAs) are a class of non-coding short RNAs of ~22nt which have a key role in the regulation of many cellular and physiological processes in the animal. The current study was aimed to predict and annotate the potential mutations in indicine miRNAs throughout the genome using de novo and homology-based in silico approaches. Genome-wide mapping was performed in available indicine assembly by the homology-based approach and 768 miRNAs were recovered out of 808 reported taurine miRNAs belonging to 521 unique mature miRNA families. While 42 precursors were dropped due to lack of secondary miRNA structure, increasing stringency or decreasing similarity between the two genomes’ miRNA. Increasing tendency of miRNAs incidence was observed on chr5, chr7, chr8, chr12 and chr21 with 19 polycistronic miRNA within 1-kilobase distance throughout the indicine genome. Notably, 12 miRNAs showed copy number variation. Eighteen miRNAs showed a mutation in their mature sequences in which eight were found in their seed region. Whilst in de novo based approach, 12 novel potential miRNAs on Y chromosome in indicine cattle along with a new miRNA (bind-miR-1264) on chrX were found. The final data set is annotated and explains the impending target genes that are responsible for enhanced immunity, heat tolerance and disease tolerance regulation in indicine. The study conforms to better understanding and perceptive approach towards indicine genome.

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          Origin, biogenesis, and activity of plant microRNAs.

          MicroRNAs (miRNAs) are key posttranscriptional regulators of eukaryotic gene expression. Plants use highly conserved as well as more recently evolved, species-specific miRNAs to control a vast array of biological processes. This Review discusses current advances in our understanding of the origin, biogenesis, and mode of action of plant miRNAs and draws comparisons with their metazoan counterparts.
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            microRNA target predictions in animals.

            In recent years, microRNAs (miRNAs) have emerged as a major class of regulatory genes, present in most metazoans and important for a diverse range of biological functions. Because experimental identification of miRNA targets is difficult, there has been an explosion of computational target predictions. Although the initial round of predictions resulted in very diverse results, subsequent computational and experimental analyses suggested that at least a certain class of conserved miRNA targets can be confidently predicted and that this class of targets is large, covering, for example, at least 30% of all human genes when considering about 60 conserved vertebrate miRNA gene families. Most recent approaches have also shown that there are correlations between domains of miRNA expression and mRNA levels of their targets. Our understanding of miRNA function is still extremely limited, but it may be that by integrating mRNA and miRNA sequence and expression data with other comparative genomic data, we will be able to gain global and yet specific insights into the function and evolution of a broad layer of post-transcriptional control.
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              Evolution of microRNA diversity and regulation in animals.

              In the past decade, microRNAs (miRNAs) have been uncovered as key regulators of gene expression at the post-transcriptional level. The ancient origin of miRNAs, their dramatic expansion in bilaterian animals and their function in providing robustness to transcriptional programmes suggest that miRNAs are instrumental in the evolution of organismal complexity. Advances in understanding miRNA biology, combined with the increasing availability of diverse sequenced genomes, have begun to reveal the molecular mechanisms that underlie the evolution of miRNAs and their targets. Insights are also emerging into how the evolution of miRNA-containing regulatory networks has contributed to organismal complexity.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Project administrationRole: Supervision
                Role: Funding acquisitionRole: Project administrationRole: ResourcesRole: VisualizationRole: Writing – review & editing
                Role: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: Funding acquisitionRole: SupervisionRole: VisualizationRole: Writing – review & editing
                Role: InvestigationRole: SupervisionRole: Visualization
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 October 2018
                2018
                : 13
                : 10
                : e0206154
                Affiliations
                [1 ] Key Laboratory of Animal Genetics and Breeding and Reproduction of Ministry of Agriculture, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
                [2 ] Bioinformatics and Computational Biology Laboratory, National Institute for Biotechnology and Genetic Engineering, (NIBGE), Faisalabad, Pakistan
                [3 ] Pakistan Institute of Engineering and Applied Sciences, Islamabad, PK
                [4 ] Environmental Toxicology Laboratory, National Institute for Biotechnology and Genetic Engineering, (NIBGE), Faisalabad, Pakistan
                University of Illinois, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-9841-8055
                http://orcid.org/0000-0003-0704-3372
                Article
                PONE-D-18-10866
                10.1371/journal.pone.0206154
                6203363
                30365525
                e5466ec1-1da8-48bb-935e-90f392135e15
                © 2018 Hanif et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 April 2018
                : 8 October 2018
                Page count
                Figures: 7, Tables: 2, Pages: 18
                Funding
                The current study was supported by an agricultural project, ICARDA project # 1198 and initiated by National Institute for Biotechnology and Genetic Engineering (NIBGE). Yi Zhang was supported by the Program for Changjiang Scholars and Innovative Research in University (IRT1191).
                Categories
                Research Article
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                Natural antisense transcripts
                MicroRNAs
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                MicroRNAs
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Bovines
                Cattle
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Cattle
                Biology and Life Sciences
                Immunology
                Immunity
                Medicine and Health Sciences
                Immunology
                Immunity
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Sequence Assembly Tools
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Sequence Assembly Tools
                Biology and Life Sciences
                Computational Biology
                Genome Complexity
                Copy Number Variation
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Complexity
                Copy Number Variation
                Biology and Life Sciences
                Agriculture
                Livestock
                Biology and Life Sciences
                Genetics
                Genomics
                Animal Genomics
                Mammalian Genomics
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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                Uncategorized

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