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Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish
Terminologies of ovary development, by somewhat subjective describing and naming main changes of oocytes, have been criticized for confusing and inconsistency of terms and classifications, and the incurred consequences impede communication among researchers. In the present work, we developed regress...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482860/ https://www.ncbi.nlm.nih.gov/pubmed/28646175 http://dx.doi.org/10.1038/s41598-017-04327-y |
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author | Shen, Zhi-Gang Yao, Hong Guo, Liang Li, Xiao-Xia Wang, Han-Ping |
author_facet | Shen, Zhi-Gang Yao, Hong Guo, Liang Li, Xiao-Xia Wang, Han-Ping |
author_sort | Shen, Zhi-Gang |
collection | PubMed |
description | Terminologies of ovary development, by somewhat subjective describing and naming main changes of oocytes, have been criticized for confusing and inconsistency of terms and classifications, and the incurred consequences impede communication among researchers. In the present work, we developed regression between ovary development and three ribosome RNA (rRNA) indexes, namely 5S rRNA percent, 18S rRNA percent, and 5S–18S rRNA ratio, using close relationship between volume percent of primary growth stage oocytes or gonadosomatic index and rRNA content, demonstrating species-specific quantification of ovary development can be established in species with either synchronous and asynchronous oogenesis. This approach may be extended to any species with primary growth oocytes, e.g. anurans and reptiles, to predict maturity stages in females. We further confirmed that 5S rRNA percent and 5S/18S rRNA ratio can serve as markers to distinguish sexes unambiguously. A micro-invasive sampling method may be invented for non-lethal prediction of ovary development and sex because only a small amount of ovary sample (<50 mg) is needed for the approach established in the current work. Researchers who work with ovary RNA-seq in these taxa should realize that insufficient depletion of rRNA will probably lead to incorrect quantification of gene expression and inaccurate conclusions. |
format | Online Article Text |
id | pubmed-5482860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-54828602017-06-26 Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish Shen, Zhi-Gang Yao, Hong Guo, Liang Li, Xiao-Xia Wang, Han-Ping Sci Rep Article Terminologies of ovary development, by somewhat subjective describing and naming main changes of oocytes, have been criticized for confusing and inconsistency of terms and classifications, and the incurred consequences impede communication among researchers. In the present work, we developed regression between ovary development and three ribosome RNA (rRNA) indexes, namely 5S rRNA percent, 18S rRNA percent, and 5S–18S rRNA ratio, using close relationship between volume percent of primary growth stage oocytes or gonadosomatic index and rRNA content, demonstrating species-specific quantification of ovary development can be established in species with either synchronous and asynchronous oogenesis. This approach may be extended to any species with primary growth oocytes, e.g. anurans and reptiles, to predict maturity stages in females. We further confirmed that 5S rRNA percent and 5S/18S rRNA ratio can serve as markers to distinguish sexes unambiguously. A micro-invasive sampling method may be invented for non-lethal prediction of ovary development and sex because only a small amount of ovary sample (<50 mg) is needed for the approach established in the current work. Researchers who work with ovary RNA-seq in these taxa should realize that insufficient depletion of rRNA will probably lead to incorrect quantification of gene expression and inaccurate conclusions. Nature Publishing Group UK 2017-06-23 /pmc/articles/PMC5482860/ /pubmed/28646175 http://dx.doi.org/10.1038/s41598-017-04327-y Text en © The Author(s) 2017 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shen, Zhi-Gang Yao, Hong Guo, Liang Li, Xiao-Xia Wang, Han-Ping Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title | Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title_full | Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title_fullStr | Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title_full_unstemmed | Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title_short | Ribosome RNA Profiling to Quantify Ovarian Development and Identify Sex in Fish |
title_sort | ribosome rna profiling to quantify ovarian development and identify sex in fish |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5482860/ https://www.ncbi.nlm.nih.gov/pubmed/28646175 http://dx.doi.org/10.1038/s41598-017-04327-y |
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