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      Profiling several key milk miRNAs and analysing their signalling pathways in dairy sheep breeds during peak and late lactation

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          Abstract

          Background

          The comprehensive understanding of microRNAs (miRNAs) in sheep milk during various lactation periods and their impact on milk yield and composition remains limited.

          Objectives

          This study aimed to investigate the expression patterns of four highly expressed miRNAs in sheep milk and their association with milk composition and yield parameters during peak and late lactation stages.

          Methods

          A total of 40 healthy 4‐year‐old Akkaraman ( n = 20) and Awassi ( n = 20) ewes registered with the Ministry of Agriculture and Forestry of the Republic of Türkiye were used in the present study. For miRNA isolation from milk, the Qiagen miRNeasy Serum/Plasma Advanced Kit was utilised following the manufacturer's instructions. The expression levels of miRNAs were assessed using Qiagen miRNA PCR Assays.

          Results

          The significant fold changes in the expression levels of oar‐miR‐30a‐5p, oar‐miR‐148a and oar‐miR‐181a were observed between peak and late lactation periods in the Awassi sheep breed. Conversely, only oar‐miR‐30a‐5p and oar‐miR‐148a exhibited statistically significant changes in the Akkaraman sheep breed during the same lactation periods. Furthermore, oar‐miR‐21‐5p demonstrated a significant fold change exclusively in peak lactation compared to Akkaraman and Awassi ewes.

          Conclusions

          The findings suggest that the expression of the analysed miRNAs is influenced by both the lactation stage and different sheep breeds. This study offers valuable insights into the relationship between key miRNA expressions in sheep milk and milk composition and yield parameters during peak and late lactation, contributing to the existing knowledge in this field.

          Abstract

          • This study aimed to investigate the expression patterns of four highly expressed miRNAs in sheep milk and their association with milk composition and yield parameters during peak and late lactation stages.

          • Notably, significant fold changes in the expression levels of oar‐miR‐30a‐5p, oar‐miR‐148a, and oar‐miR‐181a were observed between peak and late lactation periods in the Awassi sheep breed.

          • oar‐miR‐21‐5p demonstrated a significant fold change exclusively in peak lactation compared to Akkaraman and Awassi ewes.

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          Most cited references39

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

            A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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              The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

              Abstract Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.
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                Author and article information

                Contributors
                ozgeozmen@ankara.edu.tr
                Journal
                Vet Med Sci
                Vet Med Sci
                10.1002/(ISSN)2053-1095
                VMS3
                Veterinary Medicine and Science
                John Wiley and Sons Inc. (Hoboken )
                2053-1095
                25 June 2024
                July 2024
                : 10
                : 4 ( doiID: 10.1002/vms3.v10.4 )
                : e1505
                Affiliations
                [ 1 ] Faculty of Medicine, Institute of Molecular Gastroenterology and Hepatology Kocaeli University Kocaeli Türkiye
                [ 2 ] Faculty of Veterinary Medicine, Department of Genetics Ankara University Ankara Türkiye
                [ 3 ] Faculty of Veterinary Medicine, Department of Animal Breeding Yozgat Bozok University Yozgat Türkiye
                Author notes
                [*] [* ] Correspondence

                Özge Özmen, Faculty of Veterinary Medicine, Department of Genetics, Ankara University, Ankara, Türkiye.

                Email: ozgeozmen@ 123456ankara.edu.tr

                Author information
                https://orcid.org/0000-0002-8577-7323
                Article
                VMS31505
                10.1002/vms3.1505
                11198020
                38924289
                093e0add-ff28-4510-8bcc-c11fec6b9ed8
                © 2024 The Author(s). Veterinary Medicine and Science published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 23 April 2024
                : 15 May 2023
                : 24 May 2024
                Page count
                Figures: 15, Tables: 4, Pages: 19, Words: 9080
                Funding
                Funded by: Scientific Research Projects Council of Tokat University
                Award ID: 2020/50
                Categories
                Original Article
                RUMINANTS
                Original Articles
                Custom metadata
                2.0
                July 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.4 mode:remove_FC converted:25.06.2024

                lactation,milk composition,milk mirna,milk yield,sheep
                lactation, milk composition, milk mirna, milk yield, sheep

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