Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Shen, Zhi-Gang, Yao, Hong, Guo, Liang, Li, Xiao-Xia, Wang, Han-Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
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
_version_ 1783245643151572992
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
work_keys_str_mv AT shenzhigang ribosomernaprofilingtoquantifyovariandevelopmentandidentifysexinfish
AT yaohong ribosomernaprofilingtoquantifyovariandevelopmentandidentifysexinfish
AT guoliang ribosomernaprofilingtoquantifyovariandevelopmentandidentifysexinfish
AT lixiaoxia ribosomernaprofilingtoquantifyovariandevelopmentandidentifysexinfish
AT wanghanping ribosomernaprofilingtoquantifyovariandevelopmentandidentifysexinfish