IDEAS home Printed from https://ideas.repec.org/a/caa/jnlcjs/v61y2016i3id8782-cjas.html
   My bibliography  Save this article

Combination of let-7d-5p, miR-26a-5p, and miR-15a-5p is suitable normalizer for studying microRNA expression in skin tissue of Liaoning cashmere goat during hair follicle cycle

Author

Listed:
  • W.L. Bai

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • Y.L. Dang

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • R.H. Yin

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • R.L. Yin

    (Research Academy of Animal Husbandry and Veterinary Medicine Sciences of Jilin Province, Changchun, P.R. China)

  • W.Q. Jiang

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • Z.Y. Wang

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • Y.B. Zhu

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • J.J. Wang

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

  • Z.H. Zhao

    (College of Animal Science and Veterinary Medicine, Jilin University, Changchun, P.R. China)

  • G.B. Luo

    (College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, P.R. China)

Abstract

The microRNAs are non-coding RNA molecules of approximately 20-22 nucleotides that are found to be implicated in a wide range of physiological processes. In this study, the suitability of 10 candidate reference RNAs was evaluated for microRNA expression data in the skin tissue of Liaoning cashmere goat including 1 small nuclear RNA (snRNA; RNU6B), 1 small nucleolar RNA (snoRNA; Z30), 1 rRNA (5S), 1 transfer RNA (tRNA; Met-tRNA), and 6 microRNAs (miR; let-7d-5p, miR-15a-5p, miR-26a-5p, miR-125a-5p, miR-214-3p, and miR-221-3p). Based on geNorm and NormFinder algorithms, we identified let-7d-5p, miR-26a-5p, and miR-15a-5p as the most stable reference RNAs. Also, three reference RNAs (let-7d-5p, miR-26a-5p, and miR-15a-5p) were sufficient for the normalization of microRNA expression data in the skin of this breed. We further assessed the suitability of let-7d-5p, miR-26a-5p, and miR-15a-5p in a combination as reference RNAs through detecting the relative expression of miR-24-3p, miR-29a-3p, miR-145a-5p, and miR-205-5p as putative genes of interest. Significant differences were revealed in the relative expression of miR-24-3p, miR-29a-3p, miR-145a-5p, and miR-205-5p at telogen stage of hair follicle cycle when a combination of let-7d-5p, miR-26a-5p, and miR-15a-5p vs a single let-7d-5p were used as reference RNA. Based on the results from this study, we suggested that the combination of let-7d-5p, miR-26a-5p, and miR-15a-5p as normalizers for microRNA expression data would be more reliable than that of single let-7d-5p, and the geometric mean of these three microRNAs (let-7d-5p, miR-26a-5p, and miR-15a-5p) can be used for the normalization of microRNAs expression data in the skin of Liaoning cashmere goat.

Suggested Citation

  • W.L. Bai & Y.L. Dang & R.H. Yin & R.L. Yin & W.Q. Jiang & Z.Y. Wang & Y.B. Zhu & J.J. Wang & Z.H. Zhao & G.B. Luo, 2016. "Combination of let-7d-5p, miR-26a-5p, and miR-15a-5p is suitable normalizer for studying microRNA expression in skin tissue of Liaoning cashmere goat during hair follicle cycle," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 61(3), pages 99-107.
    • Handle: RePEc:caa:jnlcjs:v:61:y:2016:i:3:id:8782-cjas
    DOI: 10.17221/8782-CJAS
    as

    Download full text from publisher

    File URL: http://cjas.agriculturejournals.cz/doi/10.17221/8782-CJAS.html
    Download Restriction: free of charge
    File URL: http://cjas.agriculturejournals.cz/doi/10.17221/8782-CJAS.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.17221/8782-CJAS?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Matthias Selbach & Björn Schwanhäusser & Nadine Thierfelder & Zhuo Fang & Raya Khanin & Nikolaus Rajewsky, 2008. "Widespread changes in protein synthesis induced by microRNAs," Nature, Nature, vol. 455(7209), pages 58-63, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David Lyon & Maria Angeles Castillejo & Christiana Staudinger & Wolfram Weckwerth & Stefanie Wienkoop & Volker Egelhofer, 2014. "Automated Protein Turnover Calculations from 15N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    2. Alicia Hurtado & Irene Mota-Gómez & Miguel Lao & Francisca M. Real & Johanna Jedamzick & Miguel Burgos & Darío G. Lupiáñez & Rafael Jiménez & Francisco J. Barrionuevo, 2024. "Complete male-to-female sex reversal in XY mice lacking the miR-17~92 cluster," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Shuangmei Tian & Ziyu Zhao & Beibei Ren & Degeng Wang, 2024. "Non-Linear Relationship between MiRNA Regulatory Activity and Binding Site Counts on Target mRNAs," Data, MDPI, vol. 9(10), pages 1-13, September.
    4. Adam A Margolin & Shao-En Ong & Monica Schenone & Robert Gould & Stuart L Schreiber & Steven A Carr & Todd R Golub, 2009. "Empirical Bayes Analysis of Quantitative Proteomics Experiments," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-15, October.
    5. Chikako Ragan & Michael Zuker & Mark A Ragan, 2011. "Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-11, February.
    6. Peng Wang & Shangwei Ning & Qianghu Wang & Ronghong Li & Jingrun Ye & Zuxianglan Zhao & Yan Li & Teng Huang & Xia Li, 2013. "mirTarPri: Improved Prioritization of MicroRNA Targets through Incorporation of Functional Genomics Data," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-12, January.
    7. Panagiotis Alexiou & Manolis Maragkakis & Giorgio L Papadopoulos & Victor A Simmosis & Lin Zhang & Artemis G Hatzigeorgiou, 2010. "The DIANA-mirExTra Web Server: From Gene Expression Data to MicroRNA Function," PLOS ONE, Public Library of Science, vol. 5(2), pages 1-7, February.
    8. Ramkrishna Mitra & Sanghamitra Bandyopadhyay, 2011. "MultiMiTar: A Novel Multi Objective Optimization based miRNA-Target Prediction Method," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-13, September.
    9. Wenliang Zhu & Xuan Kan, 2014. "Neural Network Cascade Optimizes MicroRNA Biomarker Selection for Nasopharyngeal Cancer Prognosis," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-7, October.
    10. Yuheng Lu & Christina S Leslie, 2016. "Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-18, July.
    11. Parawee Lekprasert & Michael Mayhew & Uwe Ohler, 2011. "Assessing the Utility of Thermodynamic Features for microRNA Target Prediction under Relaxed Seed and No Conservation Requirements," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-13, June.
    12. Jana Zecha & Wassim Gabriel & Ria Spallek & Yun-Chien Chang & Julia Mergner & Mathias Wilhelm & Florian Bassermann & Bernhard Kuster, 2022. "Linking post-translational modifications and protein turnover by site-resolved protein turnover profiling," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    13. Urmo Võsa & Tõnu Esko & Silva Kasela & Tarmo Annilo, 2015. "Altered Gene Expression Associated with microRNA Binding Site Polymorphisms," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-24, October.
    14. Zhdanov, Vladimir P., 2010. "ncRNA-mediated bistability in the synthesis of hundreds of distinct mRNAs and proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 887-890.
    15. Ray M Marín & Jiří Vaníček, 2012. "Optimal Use of Conservation and Accessibility Filters in MicroRNA Target Prediction," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.
    16. Youjia Hua & Shiwei Duan & Andrea E Murmann & Niels Larsen & Jørgen Kjems & Anders H Lund & Marcus E Peter, 2011. "miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-16, October.
    17. Yasemin Oztemur & Tufan Bekmez & Alp Aydos & Isik G Yulug & Betul Bozkurt & Bala Gur Dedeoglu, 2015. "A Ranking-Based Meta-Analysis Reveals Let-7 Family as a Meta-Signature for Grade Classification in Breast Cancer," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    18. Evelyn Zacharewicz & Paul Della Gatta & John Reynolds & Andrew Garnham & Tamsyn Crowley & Aaron P Russell & Séverine Lamon, 2014. "Identification of MicroRNAs Linked to Regulators of Muscle Protein Synthesis and Regeneration in Young and Old Skeletal Muscle," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-25, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:caa:jnlcjs:v:61:y:2016:i:3:id:8782-cjas. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.